How would Conversational Search work for me?

Search is evolving fast.

People no longer want to guess keywords and trawl through a list of results. They want to ask questions and expect human-like responses.

Organizations need to adapt their digital strategies to meet these changing expectations.

But what exactly is on-site conversational search, and how could it work for your organization? Let's dive in and explore the advantages that make this approach uniquely powerful.

Think about using a traditional search bar on any website. You test different keywords, hoping to pull up the right content, then browse through a list of links that might contain what you're looking for.

Your website visitors go through this same process when searching your site. Their journey to find an answer or complete an action quickly turns into a research project.

In contrast, conversational search offers an AI-powered experience that allows users to ask questions in their own words. It mimics a human-like interaction, understanding intent and supporting multi-step queries – where users can ask follow-up questions that build on previous answers – to help users get the specific information they need, with specific answers sourced from your content.

The AI-generated answers come directly from your own content (and only the content you wish them to come from), avoiding hallucination risk.

So, while keyword-based search places a cognitive load on audiences to find their answer, on-site conversational searchworks like a knowledgeable assistant. It understands user intent and instantly delivers the specific information they're looking for.

For a deeper dive into what conversation-based search is, read this blog.

One of the key Conversational Search advantages lies in how it combines enterprise-grade retrieval with a conversational interface.

Conversational Search works through a simple but powerful process:

1. Your visitor asks a question in their own words through the search bar.
2. Behind the scenes, Squiz Funnelback Search interprets the question in the context of the conversation and draws together the relevant information from your approved content, validated in advance.
3. Conversational Search then transforms that content into a clear, direct answer, complete with links to supporting pages so users can complete their task or explore related topics.

In more detail, this process includes a Retrieval-Augmented Generation (RAG) framework. Accuracy is built in before anyone asks a question. Content Intelligence analyzes your approved content, flags contradictions and gaps, and validates the knowledge Conversational Search draws on. When a visitor asks, Conversational Search interprets the question in the context of the conversation, pulls together the relevant validated information, and writes a clear, natural-language answer, streamed in seconds, within guardrails that keep it on topic.

This framework was also built to handle complex questions that include more than one concept, like 'How do I apply for a postgraduate scholarship if I’m an international student?', where the system must search across multiple content sources and combine details into one cohesive answer.

Here’s how it works, step by step:

1. Smart understanding: When a visitor asks a question, Conversational Search interprets it in the context of the conversation so far, including follow-ups, and identifies the validated information from your approved website content that is needed to answer it.
2. Answer guidelines: The matched information is combined with your answer guidelines and default response, which control the tone, format, and fallback behavior of the AI response (e.g., what to say when no answer is found).
3. Answer generation within your environment: The Large Language Model (LLM) is hosted within Funnelback Search's secure environment and generates an answer using your content only - never general internet data.
4. Proactive accuracy checks: Content Intelligence validates the question and answer foundation during indexing, flagging contradictions, gaps and ambiguity before launch. Guardrails then keep answers in scope.
5. Response delivery with full visibility: The user receives a direct answer with source attribution and can continue the conversation naturally. These interactions can be analyzed for performance, accuracy, and sentiment, giving you insights needed to improve the user experience, with full visibility and control through the conversational monitoring tool.

Example of this in practice:

The user asks: “How do I apply for a postgraduate scholarship if I’m an international student?”

Behind the scenes, Conversational Search uses the RAG process:

1. It first matches the question against validated questions and answers prepared from your approved content (e.g. a postgraduate scholarships page).
2. It then augments that content and generates a plain-language answer using that content only, never from general internet data.
3. The content behind that answer was already validated for accuracy during indexing.

Conversational Search then responds:

“To apply for a postgraduate scholarship as an international student, you’ll need to complete the online application form by July 31. You must have an offer of admission and meet the eligibility requirements outlined here [link].”

This process, from validating your content to guardrails on every answer, is how Funnelback Search keeps answers grounded in your approved content.

Squiz Funnelback Search is designed to integrate seamlessly with any website platform or content management system. So, there's no need to overhaul your entire website or replace your tech stack to start using it.

Conversational Search works independently of keyword search. Use it on its own, alongside Funnelback Search keyword search, or alongside a third-party search product.

The Funnelback implementation connects with your existing content sources, authentication systems, and analytics platforms, ensuring comprehensive access to all the information you want it to examine.

Handling all types of content

Conversational Search can process both structured and unstructured data across your organization.

What does this mean? Many of your most valuable information resources don't fit neatly into traditional databases with defined fields and formats. Think of PDFs, long-form articles, social media feeds or documents with varying layouts – this is unstructured data.

