Beyond static experiences: Where AI is taking the next generation of websites
How to prepare your content, technology and team for digital experiences that respond to individual intent.
For 30 years, websites have been built around predefined pages, personas and journeys. Even with personalisation, people have to find and navigate the path that most closely matches their needs. The cognitive load for visitors is high.
AI is changing expectations. In this webinar, we explore how and how you can get your website ready.
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Watch the Australia & New Zealand webinar
Transcript: Watch the webinar (ANZ)
Welcome, everyone.
Welcome to this Squiz webinar, Beyond static experiences. Today we're going to be looking at where AI is taking the next generation of websites.
I'm Lorna Hegarty. I'm director of marketing at Squiz, and I'll be your host today. Shortly we're going to throw to a pre-recorded session. The reason for this is so that we can bring in all the expertise from across our business to really bring you across this new topic.
We've got multiple insights from different parts of the business, and also multiple time zones, so it's really lovely that we can bring all those people together in one space. But please do stick around, because we're going to have a live Q&A at the end.
I'll be joined by my wonderful colleague Megan Andrews, who's our head of customer. She's going to be joining us for a live Q&A. So share all the questions you have throughout the session – pop them in the Q&A box just over there to the right, and we'll revisit them at the end of the session. All right.
Let's get started.
Welcome to this month's webinar. We're calling it Beyond fixed experiences: where AI is taking the next generation of websites. What we at Squiz have been thinking through a lot is just how long we've had these websites that are built around predefined pages and navigation and journeys.
They kind of leave people to find their own path, to figure out what's there. And a lot of work can be done to make those journeys great and very frictionless for people. But wouldn't it be great if we could preempt what they want and give them something dynamically that's really customized to them?
And if you've been around online and tech at all, the answer is probably AI, right?
But there could be a trap there.
There could be a trap there. Putting AI on top of a website without any thought as to how it interacts with the content that you have, and without thought towards how it's going to interact with the users that visit your site, isn't really so much of a strategy as it is – I don't know – maybe a small cry for help. But not to worry, we're here to help you think through some of these things. I'm joined by my colleagues Kat and Ricky, and we're going to talk through some of the shifts that we've been seeing at Squiz, as well as some of the tools that we've been building to assist you in adapting to this new era of usage on the web.
So I'm excited to have you both here. Hi, Kat. Hi, Ricky. How are y'all doing today?
Hey. Good. How are you?
I'm doing all right. We are a global webinar team today. We've got Ricky in New York City, and Kat's in Australia. I'm in the middle of the south of the US, and we've got some cool demos for everyone.
So I think what we want to do is get into it. Keep questions coming – you can toss them in the chat here. Someone will answer them during our chat today, but we'll also leave time at the end for you to talk with maybe not all three of us, but some of our colleagues will be jumping on to do the Q&A with you.
So first, I want to start with a question for you, Kat.
What is the change that you have noticed around how audiences expect content to serve them? And why is this fixed website model reaching its limits?
Yeah, that's a great question. We spend so much time talking to customers all around the world about this exact topic, because it's very front of mind for everybody. I think the thing that we're really noticing is the disintegration, if you like, of browsing as we know it.
In all of the eras of experience design up until now, a lot of the effort, a lot of the cognitive load, has been placed on the end user. So, for example, I'm busy shopping for a fridge right now. Back in the day, that would have meant I have to go to Google, I have to come up with the right kind of combination of keywords, get six pages of search results, open 25 different tabs, compare different models, and possibly make physical notes as well.
And then go to your website and understand your information architecture. How do I find things? Use your search to do a secondary search on your website. So there was a lot – pretty much all – of the work really placed on the user to figure out how to find the information that they needed.
We created a digital destination, and the user had to come to it and figure out how to use it. And I think what's really interesting now is that we are seeing a much lower tolerance from users for that kind of effort. They no longer want to have to do all of that work. They very much expect – and are being trained to expect by ChatGPT and the like – that we will present that information to them contextually and personalized, in response to a question that they've asked.
And so that's really what we're seeing in terms of changes in behavior.
We're calling this the Intelligence Era. I wonder if you could give a quick overview of that transition period that you've seen, from these fixed experiences into what we're dealing with today with more personalized, customized, dynamic, rich experiences.
Yeah, absolutely. You're right, we're calling it the Intelligence Era, and era is a big word. But what we're really trying to communicate there is that things are fundamentally different moving into this new era compared to how we've been doing things in the past. So we've roughly split the evolution of digital experiences into four eras. We started with the system era, which was the birth of computing.
Interfaces were very much built by developers for developers, so there was no graphical user interface. It was all command line. And so there was no real acknowledgment that there were people on the other side of the system who had to be able to use it.
From there we moved into the usability era. That's where we started thinking about: hey, there are people on the other side of this. They need to be able to interact with it. How about we give them some kind of graphical interface to use? How about we think about some basic concepts of usability?
And then from there we went into the era that we've been in for the past couple of decades probably, which is what we've called the experience era. That's really where we started getting a little bit more nuanced. So rather than just creating an interface for humans as a homogenous blob of people, we started thinking about: hey, people are different.
Some people have different needs, for example. So we developed concepts like accessibility. We want things to be easy and intuitive to use. So we started thinking about customer journeys and user research and all of those great things.
And now we are transitioning into the Intelligence Era. I think the defining shift that we're looking at there is going from designing for a group of people and making a bunch of assumptions about what those people need and want, to experiences being dynamically generated and created and crafted for one single person. So from designing for many to designing for me. And I think it's a really interesting shift, because it very much implies that we have to start thinking about things and doing things very differently moving forward.
And what comes to mind for everyone immediately is: well, we have all these AI tools now, right? It's all we've been able to talk about, all we've been able to see or read about for the last, what, two or three years, for any of us that do our work on the web at all.
Why is it that organizations can't just simply add AI to an existing website that they have? What are the considerations that need to go into deploying AI, picking the right application for AI, but then also the underlying infrastructure that's going to make some sort of AI-powered, intelligent front end useful and effective?
Yeah, great question. There are a couple of things to unpack there. I think the first is: why can't we just add AI? You totally can if you want to, if you have that kind of risk tolerance and you're willing to just go for it. But generally speaking, we don't recommend just adding AI. The reason for that is that for AI to get you really great results, there's a lot of foundational work that needs to happen first.
AI is looking at your content. That's its primary source of information. So if you haven't got your content up to date and accurate and well structured and all of those good things, chances are your AI is not going to give you particularly good results.
So that's the first thing. Because ultimately, if you're plopping AI onto your website, you want it to be giving accurate, reliable, helpful responses – not making things up and writing poems and doing other strange stuff. So it's really important that you are thinking about getting your content sorted out. And then I think the second thing there – and we're seeing this more and more – is that for AI to operate somewhat autonomously, you need to be thinking about the governance that it's operating within.
We had this really useful concept of AI as an intern in our trends report a couple of years ago. If you think about an intern, or even a junior employee, you're not going to send them out there to deliver work without guidelines, without training materials, without best practices, without oversight and a leader in the loop. AI is the same. You've really got to be thinking about the surrounding governance that it's operating within, so that you can feel like you have peace of mind that it's going to deliver good results.
I think there's something that's maybe not overtly said within that. For those that are on the web a lot, they've heard of all these technologies that allow you to connect the general models that you might be using to a lot of other software. And we're seeing that pop up a lot more across the CMS space. I think the key there is that governance piece. Sure, you can take any old model and hook it up to whatever you want. But if you don't have those governance guardrails, if you don't have that information and context for it to be able to go and work alongside the software, then you're kind of introducing a little bit more risk into that content process.
It's not necessarily that something bad's going to happen, but it opens it up a lot more to risky hallucination and risky moves within your content. It could break your entire content model if you're not careful about how that AI is being deployed within the infrastructure that you have.
Yep, absolutely. And we're starting to talk about this idea of your website moving from being a digital destination to being more of an experience engine – a system that is going to allow you to generate these experiences. And for that to happen, and for you to be able to have great experiences that you're generating, you've really got to get the basics right, the building blocks.
And I know that doesn't necessarily sound that sexy in the world of AI. But at the end of the day, it's the foundations and the building blocks that are going to create a really great system. So it's things like your content guidelines and governance.
It's things like your design system. Have you got a good, structured, consolidated design system, or do you have design proliferation all over the place? It's things like your actual underlying technology and platforms. Do you have a really well maintained, modern, integrated platform, or have you got a really fragile custom build with lots of really old integrations and things that are really high maintenance?
It's all of that best practice stuff that you've got to look at and sort out first, before you start thinking about just throwing AI over the top. And there are ways and means that you can gradually introduce AI and help you with those things, but it's really important to understand just what a critical role they play in this AI future.
When I think about all the pain that came into so many universities when they put a chatbot on their website five years ago – maybe three years ago, when we started to have the more generative AI approaches to it – and found out that their content isn't ready for this, they then had to rewrite a whole bunch of content and retrain it manually.
Yes.
And those are the things that cost time and cost real money and real effort for any organization that's trying to put that in place. I think it underscores that riskiness that comes into play when you don't understand how ready your website, your content, your design models – all of that schema and architecture that goes into it – actually are. When you don't understand where it's at, then you're risking having to spend a lot of time overcorrecting, or secondarily correcting something that should have worked in the first place, right?
You're absolutely right. Most of our customers have what I call a content problem, or a content monster sitting in the corner. They know. Especially education and government – they know that they've got a proliferation of content. Sometimes these sites are 50,000 or 60,000 pages. So they know there's a lot of content out there that they don't necessarily have great visibility of.
They've been putting it off for a long time. AI is creating an impetus that you actually need to solve these problems.
But to your point, it does take time. It is an investment of effort to get that content right. And I think what's interesting about chatbots of the past, versus where we're recommending people head now, is that they created another repository of content that you needed to manage. What we're really trying to get our customers to think about is: how do you create one authoritative source of truth, so that you can slay the content monster?
You can get everything sorted out, and it's all within that one place, and you've got visibility of it there. And you can serve it out to wherever you want it to go, rather than going, "Hey, I really need an AI chatbot, let me go and get some third-party thing where I've got to create another whole knowledge base" – because now you've just duplicated the content monster.
Now you've got another place that you need to be managing that content. So a lot of our customers are really thinking about how they consolidate, and how they identify the single source of truth for a particular kind of information, and protect that and maintain that.
And you get so many gains on the governance side of things when you start to think about that. A lot of the sectors that we work with – government, higher education, these content-dense organizations – have spent years trying to get a handle on the governance side of what they're doing with their websites, only to be set back a couple of steps by a lot of the so-called solutions out there. So to your point, that's what we're really trying to tackle: how do we help organizations get to a point where they have that one authoritative source of truth, simplify their governance structures, not create a bigger monster, not add to the pile of confusion?
And in the end, that helps their users – their website visitors, their customers, their clients, their constituents, whoever it is – find that content better in a number of different places. Ricky, I didn't mean to ignore you on this webinar recording, but you've been sitting over there, and I want to get your input on the technical side of these things, because you're using our tools every day and you're making recommendations for how they might be placed into the technical structures of the organizations that we talk to all the time.
Can we start at just what you know needs to technically be in place for some of these experiences to be reliable?
Yeah. Well, as Kat was saying, the content is really king when it comes to these technical implementations.
And the product should be able to enable that – being able to tell you where the gaps are in your content, and why something is coming back a certain way. If it's not showing the right content, or if there's a content gap or anything like that, our tools can help provide answers based on that, and so give you more informed ways of fixing those sorts of issues.
Awesome. I think we've got a little demo here, right? You're going to show us some of this stuff. Because we've already established how these fluid experiences need that trusted content, effective search, strong governance, all these different things.
I wonder if you could walk us through the Content Intelligence and Conversational Search tools that we have, especially some of the ideas that we've got coming up for these more dynamic experiences.
Yeah, sure. Okay. So this is our content health tool. This is the kind of tool that I was talking about that could help identify gaps.
One of the big things about these tools is that it should be accessible as well. So accessibility is really important for AEO – answer engine optimization, or being found in AI answers. So wrapped up in this content health tool is an accessibility report. Clicking into this will show the sort of stuff that it comes back with.
It's a really nice, simple, easy-to-read report. It gives you a nice overview of your overall scoring of your accessibility, and an audit summary of how many resolved issues there have been since the last scan.
Importantly, with this tool, we've tried to make it so it prioritizes issues for you, so it doesn't overload you with accessibility issues. Other tools out there can show you tens of thousands of accessibility issues and can be really overwhelming.
So we sort them into quick wins here. You can also filter by fix type, because not all accessibility issues are specifically content. They could be code, so it requires a developer to go in and fix it.
Clicking into this, let's take a look at what kind of information comes back here. We do also attempt to group accessibility issues, again so it doesn't overwhelm you. So this is one overall accessibility issue, which is "ensure headings have discernible text". It tells you why it fails and the impact it has on users.
It also gives you what the actual implementation is. So what is the code that's generating this issue? And then it generates a fix here for you. This is where it uses AI to recommend fixes, both by reading the overall page and the classes and all that sort of stuff that's applied to it, and giving you the actual code that you can use to fix this accessibility issue.
It also tells you all the affected locations, and then all the grouping over here – so similar heading discernible text issues.
Going back out to the dashboard, we get detailed results here as well. So the total number of failed rules. And then finally, down here, all the different accessibility issues that are available to you. Again, here you can sort by categories. So different sorts of accessibility issues here, the kind of impact it has on users – so if it's critical, serious or moderate – and then also conformance level up to WCAG 2.2 AA.
