The demo videos are compelling, and the pitch is always some version of the same thing: why spend time and money talking to real users when AI can simulate them for you?

We decided to find out if any of that holds up. Over the course of February and March, The Good’s team of UX researchers and strategists ran hands-on evaluations of six AI user research tools.

We tested them against real client projects, comparing outputs side-by-side with findings from our established methods, and sitting through demos with enough pointed questions to make the sales reps uncomfortable.

Our answer isn’t a simple thumbs up or thumbs down. Some of these tools are genuinely useful for the right team, in the right situation. Others are impressive on the surface, with not much underneath. And nearly all of them, once you get past the marketing language, will quietly acknowledge they can’t replace real user testing.

Here’s what we actually found.

First: “AI user research” is not one category

Before getting into the tools, it’s worth noting something that may not be intuitive to all. “AI user research” is a catch-all term that covers fundamentally different capabilities. Just as we have a variety of research tools and methods as an expert UX agency, the AI tool market includes a variety of tools with fundamentally different capabilities.

As we went deeper, we found most tools fall into one or more of these buckets:

• AI-assisted study setup: Helps you design a study or write a test plan.
• AI-moderated interviews: Replaces a human moderator with AI-guided conversation.
• Synthetic users: Generates AI personas that simulate user responses.
• AI follow-up questions: Dynamic probing within surveys or tests based on participant responses.
• AI analysis and synthesis: Themes survey responses, generates summaries, builds highlight reels.
• AI-driven roadmap and recommendation tools: Scans a site and generates prioritized UX recommendations.
• AI-powered heatmaps: Predicts visual attention without requiring real user data.

Knowing which category a tool belongs to matters because it changes what you should expect from it and what you shouldn’t.

The tools we evaluated

1. Synthetic Users

Category: Synthetic users/AI-assisted study setup

What it does:

Generates AI user profiles and simulates how those users would respond to a screenshot or Figma prototype, producing a full usability report with findings, quotes, and prioritized recommendations.

What we did:

One of our strategists ran the same test through Synthetic Users and through PlaybookUX with real recruited participants. It was the same landing page, with the same research questions. This is as close to a controlled comparison as we could get.

Where the findings matched:

• Both groups flagged information overload and cluttered design as major issues.
• Both raised privacy concerns about submitting a phone number.
• Both produced skepticism about the page’s bold marketing claims.
• Severity rankings were similar across both sets, and some of the language in the synthetic “user quotes” was remarkably close to what real participants said.

Where they diverged:

Synthetic Users can only test screenshots or Figma prototypes, not live URLs. No live interactions, form fills, or navigation behavior. In that way, real users provided behavioral data (where they actually clicked, how long they hesitated, what they scrolled past) that synthetic users can’t replicate.

The report itself output eight sections, including executive summary, task-by-task analysis, error patterns, user flows, learnability, satisfaction ratings, recommendations, and sub-sections. Each section largely repeated the same three or four findings in different formats. An experienced researcher would synthesize this into a focused, actionable deck while the tool generates volume.

The bottom line:

Synthetic Users got the big, surface-level findings right. If your question is “are there obvious issues with this page?”, it can answer that quickly. If your question is “how do real users actually interact with this experience?” it falls short. Think of it as a fast, automated heuristic review. It’s useful as a starting point, not a replacement for behavioral data.

2. Uxia

Category: Synthetic users/prototype testing

What it does:

Creates custom AI-generated users based on the audience information and test plan you provide (a step you can review and refine manually before the test runs). Those users then move through your prototype, and the tool automatically produces a synthesized report with ranked themes, findings, and a shareable output. No manual analysis required.

What we did:

One of our researchers gave Uxia’s team a Figma prototype of a site element that we had already tested and synthesized using Lyssna. This gave us a direct basis for comparison between their AI-generated output and our real user findings.

What worked:

The output is genuinely robust. Themes are already pulled and ranked, the report generates automatically, and it’s ready to share without anyone watching hours of recordings first. For an in-house team without a dedicated researcher, that’s a real time savings.

The AI users also flagged the same top finding that we identified in our test with real users. That kind of alignment on a specific, nuanced finding was notable.

Uxia positions itself honestly as a supplement to real user testing, not a replacement for it. They expect their users to be running studies with real participants alongside the tool, and they’re upfront about that. Researchers using their tool actually conduct more research because of the fast turnaround, not less.

Where they diverged:

AI users interpreted placeholder imagery as real content and confused a navigation menu for a standalone page.

Our team’s assessment: it doesn’t have the emotional intelligence a human user would.

What Uxia catches are surface-level friction points, including broken flows, confusing layouts, and missing content hierarchy. What it misses are the nuanced reactions that drive the most valuable optimization decisions.

The deeper limitation is scope. Many of the test types we run with human participants simply cannot be conducted with synthetic users. If 20 out of 30 real users say something similar, that’s a trustworthy signal built from independent behavior. If AI generates 30 synthetic responses that say the same thing, that’s one opinion multiplied.

Price is custom per team.

The bottom line:

Uxia works best as a pre-step. Running a prototype through it before live user testing to catch dead ends early, or to inform A/B test concepts, could be helpful. It’s not a replacement for behavioral research. The tool’s honest positioning about this was one of the more refreshing things we encountered in this evaluation.

3. Maze

Category: AI-moderated interviews / unmoderated testing

What it does:

Unmoderated usability testing platform that’s bolting on AI features, including AI-moderated interviews. Functionally similar to Lyssna, with AI moderation as the main differentiator.

What we did:

Our team ran a full walkthrough and tested its core capabilities.

What we found:

Maze predates AI. It’s a standard unmoderated testing tool that’s adding AI capabilities, not a purpose-built AI research solution. The AI moderation feature is built for teams that run a high volume of moderated studies and want to scale without adding headcount.

The AI follow-up question feature, which probes participants based on their responses, felt shallow in practice. It pulls a word from what someone typed and asks them to elaborate. One of our team members called it “advanced survey piping.” It’s an improvement over a static questionnaire, but it’s not a substitute for a skilled moderator who follows a line of inquiry.

The bottom line:

This is a capable unmoderated testing tool. The AI moderation pitch is most relevant to agencies or in-house teams running dozens of moderated sessions monthly. If you’re already using Lyssna and happy with it, there’s no compelling reason to switch.

4. Strella

Category: AI-moderated interviews/analysis and synthesis

What it does:

Replaces human moderators with AI-guided voice interviews, then auto-generates highlight reels, segmentation analysis, and synthesized findings reports.

What we did:

One of our researchers completed a demo and detailed review of capabilities and pricing.

What we found:

Strella’s synthesis features are genuinely interesting. Auto highlight reels, AI-generated segmentation, and an analysis interface that lets you ask questions of your data are all capabilities that could save significant time for teams running large volumes of qualitative research.

The problem is the price at $5,000 or more per project, not including participant recruitment or incentives. That math only works for organizations doing frequent, large-scale interview research.

We also acknowledge a gap in our evaluation here: we weren’t able to run a direct comparison of a real moderated interview against an AI-moderated one, because we don’t often conduct live moderated sessions for clients. Before making a definitive claim about quality differences, we’d want to test that directly. What we can say is that the tool solves problems a specific type of research operation has, not most in-house optimization teams.

The bottom line:

Potentially compelling for agencies or enterprise teams doing 20+ moderated studies a year. At current pricing, it’s a hard sell for most others. The synthesis capabilities are the most interesting part of the product, and we will be watching for those features to appear in more accessible tools.

