How AI is Augmenting, Not Replacing, UX Researchers

As AI transforms the UX research landscape, product teams face an important choice that extends far beyond functionality: how to integrate AI while maintaining the security and privacy standards your customers trust you with. At Optimal, we've been navigating these waters for years as we implement AI into our own product, and we want to share the way we view three fundamental approaches to AI integration, and why your choice matters more than you might think.

‍

Three Paths to AI Integration

‍

Path 1: Self-Hosting - The Gold Standard 

‍

Self-hosting AI models represents the holy grail of data security. When you run AI entirely within your own infrastructure, you maintain complete control over your data pipeline. No external parties process your customers' sensitive information, no data crosses third-party boundaries, and your security posture remains entirely under your control.

‍

The reality? This path is largely theoretical for most organizations today. The most powerful AI models, the ones that deliver the transformative capabilities your users expect, are closely guarded by their creators. Even if these models were available, the computational requirements would be prohibitive for most companies.

‍

While open-source alternatives exist, they often lag significantly behind proprietary models in capability. 

‍

Path 2: Established Cloud Providers - The Practical, Secure Choice 

‍

This is where platforms like AWS Bedrock shine. By working through established cloud infrastructure providers, you gain access to cutting-edge AI capabilities while leveraging enterprise-grade security frameworks that these providers have spent decades perfecting.

‍

Here's why this approach has become our preferred path at Optimal:

‍

Unified Security Perimeter: When you're already operating within AWS (or Azure, Google Cloud), keeping your AI processing within the same security boundary maintains consistency. Your data governance policies, access controls, and audit trails remain centralized.

‍

Proven Enterprise Standards: These providers have demonstrated their security capabilities across thousands of enterprise customers. They're subject to rigorous compliance frameworks (SOC 2, ISO 27001, GDPR, HIPAA) and have the resources to maintain these standards.

‍

Reduced Risk: Fewer external integrations mean fewer potential points of failure. When your transcription (AWS Transcribe), storage, compute, and AI processing all happen within the same provider's ecosystem, you minimize the number of trust relationships you need to manage.

‍

Professional Accountability: These providers have binding service agreements, insurance coverage, and legal frameworks that provide recourse if something goes wrong.

‍

Path 3: Direct Integration - A Risky Shortcut 

‍

Going directly to AI model creators like OpenAI or Anthropic might seem like the most straightforward approach, but it introduces significant security considerations that many organizations overlook.

‍

When you send customer data directly to OpenAI's APIs, you're essentially making them a sub-processor of your customers' most sensitive information. Consider what this means:

‍

• User research recordings containing personal opinions and behaviors
• Prototype feedback revealing strategic product directions
• Customer journey data exposing business intelligence
• Behavioral analytics containing personally identifiable patterns

‍

While these companies have their own security measures, you're now dependent on their practices, their policy changes, and their business decisions. 

‍

The Hidden Cost of Taking Shortcuts

‍

A practical example of this that we’ve come across in the UX tools ecosystem is the way some UX research platforms appear to use direct OpenAI integration for AI features while simultaneously using other services like Rev.ai for transcription. This means sensitive customer recordings touch multiple external services:

‍

1. Recording capture (your platform)
2. Transcription processing (Rev.ai)
3. AI analysis (OpenAI)
4. Final storage and presentation (back to your platform)

‍

Each step represents a potential security risk, a new privacy policy to evaluate, and another business relationship to monitor. More critically, it represents multiple points where sensitive customer data exists outside your primary security controls.

‍

Optimal’s Commitment to Security: Why We Choose the Bedrock Approach

‍

At Optimal, we've made a deliberate choice to route our AI capabilities through AWS Bedrock rather than direct integration. This isn't just about checking security boxes, although that’s important,  it's about maintaining the trust our customers place in us.

‍

Consistent Security Posture: Our entire infrastructure operates within AWS. By keeping AI processing within the same boundary, we maintain consistent security policies, monitoring, and incident response procedures.

‍

Future-Proofing: As new AI models become available through Bedrock, we can evaluate and adopt them without redesigning our security architecture or introducing new external dependencies.

‍

Customer Confidence: When we tell customers their data stays within our security perimeter, we mean it. No caveats. 