The other reporting tool that we have here is our AI Readiness Auditor. This is a really great tool for understanding the gaps in your content where AI is concerned, because AI is already scanning all of your content and it's already reading it. If it finds conflicting information, it's going to give conflicting answers back to users if they're asking AI about your content.
When we scan your website, we organize it into topics. So here we've scanned the squiz.net website. We have content management, enterprise search, government digital services, all that sort of stuff.
The AI organizes all your web pages into specific topics, and then it asks you: do you want to start monitoring this topic? And that's when AI does a deep dive on all the content inside it. So when it reads all the content inside it, it asks itself: how many possible questions could someone ask about this content?
And then once it generates all of those questions, it attempts to answer all those questions based off the content that's available to it when it indexes your website. When it answers those questions, it rates itself. So it says: how well did I answer this question? And if it doesn't have a good answer, then it says, "I didn't answer this very well." So this is a little gap in the content – somewhere in the content has generated this bad answer. So, clicking into content management, let's take a look at the high-priority issue that's identified.
Here, again, we're attempting to prioritize the issues, because we don't want to overload you with issues; we try to prioritize the ones that are going to have the most impact if you fix them. So this one here is obviously a high-priority issue: correct the description of digital asset management to reflect centralized DAM functionality. Let's click into this. It gives me an overview of the issue: visitors may believe the digital asset management feature is about building integrations and connectors, when it actually provides a centralized library for managing approved assets across sites and campaigns.
So it's detailed the issue. It recognizes what the issue is. Obviously we're talking about DAM one way in one place and another way in another. So it's conflicting information, and we're basically generating a contradiction.
So here's the fix that it recommends for us. It's basically generating a sentence that we can use to improve the answer on the website, and it also tells us the pages where this is actually referenced. So this is where we actually go to change the content to make this answer not conflicting. So the next time AI scrapes that part of the site, it's going to have a more straightforward answer and be able to answer users' questions about what Squiz's DAM is much better.
Going back –
It sounds like I need to go fix that content on the website, Ricky.
Please don't, because it's a great demo.
Fair. All right.
So we can also ask questions directly to it. We can ask how it actually answers a question – a question that I had. I was wondering: how would AI answer a question when someone asks this specific thing about my website? So we can say, "describe the content management system".
Now this tool is going to look at all the content inside it and say: how would I answer this question based off all the web pages that are assigned to this topic? And here you get an idea. This is how AI is probably going to answer this question based off the content that has been indexed here. So it's a really great tool for seeing how your content can respond when someone asks a question like that.
I love how fast that response is too, Ricky.
I know.
It's very quick.
That was quick because – we all use AI a lot in a lot of different ways, and answers never come up that quick. That was super fast.
Yeah, it's really fast now, and it's great.
I should show you here too that it does show you all the issues that it's finding. So when it's pulling back all the sources or references that it used, we can see here that these are all the different answers that are generated and the issues that are being generated along with them. So we can go in here and figure out why this is an issue, which again is going to be really helpful for making our answers a lot better.
And there's just one last thing I want to show here: these are all the questions that it generates. Actually, I should show it here as well. There are only 51 pages in this specific topic – we have a really small website – but it's generated 4,500 questions. So you can see that AI is trying to guess all the different permutations of however anyone can ask a question about the content on the site. So for a larger website, which might contain 1,000 to 2,000 or 10,000 pages on a topic, it could generate tens of thousands of questions, and is really trying to cover all of its bases.
I'll take a pause there. What do you guys think?
Well, I'm a big fan, personally.
No, I think it's really great. One of the things that always really resonates, Ricky, with customers when we talk them through this is that prioritization – the biggest bang for your buck in terms of what you should be addressing next. Because a lot of them have other tools, and I've worked with other tools where, like you say, it will give me 10,000 issues. Everything's red. It's very overwhelming, and ends up just being put in the corner with the content monster, really, and just ignored.
Whereas I think this is a really great way of being able to build better content optimization practices into your everyday, into your BAU, because you can really just log in here once a week and address a couple of issues. And that way you're constantly, incrementally optimizing, which I think is really, really valuable.
Yeah, I'll echo that as well. That's been a real crowd pleaser with clients, because other auditing tools can be really overwhelming when you see thousands of issues, right? So the prioritization feature really helps them prioritize where to start. There's just one last thing that I wanted to show.
I thought I could give a little demo of the actual conversational search, working out in the wild, with a new feature we've just released, which is our rich content.
So this is just a demo instance I have that's hooked into our website again. That AI readiness report, I should also mention, actually becomes like an FAQ database for our Conversational Search. That means that we've pre-generated all the questions and answers, which means it's going to be really fast when it comes back with an answer here for me. And it also gives me certainty around how it was going to answer questions as well.
But we've tied it into this rich content experience, where you want AI to be able to answer questions based off your content with little input from you. You just want to know that your content is right, so it's going to answer right, which is great. But sometimes you want to add a little bit of additional content in there, when it picks up on things like trigger words.
So, for example, for a university client it might be admissions, like "how do I apply?". And you want to be able to display things like a form or maybe a call-to-action card. So this is where we come out with a new feature called our promo blocks. I'm going to ask a question here.
So: what is conversational search?
It's going to come back with an answer, a nice answer that comes straight from our AI. But importantly, it's hooked into keywords here. So it's recognized that I've asked about conversational search. And so what it's going to do is display this additional content here, which is actually inserted by our content management system.
So an editor has said: well, when someone talks about conversational search, I want to be able to add additional content to supplement the AI-generated answer. This is also built on top of our component service, which uses our inline page builder feature. So this means that we can actually put any sort of content into this response. It could be an embedded map, an embedded form, or just, like we have here, cards that display links that take me out to other areas.
So I really like this tool, because it has that automated response that we've come to love from AI, but gives you a greater level of control over what kind of content you want to display to that user when they've asked those questions.
Yeah, I think this is a real game changer. If we think back to what we were talking about earlier in terms of the Intelligence Era, and this idea that experiences are going to be generated around the user rather than us making assumptions about what they want to see, I feel like this is really that first quite big step into that world, where we are dramatically reducing the cognitive load, because they're not having to click around all over the place.
We are dramatically shortening the pathway from information to action as well, which I think is so critical, especially when you think about how browsing behaviors are changing generally. People are doing a lot more of that early-stage discovery inside their LLM of choice, inside ChatGPT or wherever it is that they spend their time. And when they're coming to your website, they're often a lot more task-focused and a lot more ready to just get the job done. This kind of interface is really great in terms of combining that browsing behavior with that search behavior, and being able to go: here's the exact information that you asked for, the exact form that you need to fill out, and off you go.
I think it's fantastic.
And just to be explicit about it: that Content Intelligence piece, where we did the full audit of all the content and generated that FAQ database, that powers this. So you don't have to retrain it. You don't have to go back and correct a whole bunch of content or spend a year on a massive content project. All you really have to do is maybe fix some of the contradictions that come up.
Yep.
And then put in place a content plan to revise and improve as you get that feedback loop of questions people are asking. Is it coming up with answers that are satisfying the question that they had? If not, create that new content.
Go back in, see what's coming up in Content Intelligence, see what's coming up in the conversations that people are having through this interface. And that means you have this constant optimization loop of a better experience every single time someone comes back onto the site and uses your conversational search. Ricky, thanks so much for the demo. That was awesome.
And to start to wrap this up, Kat, I wonder if you could give us a summary of how you're thinking through these things. So summarize what we've seen, where we're going, and our excitement for the future of web experiences.
Yeah, absolutely. Look, we are excited about the future of web experiences. I think there's a lot of narrative out there at the moment around "oh, websites are dead, you don't need a website".
That couldn't be further from the truth. You absolutely do need a website. It's just changing the role that it plays in your overall organization, and I think that is so exciting.
From a human perspective, you absolutely still need a website. Your website becomes a really important source of truth for AI, and it also becomes an even more important source of truth and source of information for you. As you said, there's this virtuous circle of feedback, where you're getting really great data from these AI interfaces. So, to summarize, as we said at the beginning, we're entering this new era.
We're very much in a transition phase into this new era as well.
We don't necessarily have all the answers. No one knows exactly what we're going to have to do. But what we do know is the criticality of getting the foundations right. And what we do know is that it's important to start embracing this new technology – but embracing it in a way that is controlled, that is structured, that is managing risk effectively. Having the kinds of tools that Ricky just demoed, your Content Intelligence, your Conversational Search, allows you to start embracing the power of AI, allows you to start addressing your foundations, getting your content right, and all of those good things, in a way that's going to provide you immediate value but is also going to lay really important foundations for the future that we're moving into.
All right. So thank you so much for joining us in this webinar. We hope you learned a lot. We would love to talk to you more about this.
If you're curious about how to self-assess where your organization is on this process, click the link that's in the chat or the QR code that's on the screen, and take our website readiness assessment. It's there to help you understand where you're at on this journey from fixed to fluid, and how ready you are to start putting these fluid experiences into place. And if you don't like the score, we want to talk to you about it. We want to find out what it is that seems to be in the way, and maybe we can offer some recommendations.
We're very happy to show you more in-depth demos of the products that we have, or talk to you about strategy. We are here to help. Thank you all for joining. Kat, thank you for being on.
Ricky, thank you for being on. It's been a great conversation. I feel lucky to have been able to be on this webinar speaking with you both. You're both super smart, and it's always a joy.
Thank you.
Thanks, Joel.
Fantastic stuff. Really exciting to see and hear all of that from our super smart colleagues. As a marketer myself, I'm very excited about the way things are heading. Just seeing those rich experiences assemble and come together is so satisfying.
And welcome to the stage, to the webinar party, Megan Andrews. Thank you so much for joining me. As I mentioned at the beginning, Megan's going to be joining us to go through the questions. We've had loads of questions, which is great, so we'll be working our way through as many as we can today.
Do you want to say hello, Megan, and welcome yourself to our attendees?
Yeah, thanks for having me, Lorna. I was loving that, and I noticed a great little comment about the Fender guitar in the background – Joel's always got a great background. But to your point, so exciting, from marketing all the way through to technical, just all the impact. Can't wait to answer some questions coming up.
Awesome. I'm actually going to be cheeky, and before we jump into the questions, to give people a little bit more time – if it's got the cogs going, keep those questions coming in. We would like to hear from you as well.
So we're going to launch a quick poll in a second. Just thinking about everything that we've covered today, we would like to hear from you: which area would make the biggest difference to your organization's ability to deliver reliable AI-powered website experiences? So the poll is up there.
Please do pop your responses in there, and once we've got a few more of those back, we will jump into the Q&A.
But keep popping your answers in, plus your questions – we'd love to hear them.
Oh, and we get a live update. Yeah. This is always really interesting to see where people are with their organizations.
There's a range, so don't be ashamed. If you don't feel like you're prepared, that's okay.
Yeah, absolutely. And it is nice to see those numbers coming in live. It's quite fun. Makes it like a race.
Yeah, exactly.
I love listening to Kat talking about slaying the content monster. I think that's such a good way of putting it. So relatable.
Yes, the visual on that. I actually wrote that down. I was like, this is something that will come up as a motto for me as well.
Yeah, exactly.
Getting close here.
What do you reckon, Megan? Is that a surprise, where we're landing at the moment?
You know, it makes sense to me.
Yeah. The real part here is, I think to your point, content is the foundation, but it's also understanding what your users are looking for now. How have things changed, and how do you need that to be reflected on your own site? We know large language models and AI are changing user behavior everywhere else off our sites, so this is really great. Search to better understand audience intent – I think that's a solid one we see a lot as well.
All right. We've got about ten minutes left. Thank you, everyone, for taking part in the poll, but let's jump into the Q&A. On the back of the discussion about content, I'm going to combine a couple of questions here, because I think there are a couple that we can answer in one go, and I really want to make sure we cover as much as we can.
The first question that we had in is very topical: we've got thousands of pages and a small team – how do we work out what to fix first? And then, as a nice follow-up, Megan, it would be good to hear: do we need to fix all of our content before we can turn conversational search on?
I think that's something we hear a lot, right? There's an intimidation around the amount of content that people have and being able to use AI tools like conversational search.
Yeah, great questions to combine, actually. And so many different organizations are in this similar space. You may have a large website – I was just working with a client this week who has 300,000 pages across their site, one of our higher education customers. And that's no joke, right? You've got a lot you need to figure out in terms of how you will even approach this.
One of the most important things to do is don't be scared to get started. You don't want to end up thinking about all of this for the next six to twelve months and never making any progress. A lot of these tools are designed so that you can take it bit by bit. You can point them at a certain part of your domain.
You can even exclude different areas of your site that you're not interested in. You just start small, or start where it's most important. So start with high-impact places, get an assessment and baseline of where you are.
And then, to your point, Lorna, there's no need to just flip on the switch for everything.
Similarly, if there's a strategy around what your priorities are – let's say you're really focused on increasing enrollments – let's go ahead and optimize content in that specific area and then turn on conversational search for that space.
Like any good marketing team would know: test and learn and improve, test and learn, improve. Keep deploying what you've learned and iterate on that process. I think that's the best recommendation.
Awesome. To that point, then: Ricky showed us a few of the tools that we have available to help our customers with this. One of the questions that we've had here is, can our content team use these tools themselves, or is it mainly something for developers? Again, I think that's a real concern, right, with new tools and teams having to get across things. What's your take on that one?