5. Baymard UX-Ray

Category: AI-driven roadmap and recommendation tool

What it does:

Scans a website and generates a prioritized UX recommendation report, pulling from Baymard’s extensive research library to categorize and rank issues by page type and severity.

What we did:

We evaluated UX-Ray’s output against a real site, reviewed the tool’s methodology, and attended a Baymard-led NNG webinar where the founders discussed AI accuracy in UX recommendations.

What we found:

UX-Ray generated 342 UX insights for one site, a number that sounds impressive until you’re in the report and realize that quantity isn’t the same as usefulness. Many of the insights are gated behind paid tiers, and without the ability to prioritize by business impact, revenue potential, or implementation effort, a list of 342 findings is as overwhelming as it is informative.

The tool’s presentation is polished: dynamic, clickable, and organized by page type with thumbnail previews. And Baymard’s content library is a trusted source in UX research, whose credibility carries into the tool.

But the more fundamental limitation isn’t accuracy, it’s context. UX-Ray scans your site against a library of best practices and known UX patterns. It has no visibility into who your actual users are, how your specific audience behaves, or where your real conversion friction lives.

Entering a URL without that context assumes a lot. A recommendation that’s technically correct by best-practice standards may be irrelevant, or even counterproductive, for your particular visitors and traffic mix. Best practices are a starting point, not a strategy. That’s as true here as it is anywhere else in optimization.

Mid-tier pricing is $399 per month.

The bottom line:

Useful for teams that want a structured starting point for a UX audit and have the expertise to evaluate and filter the output. It’s not a replacement for a research-informed optimization strategy. The accuracy caveat matters; a list of 342 recommendations that’s 70–95% correct still requires an expert to separate the signal from the noise.

6. Brainsight

Category: AI-powered heatmaps

What it does:

Generates predictive attention heatmaps without requiring real user data, using AI trained on eye-tracking studies to model where users will look on a given page.

What we did: Unlike the other tools in this evaluation, we already use Brainsight in select client work. We’ve used it extensively enough to have a genuine, experience-based opinion.

What we found:

Of all the tools in this evaluation, Brainsight is the one we recommend most readily. But we present it with caveats, because that’s the honest way to use it.

The predictive heatmaps are reliable as a starting point. The tool reads contrast, copy, imagery, and dark areas on screen and makes assumptions about where human attention will land. That works often enough to be useful.

They also compare favorably to DIY AI heatmap alternatives (which our team found consistently unreliable), and the tool is priced accessibly enough to function as a genuine entry point for teams that haven’t yet invested in full heatmap research.

But it’s modeling visual salience, not actual user behavior. A true heatmap might show no heat on a long block of text that the AI flagged as a high-attention area, because real users navigated away without reading it. The AI doesn’t know that. It sees contrast; it doesn’t see intent.

So, this is a good starting point, not a definitive picture. If you want heatmap data you can trust completely, that comes from real users in a full engagement.

Here’s how we’d describe Brainsight to any client considering it: it gets you to 70% of the answer faster and cheaper than doing nothing. You’ll see where attention concentrates, where it drops off, and what’s fighting for visual priority.

The remaining 30%, understanding why users look where they look, what they do next, and what it means for your conversion strategy, is where a full optimization strategy makes the difference.’

Brainsight is also adding AI-generated recommendations following the heatmap output, a feature we haven’t fully evaluated yet. We’ll be watching it closely.

The bottom line:

This is a tool we use and would actively recommend as a starting point. Best positioned as an affordable entry into attention data, with the honest caveat that real engagement data tells you more.

What we learned across all of it

After evaluating all six tools, a few themes cut across the whole category.

They find the obvious. They miss the subtle.

In every comparison, AI-generated findings matched the surface-level issues an experienced researcher would spot in the first ten minutes of reviewing a page, for example, information overload, privacy friction, and confusing hierarchy.

The gap shows up in depth: navigation hesitation, emotional reactions, and the unexpected workaround a user invents that tells you your information architecture is broken. For high-stakes optimization decisions, the subtle findings are where the value lives.

More output is not better output.

Volume was the consistent way these tools tried to signal quality. 342 UX insights. Eight report sections for a single landing page. 12-page persona profiles in under a minute. Quantity without prioritization and context is noise. A skilled researcher delivers fewer, better, more actionable insights and knows which ones actually matter.

They’re genuinely useful for teams starting from zero.

This is worth saying clearly. An in-house optimization team that has never run a user test would benefit from these tools. Getting 70% of the answer is better than getting none.

These tools lower the barrier to research-informed decision-making. The risk isn’t using them, it’s treating their output as final rather than as a starting point that needs validation with real users.

The best use cases aren’t what the tools advertise.

The most promising applications we found weren’t the primary pitch of any tool we evaluated. Running a prototype through a synthetic user tool before live user testing to catch dead ends. Using Brainsight as a fast stakeholder-conversation starter. Using AI synthesis tools to surface patterns in data that a team has already collected but hasn’t had time to analyze. None of these tools market themselves this way, which our team found consistently surprising.

The vendors themselves will tell you.

This was the most telling finding of the entire evaluation. Every single tool vendor, once you moved past the landing page and into a real conversation, acknowledged that their tool won’t replace real user testing. When the sellers aren’t making the replacement claim, pay attention.

When to use AI research tools (and when not to).

AI tools earn their place when you’re tracking patterns over time, when the problem is well-defined and the stakes are low, when you need directional input quickly and the alternative is doing nothing, or when you’re QA-checking a prototype before investing in live user testing.

Keep humans in the lead when the decision is high-stakes, when you need behavioral data (not just stated responses), when you’re entering an unfamiliar market, or when you need findings you can defend with evidence.

For most teams, the answer isn’t either/or. These tools slot into a research process as a first step, a pre-launch check, or an accelerator for analysis you’re already doing. Their ceiling is lower than the marketing suggests, and their floor is higher than the skeptics give them credit for. Use them where they fit.

Frequently asked questions on AI user research

Can AI replace user research?

As of right now, no. And the vendors building these tools will tell you the same thing.

AI research tools can surface obvious usability issues, generate directional insights quickly, and lower the barrier to research-informed decision-making for teams that have never run a study before.

What they can’t do is replicate real user behavior: the navigation hesitation, the emotional response, the unexpected workaround that tells you something important about your experience.

For low-stakes, directional questions, AI tools are a reasonable starting point. For decisions that matter, real users are non-negotiable.

What is the difference between Synthetic Users and Uxia?

Both tools generate AI-simulated users to evaluate a design, but they serve slightly different purposes. Synthetic Users runs AI personas through screenshots or Figma prototypes and produces a full usability report with findings, quotes, and severity ratings, functioning most like an automated heuristic review.

Uxia takes a similar approach but focuses more specifically on prototype testing and positions itself explicitly as a first step alongside, not instead of, real user research.

In our side-by-side comparisons, both tools got the big surface-level findings right and missed the behavioral nuance. Uxia’s honest framing about its own limitations stood out as a green flag.

Is Brainsight accurate?

In our experience, yes. More so than DIY AI heatmap alternatives, which our team found consistently unreliable.

Brainsight’s predictive heatmaps are trained on real eye-tracking data and produce results we’ve found dependable enough to use in client sprint work. That said, predictive heatmaps model where users are likely to look based on visual patterns, they don’t capture actual user behavior, intent, or what users do after their attention lands somewhere.

We use Brainsight as a fast, accessible starting point. Real engagement data from actual sessions tells a more complete story.

How accurate are AI-generated UX recommendations?

According to Baymard’s own founders, AI-generated UX recommendations are generally around 70% accurate across the industry.