‍

Moving Forward Responsibly

‍

The path your organization chooses should align with your risk tolerance, technical capabilities, and customer commitments. The AI revolution in UX research is just beginning, but the security principles that should guide it are timeless. As we see these powerful new capabilities integrated into more UX tools and platforms, we hope businesses choose to resist the temptation to prioritize features over security, or convenience over customer trust.

‍

At Optimal, we believe the most effective AI implementations are those that enhance user research capabilities while strengthening, not weakening, your security posture. This means making deliberate architectural choices, even when they require more initial work. This alignment of security, depth and quality is something we’re known for in the industry, and it’s a core component of our brand identity. It’s something we will always prioritize. 

‍

Ready to explore AI-powered UX research that doesn't compromise on security? Learn more about how Optimal integrates cutting-edge AI capabilities within enterprise-grade security frameworks.

‍

Definition of a website footer

‍

The footer of a website sits at the very bottom of every single web page and contains links to various types of content on your website. It’s an often overlooked component of a website, but it plays several important roles in your information architecture (IA) – it’s not just some extra thing that gets plonked at the bottom of every page.

Getting your website footer right matters!

The footer communicates to your website visitors that they’ve reached the bottom of the page and it’s also a great place to position important content links that don’t belong anywhere else – within reason. A website footer is not a dumping ground for random content links that you couldn’t find a home for, however there are some content types that are conventionally accessed via the footer e.g., privacy policies and copyright information just to name a few.

Lastly, from a usability and navigation perspective, website footers can serve as a bit of a safety net for lost website visitors. Users might be scrolling and scrolling trying to find something and the footer might be what catches them and guides them back to safety before they give up on your website and go elsewhere. Footers are a functional and important part of your overall IA, but also have their own architecture too.

Read on to learn about the types of content links that might be found in a footer, see some real life examples and discuss some approaches that you might take when testing your footer to ensure that your website is supporting your visitors from top to bottom.

‍

‍

What belongs in a website footer

‍

Deciding which content links belong in your footer depends entirely on your website. The type of footer, its intent and content depends on its audience of your customers, potential customers and more — ie your website visitors. Every website is different, but here’s a list of links to content types that might typically be found in a footer.

• Legal content that may include: Copyright information, disclaimer, privacy policy, terms or use or terms of service – always seek appropriate advice on legal content and where to place it!
• Your site map
• Contact details including social media links and live chat or chat bot access
• Customer service content that may include: shipping and delivery details, order tracking, returns, size guides, pricing if you’re a service and product recall information.
• Website accessibility details and ways to provide feedback 
• ‘About Us’ type content that may include: company history, team or leadership team details, the careers page and more 
• Key navigational links that also appear in the main navigation menu that is presented to website visitors when they first land on the page (e.g. at the top or the side)

‍

‍

Website footer examples

‍

Let’s take a look at three diverse real life examples of website footers.

‍

IKEA US
‍

‍

IKEA’s US website has an interesting double barrelled footer that is also large and complex – a ‘fat footer’ as it’s often called – and its structure changes as you travel deeper into the IA. The below image taken from the IKEA US home page shows two clear blocks of text separated by a blue horizontal line. Above the line we have the heading of ‘All Departments’ with four columns showing product categories and below the line there are seven clear groups of content links covering a broad range of topics including customer service information, links that appear in the top navigation menu and careers. At the very bottom of the footer there are social media links and the copyright information for the website.
‍

‍

As expected, IKEA’s overall website IA is quite large, and as a website visitor clicks deeper into the IA, the footer starts to change. On the product category landing pages, the footer is mostly the same but with a new addition of some handy breadcrumbs to aid navigation (see below image).
‍

‍

When a website visitor travels all the way down to the individual product page level, the footer changes again. In the below image found on the product page for a bath mat, while the blue line and everything below it is still there, the ‘All Departments’ section of the footer has been removed and replaced with non-clickable text on the left hand side that reads as ‘More Bath mats’ and a link on the right hand side that says ‘Go to Bath mats’. Clicking on that link takes the website visitor back to the page above.
‍

‍

Overall, evolving the footer content as the website visitor progresses deeper into the IA is an interesting approach - as the main page content becomes more focussed as does the footer while still maintaining multiple supportive safety net features.