One of my favorite features in the tool is actually a filter you can put on, so you can understand – at least on the accessibility side – does a developer or technical user need to look at this, or is this something a content team could manage? So you have it right there in front of you. I would say the interface itself is extremely easy to navigate. I've been onboarding a lot of our customers in the US, and the content teams are elated.
It's not this overwhelming huge list. It's organized in a really thoughtful way. And you don't have to know all the details and the code behind the fixes on the site – it walks you through those if you need it.
But you can also use that filter and then bring in one of your technical counterparts and say, "Hey, let's tackle this together."
So that's really useful. I think the other piece, in terms of the AI readiness component, is that it's extremely intuitive. That interface is really easy for teams to use. So no matter who it is, you can pop in there, get an understanding of the assessment of your content, and those recommendations are fairly straightforward. If you need more information, or you have conflicting information across the site, these are really intuitive fixes that it's going to give you there in the queue.
Nice. And I think, particularly as a marketer myself, one of the things that I feel – and I know the team feels – is almost the fear of bringing in AI and knowing how to manage it and control it. One of the questions that we had there was: Kat had compared AI to an intern who needs guidelines – what sort of guardrails do you recommend organizations put in place?
I love this question, because this is when we always get to say: we still have our jobs. Keep a human in the loop. AI doesn't know everything yet. And I actually think it's important to understand there's some global discourse around what it may be capable of and where it could be deployed.
Tools like this are designed around only doing specific things. So you can have confidence that if you deploy this across your site, you've already ring-fenced the type of content it's allowed to access. It's not going to hallucinate. So you already have guardrails in place.
So there's that ease of understanding where your risk is as you begin.
And then, again, just shutting out the noise of that global conversation, and being aligned with your internal AI review board if you have one, or someone in one of the new positions we've seen rolling out – maybe a VP of AI. Have some of those conversations, bring them into your process. And I think you'll find that, especially with this tool, it's really focused on controlling what you can control.
It's really a lot about a content exercise. So there's not a whole lot you're asking the AI to do. You have great ways to test it. It's really just about facilitating that information flow on your site.
Amazing. You've answered a couple of questions there, I think, so that's really cool, because we can go through two. I wanted to pick up on one of the ones that was around what Ricky was showing for the more rich experience that we're now bringing out into market, which, again, I just find so exciting. It's a real reflection of the way things are moving, and something that we kind of expect to see very soon – but it's going to come out of nowhere like everything else in AI has done. So the question was: these cards that Ricky's showing alongside the answer – can we choose what shows up there, like a form or a link or a next step?
Yes, I love that. If you can remember back to what he showed on the screen, essentially you've got a conversation, a dialogue box, and then around that you can feed in these dynamic content pieces, right?
So I love this. Think of it as like a dynamic sticky note, or putting something up on the board, or think of content posters when you're at a coffee shop – where things that are relevant to the conversation can be fed in, and that's all configured on the back end. So what I really like about this piece, having managed content before in lots of different buckets, is that you don't have to do that. Once you plug in Content Intelligence and you've optimized your content, you hook in all the topics and conversation points that you would want to flow around certain areas.
And then you direct just really simple prompts for those little card placements around the conversation, and they can be really simple CTAs. So on the back end, you can say: anything about admissions, go ahead and bring in this call to action, go straight to the application page.
Or anything about getting a new bin for collection days – whatever your organization is managing, government, higher ed – you can configure that really easily on the back end, much like you would with your normal CMS and personalizing for different audiences. So I love it. It seamlessly feels dynamic, but the content and the configuration behind it are really easy to manage. So I think it is, to Kat's point and to the whole conversation really, entering a new era where that user experience is going to feel really personal very easily.
Yeah. Building for me. I can't wait to have my own website built just for me.
And going back a little bit – we've got a few more minutes – I just want to dig into some more questions around monitoring and improving content. Someone asked here: can we see whether answers are improving over time?
You can, and actually it'll continue to learn. What's nice is you can set an audit schedule for your content. Let's say you're heading into a content-focused time, and you're focused on one area of the site really specifically.
So you're like, "Hey, every week, why don't we do a quick audit on this and make sure that the questions are being answered the way we hope?" So come up with your top twenty or fifty questions, load them in, and you can see how it's improving. Then make changes on the site, and see if that content's actually really helpful and getting better information through.
There's a very live, interactive Q&A type of ability on that back end.
So what's nice is that once you get answers to a great spot, they're banked there. That becomes the large language model's own FAQ. So if users on the front end are asking something about that topic, you can rest assured that they're going to get surfaced that answer you've already seen on the back end, which is correct and accurate.
Amazing. I reckon we've got time for one more, so I'm going to squeeze it in. If someone asks something our content doesn't cover, what does conversational search do?
Oh, you can tell it what to say. That's the best part. If it doesn't know, it's not going to make something up. You can set a default response that says, "Appreciate your question. If you have specific questions about this topic, you can go here." And you can point them to a different place, but direct that large language model not to come up with something.
Amazing. Very good at the quickfire. Well done. I've covered off pretty much all the questions, I think.
There were a couple, I'm sorry, that I did skip over. So if I've skipped over yours, please rest assured we will be answering all of the questions in a written follow-up. You will get answers to all of these in writing in our follow-up comms.
Also, make sure that you head over and do your own self-assessment, and give us a shout if you'd like us to talk through that and what it means for you and your website, and how you can improve things to really meet the expectations of this new Intelligence Era that we're entering. Thank you so much to our presenters of the webinar session, and thank you so much, Megan, for being here to answer all the live questions.
Sure. Great to be here, Lorna, and thanks.
Thank you, everyone.
Video: Watch the webinar (ANZ). Captions and transcript available on playback.
Poll Results
- Clearer, more trustworthy content – 43%
- Search that better understands audience intent – 35%
- Stronger governance, permissions and ownership – 13%
- Better connected technology and services – 9%
Watch the Europe webinar
Transcript: Watch the webinar (UK)
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Toby Margetts: Yeah, yeah, hi for those of you who've joined, just give it another, kind of, 30 seconds or so before, before we jump in.
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Toby Margetts: Alrighty, hello, and welcome, everybody. Thank you very much for, for joining us this morning. Really great to have you, have you on board.
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Toby Margetts: Today, we're going to be talking about how we can keep our content healthy in the world of AI. So, most content teams, I think, I'm pretty sure, I know, know what good content looks like and what it should do. It should be useful, it should be accurate, easy to find, easy to maintain.
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Toby Margetts: The hard part is keeping it that way once things like requests and updates and ownership changes and business priorities start moving faster than the team can realistically track.
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Toby Margetts: My name is Toby. I'm one of the Digital Strategy Directors here at Squiz. I'm joined by the wonderful Jamie Sharp, who is our Head of Customer. And just before we kind of jump in, I'm going to hand over to Jamie, who's going to say just a quick word on Squiz. So, Jamie, over to you.
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Jamie Sharp: Thank you, Toby, and morning, everyone. It's really nice to see so many new and familiar faces. So, just a little bit of background about Squiz for those of you who don't know us yet.
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Jamie Sharp: Squiz is a digital experience platform, so we've got a really powerful website platform that you can use to build websites, intranets, multiple sites, and get really great data out of that platform to help you prioritize how you drive your commercial marketing strategies. So, our platform is made up of three tools.
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Jamie Sharp: It's the digital experience platform, it's funnel-back conversational search, which brings that experience of AI search onto your website today, and then also content intelligence, and that will scan your website for AI search visibility, and it'll tell you exactly how to improve
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Jamie Sharp: to be found and to avoid that scenario of your competitors being found before you. And it's that AI visibility and the learnings and insights we've made about content from doing this ourselves and from working with hundreds of customers globally that's going to be informing what we're talking about today.
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Toby Margetts: Lovely stuff. Thank you very much, Jamie.
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Toby Margetts: So in terms of what we will be covering today, there are really four key things, I would say. Number one is why good content practice quietly breaks down. So I think with the best will in the world, it can be really tough to stay on top of your content's health for a number of reasons, and we'll get into that very shortly.
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Toby Margetts: Number two is the four AI discovery signals. We have actually talked about them in a previous webinar. Just as a quick reminder, we're talking about structure, metadata, authority, and freshness.
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Toby Margetts: keeping these healthy is absolutely essential. Number three is how to use those signals in a content discovery loop. What practical steps can you actually take to stay on top of ensuring your content adheres to those signals?
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Toby Margetts: For how Squiz's content intelligence tool actually helps you do this, even when you're dealing with thousands of pages of content, which I think it's fair to say most of our customers are.
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Toby Margetts: So, first up, why does good content practice frequently break down? So, none of this is new to a good content team. You already know content needs to be clear, accurate, useful, current, findable, and, of course, owned.
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Toby Margetts: The problem is, I think, what happens after publication, so new requests keep arriving, old pages keep on aging, similar answers appear in different places, ownership changes, audits go stale.
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Toby Margetts: over time, good practice breaks down, because no one actually has a current picture of the whole estate. That's a really difficult thing to do.
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Toby Margetts: A couple of examples, so, for example, there might be a policy update made on one part of the site, but it's not updated somewhere else.
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Toby Margetts: Maybe there's a PDF that's remained live after the web page it's been generated from has changed. Lots of ways that this can happen, and we don't often realize that we have these content issues until a user runs into them.
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Toby Margetts: And what I would say is that's kind of always been a problem, but AI is really putting a kind of enormous magnifying glass over these issues.
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Toby Margetts: I think a really good way to think about it, is that AI search is basically raising the cost of unhealthy content to organizations. So, I often find there's a bit of a misconception when it comes to content and AI. It's the idea that content is somehow sort of less important because of AI.
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Toby Margetts: But I think it's, it's actually the complete opposite, right? So, if the content estate contains duplicates, stale, or conflicting answers.
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Toby Margetts: AI systems have a much weaker foundation to work from. The really controllable part, I think, is not guaranteeing a citation, for example. The controllable part is actually making your content clearer, more current, and ultimately much more answerable.
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Toby Margetts: We're actually just going to jump into, a quick pile, bit of, early audience engagement, and I'm really genuinely interested to see what comes up here. It's gonna be, it's going to be interesting. But the question is, and we'd love everybody to answer if they can, which of these do you see most often in your content? So…
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Toby Margetts: Is it out-of-date information? Is it duplicate or conflicting pages? Is it gaps nobody spots until a user asks? Or is it too many requests and no clear priorities?
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Toby Margetts: We'll give it about, kind of, 30 seconds to a minute for people to answer.
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Toby Margetts: And then we'll see, we'll see what comes up. What's, Jamie, what's your, what's your money on, if you had to, if you were a gambling woman?
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Jamie Sharp: Aha, which I am. It's really interesting, because we see all of these all the time, like, I'm actually genuinely really interested to see which one is the most common, because out in the field talking to people all the time, I see these come up. Every single one of these come up, actually.
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Toby Margetts: Yeah, 100%, totally agree. I think if I was pressed, I'd probably go, like, duplicate or conflicting pages. We do see a lot of that. I feel like that's something that's actually really hard to…
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Toby Margetts: Stay on top of, particularly when we've got, yeah, lots of devolved content teams as well.
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Toby Margetts: Right, we'll just give it a few more seconds, and then we will see, see where we're at.
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Toby Margetts: Nice one. Okay, that's interesting. There's quite a big split, which is, I think, particularly interesting.
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Toby Margetts: We've got out-of-date information is coming out, on top, 34%, duplicate or conflicting pages, 24%, gaps nobody spots until a user asks, 16%, too many requests, and no clear priorities at 26%, percent.
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Toby Margetts: I think this is really interesting, because ultimately, like, whichever answer actually wins, it creates a problem for AI search, as well as for content teams. So, if we think about out-of-date content, that really weakens freshness, obviously.
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Toby Margetts: Duplicate and conflicting pages weaken authority. Gaps make it harder to actually answer the question for AI.
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Toby Margetts: too many requests without priorities, that creates more content debt. So, the content problems that content editors are firefighting are often the same problems that actually stop that healthy content being found and trusted by AI.
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Toby Margetts: But yeah, really interesting to see such a broad split across the board, key point being that, yeah, all of these really contribute towards you needing to get your content in really great health, to ensure that AI can generate really great answers from it.
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Toby Margetts: I'm going to pass to Jamie now, who is going to talk to us a little bit about some of the discovery signals that AI uses to generate good answers. So, yeah, Jamie, back to you.
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Jamie Sharp: Thank you. So…
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Jamie Sharp: Content health and AI discovery, they're two separate topics. If the answer's buried, then AI effectively is going to struggle to extract it. If your page is poorly labeled, again, AI is going to struggle to extract that. And if you've got five pages that are saying slightly different things, then you're going to find, of course, AI's got less reason to trust any of those sources.
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Jamie Sharp: If your information is stale, then it's likely AI is going to choose another source. So, in our previous webinar, we called these the four AI discovery signals, so structure, metadata, authority, freshness.
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Jamie Sharp: And I hear a lot in everyday conversations with customers that this can feel a bit complicated, the language is quite technical, so if you're thinking that, don't worry, you're absolutely not alone. But it's actually really straightforward, it's really practical, and it's actually a lot less technical than, like, an SEO checklist, those types of things that we're more used to. So today, we're going to go through really actionable steps that you can implement tomorrow, and the important takeaway here is that
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Jamie Sharp: content health matters for AI discovery. It really protects those signals that help AI find, understand, trust your content. So we're going to focus on how teams keep those signals healthy. As Toby was saying, when the estate keeps changing, that's when it's really difficult. So we're going to jump onto the next slide, which we are talking about, the loop.
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Jamie Sharp: And walk through how you build those signals into day-to-day content work.