Baymard claims their UX-Ray tool performs at approximately 95%, but even at that rate, a meaningful portion of recommendations in any given report shouldn’t be implemented without validation.

The more important point: Baymard itself says all AI-generated recommendations require testing before you act on them. A tool that generates hundreds of insights you still need to verify manually isn’t saving as much time as the pitch suggests.

When should a team use AI user research tools?

AI research tools make the most sense when the alternative is doing no research at all, when you need quick directional input on a well-defined and lower-stakes question, when you’re doing pre-launch QA on a prototype before investing in live testing, or when you have existing data that needs faster synthesis.

They make the least sense when you’re making high-stakes optimization decisions, entering an unfamiliar market, or need findings you can defend with behavioral evidence. For those situations, real users and experienced researchers aren’t optional; they’re the whole point.

Do AI user research tools save time?

For teams with established research processes, the promised time savings largely didn’t materialize in our evaluation. Research teams can build test plans in their sleep and likely use AI to assist with analysis.

The tools that promised speed often delivered volume, lengthy reports that repeated the same findings across multiple sections, requiring a researcher to synthesize the synthesis.

For teams earlier in their research maturity, the time savings are more real: automating analysis and report generation genuinely helps when the alternative is doing it manually from scratch. But they will likely be bogged down in these unnecessarily long reports.

The verdict

We say the same thing about AI user research tools that we say about best practices: they’re a starting point, not a strategy. They get teams that have never done research to 70% of the answer. For a team with established processes and real users to test with, they don’t solve problems we have.

The hype runs well ahead of the utility, and the most dangerous outcome isn’t a team using these tools and getting incomplete results; it’s a team using them and thinking they have the full picture.

The last 30% of research quality, the part that connects real human behavior to your most important optimization decisions, still requires real users, real data, and experienced researchers who know what to do with both.

Not sure where AI tools fit in your research process…or if they should? Our team has done the testing. Book a call and let’s talk through it.

The post We Tested 6 AI Research Tools Against Real Users. Here’s What We Found. appeared first on The Good.

Fritz O’Connor, former VP of Marketing at Ironman 4×4 America, exemplifies this approach. With over two decades of experience spanning manufacturing, sales, and marketing leadership, Fritz has developed a methodology for building high-performing organizations that deliver results consistently, even in challenging circumstances.

A marketing leader built for manufacturing

Fritz’s career journey reads like a masterclass in understanding customers across different industries. Starting in the printing and paper industry, he cut his teeth in structured sales training programs that taught him the fundamentals of professional sales and business operations.

“I’ve spent my entire career in sales and marketing roles. Almost exclusively in the manufacturing sector for companies that make stuff,” Fritz explains. This foundation in manufacturing would prove invaluable throughout his career, giving him deep insight into the complexity of bringing physical products to market.

His two-decade tenure at GE further refined his skills across diverse business environments. “We always used to say we can work in any industry, anywhere in the world, and still get paid by the same company,” he recalls. This experience working across plastics, appliances, and GE Corporate gave him a unique perspective on how great companies operate at scale.

But it was during his time at GE Corporate that Fritz discovered what would become his career-defining framework: differential value proposition (DVP). Working in a marketing consulting role with virtually every business in GE’s global portfolio, he helped launch this customer-centric approach to messaging and positioning throughout the organization.

This systematic approach to understanding and serving customers became foundational to Fritz’s ongoing success.

Implementing systems and frameworks that take teams from features to solutions

Originally coined by the founder of Valkre Solutions, Jerry Alderman, the DVP framework transforms how companies think about customer messaging and competitive positioning. Fritz became a master at implementing this methodology across diverse organizations.

“What are you offering? Be it a product or service that is better than the customer’s next best alternative,” Fritz explains. This might seem simple, but the implications are profound. Rather than competing on features or price, DVP focuses on solving customer problems in ways that competitors simply cannot match.

The challenge, as Fritz learned during his GE implementation, is that DVP represents a fundamental shift in thinking. "Every business, product, or service has a value proposition, but not every value proposition is differential. So many companies have the same value proposition. The white space is that differential part."

"It's about switching thinking from a feature to a benefit. For example, a blue appliance is not a differential value proposition. It's a feature."

Fritz teaches teams to make this shift by leading with problems and solutions.

"It's how it makes the consumer or customer's life better, how it solves that problem. You have to identify what the problem is. You have to articulate how you can fix that problem in a different way, better than anybody else."

This shift from features to solutions requires teams to understand their customers' actual problems, not just their stated needs.

For leaders, this translates directly into more effective product messaging, clearer value propositions, and ultimately, higher conversion rates.

Overcoming the "this is how we've always done it" challenge

One of Fritz's biggest career wins (and ongoing challenges) centers around implementing the Differential Value Proposition (DVP) methodology across organizations. The implementation at GE became both a success story and a learning experience in change management.

"As you can imagine, anytime you try and launch a new process in a company the size of GE, you can be met with resistance. Especially when you're coming out of corporate."

This resistance taught Fritz a crucial lesson about implementing change: "I don't view that as a challenge or a stumbling block, but as a fantastic and wonderful opportunity because when you flip those people, they become your biggest proponents."

His approach centers on listening first, then demonstrating value in the stakeholder's own language. "It's a listening journey. You've gotta understand what the challenges are that of the people with whom you're working, whether it's an external customer or an internal customer."

"Proactively listen and walk in the shoes of the people I'm working with. When I'm trying to introduce something as significant as DVP or other business tools."

This listening approach helps identify the real challenges and resistance points, making it possible to address them effectively.

The foundation: accountability, responsibility, and challenge

But having the right frameworks isn't enough. Fritz learned that execution depends on creating the right team culture. He is quick to credit his teams as the backbone of his successful projects, and one of the ways he supports them is with clear organizational principles.

"I have a few underlying business principles that I've gained along the way that are the foundational threads for me," Fritz explains. "One is, any team I work with or works for me, my job is to make them as successful as possible."

This people-first approach manifests through three guiding principles:

• Accountability: Holding yourself and your team responsible for deliverables and outcomes
• Responsibility: Taking ownership of significant business challenges
• Challenge: Embracing difficult problems that create meaningful business impact

"The way I do that is through three guiding principles, which are accountability, responsibility, and challenge," Fritz notes. "I want to be entrusted with significant responsibility that is helping to solve a significant business challenge."

These principles translate into a simple but powerful operational mantra: deliver on time, complete with excellence.

"I know those all sound like buzzwords, but they're not meant to be. And we don't treat them as such. We treat them as very simple guiding principles to keep us focused."

Putting it all together at Ironman 4x4

When Fritz joined Ironman 4x4 America, he found the perfect opportunity to apply all of these frameworks.

Ironman 4x4 is a global company that sells off-road parts and accessories for 4x4 vehicles (lift kits, suspension parts, bumpers, etc.). They have been around since the 1950s, but were new to the United States, so Fritz had the opportunity to find new ways to market their complex "fitment" products, or parts that must work with specific vehicle makes and models. This complexity creates both technical and marketing challenges that Fritz's team had to solve systematically.

His sales background gave him an invaluable perspective on marketing effectiveness. "If you spend any time in sales, that means you're around customers, whether those are B2B or B2C customers. And you learn what's important to them."

This customer proximity taught him the critical principle of "show me, don't tell me." Rather than relying on feature lists or industry awards, effective marketing demonstrates value through customer experiences and outcomes.

"We always, in both sales and marketing, it's easy to get into the trap of just talking, talking, talking, describing stuff, talking about features and benefits. Talking about the industry's best. Nobody cares about your industry. They care about how your product or service is going to impact them."