‍

‍

M.A.C Cosmetics US
‍

The footer for the US website of this well known cosmetics brand has a four part footer. At first it appears to just have three parts as shown in the image below: a wide section with seven content link categories covering a broad range of content types as the main part with a narrow black strip on either end of it making up the second and third parts. The strip above has loyalty program and live chat links and the strip below contains mostly links to legal content.
‍

When a website visitor hovers over the ‘Join our loyalty program’ call to action (CTA) in that top narrow strip, the hidden fourth part of the footer which is slightly translucent pulls up like a drawer and sits directly above the strip capping off the top of the main section (as shown in the below image). This section contains more information about the loyalty program and contains further CTAs to join or sign in. It disappears when the cursor is moved away from the hover CTA or it can be collapsed manually via the arrow in the top right hand corner of this fourth part. It’s an interesting and unexpected interaction to have with a footer, but it adds to the overall consistent and cohesive experience of this website because it feels like the footer is an active participant in that experience.
‍

‍
‍

Domino’s Pizza US
‍

Domino’s Pizza’s US website has a reasonably flat footer in terms of architecture but it occupies as much space as a more complex or deeper footer. As shown in the image below, its content links are presented horizontally over three rows on the left hand side of the footer and these links are visually separated by forward slashes. It also displays social media links and some advertising content on the right hand side. The most interesting feature of this footer is the large paragraph of text titled ‘Legal Stuff’ below the links. Delightfully it uses direct, clear and plain language and even includes a note about delivery charges not including tips and to ‘Please reward your driver for awesomeness’.
‍

‍

‍

How to test a website footer

‍

Like every other part of your website, the only way you’re going to know if your footer is supporting your website visitors is if you test it with them. When testing a website’s IA overall, the footer is often excluded. This might be because we want to focus on other areas first or maybe it’s because testing everything at once has the potential to be overwhelming for our research participants.
‍

Testing a footer is fairly easy thing to do and there’s no right or wrong approach – it really does depend on where you are up to in your project, the resources you have available to you and the size and complexity of the footer itself!
‍

If you’re designing a footer for a new website there’s a few ways you might approach ensuring your footer is best supporting your website visitors. If you’re planning to include a large and complex footer, it’s a good idea to start by running an open card sort just on those footer links. An open card sort will help you understand how your website visitors expect those content links in your footer to be grouped and what they think those groups should be called.
‍

If you’re redesigning an existing website, you might first run a tree test on the existing footer to benchmark test it and to pinpoint the exact issues. You might tree test just the footer in the study or you might test the whole website including the footer. Optimal's tree testing is really flexible and you can tree test just a small section of an IA or you can do the whole thing in one go to find out where people are getting lost in the structure. Your approach will depend on your project and what you already know so far. If you suspect there may be issues with the website’s footer, for example, if no one is visiting it and/or you’ve been receiving customer service requests from visitors to help them find content that only lives in the footer,  it would be a good idea to consider isolating it for testing. This will help you avoid any competition between the footer and the rest of your IA as well as any potential confusion that may arise from duplicated tree branches (i.e. when your footer contains duplicate labels).
‍

If you’re short on time and there aren’t any known issues with the footer prior to a redesign, you might tree test the entire IA in your benchmark study, iterate your design and then along with everything else, include testing activities for your footer in your moderated usability testing plan. You might include a usability testing scenario or question that requires your participants to complete a task that involves finding content that can only be found in the footer (e.g., shipping information if it’s an ecommerce website). Also keep a close eye on how your participants are moving around the page in general and see if/when the footer comes into play – is it helping people when they’re lost and scrolling? Or is it going unnoticed? If so, why and so on. Talk to your research participants like you would about any other aspect of your website to find out what’s going on there. When resources are tight, use your best judgement and choose the research approach that’s best for your situation, we’ve all had moments where we’ve had to be pragmatic and do our best with what we have.
‍

When you’re at a stage in your design process where you have a visual design or concept for your footer, you could also run a first-click test. First-click tests are quick and easy and will help you determine how your website visitors are faring once they reach your footer and if they can identify the correct content link to complete their task. Studies can be run remotely or in person and just like the rest of the tools in Optimal's user research platform, are super quick to run and great for reaching website visitors all over the world simply by sharing a link to the study.

Let's talk about something that's changing the game for all of us in digital product design: AI search. It's not just a small update; it's a complete revolution in how people find information online.

‍

Today's AI-powered search tools like Google's Gemini, ChatGPT, and Perplexity AI aren't just retrieving information they're having conversations with users. Instead of giving you ten blue links, they're providing direct answers, synthesizing information from multiple sources, and predicting what you really want to know.