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Jamie Sharp: So this loop that you can see on screen, this is a practical operating rhythm that your teams can use and keep applying this checklist as your content changes. So the four signals here tell us what AI-ready content needs, which
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Jamie Sharp: As discussed is structure, metadata, authority, and freshness.
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Jamie Sharp: But keeping those things true after you've published, that matters just as much. So, sticking with our theme of giving you actionable steps to use with your team, and not just a load of buzzwords, we're going to use this loop to enable teams to decide what to do before creating new content, what to check before publishing, what to monitor afterwards, and then how to turn gaps into clear actions. So, just briefly touching on all of the steps in this loop, we've got plans, so you need to audit before you just
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Jamie Sharp: fall into the trap of adding more content. Publish, so obviously make the answer easy to find.
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Jamie Sharp: easy to understand and trustworthy. Monitor, so once you've got that content out there, then continuing to look for signs that the signals there are weakening, and then continue to improve. So turn those gaps into decisions. So if we jump to the next one, we'll jump into each of those stages in a bit more detail.
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Jamie Sharp: So this is the plan stage. So, planning really protects that structure, your authority, your freshness, by making sure your team answers the right questions in the right places, simply. So instead of just adding more content, and this phase really is about, like I said before, falling into that trap of adding more content. We see folks all the time thinking.
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Jamie Sharp: Okay, we know that…
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Jamie Sharp: an LLM or an AI model is looking for a particular answer, we can see our user base, our customers are struggling to find a certain answer, so we're just going to create more content to fill that gap, but actually adding to that content that can actually weaken your AI discoverability.
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Jamie Sharp: So before creating a new page, the most important thing to do is audit what you've already got. So check whether the answer already exists.
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Jamie Sharp: You need to agree which page owns it, and then you need to decide, do I need to create something new? Do I need to update what we've already got, or can I consolidate? And the important thing here is less duplication means a much clearer source of truth.
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Jamie Sharp: Let me jump to the next one, please, Toby?
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Jamie Sharp: So then this is Publish. So publish is not only about getting your content live, it's that moment where you make the page either easier or harder for the AI to read, for it to categorize, for it to trust, and importantly, you want it to choose your content.
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Jamie Sharp: So this is where it's really easy, and we see a lot of customers, a lot of folks making mistakes. So if the answer's buried, if the labels are vague, if the source of truth is unclear, if no one knows when it should be reviewed, that page is already weakening before it's even had a chance to perform.
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Jamie Sharp: So if we just talk through, again, those four key things, we've got structure, so you need to think about, here, is the answer clear? Is it specific? Is it near the top? And clear writing doesn't have to mean bland writing, but it's important to think about those steps.
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Jamie Sharp: Metadata, so if you've got titles, are the descriptions, labels, is the content type clear?
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Jamie Sharp: For authority, is this the source of truth? Is it aligned with related pages, or have you got slightly different conflicting information across these different spots? And the page needs to make the main answer explicit. Again, you don't want to be hiding the answer across multiple sections.
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Jamie Sharp: And then freshness. So, is there an owner? Do you have a review trigger? What's the update expectation on this? And a last updated date by itself doesn't necessarily mean that the content's fresh.
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Jamie Sharp: If you think about all of that, this is where technology really helps, so these checks are easy if you've just got one page, but if you're trying to do this across a whole estate, tooling can really help limit that
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Jamie Sharp: cognitive load when all of our teams are trying to do so much more all the time. It can really help you by flagging those vague labels, jumping straight into identifying where have you got missing answers, where's there unclear ownership at publishing time, and just take that mental load out of where to start and how to keep the content healthy.
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Jamie Sharp: If you jump into the next one, please, Toby?
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Jamie Sharp: So now we're looking at signals. So, the work doesn't stop at publications, you've done your audit, you've got your content in a good spot, and you've published it out, but a page can be really clear today. You feel really good about what you've got out there at this moment, but then it could become buried under a load of related pages next week.
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Jamie Sharp: You can be really confident, you've done your review, it's authoritative today, but then actually, a couple of months down the track, it needs to compete with 3 new campaign pages that have been released.
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Jamie Sharp: Again, you can be really confident that it's not out of date, and that everything is in a really good spot with regard to freshness, but then your figures update, policy changes, and again, your content's not in a great spot. So monitoring is all about looking for these practical signs that those signals are weakening, and it's all about focusing on that, handing your marketing content teams
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Jamie Sharp: Signals that they can recognise, so that this doesn't become another thing that they've got to be thinking about and worrying about as part of their already hectic days.
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Jamie Sharp: So again, we're looking for AI discovery signals, your prioritization inputs to help you decide where to focus. So the types of things you want to watch out for are important questions that are not answered clearly, related pages that are giving different answers, new pages that are appearing on an already existing topic.
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Jamie Sharp: Obviously, broken links, stale dates, outdated facts.
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Jamie Sharp: Important pages that might have unclear titles, headings, descriptions, search items, or analytics or feedback that show that people aren't finding those answers.
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Jamie Sharp: And then demand is how you decide what to look at first. So you've probably got a heap of data there, but then you're looking for possible evidence to action items. So some examples of that could be.
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Jamie Sharp: If you've got lots of missing answers, then that probably points to you, do you need to create something to fill the gap? If you've got lots of competing or conflicting pages, then that probably points to the fact that you need to look at that estate of what you've got and consolidate to make sure the answers are really clear, you've got a single source of truth. If you've got lots of outdated
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Jamie Sharp: Pages, then you need to update, and if you've got redundant or risky pages, then at that point you want to be looking at retiring some of that content.
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Jamie Sharp: And again, this is where technology really helps, because this is usually the first stage that we see where
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Jamie Sharp: where people break down, so if you've got hundreds, tens of thousands of pages, monitoring that by hand is a huge job, and you really do need technology for it, and there are tools to do this. We happen to make one, and it's built on real-life learnings that we've made, and from what we can see happening within the market with our customers globally, so in a little bit, we'll run you through that.
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Jamie Sharp: But the main takeaway on this point in the loop is that monitoring is just about spotting where the structure, the metadata, the authority, the freshness might be slipping before the estate becomes harder for people and for AI to use.
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Jamie Sharp: And then on to the final piece of the loop.
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Jamie Sharp: So this is where we're looking to turn gaps into decisions. This stage is where the loop helps teams choose the right content action, rather than, again, falling into that tempting trap of, oh, let's just create some more content. And the more you get into the routine and using the loop, the more it becomes second nature. So, things to think about is, if an important question's got no clear answer, you might need to create or update.
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Jamie Sharp: If the right page exists, but the headings, the titles are vague, you need to update that.
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Jamie Sharp: If several pages compete, or they contradict, you consolidate. If the content's stale, or it's critical, you need to update, you need to redirect, you need to retire. So.
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Jamie Sharp: the critical point here is not about reducing more content by default, it's about strengthening the content that you've got and the conditions that help AI find your content, understand it, trust it, and crucially, you want it to cite your content, the right content. So the more you get into that routine, you should see it as just a natural way of reducing unnecessary production, not adding to it. And again.
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Jamie Sharp: that's where technology really helps. So the hard part is deciding what to fix first, and that prioritization by topic, importance, page value, risk.
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Jamie Sharp: That's where getting a tooling can save the most time.
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Jamie Sharp: All right, I think we're going to jump into another poll at this point, so we are really keen to hear when you last audited your content. So we've got a few options that are going to come up, and again, keen for everybody to provide some answers if they can, so we're interested to see
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Jamie Sharp: Was it in the last 3 months? In the last 6 to 12 months? More than a year ago? Never or not that I know of.
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Jamie Sharp: So we kind of see most teams audit rarely, because it's a bit of a beast to do, which is why your content health can slip.
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Jamie Sharp: But really keen to see what everybody's thinking, so if, if you wouldn't mind just clicking the button while you get a sec. Toby, you're… you're really close to teams and talking about this sort of stuff all the time. Any thoughts on what you think the most likely winner will be out of these?
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Toby Margetts: I mean, yeah, I think they were probably, like, a long time ago, maybe more than a year ago, I feel like…
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Toby Margetts: content audit… I've never met anyone who, like, loves, gets really excited about a content audit. They tend to be, they tend to take a long time. They tend to be things that people put off, even though they are, or traditionally have been super important.
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Toby Margetts: So yeah, it's going to be interesting to see. I can totally understand why people do put them off, but yeah, we shall see.
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Jamie Sharp: I don't know, everyone's favourite job. We'll give it a couple more seconds, and then we will get
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Jamie Sharp: Alright, interesting. It's a bit of a split again, so I would say in the last 3 months is probably the highest, so we've got just over a third of folks saying in the last 3 months, which is really positive, because this is what everybody should be thinking, and it's really important.
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Jamie Sharp: In the last 6 to 12 months, it's just very close after that, and then we've got about a quarter of people saying more than a year ago, and about…
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Jamie Sharp: just over 10% of folks saying never or not that I know of. So, I would say, you know, if you're answering more than a year ago, that's really normal. As Toby said, like, audits are big, they take a long time, we see a lot of folks, they sort of become set and forget, they're, like, stale as soon as they finish. So, again, like, just getting into the habit of that loop, rather than feeling you need to do a big audit, is exactly where you need to be thinking. Small, regular, prioritized, let tech do the work for you.
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Toby Margetts: Yeah, absolutely. Yeah, really interesting, again, to see, to see a bit of a split in there. I think for those that, did say it's not happened for quite a while.
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Toby Margetts: I don't think that's a discipline problem,
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Toby Margetts: Yeah, it's a scale problem, I think, more than anything. It just becomes a really daunting thing to want to do. As Jamie mentioned, when you've got tens of thousands, maybe hundreds of thousands of pages, that's a super daunting thing.
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Toby Margetts: But everything I think that we've just talked about, is kind of quite straightforward on one page, as I said, but most teams, you know, are managing hundreds, thousands of pages, tens of thousands of pages across lots of different teams. There are campaigns, there are PDFs, there are service areas, and there's old content.
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Toby Margetts: And of course, it's not static, right? The estate keeps changing all the while that you're auditing it. That's why often content audits fail sometimes. You know, by the time you've started it and finished it, a bunch of content on your site's changed in that time.
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Toby Margetts: And that's why they often get put off, and why the ones that you do finish tend to go stale very quickly.
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Toby Margetts: Squiz Content Intelligence, which we've, talked a little bit about, helps by giving teams a really kind of current view of the estate, so surfacing the issues, prioritizing actually what it is that matters, and tracking that progress.
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Toby Margetts: as content changes. So, content health then actually becomes something you keep an eye on, not something you sort of schedule a yearly project on to actually go and have a look at.
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Toby Margetts: What I'm gonna do is jump into a quick video, which shows content intelligence in action. It'll show content intelligence, it will show a little bit about how it works with conversational search.
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Toby Margetts: It is a video, and I… apologies to everybody, I'm going to be doing the voiceover, so I'm going to probably be, clicking around a little bit and stopping.
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Toby Margetts: But I'll do my best to make it as seamless as possible.
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Toby Margetts: What we can see straight off the bat here is a view of the DXP console. Content Health is where content intelligence exists, so we're going to show somebody kind of clicking in there. We're actually using Squiz's website as the example here. We're getting a bit of an insight into, yeah, the AI readiness of Squiz's website. Not a particularly big website, probably quite small compared to a lot of people that are on the webinar.
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Toby Margetts: 212 pages, but nonetheless, it'll be interesting to kind of see what's in there.
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Toby Margetts: When we click in, we can see, kind of, straight off the bat when the last scan was done, when the next scan is due. You'll notice as well, straight off the bat, it's split into two different areas. So, on the left-hand side, we have accessibility, which we've not talked about loads yet.
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Toby Margetts: And then AI readiness on the right-hand side. I'm actually just going to jump into the accessibility side of things to begin with, and then I'll jump into the AI readiness. But it's good just to kind of see how holistic the tool is.
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Toby Margetts: A lot of people use tools for accessibility. Accessibility is super important. The content intelligence covers that in its entirety.
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Toby Margetts: We can see when we click into the accessibility auditor, straight off the bat, we get some really useful information, so we get a view of what your overall accessibility score is. Luckily, ours is excellent, would have been maybe a different story if it wasn't.
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Toby Margetts: But you can see what your score is, you can see how many issues that you've resolved since you last scanned. You can also see, you know, the percentage of pages that you have that have issues. Again, luckily, we're 99.1% of pages.
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Toby Margetts: don't have significant issues, which is obviously great. What we can do is we can actually filter by fix type as well, so you can see here, you can choose either code fixes or content fixes. In this particular example, we're going to have a look at some of the code fixes we might want to do across the site.
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Toby Margetts: under the kind of quick wins section here, this is showing us what things could we do right now that are going to have the most, kind of, profound impact on our accessibility score. So we could click into those and just, kind of, do those straight off the bat.
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Toby Margetts: As we scroll down, there are a bunch of, kind of, useful things related to why we're failing, where we're failing.
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Toby Margetts: We can also see, basically, all of the issues that we have across the site down here, and what a lot of people like to do is to filter by impact, so we can select the critical and serious issues here. We can see that there are three issues, really, that need our attention, and we can then click into one of those to find out a little bit more.
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Toby Margetts: Crucially, what this tool will do, it won't just tell you you've got issues, it will actually give you a solution to that issue, which I think is a bit of a differentiator. That's one thing being told, hey, you've got accessibility issues, and most people would go, yeah, I know, thanks. What do I do? How do I fix them, and in what priority do I need to, do I need to attack them?