The key to marketing complex products, Fritz knew, is understanding how customers think about their problems. Rather than leading with technical specifications, the focus should be on the customer's end goal and the emotional drivers behind their purchase decisions.

Fritz emphasizes the importance of demonstrating value rather than just describing it: "Really, visual storytelling, video storytelling, placing the customer in the scene so they understand your value. That ability comes from firsthand experience of seeing that happen in the sales arena."

A data-driven website replatforming

His POV shaped everything he was involved in at Ironman 4x4 America, from new product introduction processes to website optimization. Fritz implemented structured new product integration toll gates with clear deliverables and cross-functional accountability, ensuring every product launch was executed with precision across creative, digital, and channel marketing.

His customer-centered thinking and frameworks proved essential when his team tackled a complex website migration from an outdated platform to Shopify. The project was based on their understanding that a website change was necessary to better serve their audience and increase ecommerce sales.

Working with The Good on a DXO Program, the Ironman 4x4 team executed the redesign and replatforming with data-driven methodology. Rather than relying on opinions about what the site should look like, they embraced rapid prototyping and continuous testing.

"Any decision made without data is just an opinion, right?" Fritz notes, referencing CEO Luke Schnacke's philosophy.

"We try to be very data-driven, which is why it was so important for us to work with The Good, to get that data and share it with the team managing the website replatforming so that they were making data-driven decisions on design and functionality."

They didn’t wait for a “perfect website” to figure out what customers wanted. They tested and got feedback throughout the entire process to make sure they were developing the right ideas.

"I realized we were never going to do it perfectly," Fritz recalls. The team was getting bogged down in opinions about checkout processes, product customizers, and overall site design. "We could end up using half our development budget on building something that doesn't perform."

"Ultimately, we agreed to launch and then test the heck out of it. We didn't want to overburden the development pipeline with projects that don't have a financial impact."

This represents a fundamental shift in thinking. They went from trying to build the perfect site to building a testable foundation for continuous improvement.

The beauty of working with The Good in this situation, Fritz explains, was "the rapid prototyping, the test and learn. We could very quickly get feedback and iterate and then test and learn again."

Multiplying results through partnership

Leveraging an external partnership accelerated progress beyond what internal resources could achieve alone and held the team accountable to the frameworks and goals of staying user-centered and data-driven.

"If you're not an expert, I would recommend doing a website project with a company like The Good. It wasn't a cost, it was an investment," Fritz emphasizes. "And I think that Ironman 4x4 is the beneficiary of the investment that they made with The Good as they migrated over to Shopify and learned about what customers would like."

The partnership enabled intentional, studied testing with proper dependencies and measurable results tracking.

"That whole test and learn methodology is done in a very structured, deliberate way. Making changes in a waterfall, with the proper dependencies articulated, and then tracking the measurable benefits of changes, and then tweaking accordingly from there."

This approach breeds confidence because it's entirely data-driven, removing guesswork from critical business decisions.

Lessons for marketing and sales leaders

For marketing and sales leaders looking to build similar operational excellence, Fritz's approach provides a roadmap: start with principles, understand your customers deeply, make decisions based on data, and never underestimate the power of strategic partnerships to unlock potential.

Start with principles, not tactics

Before implementing any marketing or optimization program, establish clear guiding principles. Fritz's framework of accountability, responsibility, and challenge provided a foundation that influenced every decision and created lasting organizational change.

Understand your customer's next best alternative

Move beyond feature-benefit messaging to understand what your customers would do if your solution didn't exist. This "next best alternative" thinking is the foundation of truly differential value propositions.

Convert resistance through understanding

When facing organizational resistance to change, focus on understanding stakeholder concerns rather than pushing solutions. Meet people where they are and demonstrate value in their language.

Embrace data-driven decision making

Resist the temptation to rely on opinions or best practices. Instead, create structured testing methodologies that let customer behavior guide optimization decisions.

Invest in external partnerships strategically

Recognize when external expertise can accelerate progress. The right partnerships provide capabilities and perspectives that internal teams may not possess, ultimately delivering better results faster.

Starting an optimization journey

Fritz's approach to building and scaling teams, including Ironman 4x4's US marketing operations, demonstrates how principled leadership, customer-centric thinking, and strategic partnerships can create sustainable competitive advantages.

"There's no obstacle too big that can't be overcome with data and optimization, right?" Fritz states emphatically. "The whole point of being data-driven and optimizing is to get time back and to become more efficient."

His advice for other leaders facing similar challenges?

"Get to yes. Figure out how to do it. Don't say, this is why I can't do it. Say this is how I'm going to do it. Here are things I need to do in order to do it. Then hold yourself accountable. Make it happen. Do it."

The secret, according to Fritz, lies in celebrating small wins that compound over time: "Little steps, I always like to say, celebrate the little wins. Go after the little wins because they compound on one another and then all of a sudden you're gonna look back and go, holy mackerel, I can't believe I am where I am."

The secret is consistency: "And it starts with data as your foundation and optimization as the accelerator."

For ecommerce leaders looking to build similar operational excellence, Fritz's framework provides a proven template: establish clear principles, understand customer problems deeply, make data-driven decisions, and never underestimate the power of strategic partnerships to accelerate growth.

Ready to optimize your ecommerce experience with data-driven methodology? Learn more about The Good's Digital Experience Optimization Program and discover how strategic partnerships can unlock your growth potential.

The Good helps ecommerce brands like Ironman 4x4 optimize their digital experiences through research-backed testing and strategic partnerships. Our team combines deep technical expertise with proven methodologies to deliver measurable results for growing brands.

The post Fritz O’Connor Stays User-Centered and Leads with Data During Uncertain Times appeared first on The Good.

Don’t get me wrong, A/B testing is incredibly powerful. It’s the gold standard for high-stakes, high-traffic decisions where statistical significance matters most. But when it becomes your only tool, you create unnecessary constraints that can paralyze decision-making and slow innovation.

The reality is that different decisions require different levels of rigor, confidence, and investment. Luckily, there is a complementary approach that fills critical gaps in your experimentation toolkit. By understanding when each method is most appropriate, teams can make faster, more informed optimizations while maintaining the rigor needed for their most high-stakes decisions.

Creating “experience rot”

A/B testing borrowed its methodology from medical intervention studies, where 95% confidence intervals and statistical significance aren’t just nice-to-haves; they’re life-or-death requirements.

But we’re not rocket scientists, and we don’t always need the same level of assurance in product decisions to move towards the right outcome.

A/B testing can be overkill for the decisions product teams need to make daily. Yet teams have become so committed to this single methodology that they’ve created what researcher Jared Spool calls “Experience Rot,” the gradual deterioration of user experience quality from teams moving too slowly or focusing solely on economic outcomes.

The costs of slow testing cycles are tangible and measurable:

• Market opportunities disappear while waiting for test results
• Competitors gain ground during lengthy testing phases
• Development resources get tied up in prolonged testing initiatives
• Customer frustration builds as issues remain unfixed
• Decision fatigue sets in as teams debate what to test next

But the problem runs deeper than just speed. Many teams face contexts where A/B testing simply isn’t feasible. Regulatory challenges in healthcare and finance, low-traffic scenarios for B2B products, technical constraints, and organizational politics all create barriers to traditional experimentation.

By the time a test idea passes through all the bureaucratic loopholes and oversight at an organization, it’s often no longer lean enough to justify testing. Without an alternative testing method, teams are left without any data at all.

So, how do we:

1. Circumvent the challenges of A/B testing, and
2. Prevent experience rot?

Enter rapid testing

Rapid testing isn’t about cutting corners or accepting lower-quality insights. It’s about matching your research method to the decision you’re trying to make, rather than forcing every question through the same rigorous, but often slow, process.

