Conversational AI Search

Conversational search is an AI-powered search experience that allows your website visitors to ask questions in their own words, get direct AI-generated answers, and follow up with clarifying questions. 

Traditional search requires audiences to use the right keywords in their query, presenting a list of results for them to browse through in the hope it might contain the information they are looking for.

While traditional search places a cognitive load on audiences to find their answer, conversational search works like a knowledgeable assistant that understands user intent and instantly delivers the specific information they need, eliminating the need for users to trawl through search results. 

To summarize the key differences: 

• Input method: Traditional search relies on keywords; conversational search accepts natural language questions.

• Output format: Traditional search returns links to pages; conversational search provides direct answers from relevant content.

• Context awareness: Traditional search treats each query independently; conversational search maintains context throughout an interaction.

• User experience: Traditional search requires users to hunt through results; conversational search delivers immediate, specific answers.

• User intent: Traditional search matches keywords; conversational search understands the meaning and intent behind questions.

Conversational search can make a significant impact on both user satisfaction and business outcomes: 

• Boost conversions by making things easier: When visitors can simply ask questions and get clear answers right away, they're more likely to take action.

• Reduce support costs: With conversational search handling common customer questions, your team is able to focus on more complex issues that need a human touch.

• Learn what your visitors really want: By seeing what natural language questions users are asking, you get a deeper understanding of their true needs and intentions. These insights highlight content gaps and inform strategic decisions in ways that traditional keyword analysis can’t match.

When evaluating conversational search tools for your organization, be sure to ask:

• How effective is the underlying search technology?

  The tool's ability to find truly relevant content is essential. No matter how smooth the conversation feels, it fails if the underlying answers are incorrect or unhelpful. Look for proven search technology with a strong track record of surfacing accurate information.

  
  

• What AI model(s) does it use? 

  Once relevant content is surfaced, it is transformed by AI models into a natural-language answer. A reliable conversational search will use an agentic flow – where specialized AI agents check each other's work, keeping responses within established guardrails to prevent hallucinations and maintain accuracy.

  
  

• How well does it deliver on critical requirements: faithfulness to scope, performance, and accuracy? 

  A superior conversational search excels at all three requirements: strict adherence to your approved sources (ensuring responses reference only your content, not external knowledge), fast response times that meet user expectations, and precise answers that directly address the question asked. Many solutions perform well in only one or two areas, so evaluate thoroughly against all three critical requirements.

  
  

• What governance controls are available?

  Choose a solution that gives you comprehensive oversight of AI-generated answers. You need tools to audit responses, monitor performance, and make adjustments to ensure your AI represents your organization appropriately.

  
  

• How is user data handled and protected?

  Understand how user queries and interactions are stored, who has access to this data, and whether it's used to train models. Ensure the tool complies with relevant regulations and allows you to maintain control over sensitive information.

  
  

• How does it address responsible and ethical AI practices? 

  Look for tools that demonstrate ethical AI principles in how they handle your content and generate responses. The best solutions prioritize transparency about AI use, proper attribution of sources, and fair representation of your content without mining or misusing it. Ethical considerations should be built into the system's design rather than added as an afterthought.

  
  

• Will it integrate with your existing systems?

  The tool should connect seamlessly with your existing content sources, authentication systems, and analytics platforms. Consider whether it can access all your relevant information, including protected internal content when appropriate.

  
  

• Can you customize the experience to match your brand?

  Look for the ability to tailor the conversational experience to match your brand voice, adjust response formats, and guide users toward specific actions that align with your goals.

  
  

• What analytics and insights will you get?

  Strong reporting features help you understand how users interact with the tool and identify opportunities to improve both the search experience and your underlying content.

Search Generative Experience (SGE) refers to AI-powered search tools that provide direct, conversational answers rather than just serving up a list of links. Squiz conversational search is an example of an SGE. 

When you're using a search engine with SGE functionality, you'll see a helpful summary at the top of your results that draws information from multiple sources. These systems typically cite where they got their information from and still give you access to the traditional list of search results below – which can be helpful when you want to dig deeper. 

Squiz conversational search enables users to benefit from a Search Generative Experience (SGE), allowing them to ask questions in their own words and receive instant, accurate answers.

Generative Engine Optimization (GEO) is a marketing approach that focuses on getting your content included in AI-generated search summaries rather than just appearing in regular search results. While traditional SEO helps your website rank higher in search listings, GEO helps ensure your information appears directly in the AI-created answers that users see first. This means creating content that's easy for AI systems to understand and use, organizing your information clearly, and adapting how you write to match how AI systems process information.

Squiz conversational search uses a three-pronged approach that ensures powerful search technology, high-quality underlying content, and specialized AI agents work together to deliver consistently accurate answers.

Powered by superior search technology

Squiz conversational search is built on Squiz Funnelback Search, our enterprise search solution with 25 years of expertise. We consistently outperform competitors in surfacing the most relevant information to power your AI answers, through features like:

• Multi-source indexing – Access content from anywhere including third-party platforms and internal systems, not just your primary CMS.