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Toby Margetts: So this will tell you why there is a failure, it'll tell you the impact that's having on users, and crucially here, it gives you the fix, right? So there is the current implementation, here is the AI-generated recommended fix. We can copy that, and we can paste it straight into our CMS.
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Toby Margetts: And we get the fix, which is, which is great.
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Toby Margetts: So that's accessibility. Appreciate I've kind of rattled through that in quick time. Very happy if people want to talk to me in more detail about it and have a kind of deeper walkthrough of the platform from an accessibility point of view. Absolutely love to do that. What I'm going to show you now is the AI readiness side of things. So again, panel on the right-hand side when we go into Content Health.
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Toby Margetts: We're gonna click in, and we're going to see some really interesting information. So, the 9 out of 12 score on the left-hand side, that is essentially saying that content intelligence has determined that we have 12 sections of our site, or 12 topics, we call them.
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Toby Margetts: It's saying that 9 of my 12 topics are AI-ready, which is great. There are 3, however, that aren't AI-ready, and that we need to do something, something about.
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Toby Margetts: what it will do, as we scroll down, we can see what all of those topics are. Obviously, most of the people, watching this webinar aren't DXP providers. Your topics will likely be very different to, to ours.
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Toby Margetts: But what we're going to do here is just click into one, more or less kind of at random, to show you what happens when we click into a particular topic.
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Toby Margetts: And then where we can see the problems that we've got, and how we might be able to deal with those.
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Toby Margetts: So what I'm going to do here, we're going to click into the conversational AI searches a little bit better, because we're sort of talking about that as part of the webinar as well. Conversational AI search is a section on our site where we talk about it and what it can do for people, how it can improve user experience.
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Toby Margetts: And yeah, I'll show you a little bit about what it's telling us about that particular section of the site.
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Toby Margetts: So, in here, there are a few really interesting things. So, it is telling us, at the top here, for those who've got, kind of, eagle eyesight, there are 31 pages on our site which cover this particular topic, or have content related to this particular topic.
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Toby Margetts: It also mentions 2,771 questions. So it's really important to understand broadly how this tool works. What it's doing in the background is it is generating, 50,000 plus, sometimes hundreds of thousands of questions.
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Toby Margetts: related to the content on your site, and more broadly about the, sort of, the organization that you are. It is then asking those questions to the LLM, and it is generating answers, based off of the content that you have.
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Toby Margetts: where it is struggling to give answers to those questions, that essentially is where it flags that you've got issues, and it will explain, this is the reason that you've got issues. So, it's basically a really super advanced sort of Q&A tool where it says, here are 100,000 questions that somebody that could come into your website is likely to ask.
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Toby Margetts: Of that 100,000, you know, 99% were getting really great answers, 1% were not. In order to get that 1% up, we need to do, the following kind of, the following kind of things.
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Toby Margetts: So that's just a bit of an insight into broadly, how the tool is working. Again, what this will do, so within the conversational AI search section, it's telling us that there are 31 pages. We could click into that if we wanted to, and kind of assess it in a bit more detail at a page-by-page level.
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Toby Margetts: What I find most of our customers like to do, though, is to actually focus on where we've got priority issues here. So, regardless of what page they're on, this is telling us these are the issues that we recommend you go and sort out first, because they will have the biggest impact on your AI visibility score.
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Toby Margetts: We can obviously click View All and see all of them.
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Toby Margetts: We can also see all of the questions in this particular section, so just under 3,000. We can scroll through. I'm not going to sit here and make you look at 3,000 questions, but you can go in here as a content editor and get an understanding of the type of question that's being asked.
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Toby Margetts: see the response that is being given. I can search if I want to find something very specific that I'm looking for, but it allows us to kind of make that mental bridge between the section of the site and the type of questions that the tool determines are really important.
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Toby Margetts: What we can do is actually click on a particular example that it's called out. This is one of the really high priority, issues.
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Toby Margetts: And again, very much like the accessibility auditor, this doesn't just tell us that we've got an issue, it gives us, a suggestion. So, here it talks specifically about a problem, and this is very much, I've been told I'm not allowed to say, eating our own dog food, it's drinking our own champagne.
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Toby Margetts: It thinks that we have an issue related to this, so we should add a concrete example of answering a complex user query with the postgraduate scholarship scenario. It thinks we've got a gap there.
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Toby Margetts: It explains why that's an issue, and then it actually gives us a really explicit suggested revision. So it says, we think in this section of the site, you should add this copy. This will then allow the LLM to take that information, create a question and answer pair from it, and we'll then be able to deliver a really good answer to the customer.
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Toby Margetts: So, at a high level, it's doing this across your entire estate, which is why it's so good at scale, right? So, a user could go in and kind of manually do this, but across 10,000 pages, that becomes basically a full-time job, probably more than a full-time job.
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Toby Margetts: This tool scans everything, and then orders everything for you, tells you where you need to focus, and it just makes things much, much easier for the content editor.
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Toby Margetts: Finally, what I'm going to do is just show you the kind of final part of the loop, I guess. I'm just going to kind of click into a page on our website and show you conversational search in action.
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Toby Margetts: It's important to realize that the way conversational search broadly works on the front end is it uses that enormous database of Q&A pairings that the tool has generated to generate its answers from. And because they're all sort of compliant and verified, and we know that they're good, it means that the speed of the answer is really fast. We can be really confident that what's in there is correct, because content intelligence has assessed it all and said, yep, great, we can get answers to these
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Toby Margetts: questions. That makes the job of the LLM on the front end to provide answers so much quicker and so much more accurate as well.
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Toby Margetts: So we have it implemented just kind of in our, normal search. A user can go to the site, they can search, so how can Squiz help website engagement and conversions? We hit enter like we would any kind of normal search.
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Toby Margetts: And we get an AI answer to our question, and you can see it only takes a couple of seconds to get that answer. The answer streams, which is pretty cool. It tells us what sources it's generated that particular, that particular answer from.
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Toby Margetts: And as I said, we can be super confident, that the answers that it's given are accurate, because it's all based on content intelligence having verified them. We can, of course, ask follow-up questions, so tell me more about conversational search. I get an answer to my question.
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Toby Margetts: The way that we've implemented on the Squiz site, we have included the search results below as well. We call it, like, a hybrid implementation. You can see search results still exist down here. They don't have to, you don't have to have it implemented that way, it could just be a four-page kind of takeover.
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Toby Margetts: But a lot of people are somewhat wedded to their search results, I would say, and who are we to say that you should absolutely get rid of them straight off the bat?
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Toby Margetts: Alrighty, so that is a walkthrough of content intelligence, conversational search, hopefully a bit of understanding around how practically it can help you across a really, really broad, broad estate.
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Toby Margetts: What we've got at the moment is the ability to try Content Intelligence for a month. If that looks at all interesting, please do scan the QR code or get in touch with myself or Jamie directly. We would be happy to work with you to get that set up, if it's something that you're interested in.
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Toby Margetts: We do also, offer, sort of, the ability to have a bit of a look at some of your content, so we use some of the tooling to say, hey, we'll look at maybe a small size of your site to give you a bit of an insight into how you're scoring. Maybe that's a bit of a toe in the water.
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Toby Margetts: If you're not ready to sort of commit fully to content intelligence at the moment, although we do strongly encourage that customers do, this is going to be something that is so, so important, I think, for anybody who's got any kind of…
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Toby Margetts: Any amount of, content going forward.
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Toby Margetts: In terms of key takeaways, and what we've kind of run through today, there are sort of four key things. We talked up front about the fact that AI search is really kind of magnifying the existing content health problems that people are having.
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Toby Margetts: AI depends on having a strong structure, metadata, authority, and freshness. Jamie touched on that at length. It's so, so important to get those four aspects right.
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Toby Margetts: a repeatable loop that keeps those signals strong. We can't just treat these as, like, one-hit projects and go, yeah, great, we did that 3 months ago, we're gold. It's something that has to happen on a continual basis, because content is being changed and updated so frequently on people's websites.
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Toby Margetts: And yeah, finally, Squiz Content Intelligence is hopefully that tool that can really, really help you do that, to help you stay on top of it, to proactively scan your site, and to say, here are where you've got issues, this is how you go and deal with them.
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Toby Margetts: That's so useful when you've got content being constantly added to a site, potentially across devolved teams. Yeah, that, to our mind, beats doing content audits any day of the week.
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Toby Margetts: Given the nature of them, where they take maybe 3 months to run, and by the time you finish them, half the content on your site maybe has changed anyway.
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Toby Margetts: That's it from Jamie and I. I did see a flurry of questions flying in as we were going, which is amazing, and maybe we can jump into some of those and talk a little bit about them.
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Toby Margetts: I'm happy to jump in, Jamie. I don't know, Jamie, if you've got your eye on any in particular that you fancied answering. I did see one crop up, I think it was maybe the first one that came in.
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Toby Margetts: which was, in terms of freshness, can this be as simple as going into a page and updating slash republishing it? Will an LLM know that that's happened? Basically, yes, it can absolutely be as simple as that, so content intelligence would
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Toby Margetts: go in, and it would say, yep, you have got some out-of-date content here, we recommend that you go in and make it up-to-date. Of course, the beauty of that, using that tool is it will find all the instances of that.
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Toby Margetts: And then, yeah, the next time that you scan your site, Content Intelligence will say, yep, great, we don't have that issue anymore, the content is fresh now, it's not out of date, and it will proactively kind of keep you, keep you on track in that way. So yeah, in short, you're kind of, you answered your own question there, and LLM will.
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Toby Margetts: Once it re-indexes the page, it will be using the new information, because that's the most current. It won't be using, kind of, archived content.
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Jamie Sharp: Yeah, and I would maybe just add to that, you know, like, you don't want to think of freshness as just being performative, like, the readers and the governance processes could stop trusting it. So again, this is where, like, don't overthink it, stick to having that, like, methodical process, like we've demonstrated with the loop. Having a tool in there that can just direct you to where you need to make changes is the best thing to do, rather than just feeling like you need to make performative changes just to tick a box.
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Toby Margetts: Yeah, 100%, great, great shout.
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Toby Margetts: Yeah, to pull out maybe a couple more, what is the best way to decide which pages need attention first? It's a great question, and actually, like, so much of the, sort of smarts and intelligence that went into building content intelligence was around that kind of exact question. It was like, hey, there are sort of tools out there that are sort of okay at telling you what you need to do.
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Toby Margetts: But there aren't many that actually are really good at telling you where you need to start, and that's so crucial when you're dealing with, you know, a big website with thousands and thousands of pages.
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Toby Margetts: It can be overwhelming, even for content intelligence, to say, hey, yeah, you've got, you know, like, 50 critical issues, and you go, right, okay, where do I start? The tool will specifically call out the most profound impact to your AI readiness.
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Toby Margetts: will be, by changing these particular things. One thing that's actually really interesting is, so that shouldn't… there is a bit of nuance here, that shouldn't necessarily just be dictated by, like, having a bad score. So if there's a web page that has a particularly bad score.
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Toby Margetts: That isn't necessarily the first place to start, so…
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Toby Margetts: To give, like, a bit of an analogy, if that's not a very high-trafficked page, say 20 people visit that page a year, and the content's in bad shape.
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Toby Margetts: that's maybe not as big a priority as some content that's in better shape, albeit still not great shape, but that gets thousands and thousands of visits a year. Obviously, there's a bit of balance to be had there between how sort of visible and active that page is.
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Toby Margetts: And the tool will factor that in. It's kind of based on risk as much as anything, so…
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Toby Margetts: Not just about what's got the lowest score, it's about what's got
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Toby Margetts: The most kind of visibility and is having, you know, the most impact on your particular users.
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Jamie Sharp: Yeah, nice. We did get a question about a lot of our important information lives in PDFs, how should we fit those into a content health routine? And that question comes up a hell of a lot.
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Jamie Sharp: So, you know, like, as part of… as part of the process, we can absolutely scan those PDFs and provide answers on that, but what… what our strong advice would be is to try and keep
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Jamie Sharp: PDFs when it's required. So, you know, if you need formal documents, printable forms, signed publications, things like that, but don't try and force users or AI into extracting basic guidance from PDFs. Our strong advice with regard to PDFs, and I know it's difficult, especially for a lot of organizations that are sort of deeply embedded into having heaps of stuff in PDFs, but try and track PDFs as
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Jamie Sharp: assets with an owner and a review cadence, and prioritize trying to convert as many of your, sort of, frequently asked questions into proper content. That will make it way easier for you to be confident that you're getting the right answers, that it'll be really visible and well-cited by AI, and obviously making it much easier for human
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Jamie Sharp: users to also find the content that you want them to get at, so I think, you know, as part of this process, it's an important and really useful step to be thinking about, actually, like, what information should live in a PDF, and how best to handle that as well. Did you want to add anything to that, Toby?
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Toby Margetts: I don't think so, I think you covered it really nicely. Yeah, we, like, PDFs are a bit of a sort of dirty word, aren't they, these days? Ideally, you don't want to have them on your estate, but we understand that people do, and, you know, it's not easy to just say, hey, put everything into HTML. But yeah, I think outside of that, you covered it really well.
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Toby Margetts: one of the final questions in here is around, getting content intelligence set up, or how easy is it to get it set up? The answer, the short answer, I guess, is, like, it's very, very easy to set up, so…
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Toby Margetts: There's maybe, like, a sort of 3-4 step process, where you literally insert the URL of your site, and it will basically scan everything and all of the child pages underneath that, so most people would put their homepage URL in, and it will scan absolutely everything.