Squiz Funnelback Search, the search engine that powers Conversational Search, was specifically built to handle this challenge. It can analyze and extract meaningful information from these diverse content sources to power accurate AI responses.

Introducing Conversational Search involves two key types of upfront investment: technology and its related preparation work.

The other consideration at this early stage is whether your content is AI-ready. The good news is the Squiz team is here to help.

Technology investment

AI search pricing varies significantly across providers, with most basing licensing and subscription fees on usage metrics such as the number of search queries, data volume and indexing, and the use of any advanced features.

For Conversational Search, the subscription fee is based on the number of questions and page audits per year.

Our pricing model is different because we built it around the metrics that matter. The questions your audience asks and the pages behind the answers.

Unlike other models, our business-centric pricing model means finance teams can easily understand and forecast costs based on real business drivers, not technical complexities. This enables you to plan your search investment with the same clarity you use for other business-critical tools.

Content preparation

Tools like ChatGPT and Gemini are already scraping and interpreting your website content to answer user questions, whether you've optimized for AI or not. By proactively auditing your content for accuracy, comprehensiveness, and clarity, you're not only preparing for your Conversational Search implementation but also ensuring that external AI tools provide correct information about your organization.

This preparation typically involves reviewing your existing content to identify gaps, inconsistencies, or outdated information that might affect AI performance. Depending on your content volume and current quality, this may require time from your internal marketing and content teams or support from external consultants. Content Intelligence speeds this up by analyzing your content and flagging contradictions, gaps and ambiguity before launch.

The benefit extends beyond just powering Conversational Search. It improves your overall content quality, which enhances user experience and helps you maintain control over how your information is presented across all AI platforms.

Implementation costs

Getting your Conversational Search up and running is straightforward and flexible, with options to suit your organization's resources and capabilities:

• Internal team collaboration: If you have technical resources available, your developers can handle the integration with guidance from Squiz, allowing for valuable knowledge transfer and skill development within your team.
• Fully managed implementation: For organizations focusing on their core business, Squiz's professional services team can manage the entire process from start to finish, with tailored solutions that align with your specific requirements and timeline.

Many organizations find that a hybrid approach works best. Your team handles content-related tasks where they have the most expertise, while Squiz manages the technical configuration. This partnership approach optimizes resource allocation while ensuring a smooth implementation.

Conversational Search typically delivers significant returns through:

• Improved user engagement and reduced bounce rates as users are more likely to stay on your site and take action rather than leaving without answers.
• Increased conversion rates as users find what they need faster.
• Reduced support costs with Conversational Search handling common customer questions, allowing your team to focus on more complex issues.
• Deeper user insights by seeing what natural language questions users are asking, you get a better understanding of their true needs and intentions.
• Highlighting content gaps to inform strategic decisions in ways that traditional keyword analysis can't match.

Maximizing the value of your Conversational Search involves these important ongoing considerations for the organizations that have implemented it:

Content quality management

On-site conversational search responses will only ever be as good as the content that the organization indexes as a source for answers. This foundation is important for answer accuracy. You may need to allocate resources within the organization for:

• Regular content audits to identify and address information gaps
• Updating content that becomes outdated over time
• Creating new content based on conversation patterns to fill identified needs

These content activities require resources but deliver benefits across your entire digital presence, not just for Conversational Search.

Governance and monitoring

Governance is central. Conversational Search gives you visibility and control, so answers can be explained, monitored and audited.

As an organizational user of on-site conversational search you can ensure it continues to perform well by:

• Reviewing conversation history to identify successful and unsuccessful interactions
• Analyzing performance metrics to spot trends and opportunities
• Adjusting search configurations based on real-world usage patterns

Please note, while you, as a website owner, will be able to monitor and review conversation history to ensure customers are getting high-quality answers, this is not a feature that is available to the customer (end user) at this time.

Training and skill development

Your team may need to develop new skills to effectively manage Conversational Search, including:

• Learning to structure content in ways that work well for both humans and AI
• Understanding conversation analytics and what they reveal about user needs
• Making informed decisions about content strategy based on AI interaction data

While these activities require planning and resources, they represent valuable capabilities that strengthen your overall digital strategy and user experience.

Search is changing fundamentally. As users increasingly turn to conversational interfaces for answers, the organizations that adapt will be the ones that stay relevant and accessible.

The question isn't whether Conversational Search will become the standard - it's already happening. The question is whether your organization will adapt.

If you are interested in seeing how conversational search could work for you, just book a call and we can show you it in action.