‍

This raises a huge question for those of us creating digital products: How do we design experiences that remain visible and useful when AI is deciding what users see?

‍

‍

AI Search Is Reshaping How Users Find and Interact with Products

‍

Users don't browse anymore: they ask and receive. Instead of clicking through multiple websites, they're getting instant, synthesized answers in one place.

‍

The whole interaction feels more human. People are asking complex questions in natural language, and the AI responses feel like real conversations rather than search results.

‍

Perhaps most importantly, AI is now the gatekeeper. It's deciding what information users see based on what it determines is relevant, trustworthy, and accessible.

‍

This shift has major implications for product teams:

‍

• If you're a product manager, you need to rethink how your product appears in AI search results and how to engage users who arrive via AI recommendations.
  ‍
• UX designers—you're now designing for AI-first interactions. When AI directs users to your interfaces, will they know what to do?
  ‍
• Information architects, your job is getting more complex. You need to structure content in ways that AI can easily parse and present effectively.
  ‍
• Content designers, you're writing for two audiences now: humans and AI systems. Your content needs to be AI-readable while still maintaining your brand voice.
  ‍
• And UX researchers—there's a whole new world of user behaviors to investigate as people adapt to AI-driven search.
  ‍

‍

How Product Teams Can Optimize for AI-Driven Search

‍

So what can you actually do about all this? Let's break it down into practical steps:

‍

Structuring Information for AI Understanding

‍

AI systems need well-organized content to effectively understand and recommend your information. When content lacks proper structure, AI models may misinterpret or completely overlook it.

‍

Key Strategies
‍

• Implement clear headings and metadata – AI models give priority to content with logical organization and descriptive labels
  ‍
• Add schema markup – This structured data helps AI systems properly contextualize and categorize your information
  ‍
• Optimize navigation for AI-directed traffic – When AI sends users to specific pages, ensure they can easily explore your broader content ecosystem
  ‍

‍

LLM.txt Implementation

‍

The LLM.txt standard (llmstxt.org) provides a framework specifically designed to make content discoverable for AI training. This emerging standard helps content creators signal permissions and structure to AI systems, improving how your content is processed during model training.

‍

How you can use Optimal:  Conduct Tree Testing  to evaluate and refine your site's navigation structure, ensuring AI systems can consistently surface the most relevant information for users.

‍

Optimize for Conversational Search and AI Interactions

‍

Since AI search is becoming more dialogue-based, your content should follow suit. 

‍

• Write in a conversational, FAQ-style format – AI prefers direct, structured answers to common questions.
  ‍
• Ensure content is scannable – Bullet points, short paragraphs, and clear summaries improve AI’s ability to synthesize information.
  ‍
• Design product interfaces for AI-referred users – Users arriving from AI search may lack context ensure onboarding and help features are intuitive.
  ‍

How you can use Optimal: Run First Click Testing to see if users can quickly find critical information when landing on AI-surfaced pages.

‍

‍

Establish Credibility and Trust in an AI-Filtered World

‍

AI systems prioritize content they consider authoritative and trustworthy. 

‍

• Use expert-driven content – AI models favor content from reputable sources with verifiable expertise.
  ‍
• Provide source transparency – Clearly reference original research, customer testimonials, and product documentation.
  ‍
• Test for AI-user trust factors – Ensure AI-generated responses accurately represent your brand’s information.
  ‍

How you can use Optimal: Conduct Usability Testing to assess how users perceive AI-surfaced information from your product.

‍

‍

The Future of UX Research

‍

As AI search becomes more dominant, UX research will be crucial in understanding these new interactions:

‍

• How do users decide whether to trust AI-generated content?
  ‍
• When do they accept AI's answers, and when do they seek alternatives?
  ‍
• How does AI shape their decision-making process?
  ‍

‍

Final Thoughts: AI Search Is Changing the Game—Are You Ready?

‍

AI-powered search is reshaping how users discover and interact with products. The key takeaway? AI search isn't eliminating the need for great UX, it's actually making it more important than ever.

Product teams that embrace AI-aware design strategies, by structuring content effectively, optimizing for conversational search, and prioritizing transparency, will gain a competitive edge in this new era of discovery.

‍

Want to ensure your product thrives in an AI-driven search landscape? Test and refine your AI-powered UX experiences with Optimal  today.

‍