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Toby Margetts: You can choose to exclude things if you want to. Often people don't, because they want to see a view of everything, but sometimes there is a need to, maybe if there's a part of the site which is, I don't know, going through a ton of changes at the time, or whatever.
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Toby Margetts: often a few different reasons why certain things might want to be excluded. You can do that. You simply just enter the URLs of what you want excluded.
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Toby Margetts: You then have, like, a drop-down list where you say how frequently do you want to run the scan, so it could be quarterly, it could be monthly, it could be weekly. You could do it every day if you wanted to, if you had a real, kind of, sort of fast turnaround of how content is created. But yes, as I say, it's like a three, four-step process. You run your first scan, it will tell you all of the different topics that your site is comprised of.
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Toby Margetts: You then decide, of those topics, which ones you want to monitor in more detail. You might want to just look at everything, or you might say, nope, we want to focus on this particular part of the site to begin with, and work through it in whichever way that you see fit.
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Toby Margetts: But yeah, basically, it's super easy to get set up. We also have, a fabulous customer success team that onboard you in the tool.
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Toby Margetts: To be brutally honest, like, the tool is so easy to use, you don't really need customer success to onboard you, like, it is super straightforward and intuitive, but we do like to have customer success kind of just there when we get everything set up to make sure people feel comfortable and we have any kind of questions answered.
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Toby Margetts: But yeah, 99 times out of 100, I would say, customers are perfectly capable of, kind of, almost onboarding themselves, because the tool is so straightforward and intuitive to use.
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Jamie Sharp: Yeah, 100%.
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Jamie Sharp: I can see a couple more questions that popped into the chat, so I can see, and David's asked, can content intelligence be used for non-squiz matrix sites, such as WordPress? Tom's just jumped into the chat to say, yes, it can, but it absolutely can, so it's, completely tech agnostic, and obviously, again, we have lots of customers that use our full DXP suite, but then also, you know, oftentimes there'll be a swathe of, I think, content that they want to capture that's elsewhere, so yes, you can add
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Jamie Sharp: Absolutely plug it in, run it across your entire estate, doesn't matter what tech it's on, it'll do the same job across everything.
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Toby Margetts: Love that. I think, that's everything in terms of what came through in the Q&A. I'm not sure if there was anything else, Jamie, in the chat that we missed,
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Toby Margetts: If not…
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Toby Margetts: we can probably, probably call it there. I would just finish by saying, yep, thank you very much for, all of the engagement and the questions that have come through, that's, that's great.
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Toby Margetts: If you're interested in the tooling at all, or just have any kind of further questions about it, feel free to scan the QR code. Feel free to fire a message through to myself or to Jamie. Always happy to answer anything via email or jump on a call, do a demo to whoever would like to see it. Yeah, we're always on hand to help out.
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Toby Margetts: So yeah, Jamie, thanks very much for joining us today. It's been a great session, and yeah, we'll see everybody at the next one.
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Jamie Sharp: Yeah, look forward to seeing you all soon. Thank you, everyone. Thanks, Toby.
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Toby Margetts: Thanks, bye-bye.
Video: Watch the webinar (UK). Captions and transcript available on playback.
Poll Results
- Out-of-date information – 34%
- Too many requests and no clear priorities – 26%
- Duplicate or conflicting pages – 24%
- Gaps nobody spots until a user asks – 16%
- In the last three months – 33%
- In the last six to twelve months – 27%
- More than a year ago – 25%
- Never, or not that I know of – 15%
Watch the US & Canada webinar
Transcript: Watch the webinar (US)
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Megan Andrews: Hello, everyone! Welcome to our webinar today. I'm Megan Andrews, Director of Client Partnerships here at Squiz, and I'm joined by my colleague, Fran Zablocki, our Client Strategy Director.
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Megan Andrews: And today, we're gonna have some exciting content for you. Everything in this webinar is about being found by AI. So, really good tips to keep your content healthy, and just keep up with the pace of all the change we see today with AI.
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Megan Andrews: So, couple housekeeping items before we jump in.
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Megan Andrews: First of all, feel free to scan this QR code. You can access a one-month trial of Squiz Content Intelligence. So, get a little insight into your content, get a little head start.
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Megan Andrews: The other thing is, we will be recording this, so if you have to leave halfway through, or you want to share this out with colleagues after, you can do that. We will send out a link to the recording, and also any follow-up questions that we weren't able to get to today. So…
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Megan Andrews: Let's get into it, Fran. Exciting stuff today.
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Megan Andrews: Really quick introduction. If you're not familiar with Squiz, you probably are, but we're a digital experience company.
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Megan Andrews: So, if you're operating on any sort of scale with your organization, you're probably using lots of different tools across your tech stack, and the great part is Squiz has all these different types of tools to help you manage your digital experience across your site.
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Megan Andrews: You can find out more on our website, but certainly we'll talk a little bit more about one of those tools today.
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Megan Andrews: So, get out your pens, or your typewriters, and get learning today. We're gonna have four different areas that we really address. One is just, why does good content practice break down? If you're on a content team, you know this can happen, it's okay, it happens to the best of us. But we'll look at some of the reasons for that.
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Megan Andrews: And if you've joined our webinar series, the last one we gave was about these four AI discovery signals. So…
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Megan Andrews: Again, new information, a new era. We'll revisit those and talk through how that impacts your content and its discoverability.
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Megan Andrews: We will also look at how to use those signals in… in practice. What does that mean for how you're looking at your content, optimizing it, and keeping up to date with that content on your site? And then the fourth area is just how Squiz Content Intelligence as a tool can help you do this, and, you know, optimize and monitor that content.
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Megan Andrews: not just once, but at scale and repeatedly, right? So that's the part that's pretty hard, is content can be in great shape for a moment in time, but how do you continuously monitor it at scale?
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Megan Andrews: So, in theory, yeah, I think about this sometimes, Fran, where it's like these beautiful moments where maybe your team has done this website redesign, and you're so excited about it, you're like, ugh, our site's down to a thousand pages, and we know each one of those pages is thoughtful and curated and good to go.
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Megan Andrews: And for, I don't know, 6 months, maybe even a year, you feel pretty good about that, right? But over time, things start to happen.
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Megan Andrews: And, it's really hard to, over time, keep up with things, but also with just new best practices and things we're learning with this changing environment of large language models. So…
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Megan Andrews: Things we're used to, right, on content teams. You've got those beautiful pages, and then, oh, there's a whole new campaign! So we've got to build out this little, little sub-area of the site, new content, new requests there from different teams.
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Megan Andrews: The aging pages, look, most of us aren't in brand new companies or organizations. We've been around for a minute. Sometimes things have been, published for a decade or more.
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Megan Andrews: And it kind of stacks over time, too. You can imagine, different deadlines that come up across year to year.
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Megan Andrews: Maybe you have an orientation page that was… August 19th was an orientation day last year, but it's gonna be August 20th this year. Do both those pages still exist? Do they have conflicting content?
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Megan Andrews: And maybe your team has gotten really good at auditing.
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Megan Andrews: Once. And then, did you do it again? How stale was that audit after time? Did you have a good way to keep up with your auditing process?
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Megan Andrews: And I think all of us understand that, you know, the firehose of requests that can come your way, and just trying to understand, you know, where do we need to prioritize our time and our team's time to keep up with content. So, these are a lot of the common pitfalls, right, Fran? And I'm sure you've seen some of these across time as well.
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Fran Zablocki: Yeah, absolutely. You're reminding me of another thing that feels very similar, and that is gardening. Getting your whole garden nice and weeded and cleaned feels terrific, but it's always gonna need it again in, like, a week or two. So, good constant maintenance is key.
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Megan Andrews: It's true, and you want to… you know, like, finding the times, too, at scale where you need to bring other people in, recruit your daughter to come in and help you out on some of those days.
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Megan Andrews: Am I right?
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Megan Andrews: So, yeah, I think the other thing, too, is that, there… in a world of SEO, where we've been, there are ways around, content that's not great on your site. When I think about the impact of large language models and AI,
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Megan Andrews: Really, it's putting… casting a magnifying glass across every page on your site.
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Megan Andrews: And what I visualize is that moment in 2022, or whenever all these models were going out across the entire internet. They were indexing every single part of the internet.
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Megan Andrews: And so, if you had pages that existed and were published on the web, those were ingested by a large language model. Now, they're not constantly doing that all the time, but some are, and in different ways, and so…
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Megan Andrews: The real question is, when any of these new platforms, TrachiPT, Gemini, we're all using these.
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Megan Andrews: When users go to these sites and they ask a question, there's a lot of different paths in terms of what's gonna come back and be surfaced in that response.
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Megan Andrews: Now, some of these, models are relying on indexed information, or some combination of indexing and then going out and looking in real time.
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Megan Andrews: But what is true is that regardless of what's, being asked, once those models go out, if they can't find consistent, current, structured, clear information on a site, whether they did it, you know, 2 years ago, or they're doing it in real time.
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Megan Andrews: it's gonna skip over, that actual content. It's just not gonna pick it up, not gonna surface it in the response.
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Megan Andrews: So, if there's this stale, duplicate, again, things we talked about, conflicting information, it's outdated, you know, it's just a bypass. It's gonna go find some other source that's more relevant and better organized.
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Megan Andrews: So, while you might think you can get away with some things, those audience questions, they're gonna rely on good content underlying it, to give a clear, specific response.
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Megan Andrews: So, we'll engage with you all, because I am very curious. Which of these do you see most often in your own content?
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Megan Andrews: So we've got… is it out-of-date information? Duplicate or conflicting pages?
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Megan Andrews: Gaps nobody spots until user asks.
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Megan Andrews: Or too many requests and no clear priorities. Fran, I'm curious, what do you think we're gonna see here?
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Fran Zablocki: I suspect a little bit of everything. I imagine that everyone probably experiences a little bit of this on some level, but the one that comes up in conversation most is that last one, too many requests and no clear priorities. I feel like that's less of a content thing and more of a governance thing. A lot of times, the folks managing content on the website just have so many people asking them to make changes all the time, and it's hard to predict when that's coming in, so it's definitely been top of mind for people.
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Fran Zablocki: I've had lots of conversations on that point.
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Megan Andrews: Yeah, great point. And I've seen some duplicate pages, too, like, a good way to understand what's duplicated and what's going on there.
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Megan Andrews: Let's see, do we have the results? We do. Okay.
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Megan Andrews: Gaps, nobody spots until a user asks, about 40% of you. That's really interesting. Yep, how do we get insight into what's happening on those platforms? And you're right, that too many requests, no clear priorities, and out-of-date information, both at about 30%, so…
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Megan Andrews: Interesting. Well, you are all in line with each other, just common challenges right now.
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Fran Zablocki: Right, so what are some of the specifics on these discovery signals that
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Fran Zablocki: will tip you off that AI might struggle with, right? So, if you attended our previous webinar, we went in a deep dive on structure, metadata, authority, and freshness as the four AI discovery signals.
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Fran Zablocki: And there's some scenarios in which, AI is just gonna have a hard time, right? So, if you don't have clearly structured information, and this is best practice that has gone back a while, right? If you don't have structured headings, structured content,
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Fran Zablocki: if you don't necessarily have a single topic with subtopics in an organized way, AI is going to struggle with that, just like SEO struggled with that in the past, and just like human beings struggle to read, right? If it's not, you know, if it's not scannable, if it's not obviously organized, AI is also going to struggle with it.
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Fran Zablocki: On the metadata side, we need to make sure that
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Fran Zablocki: AI can understand what the page is about. And this also overlaps a little bit with traditional SEO, because we're looking at things like page title and URL path and
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Fran Zablocki: in particular, the meta description. I know in my experience that
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Fran Zablocki: One of the most common gaps is that either there's no meta description for the page, or there's a default meta description that's being used across tons and tons of different pages, and in both of those cases, that's gonna kind of erode AI's trust as to exactly what this page is about, and also that this page is unique and has, you know, a particular purpose.
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Fran Zablocki: On the authority side.
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Fran Zablocki: This is actually authority of what is on the page, not necessarily your brand authority or equity that you've established, there.
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Fran Zablocki: This is… Really making sure… that…
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Fran Zablocki: has a dedicated page. Probably the closest equivalent in the SEO world would be, like, having a canonical page, right? This is the one page that…
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Fran Zablocki: is the source of truth on this particular topic. And where authority can start to erode, and where AI may struggle, is if you have multiple pages that either have identical content around that exact topic, or really, really similar content. And this happens easily over time, right? People want to put as much information to be helpful as possible, but over time, several different units or departments replicate each other, and then have slight variations. And that may not be something that a human would pick up.
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Fran Zablocki: on, because it's spread out across the site, but AI will pick up on it right away, and it will erode that trust. It will think to itself, I'm not really sure which of these three versions to believe, and so I'm just not going to include you in the results.
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Fran Zablocki: And then the last one, on the freshness side, is pretty self-evident, right? Like, we want to make sure… this is really what we're focused on today, is, like, making sure that we're checking to be sure our…
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Fran Zablocki: content is up-to-date and hasn't been, you know, hanging out for 10 years, like Megan mentioned, or to make sure that we don't have multiple versions of the same thing with multiple dates. This is a really common issue as…
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Fran Zablocki: websites grow. You have annual or maybe semi-annual reports that go out, or information that goes out, whether if it's in higher education, you have courses that are being updated every semester, or whether it's financial aid information that has tables associated with it that get updated every year.