• Search packages – Create purpose-built knowledge bases with granular control over exactly which content sources to include or exclude, ensuring AI draws only from approved sources.

• Tuning – Train the algorithm to prioritize your most authoritative content for AI-generated answers, dramatically improving accuracy and trustworthiness. Our system leverages over 70 ranking factors to automatically evaluate and optimize results based on your training data. 

• Curator – Tailor search results based on user queries, attributes, or behavior to deliver personalized, relevant answers.

Ensuring content quality for reliable AI responses

Your AI will only be as good as the content that feeds it – this foundation is critical for answer accuracy. Squiz conversational search comes with a complete set of governance tools for auditing and monitoring content quality. These include: 

• Conversational readiness – Get your content AI-ready before implementation. Simulate how AI responds to common customer questions, identify content gaps, and get actionable insights to improve your content's accuracy.

• Conversational monitoring – In the first iteration of conversational search, you’ll be able to monitor and review conversation history to ensure customers are getting high quality answers. Soon, you’ll also be able to receive alerts when conversations aren’t meeting customer needs, allowing you to make timely improvements. 

• Content health check – Maintain the accuracy of your content with content auditing tools. Soon, you’ll also get proactive alerts about content issues before they impact your customer experience, ensuring your AI continues to perform effectively as your content evolves.

Built-in checks and balances on AI-generated responses 

Squiz conversational search uses “agentic flows” – i.e. where different parts of the response generation process are handled by specialized AI agents, with each agent responsible for a specific task. This essentially enables different AI agents to check each other’s work and keep each other accountable.

To ensure accuracy of responses in conversational search, we ensure that the AI-generated response (generated by the first LLM) is then reviewed by a second LLM that conducts a “faithfulness check”. In this faithfulness check, the second LLM verifies that the first LLM’s response has been based solely on your content, and no other external knowledge. This process ensures the accuracy and groundedness of the responses. 

No. If the information isn't in your content, the LLM will not make up an answer. Instead, it will simply let users know it doesn't have enough confidence to answer, or guide them toward using traditional keyword search instead. This ensures users only receive information that actually exists in your content sources.

Squiz maintains the essential guardrails to ensure our AI delivers accurate and appropriate responses, but you'll have plenty of room to make it your own:

• Controlling your content sources: You decide exactly what information your system can access by creating and managing search packages that define your trusted sources.

• Customizing behavior: In the first release of conversational search, technical staff will be able to customize how the AI communicates, including: 

  • The language style (e.g. whether formal or more relaxed)

  • The tone of voice in responses

  • How detailed or concise answers should be

In future releases, non-technical users will be able to easily adjust the AI’s behavior via the UI. 

This gives you meaningful control over your search experience while we handle the technical aspects that keep everything running smoothly.

Focus on starting small and building on success rather than attempting a complete overhaul all at once. Here's our recommended approach:

1. Define an initial use case: Begin with a focused use case that presents a low risk, high confidence, and high impact starting point – for example, your staff directory. This lets you learn and demonstrate value quickly.

   
   

2. Analyze your current search data: Look at your existing search analytics to see what questions users are asking today. 

   
   

3. Evaluate your content quality: Use tools like the conversational readiness tool, and run a content audit to identify content gaps, inconsistent terminology, and duplicate information that might affect AI performance.

   
   

4. Update your content where needed: Address the issues found in your audit to ensure your AI has quality information to work with.

   
   

5. Set up your first implementation: Deploy conversational search for your chosen use case, connecting it to your relevant content sources.

   
   

6. Use monitoring tools to refine performance and content: Review and monitor conversation history to ensure they are meeting customer needs. Use content auditing tools to catch any content quality issues early.

   
   

7. Expand to additional areas: Once your initial project is working well, gradually apply conversational search to other parts of your digital presence.

   
   

This practical approach helps you implement AI search in manageable steps while demonstrating value along the way.

When budgeting for conversational search, you'll need to account for both the technology investment and related preparation work:

Technology investment

Many providers base 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 Squiz conversational search, the subscription fee is based on the number of indexed documents and the number of conversations (i.e. Q&A-style flows with site visitors) per year. 

Content preparation costs 

Before implementing AI search, you'll need to ensure your content is ready. This means auditing existing content for accuracy, comprehensiveness, and gaps 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.

Implementation costs 

Technical integration will also require some resource allocation. This will typically involve:

• Internal team time: If using your existing staff, allocate time for developers to handle the integration with your website systems

• External support: For organizations without in-house capacity, Squiz's professional services team can manage the entire implementation process, with pricing options tailored to your specific requirements

Many organizations find that a hybrid approach works best, with your team handling content-related tasks while Squiz experts manage the technical configuration, minimizing both costs and demands on internal resources.

Return on investment 

Conversational search typically delivers significant returns through:

• Increased conversion rates as users find what they need faster

• Reduced support ticket volume as common questions get answered automatically

• Time savings for both users and internal teams

Most organizations find that these efficiency gains and conversion improvements create substantial ROI that quickly outweighs the initial investment and ongoing costs.