Like A/B testing, rapid testing helps you understand if your solutions are working. Unlike A/B testing, rapid tests are conducted with smaller sample sizes, completed in days rather than weeks or months, and often provide qualitative insights that A/B tests can miss.

“The speed at which we obtain actionable findings has been impressive,” says Gabrielle Nouhra, Software Director of Product Marketing, who leverages rapid testing with The Good for research and experimentation. “We are receiving rapid results within weeks and taking immediate action based on the findings.”

The key is understanding when each approach makes sense. Not every decision requires the same level of rigor, and smart product teams create systems that allow critical insights to move faster.

A framework for decision making

So, how do you decide when to use rapid testing versus A/B testing? The decision starts with two critical questions: Is this strategically important? And what’s the potential risk? With those two questions in mind, you can map your ideas on a simple 2×2.

High Strategic Importance + Low Risk = Just Ship It. If you can’t explain meaningful downsides to a change but know it’s strategically important, you probably don’t need to test it at all. These are your quick wins.

Low Strategic Importance = Deprioritize. Not everything needs to be tested. Some changes simply aren’t worth the time and resources, regardless of the method you use.

High Strategic Importance + High Risk = Test Territory. This is where both A/B testing and rapid testing live. The next decision point becomes: Can you reach statistical significance within an acceptable timeframe? Are you technically capable of running the experiment?

If the test isn’t technically feasible or traffic constraints make the time-to-significance longer than is acceptable, rapid testing becomes your best option for de-risking the decision.

Rapid testing in practice

Rapid testing encompasses various methodologies, each suited to different types of questions. Here are just a few examples:

First-Click Testing helps confirm where users would naturally click to complete a task. Perfect for interface design decisions and navigation optimization.

Preference Testing goes beyond simple A/B comparisons to evaluate multiple options, often six to eight variations, helping teams understand which labels, designs, or approaches resonate most with their target audience.

Tree Testing reveals where users might stray from their intended path, using nested structures to understand navigation behavior without the distraction of full visual design.

The beauty of these methods lies in their speed and specificity. Rather than testing entire page redesigns, rapid testing allows you to validate specific hypotheses quickly. Which onboarding segments will users self-identify with? Where should we place a new feature to maximize engagement? Which design elements increase trust among new visitors?

Rapid tests can also guide our A/B testing strategy. If we’re entertaining multiple options for new nomenclature within an app experience and we’re just trying to understand which label users think would be most accurate or most likely to represent those outcomes, running a rapid test can narrow down those options and help us decide what to A/B test.

Building a rapid testing practice

Implementing rapid testing effectively requires more than just choosing the right method. Teams that see the best results follow several key principles:

1. Impact pre-mortems: Before testing, clearly define what success looks like and what impact you expect if implemented. This helps connect testing activities to business outcomes and prevents post-hoc justification of results.
2. Acuity of purpose: Keep tests focused on specific questions rather than trying to evaluate everything at once. A/B testing often encourages comprehensive evaluations, but rapid testing works best with precise hypotheses.
3. Pre-defined success criteria: Establish clear benchmarks before you start testing. If 80% of users can complete a task, is that a win? What about 60%? Define these thresholds upfront to avoid moving goalposts when results come in.
4. Mute context: When testing specific elements, remove unnecessary context that might distract from the core question. Full-page designs can overwhelm participants and dilute feedback on the element being tested.
5. Sunlight: Even experienced researchers benefit from collaborative review of test plans. Transparency builds confidence in the process, and a peer review of test designs helps identify potential issues before execution.
6. Share: Circulate your impact, what you’ve learned about your audience, and get people excited about the work. The goal is to build visibility, create a case for why this work is valuable, and encourage people to make decisions with data.

The compound effects of speed

Teams that successfully implement rapid testing alongside their existing A/B testing programs see remarkable results. Our clients report 50% improved A/B test win rates, better customer satisfaction scores, and significantly faster time-to-insights.

But perhaps most importantly, they report better team morale. There’s something energizing about seeing results from your work quickly, about being able to iterate and improve based on real user feedback rather than lengthy committee discussions.

It’s never too late to pivot. The idea is to move from long-term decision making, where we send something through the whole development and design cycle only to come up with a lackluster outcome, to form a process that helps us get quick, early signals.

Making the transition

The goal isn’t to replace A/B testing. It remains the gold standard for high-stakes, high-traffic decisions. But by adding rapid testing to your toolkit, you can accelerate the decisions that don’t require months of statistical validation while still maintaining confidence in your choices.

As decision scientist Annie Duke writes in Thinking in Bets, “What makes a great decision is not that it has a great outcome. It’s the result of a good process.” Rapid testing gives teams a process for rational de-risking that emphasizes both speed and quality.

The question isn’t whether you should test your ideas; it’s whether you’re using the right testing method for each decision. In a world where speed increasingly determines competitive advantage, teams that master this balance will consistently outpace those stuck with only one tool in their kit.

Ready to accelerate your decision-making process? Our team specializes in helping product teams implement rapid testing alongside existing experimentation programs. Get in touch to learn how we can help you cut testing time without sacrificing insight quality.

The post How To Make User-Centered Decisions When A/B Testing Doesn’t Make Sense appeared first on The Good.

Amidst the plethora of apps and algorithms promising to streamline processes, there’s an often overlooked hidden gem—a tool deeply rooted in psychology and human behavior.

Welcome to the world of heuristics, where problem-solving meets intuition to build better digital experiences.

Heuristics, or mental shortcuts, could be the key to unlocking optimal performance in your role and your digital property.

In this article, we explore how these cognitive shortcuts pave the way for smoother, more intuitive user interactions. We unravel the significance of each of our six Heuristics for Digital Experience Optimization and offer actionable strategies for enhancing user experiences.

What are heuristics?

Heuristics are mental shortcuts used to solve problems quickly and effectively. They allow people to speed up analysis and make informed, efficient decisions.

Our brains are wired to take shortcuts and make quick decisions. So, heuristics play a crucial role in how customers navigate and perceive digital experiences.

How do heuristics apply to digital experience optimization?

By understanding the mental shortcuts your customers rely on, you shift the focus squarely onto their experience. Ensuring we understand and adhere to those shortcuts aids users in quickly and successfully accomplishing their goals. At the same time, actively removing barriers that interfere with these heuristics builds a subconscious level of trust with your customers.

We unpack more of these elements in our book, Behind the Click, but fundamentally, heuristics in digital experience optimization are a way to frame common optimization challenges and turn them into a trustworthy experience that:

• Feels familiar
• Does what they say
• Functions intuitively

Feels Familiar

From the classic navigation menu to the ever-present search bar at the top right, there’s a certain rhythm to digital experiences. Customers have developed a strong expectation of how websites and apps should function.

When a digital experience adheres to these established norms, customers feel a sense of familiarity and control. This subconsciously reduces friction and makes them more receptive to your company.

Does What They Say

Customers crave predictability and transparency in their digital experiences. Honoring a promise—whether about your pricing structure, refund policy, or product features—is essential.

Unexpected fees, convoluted purchase processes, or hidden terms and conditions violate the customer’s trust. Be upfront about all costs and keep the interactions straightforward to build confidence and credibility with your customer base.

Functions Intuitively

Intuitive design is crucial, especially for SaaS products. Users are already familiar with countless digital platforms, so don’t force them to relearn fundamental workflows for your product.

Leverage common design patterns and visual design cues. When your product functions in a way that feels natural, customers can focus on the value you provide rather than the mechanics of using the interface.