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Fran Zablocki: if you don't clear out the old versions of those, they're gonna end up competing with the new versions, and they're gonna confuse the AI answer, and in a lot of cases, erode that trust as well. So, that's, you know, some really typical scenarios in which
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Fran Zablocki: These discovery signals, if we're not doing a good job with upkeep, can start to, make it hard to show up in those results.
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Fran Zablocki: Alright, so, what's our solution here? It is a simple four-step.
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Fran Zablocki: process, a content health loop for AI discovery. Fairly straightforward. The first step is to plan.
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Fran Zablocki: It's always good to have a plan at the beginning. The second step is to publish, and that includes making any changes, that's new pages or edits to existing pages. The third step is to monitor and make sure that we're keeping track of how those changes and new pages are performing, and then once we see how they are performing, the fourth step is to improve and iterate and rinse and repeat, right? This is an ongoing cycle, and it's something that can be applied either in the micro.
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Fran Zablocki: for an individual page, or in the macro for an entire site. But as we'll talk about a little bit more, when you start to scale this up for a site that has hundreds or maybe thousands of pages, that's when it gets really, really labor-intensive and really, really difficult. I'm sure that's no surprise to any of you. I mean, I think that…
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Fran Zablocki: In my experience working with content for large institutions over 15 to 20 years now, I think
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Fran Zablocki: The reality is, and this is to make everybody… Feel a little bit better.
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Fran Zablocki: The reality is that most institutions don't even get to 100% of their content because they just don't have the time to get to 100% of their content. So not only is the tool that we're going to talk about today going to allow you to
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Fran Zablocki: save time on the pages you are looking at, it's actually going to make it possible to get coverage across the entire website, in some cases for the first time, or at least, you know, much more
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Fran Zablocki: readily than, you know, like, a major, major content effort would be, to do it manually. So, that's the content health loop. Let's drill down a little bit into the different steps.
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Fran Zablocki: On the first step plan, it's always good to have a plan.
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Fran Zablocki: it's always good to know where you are before you point to where you need to go, and so the first thing to do here is to just get that audit and get that assessment. And you can see we've taken some screenshots of our content intelligence tool to the right. That's what content intelligence does a really good job of. It gives you that macro view of overall site health and readiness from the AI side, but it also drills down into specific topics and pages.
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Fran Zablocki: In terms of where they're at and what kinds of improvements that they have. So… Planning really makes sure
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Fran Zablocki: you just know what you have, and what it contains, and you can start to identify things, even at the planning stage, that are going to be easy fixes, like really old content, or duplicate content, or things that are missing, things like, you know, the correct meta description, like I mentioned earlier.
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Fran Zablocki: The next step is publish, and this is really where AI discovery signals can be strengthened, right? This is where the change is actually taking place.
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Fran Zablocki: I talked a little bit about each of those discovery signals and what, you know, can erode AI trust.
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Fran Zablocki: But this is where you're addressing things like structure and metadata and authority and freshness, and we're trying to make those answers easy to find and understand and trust. So this is really you getting into the page, into the CMS, and making the changes.
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Fran Zablocki: The next step is to monitor, and this is…
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Fran Zablocki: The thing that easily falls through the cracks, if it's something that we have to do manually, and why something like content intelligence is so valuable, because even after you've published, it's going to be taking a regular look at everything that changes.
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Fran Zablocki: And it's going to be re-ranking things to show you how much they've improved, both on the overall site level and on the page level.
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Fran Zablocki: I like to divide up the monitoring plan into prioritization of pages, right? So, like, you don't necessarily have to monitor 100% of your pages every week or two, but you probably want to monitor your really, really important pages.
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Fran Zablocki: every couple weeks or every month, and you want to get to everything at least once a year, and I'd even recommend, like, every 6 months. We've… there's been some studies out that have shown that, like, after 6 months, AI's signals for freshness really start to erode, so it's looking for things that have been published within the last 6 months. So,
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Fran Zablocki: Anyway, it's possible to actually look at certain pages more frequently. You might look at the most important ones 3 or 4 times, before you look at some of the least important ones once. Now.
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Fran Zablocki: how do you know which ones are most important and least important? One way is to take a look at your overall traffic, and analytics can help that. But I would take that traffic, and I would cross-reference it with what you know to be your core
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Fran Zablocki: customer journeys, or student journeys, depending on your industry. So, you know, let's take higher education, for example. A prospective student is going to need some really top-line information in order to enroll. They're probably going to need to look at all the admissions content, your academic program content, maybe your campus visit content. So start with all the different pages that belong on that path.
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Fran Zablocki: And make those a priority. And then make those pages that are getting a lot of traffic a priority, and, you know, when you cross-reference both, it's high traffic, and within that critical path, it should be the first group that you take care of, and so on down the line.
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Fran Zablocki: Alright, next step is… to improve. And so, once we know what has…
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Fran Zablocki: A gap, we want to make sure to decide what we need to do with that, and some common scenarios that you might run into here, and considerations for those scenarios.
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Fran Zablocki: R. Finding, an important question does not have gate, because it's going to say, here's… here are the questions that, you know, people are asking.
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Fran Zablocki: here's the questions that I, as an AI tool, am asking, that I'm getting, you know, I'm getting answers that aren't quite good enough.
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Fran Zablocki: 2, and so that will point out which pages need to create a focused answer, whether it just doesn't exist at all, and you might need a new section on a page, or a completely new page, or whether it's just that the content of the page just needs an update. Perhaps it's to change the H2 title
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Fran Zablocki: to the form of a question, and tailor that next paragraph that's after that H2 to more directly answer the question. That's kind of a practical step there.
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Megan Andrews: One thing I'd like to point out here and remind people of, too, because you make such a good point that generally as humans, right, we don't necessarily think in terms of… unless we're content people. Like, oh, that H2 could be different, or we could ask it, you know, phrase that a different way.
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Megan Andrews: this is… this tool is driven by a large language model giving an evaluation, so it's actually really helpful. We don't always, as humans, think in those terms. We might look at a page, visually assess it, right?
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Megan Andrews: And as a content team, think, we're good.
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Megan Andrews: But this is something we might miss, right? Where it's like, actually, the structure of this page, underlying this page needs to be addressed. I think that's helpful to keep in mind as you think about these things. There's two ways to design things, humans and bots, right?
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Fran Zablocki: Yeah, definitely. And they don't have to be at odds with each other, you just have to make sure that you're doing the right thing for both sides. And there's a lot of overlap, but there are some particulars around AI that, yeah, humans would not necessarily notice.
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Fran Zablocki: So, next scenario is several pages competing or contradicting. Kind of talked about this with, you know, source, ultimate source of truth.
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Fran Zablocki: what's the practical solution to that? Consolidating into one source of truth. That could be really explicit, like, you're just gonna make this page the only thing that has this content on it, but more than likely, you're gonna take one of the pages, make it the source of truth, and then look at the other pages that had repetitious content, and change that content to a reference to the source of truth page, right? So instead of trying to go into all the detail on that page.
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Fran Zablocki: You just want to create a crosslink to that page that mentions that particular topic.
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Fran Zablocki: And the last one is just content that's stale or expired or critical, and this is just that gardening analogy where we just need to make sure we're clearing out the old stuff, and we don't have old dates and figures and financials sitting around that are causing things to get
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Fran Zablocki: messed up in the, in the results. I typically take a rubric for this, that if anything is over a year old and has really low traffic, it is a prime candidate to retire.
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Fran Zablocki: there's gonna be exceptions. There's usually some really old pages that just have legs, because they're an article that somebody wrote that gets traffic annually, perennially, and, you know, you want to make sure to keep that. But use your analytics, use your, you know, age of page.
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Fran Zablocki: Use traffic to determine what can be retired, because tightening up the pages themselves and making sure that you don't have bloat is going to help with overall results.
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Fran Zablocki: Alright, so those are the four steps. Sorry, go ahead, Megan.
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Megan Andrews: You know, one of my favorite examples, we had talked about this a little earlier, was, I think… here's a practical question for you. So let's, many of you may know, like, Steve Jobs gave a very famous commencement speech, and…
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Megan Andrews: It was super popular, it's popular across YouTube, all these different places. It happened to be at Stanford University, and Stanford hosts a page that has that, commencement speech recording on it.
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Megan Andrews: and trans, transcribes it. So…
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Megan Andrews: It's a very popular page that people visit a lot. That…
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Megan Andrews: That speech was given in 2006, right? So, that's 20 years ago now. What do you do with that type of page? To your point, there are these types of pages, really popular articles, things like that. How do those sit with the freshness perspective? What do you do about those?
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Fran Zablocki: That's a really, really good question, because you can't really change the original publishing date, right? Like, you want to keep that, so it's got the historically accurate time.
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Fran Zablocki: But I could see actually creating some additional promotional content that is fresh and has newer dates to it to call attention to that… that page, right? And, like, referencing that page from a couple of different places. Or maybe, you know, create a new news article that is revisiting, you know, Steve Jobs
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Fran Zablocki: speech from 20 years ago in the light, you know, in today's context, or today's light, and then, you know, that kind of, like, surfaces it in a more modern context. If it's something that is, you know, an evergreen page and not a news article.
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Fran Zablocki: then just changing the content on the page and changing the dates will… that'll be it. But yeah, it's kind of a balance between, like, maintaining the historical record, but also, like, calling attention to it with some new, fresh content.
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Megan Andrews: Nice.
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Fran Zablocki: Alright, so, here's the honesty question. When did you last audit your content?
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Megan Andrews: Oh, boy.
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Fran Zablocki: be afraid to answer never, because that is actually a fairly common answer, right? Like, maybe you just haven't been able to get around to it, and that is exactly why we have tools like Content Intelligence to help you be able to get, you know, get through that thing that you just haven't had time to do.
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Megan Andrews: I like the never or not that I know of. You could claim… I mean, I'm not aware of an audit.
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Megan Andrews: But this is great. I will be curious, again, be honest in this, it's really good to understand what people are, are actually experiencing. And we do have a question, too, that I'd like to get to, Fran after this, related to…
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Megan Andrews: to content summaries. You know, there are lots of different ways and tools. There's everything from spreadsheets to something like content intelligence, but here we go.
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Megan Andrews: Oh, 20%, never, not that I know of. Totally fine. Most people sitting right around either in the last 3 months or 6 to 12 months, so that's pretty good. 30% each. Good job, everyone.
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Fran Zablocki: Pretty even split across everybody.
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Megan Andrews: Yeah.
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Fran Zablocki: Good work.
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Megan Andrews: Now, one question that came in that I think could be great to address here, and it's more a comment, but we could riff on this for a moment. We are a two-year community college, our SEO tool customer success manager mentioned AI overviews.
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Megan Andrews: And ways to get found in them. One of the ways is to have good quality content. So, AI-generated content is usually vague.
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Megan Andrews: And so this is a question around, or comment around AI-generated content.
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Megan Andrews: So, guess that's something to call out here. We're not necessarily saying, use this tool to generate content, right? It's very different from that.
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Fran Zablocki: Yes, yeah, I think… Using AI to generate content is only…
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Fran Zablocki: useful as a very first draft, and I think a lot of other people kind of share that, sentiment. Like, for example, the content intelligence tool is going to suggest
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Fran Zablocki: What you might… how you might want to position new content, but…
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Fran Zablocki: ultimately, you're the editor, right? Like, you're the one who needs to make sure that you agree with that statement, and that, you know, that's something that you want to publish, but I wouldn't be our recommendation to necessarily flood your site with AI-generated content. In fact, in a lot of cases, even the company… I was just reading an article yesterday, actually, that the companies…
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Fran Zablocki: Who are providing.
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Fran Zablocki: easily created AI content are now starting to realize just, how much has been flooding their platforms, right? Like, LinkedIn just put in a button that said, like, please report AI slop.
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Fran Zablocki: And so, I think it's really important for it to be human-created content. Maybe AI-assisted, but human-created, ultimately, in the end. And yeah, so we're, you know, like, our system is going to identify where things need to be improved. It is using AI to help you do that, but the actual content generation should definitely have, as they say, like, a human in the loop, and the human is the last step.
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Megan Andrews: Yep.
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Fran Zablocki: Alright, so, we know it's a lot of work.
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Fran Zablocki: We know it sometimes takes too much work to do, and we don't get to all of it, and that's why we created Content Intelligence. So, good practice at scale. We just want to be able to do all of these good practices that you've probably been doing manually, and create a tool
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Fran Zablocki: that can do this at scale across the entire site, and then maintain it across the site, so you just feel like you're on top of it, at all times, and not falling behind. And so…
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Fran Zablocki: On one page, very easy to do. On 10,000 pages, not so much. So…
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Fran Zablocki: Some of the other challenges, it's not just volume, it's also just…
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Fran Zablocki: how many people you have working on content, and where they're located, and how much you communicate. If you're in a larger institution that's decentralized, you might have 100, 200 different people managing content on the website. Coordination amongst them can be tricky. People will have different levels of
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Fran Zablocki: familiarity with all of these topics and content management in general, and so the level of quality and consistency, maybe with your branding and your voice and tone, might be, you know, there might be some gaps there. That's how we end up with multiple pages answering the same question. It's also how we end up with, you know, review dates and owners that are all over the place and that get really hard to track and centralize.
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Fran Zablocki: Publishing models may allow certain people to publish, but they might be…
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Fran Zablocki: are kind of breaking their rules or not practices. So overall, changes happen faster than manual audits can keep up, and once you actually have the audit.
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Fran Zablocki: in place, it's very difficult to take, you know, a thousand recommendations and decide which of those thousand to start with without some kind of prioritization list, and that's another key component of content intelligence that we'll… we'll show you shortly.
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Megan Andrews: Let's show them. How about that?
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Megan Andrews: We'll do a little video for you. Now, just a heads up, the video moves quickly, so our voices will as well, but you'll get a good idea of what exactly content intelligence looks like.
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Megan Andrews: So, if you were to log into your SquizDXP and go into the Content Health area, this is the backend, this is what you'd see currently.
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Megan Andrews: And this tool actually is split, right, into accessibility and AI readiness. So, it's really top of mind for everyone right now. Turns out good accessibility is critical to AI readiness and visibility. So, that's why we've paired them together. We'll take a look at the accessibility piece first.
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Megan Andrews: At the top, you're gonna get your score, your kind of roll-up summaries of everything that's going on across your domain, or the site that you've plugged in here.
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Megan Andrews: And then, I love this piece. Is it a content fix? Is it a code fix? Do I need a developer or a content editor? Really easy way to filter those quick wins, depending on who's in there. And then just snapshot of some different patterns and things it's seeing across your site.
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Megan Andrews: And of course, that big old scary long list, but don't worry, you can filter it by just focusing on what is the most critical thing we need to do, or most serious update.
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Megan Andrews: or violation here on the site. And clicking into those, it gives you all the context you could want, probably more than you would ever need, but you will deeply understand what exactly is going on, the impact it has.
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Megan Andrews: And it shows you, side by side, what's on your site right now, and what is that recommended fix that would, alleviate this issue and resolve it for you. So…
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Megan Andrews: That's a really helpful way to go through the accessibility side of your site.
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Megan Andrews: And Fran, how about AI?
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Fran Zablocki: Right? Alright, so accessibility is for humans, and the AI readiness is for the bots, is, like, what we like to say. Same kind of overview, right, giving you an overall health rating, then breaking it down into the individual topics and showing you how well you're performing. Now, this is showing…
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Fran Zablocki: Squiz.net is our website, so, priority issues, but we do have some remaining, and even without the high priority issues.
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Fran Zablocki: identified with an AI-ready section, there's plenty of detail contained within, right? So in this conversational AI search topic, there's 31 pages that are included in that topic, and we have 4 low-priority issues that we need to deal with. Each one of those is detailed in that list there, and you can drill down and see exactly what it is that's the issue. This next part, where it says 2,771 questions, is where it is emulating and showing exactly how that fan-out quiz
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Fran Zablocki: It's working, and so…
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Fran Zablocki: you can look through every individual question and see how it's being answered. It's really quite impressive. Now we're looking at an individual issue detail and some suggested revisions, so…
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Fran Zablocki: to that question earlier, it's just suggesting what you should include, and, you know, really, you should take that and edit it and publish it as you like. And it's also showing all the different pages that are referenced for this issue, and then if you, if you want, there's a link out to the specific page of your website to just make it easy to look at.
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Fran Zablocki: Now, we're looking at the Squiz
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Fran Zablocki: conversational search interface installed on our site. Feel free to go to Squiz.net and try it out for yourself. It's the best way to kind of get used to it. But this is the newest version of our search that incorporates this type of AI
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Fran Zablocki: conversational search functionality that we've gotten used to with things like ChatGPT right into the experience and flow of your website, right? So, it's got your answer in there, it's showing the different sources, it's also a place to do follow-up questions so that you can create a conversational record there.
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Fran Zablocki: And it's still paired with the traditional search results as well. So, it's very rich, kind of giving you the best of both worlds. You get that conversational AI response, but you also have that faceted search set that, you know, we've all been used to over the years, and between those two things, you're really getting a rich set of information for the questions that you're asking.
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Fran Zablocki: Okay, let's see where we go next here.
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Megan Andrews: Nice. Wow. Thank goodness.
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Fran Zablocki: Okay, here we go.
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Megan Andrews: I think that's it.
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Megan Andrews: No, we did it, and it's… you know, it's a lot of… it's a lot to take in. I think, probably a lot of this is just understanding how to equip your team, right? There… there's a manual approach that's gonna really be painful, and so…
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Megan Andrews: We're just talking through one possible solution and tool here. If you do decide you're excited and want to try Content Intelligence for a month, scan that QR code again. It will give you access to that,
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Megan Andrews: not only the AI search visibility, but that accessibility auditor.
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Megan Andrews: And give you those prioritization of fixes. And it works with whatever stack you're using, it will work.
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Megan Andrews: So that's the great piece. It is super easy to do, no matter where, where your content lives at this point. We do have a question that came in, will this video be shared afterwards? Yes, it will. So if you're registered for
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Megan Andrews: the webinar, that, email address you put on file, we're gonna go ahead and blast out everything that we did here today, including the recording. So, a look back. Key takeaways. What in the world did we talk about today? Really big point is just that AI, the AI world, it's really putting magnifying glass on your content, and that includes your content health issues or problems.
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Megan Andrews: Again, those signals that you really need to be aware of, because AI depends on them. It's strong structure, metadata, authority, and freshness. So hopefully we talk through some different good examples for you there.
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Megan Andrews: And then, a repeatable way to keep those signals strong, they could be great for a moment in time, and then over time, we've seen, right, different examples of how that could, decline. And Squiz Content Intelligence helps you do that, not just as a snapshot, but really at scale over time.
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Megan Andrews: So we'll see if we have any more questions. I saw a couple more come in in the chat.
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Megan Andrews: And let's see, here's one. Does having a page not indexed affect AI's ability to crawl that page? Fran, what are your thoughts there?
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Megan Andrews: Oh.
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Fran Zablocki: Sorry, I'm muted. I've been trying to find that article, which we're going to share momentarily. It was a New York Times article, so, so we'll follow up on that.
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Fran Zablocki: if you have something listed as noindex, it's not going to get picked up. So that is actually something that came up in our previous webinar as, like, the very first
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Fran Zablocki: gate post for being picked up by AI search results, and that is that if you've basically, you know, closed it off, as noindex, or if it's something that's behind a login, right? So if it's on an intranet or portal, it's just not gonna… not gonna show up. It's not gonna be able to get access to that.
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Megan Andrews: I had a great example of this, actually. We were putting the AI tool across one of our early higher education sites, a big university, and we were covering the topic of campus life.
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Megan Andrews: And we're trying to figure out all the URLs that were involved in that specific topic, and we thought we had them all. And pretty much towards the end of our auditing process, it was a little bit more manual a year ago.
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Megan Andrews: One of their content editor said, hey, wait, there's this whole page, it is an FAQ just about campus life and everything we'd been trying to look at, but it wasn't indexed anywhere. There was no breadcrumbs to get to it, it was just…
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Megan Andrews: floating out there in the ether. So we… you know, sometimes these processes, right, reveal where you do have these gaps. Hopefully just… you can speed up that time to where you know where the gaps are. I think that's the point of having a good tool.
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Megan Andrews: Alright.
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Megan Andrews: Do we have any other questions that came in? Let's see… The Q&A here.
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Megan Andrews: We'll do one more, I think we've got time.
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Megan Andrews: like that.
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Megan Andrews: So this came in earlier, Anne,
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Megan Andrews: How often should we review our most important content? Like, what's the… what's the pace at which we should be thinking about these audits and reviews, Fran?
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Fran Zablocki: Well, like I mentioned before, it really depends on how high priority the pages are, right? I think the range should be that the most important pages are potentially even every week, right? If you're running a newsroom, or you're running,
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Fran Zablocki: an events calendar, or you're in the midst of a really intensive period, like, if you're, for example, in higher education, you know, you're entering the fall, and, like, orientation is hitting, and people are signing up for classes, and there's just a ton of activity and a ton of people looking for, information.
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Fran Zablocki: It could be daily, but just for short periods of time, and just for really, really important pages. But that's not practical for most scenarios, and so that would be, like, a small subset of pages. So, maybe daily for that kind of scenario. Most likely every month for really important pages, you know, in normal times.
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Fran Zablocki: every quarter, maybe, for that secondary tier of priority. And then, I'm recommending every 6 months for the… for all pages on the site, and that is mainly because, you know, that freshness is such a huge key for it getting picked up by AI. You can do all… you can check all the other boxes and have all the great… the best information.
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Fran Zablocki: But if AI looks at two equally weighted pages, and one of them is, you know, a year or a year and a half old, and one of them is within, like, 3 months or 5 months of being published.
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Fran Zablocki: It's likely to pick the one that's more current, so it is important to be able to take a look at everything, at least within 6 months, a year at the very most.
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Megan Andrews: Nice, love that. Another one just came in, not sure if it was covered earlier, did you cover the importance of an FAQ schema markup in the context of AEO?
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Megan Andrews: what new words we're all working with here, AEO included?
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Megan Andrews: One quick thought I've had on this is that, I had one…
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Megan Andrews: client we were working with who was like, well, what if we just do all of our FAQs, they aren't visual for, you know, like, on the front-end display, it's just schema markup where, you know, large language models can learn what they need to learn and go on their way. So what's your thought on that, Fran?
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Fran Zablocki: Yeah, so schema markup is something interesting, and my… I mean, my simple way of understanding it in my own brain is…
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Fran Zablocki: what you provide in markup, in code, in schema, should reflect, not, like, near-identically, but it should reflect what is visible on the front end, in the design, and in the content that's being
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Fran Zablocki: read by human beings, right? So if you have a page that has a couple questions and answers, like maybe you're using an accordion component to do that, or maybe just the page itself has H2s that are in the form of questions with paragraphs that follow.
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Fran Zablocki: you can make the argument that you'd want to include the FAQ schema at least inline on that page. But what I have seen is kind of…
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Fran Zablocki: an overcorrection because of how many articles and SEO firms have been talking about how schema is really important, and it's sort of like the old days where people were, like, just putting keywords everywhere.
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Fran Zablocki: some of the recommendations of, like, let's just add all the schema and every single page and load it up, and that's overkill. And actually, Google has said that,
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Fran Zablocki: not that it's gonna penalize you necessarily, but it's definitely not helping your cause if you're just stuffing too much schema in there. So, you know, my practical approach would just be take a look at the page that you have right now.
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Fran Zablocki: If it looks good, if it's doing what it needs to do for humans who are on it.
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Fran Zablocki: ask yourself which schema makes sense to include, because in a lot of cases, there's some pretty low-hanging fruit, right? You might have that FAQ schema, or maybe for higher ed, if it's an academic program page, there is an academic program schema that should be included on every academic program page. If you have events, there's an event schema, and so on and so forth. So there's a layer of kind of like, okay, let's just match up the schema
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Fran Zablocki: to the things that we already have, and I would take that as step one, and then, you know, I think you can start to think about adding additional schema as a second pass. And if you've done something like Content Intelligence Review, and you've added more content to answer those questions, and things are being ranked as healthy.
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Fran Zablocki: that's the point at which you would want to go back in and say, okay, are there… is there any more tweaks we can make on the schema side?
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Fran Zablocki: So, it's kind of a layered approach, and I wouldn't necessarily just jump in and be like, oh my gosh, we have to add, you know, we have to add all the schema to all the pages just to try to move the needle, because it's one… it's only one signal out of many, many, and you can kind of actually overdo it.
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Megan Andrews: Yep. Yep. It's a good thing you keep in mind,
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Megan Andrews: And I think these best practices will continue to evolve, so it's good to experiment, to your point. Try some different things, make sure, measure them, see if they're working.
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Megan Andrews: One last question that came in, and then we'll wrap this up. How long does it typically take AI to drop search results for content that isn't easily accessible or outdated?
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Megan Andrews: I guess one interpretation of that may be also is, you know, what…
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Megan Andrews: Is, is, are these large language models just gonna completely ignore things that are not accessible or outdated?
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Megan Andrews: I think probably a lot of them would, yep.
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Fran Zablocki: I think so. I think, actually, there's a lot of parallels between how a screen reader interprets the content on the site and how AI crawls the site. And again, so this is a big overlap, and another reason why accessibility is such a core piece of this and getting that right. And I know a lot of you have already been doing a really good job with accessibility and really staying on top of it, and in that respect, you've already done a lot of the work you need to to be
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Fran Zablocki: To be on top of it, but if you do have accessibility issues.
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Fran Zablocki: you're kind of… you kind of have now a compound problem, right? Like, not only are you…
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Fran Zablocki: not accessible for screen readers, but AI is going to end up not being able to navigate as well, because a lot of the same structures and signals are being used by that. So, it's part of the reason why AI… sorry, why accessibility is one half of our review, and AI readiness is the other half, because you really have to have both of those buttoned up, in order to get the best results.
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Megan Andrews: Definitely. Well, if there are any other questions that you all come up with, we'll make sure we, answer them in our summary email to everybody, but
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Megan Andrews: Thanks for joining us! It's a lot of information to take in, and you know, even just having these conversations, starting to get the vocabulary and framework for this, and use this with your team, sometimes that's helpful. Watch it together, talk about these things.
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Megan Andrews: And get that, common language and understanding going with your team. But we do often have these webinars, they're very frequent. I think monthly we've got them, so keep an eye out for the next one. And we'll keep diving into these different topics, but thanks for joining us, and we'll see you next time, everyone.
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Fran Zablocki: Good to spend time with you, thanks.
Video: Watch the webinar (US). Captions and transcript available on playback.
Poll Results
- Gaps nobody spots until a user asks – 39%
- Out-of-date information – 28%
- Too many requests and no clear priorities – 28%
- Duplicate or conflicting pages – 6%
- In the last three months – 31%
- In the last six to twelve months – 31%
- More than a year ago – 19%
- Never, or not that I know of – 19%
Webinar Q&A