The Heuristics for Digital Experience Optimization

The Heuristics for Digital Experience Optimization are a tool developed at The Good to theme common optimization issues and opportunities with the user at the center of analyses.

These heuristics can guide your strategy and help you build digital journeys that feel familiar, do what they say, and function intuitively, as mentioned above.

The six heuristics are:

1. Priming & Expectation Setting
2. Trust & Authority
3. Ease
4. Benefits & Unique Selling Points
5. Directional Guidance
6. Incentives

Let’s take a look at each heuristic in more detail. We’ll cover what it is, how it manifests, and optimization examples of how you might adjust your digital experience to account for these heuristics and any barriers impeding users from accomplishing their tasks seamlessly.

Heuristic #1: Priming & Expectation Setting

Set users up for success by clarifying how the interface will perform, what actions users should take, and what they can expect.

Violations of this heuristic may manifest as:

• Unmet Expectations
• Poor Priming
• Unclear System Status

To adhere to the priming and expectation setting heuristic, you can apply a tactic like explicitly mentioning free shipping early in the journey to reduce cart abandonment rates or sharing estimated delivery dates. Doing so targets the poor priming violation.

Share Estimated Delivery Dates

Get as specific as possible with shipping dates on both PDPs and checkout pages.

You can do this in a few ways. First, you can list the date the item will arrive instead of giving a nonspecific range. “Standard Shipping 3-5 Business Days” becomes “Standard Shipping: Arrives by February 24.”

Here’s an example of estimated delivery dates. Notice the “Delivery Options” box in the bottom right corner.

Alternatively, you can add a zip code search option, where users can type in their location, and your website will provide estimated delivery dates (EDDs).

Setting clear expectations for EDDs can reduce customer anxiety, improve purchasing confidence, and even reduce the workload of your customer support team.

Heuristic #2: Trust & Authority

Establish and maintain perceived trust, authority, and security throughout the digital experience.

This is critical because issues like bugs or anything that violates users’ sense of trust can lead to disengagement. Building trust enhances users’ confidence in the website while violating it can lead to abandonment.

Violations of this heuristic may manifest as:

• Poor Usability
• Comparison Shopping

To follow the trust and authority heuristic, mitigate bugs, build trust by featuring social proof, or consider adding additional educational “how it works” content for complex products.

Highlight Positive Reviews

While brands can say a lot of great things about themselves, they can be more effective, more relatable, and more believable when real customers are singing their praises.

Featuring positive reviews can build user confidence to make a purchase decision and increase user trust.

This is especially great for brands with high-price point products (bikes, furniture) or products with trust-reducing user-dependent variables (makeup: compatibility with dark skin, shoes: true to size fit).

Offer Guarantees

Guarantees can help prime users to make purchasing decisions and incentivize them to purchase. They give users a feeling that the brand is making a commitment to them.

Highlighting guarantees in a quickly scannable way can increase a sense of trust, reduce decision paralysis, and highlight the value of a product.

Highlighting guarantees is great for sites that have high-value items (mattresses, bikes) and/or brands with trust-reducing user-dependent variables (dress fit, color match).

Add a How-it-works Model

Describing “How it Works” for some business models and/or features can give users the context and confidence that they need to understand competitive differentiators like price and quality.

Doing so for complex products will boost user trust, encourage buy-in to the brand, and instill purchasing confidence.

Heuristic #3: Ease

Ensure your interface is easy to use, including aspects like information architecture, navigability, and seamless functionality.

Violations of this heuristic may manifest as:

• High Interaction Cost
• Heavy Cognitive Load
• Content Fatigue

Making a website easy ensures that users won’t abandon it due to its complexity. It also offers better accessibility to diverse audiences. You can address the ease heuristic by reducing content or building in clear navigation elements like a mega menu.

Add a Mega Menu

Adding a mega menu can show the breadth of products, provide directional guidance, and increase visits to PDPs. This can ease product discoverability.

Mega menus are great for brands with a wide range of product offerings and/or multiple sub-categories.

Truncate Long Lists & Copy

Large amounts of copy or long lists can overwhelm users and create additional cognitive load.

Truncating long lists and copy can improve directional guidance, help users differentiate products better, and increase the likelihood of purchase.

Note that it’s not just about adding a “Read more” and hiding ineffective copy behind a click. It is sometimes necessary to bring in a copy expert to rewrite product copy entirely, focusing on decreasing the work to read and increasing the value for the user.

Heuristic #4: Benefits & Unique Selling Points

Highlight the benefits and unique features of products or services to persuade users to purchase them here instead of elsewhere.

Violations of this heuristic may manifest as:

• Low directness
• Attentive/intentional reading

To address this heuristic, consider testing factors like faster shipping times or highlighting product quality.

Add Quality Tiles

Brands often over-rely on homepages to sell the brand and product pages to sell a product’s features. Few users make it to all of a website’s pages (home, category page, product page), leaving users with knowledge gaps about brand positioning and product benefits.

Displaying quality tiles within collection pages can increase engagement, help users connect with brand values, and reiterate purchase incentives.

This is great for brands that have strong value propositions (sustainability, luxury) and selling points (hand-made, organic) that will connect with users.

Note that each quality tile variant could focus on a different theme, such as sustainable business practices in one, quality in another, and incentives like free shipping and returns in another.

Add Value Proposition to a Banner

Global promotion banners aren’t just for sales. They can be utilized to quickly communicate brand values, product benefits, and key differentiators with simple microcopy.

Showcasing positioning, brand values, and key differentiators in banners can increase engagement and decrease adds to cart.

Heuristic #5: Directional Guidance

Support users in finding and discovering what they need through visual hierarchy, way-finding, and guiding them to the next best step in their journey.

Violations of this heuristic may manifest as:

• Low Visibility/Low Discoverability
• Low Findability

This is particularly helpful for users who may need extra assistance in decision-making. Think of them as your friend who never knows where they want to go for dinner. We’re offering them an easy guide to follow, directing users toward desired actions or outcomes.

You can address the directional guidance heuristic with improvements like predictive search or sort order.

Use Predictive Search

Increasing the use of search is a great way to encourage intentional browsing, but often, users need a helping hand to guide them to relevant products or pages.

Featuring popular or relevant products in search suggestions can improve product discoverability, increase the helpfulness of search, and help users quickly and easily navigate the site.

Deeper customizations might include featuring different products based on user segment, search terms entered, seasonality, or geographic area of the site.

Change Sort Order

Sort orders often default to standard settings that don’t support user goals.

Testing alternative default sort orders (by popularity, by price) can help users quickly discover the products that are right for them and improve directional guidance.

Heuristic #6: Incentives

Provide additional motivation, confidence, and urgency for users to make a purchase. Ideally, incentives encourage a user to convert today rather than at a later date.

Violations of this heuristic may manifest as:

• Abandonment
• Comparison Shopping

You can address this heuristic by offering things like expedited shipping for VIP members, promotional offers, or guarantees.

Create Value-Based Promotions

Instead of discounting to incentivize purchases, which can ultimately devalue your product, consider a promotion that adds value. For example, buy-one-get-one-free, free shipping when you reach a minimum purchase amount, or a free gift with purchase.

Suggest Bulk Orders

Nobody likes running out of their favorite product. There are plenty of ways to incentivize adding products to the cart with tactics like cross-sells, upsells, or product bundling.

Suggesting shoppers stock up is a good way to increase AOV and secure long-term brand loyalty. This can be particularly effective if you have a shipping threshold.

How The Heuristics for Digital Experience Optimization Can Inform Your Strategic Roadmap

One of the most powerful ways to turn these six heuristics into an actionable improvement plan for your digital property is to use them to inform your strategic roadmap.

Armed with user research, identify common patterns or pitfalls that your users are experiencing. Then, group those patterns by the Heuristics for Digital Experience Optimization we covered above.

You can then prioritize the themes based on their potential impact on performance and develop a plan to test improvements. The whole process is outlined in more detail in our article on theme-based roadmaps, so I highly recommend checking that out if you’re looking to turn conversion challenges into opportunities.

The power of heuristics is being able to strategically and efficiently identify your digital challenges in a way that is centered on the user experience. At the end of the day, if your customer is getting stuck in your digital journey, you need to find out where and smooth out their path to purchase. Until that happens, not much else matters.

If you want to do just that and would like expert support in the process, take a look at our Digital Experience Optimization Program. The custom program gives you access to an entire team of researchers, strategists, designers, and developers so you can build a better website, app, or digital product.

The post How To Solve Common Optimization Issues Using Heuristics (With Examples) appeared first on The Good.

Speed bumps signal the driver to slow down, the rest stop sign reminds them they can take a break on a long trip, and rumble strips alert when they’re swerving into dangerous territory. Curbs keep drivers and pedestrians on separate sections of the road, while curb cuts offer an optional designated crossing area.

All of these indicators intuitively keep us on the right path while occasionally offering alternative routes or opportunities we may not have been thinking of. Similarly, in digital experience design, directional guidance nudges users on a path toward their end goal.

It helps users find what they are looking for by adding visibility to elements that will increase their motivation or intent. It displays compelling options of where the user can go next.

The placement of specific website elements can either guide a user toward their ideal product or take them off track. Strategizing and keeping directional guidance top of mind as you optimize can help direct users through a complicated digital journey.

What is directional guidance in UX?

Directional guidance in UX is a sum of strategies, tactics, or elements that optimization experts implement to help users accomplish a specific goal on a website.

It’s an umbrella term that encompasses anything put on a user’s path to help them find what they want.

“Directional guidance doesn’t just increase the findability of what a user knows they want, it increases the discoverability of things a user didn’t even know they wanted. It adds utility across a website so users can build a mental model of what is in the company’s catalog and how to get there.”

Natalie Thomas, Director of Digital Experience Optimization & UX Strategy at The Good

In digital experience design, directional guidance can be as direct as a clear call to action and easy-to-use navigation or as indirect as personalizing recommendations and surfacing relevant content. It’s like a personal website concierge telling you, “right this way.”

Directional guidance is one of The Good’s six Heuristics for Digital Experience Optimization. They are:

1. Priming & Expectation Setting
2. Trust & Authority
3. Ease
4. Benefits & Unique Selling Points
5. Directional Guidance
6. Incentives

5 ways to improve directional guidance (with examples)

So, what are some specific ways to improve directional guidance on your website?

Of course, we have to caveat that you should develop strategies relevant to your specific goals and users, but here are a few ideas to get the wheels turning.

1. Add suggested products to predictive search

Increasing the use of search is a great way to encourage intentional browsing, but often users need a helping hand to guide them to relevant products or pages.

Featuring popular or relevant products in search suggestions can improve product discoverability, increase the helpfulness of search, and help users quickly and easily navigate the site.

Deeper customizations might include featuring different products based on user segment, search terms entered, seasonality, or geographic area of the site.

2. Change sort order

Sort orders often default to standard settings that don’t support user goals.

Testing alternative default sort orders (by popularity, by price) can help users quickly discover the products that are right for them and improve directional guidance.

For example, we tested sorting products by featured rather than families to improve the visibility of product listings and increase engagement on category pages.

This resulted in an 8.5% increase in conversion rate.

3. Add quick links

Even within a well-organized menu, users can struggle to navigate to relevant information quickly.

Showcasing what actions users can take with “quick links” promotes directness toward relevant pages.

Improving directional guidance with quick links can encourage deeper page depth from paid ads, decrease bounce rates, and lead to increased transactions.

4. Improve visual hierarchy of mobile menu

A key principle of visual design, visual hierarchy, is crucial to improving directional guidance.

Many websites have poor content hierarchy, particularly in mobile navigation. Users can suffer from indecision without the guidance of a well-organized and directional menu.

Separating shopping-focused links from other kinds of content in the navigation can increase directional guidance and decrease distraction for would-be shoppers.

For one of our clients, re-ordering the popular navigation menu links in line with the primacy and recency effect positively impacted conversions, leading to over $4MM in annual revenue gains

5. Add sticky elements

Another way to improve directional guidance is making key elements sticky and therefore, easily accessible to users as they browse.

Sticky CTA

When users are considering a product, they will scroll through product detail pages to find details that make them more confident to purchase. For example, adding a sticky CTA like a sticky add-to-cart or a sticky buy button, can provide easy access to add-to-cart once the user decides.

Adding a sticky CTA is great for brands with longer PDPs, specifically increasing engagement with product details, reducing friction, and increasing adds to cart.

Sticky search

High-intent users often have an idea of what product they are looking for, and search users generally convert 5-7x better than non-search users. Using search can help them quickly find the product they have in mind.

So, making the search bar sticky improves directional guidance by encouraging use of search and helping guide shoppers to right-fit products.

This is especially true for sites that have a large amount of high-intent users, many SKUs, or sites where users primarily navigate with the search bar.

What are examples of poor directional guidance?

Now that you have five ways to improve directional guidance, what are some signs that your site suffers from poor directional guidance?

Low visibility or low discoverability of items: If your items or products are hidden behind multiple clicks or proverbial corners, your users can’t find what they are looking for (or discover something they don’t know they need!)

Unclear system status: If there is a break in communication between the computer or digital product and the user, then you have poor directional guidance. For example, giving an error message right when a user starts typing their password before they have even clicked ‘login.’

Content fatigue: When your site has too much content (text, images, links, etc.), the user might not find the one product that is meant for them which will trigger a purchase decision.

Confusing or unclear language: Speaking in brand language that isn’t clear to the user removes information scent and prevents them from moving down the funnel.

These are just a few things to look out for in your user testing and research to uncover poor directional guidance in your digital experience.

Is wayfinding the same as directional guidance?

At this point, UX practitioners may be asking themselves, “how is this different from wayfinding?”

Wayfinding falls under the umbrella of directional guidance but is not the same thing.

To differentiate the term, our team often uses the analogy of an airport. Wayfinding is like hanging signs in the airport. While helpful, imagine all the information you needed in an airport was on a sign. You wouldn’t know what to read or look at next.

Instead, airports analyze foot traffic and incorporate strategic pathways, seating areas, audio cues, and symbols to both get you where you need to go AND offer helpful stops along the way. This is directional guidance.

Wayfinding is the signs and cues pointing you to your gate, while the directional guidance might be a water fountain and bathroom along the way for a convenient stop before your flight. Things you may not have realized you needed, placed strategically to help you uncover your needs.

For digital experience design, it is similar.

“Wayfinding is about navigation, while directional guidance is about having the right information on the page, in the right place, so that users know what to buy or sign up for.”

– Maggie Paveza, User Experience and Optimization Strategist at The Good

Are directional cues the same as directional guidance?

Another common mistake is using directional cues interchangeably for directional guidance.  

Directional guidance and directional cues work together to keep the user on their path, but directional cues specifically are visual hints that guide a user to the most important elements on the screen.

There are explicit directional cues and implicit directional cues, including:

• Explicit directional cues:
  • Eye gaze
  • Arrows
  • Gesturing or pointing
  • Object positioning
  • Lines
• Implicit directional cues:
  • Contrasting colors
  • White space
  • Visual hierarchy
  • Framing or encapsulation

Again, directional guidance is the umbrella term, and directional cues may support that overarching goal of guiding the user to where they need to go.

The importance of directional guidance in digital experience optimization

The job of product marketing and ecommerce leaders is to guide the user to the best-fit product for them. Directional guidance is the umbrella term for doing just that.

It’s a combination of many strategies, tactics, or elements, including wayfinding, feature discovery, merchandising, information architecture, bundling, navigation, and more. Finding the right way to make these all work together for your user is the key to optimization.

It can be a lot to accomplish without an external, user-centered POV. If you’d like support in your efforts, contact us.

The post Directional Guidance: What It Is And How To Improve It appeared first on The Good.

However, with lots of research techniques associated with digital experience optimization, terms can often get mixed up. For example, some think user testing and user research are interchangeable. However, the two terms are only related, not synonymous.

What is user research?

User research is the umbrella term that user testing falls under. User research can also refer to other research methods, such as focus groups, interviews, and surveys. 

User research is a structured way to find out why users take certain actions. It’s an effective way to step out of your head and into the buyer’s journey so you can provide better products and experiences. 

The biggest benefits of user research include:

• Getting outside the jar
• Knowing what to improve (instead of guessing)
• Providing better customer-centric experiences

What is user testing? 

User testing is a specific sub-division of user research.

User testing can validate design decisions, reveal common pain points, and inform A/B testing. It asks members of your core audience to think aloud as they complete specific tasks on your site. During testing, the evaluator observes how users complete the tasks without assistance and then draws conclusions from the users’ ability to complete the tasks.

The success of your testing hinges on how you screen and select your users. To choose the right users for testing, define your core audience demographics by mining your analytics for sample data on age, gender, and location; this will tell you who is converting and who is not at a basic level. Most testing platforms will allow you to screen for gender, age, and location simply by checking a few boxes.

They are related, not synonymous

While user research and user testing are not interchangeable, they are related. When you are doing user testing, you are also doing a form of user research with a specific goal in mind to uncover the pain points of your users. This means that it is not a matter of choosing which to use between the two but rather a matter of understanding what both methods truly entail. 

Sometimes, big mistakes can come from small misunderstandings, so don’t be afraid to ask questions, even if you think they’re simple or obvious. Chances are, they aren’t as obvious as people assume.

Dig Deeper:

These are only the basics of user research and user testing. If you want to learn how to conduct high-impact user testing, we have a series of articles that you can read.

• How to Conduct High-Impact User Testing: Part 1 – Thoughtful Panel Selection
• How to Conduct High-Impact User Testing: Part 2 – Formulating Tasks and Questions
• How to Conduct High Impact User Testing: Part 3 – Analyzing the Results

The post How is user testing different from user research? appeared first on The Good.

It’s no secret that we need to be partially or fully online to live our day-to-day lives.  

With online interactions at an all-time high, any point of friction or negative experience throughout the customer journey can lead to lost business and, worse, lost customers. Its only natural for customer expectations to evolve with the times, and you need to make sure you are meeting those expectations. 

Customer expectations will be different depending on your market and your industry. However, there are still common factors and trends you should consider. 

In this article, we’ll discuss why customer expectations are important and how you can better understand them through various research methods. We’ll also cover the different types of customer expectations, focusing on digital expectations. 

Why Is It Important to Know About Customer Expectations?

Meeting customer expectations can significantly impact a business’s long-term success. In understanding a customer’s point of view, marketing and sales professionals also gain a window into spending habits and customer behavior. 

However, most businesses don’t understand customer expectations. A study from Salesforce found that 51%of customers believe most businesses fall short of their expectations. 

This presents you with a tremendous opportunity to leapfrog over your competition. Once you know the expectations of your customers, you can begin to optimize your site to meet each level of those expectations. With each level of optimization, you’ll capture more of your target market and increase your overall conversion rate.

Customer expectations are also crucial because they: 

• Impact brand image: When customers see your products or services as top-notch, it improves their overall view of your brand.
• Drive product sales: When customers expect great things from your offerings, they’re more likely to choose your brand, increasing your profits and hitting sales targets.
• Boost brand loyalty: Surpassing customer expectations can make them more likely to buy from your brand again. 
• Outshine competitors: Satisfied, loyal customers may recommend your products or services to others, giving you an edge in a competitive market.

Types of Customer Expectations

Customers can have varying expectations, and these expectations come in different types. Knowing what type of customer expectation you’re dealing with will give you an idea of how to deliver a great experience and help you achieve customer satisfaction.

Explicit Customer Expectations 

Explicit expectations are the defined expectations that every customer has in mind before they make purchasing decisions. These expectations are usually related to price, quality, and delivery time. 

For example, customers have specific price expectations for specific items with specific features. Let’s say a customer walks into a shop with the hopes of buying a new mobile phone. If the price of the product falls beyond the price range they are expecting, chances are you will lose a sale.

Implicit Customer Expectations

Implicit Expectations, on the other hand, are the expectations that customers have based on the feedback they’ve heard about your brand. This could be feedback from family, friends, or even customer reviews they have read online. 

These could also be expectations that your customers have based on knowing the competitors within your industry. It’s only normal for customers to comparison shop, but this doesn’t mean that you should start comparing your ecommerce brand or website to other companies or to industry benchmarks. 

Interpersonal Customer Expectations

Interpersonal Expectations are created from customer interactions with your team members or your employees. Note that these interactions can include in-person, chat, or phone interactions. 

As such, your customer service teams play a crucial role in meeting the interpersonal expectations of customers. If you have excellent customer service and employees who go the extra mile, chances are your customers will be more willing to make a purchase. 

Dynamic Performance Expectations

Dynamic performance expectations are the expectations customers have about the changes in the product or service over time. This means that, as a business, you should always be ready to adapt and shift depending on the overall environment or evolving customer needs. 

It can be hard to determine or keep track of customer needs, but using a customer survey or a similar tool can be an easy way to make sure you are offering positive experiences to your customers. 

Digital Customer Expectations

These are the expectations customers have relating to your website, social media channels, or even email. Digital expectations usually relate to website navigation (how easy or difficult is it to find something?) or the checkout experience (how easy is it to order and make a purchase?).

The evolution of customer expectations has a lot to do with the digital experiences offered by brands. Modern customers now anticipate increasing levels of convenience, speed, and personalization in their interactions with businesses. To align with these expectations, companies must continuously advance their digital experience. 

Brands can meet digital expectations by thinking of the following:

• Offering more options when it comes to payment methods. Customers now expect businesses to cater to their preferred payment choices, offering them flexibility in payment. 
• Providing opportunities for feedback. Your customers want to feel heard. Make sure you are giving them channels to easily communicate with you or your customer service teams. 
• Ensuring seamless connectivity across all devices. In the realm of ecommerce and SaaS, customers expect that they will be able to access your website with any device. This means you not only have to optimize your desktop experience, but you should also make sure that your mobile interface is seamless. 
• Creating tailored offerings and recommendations. Brands should be able to map the customer journey and identify areas where they can personalize the experience. You can leverage data from analytics and customer segmentation to create relevant suggestions for your customers’ needs. 
• Protecting their data and privacy. There’s nothing more important than gaining a customer’s trust and maintaining that trust, which is why it is the foundation of our hierarchy of conversions. In order to keep your customers secure, you need to make sure that you are:
  • Transparent about the data you are collecting 
  • Thorough with the security measures being implemented to safeguard their information
  • Adhering to all relevant regulations pertaining to data protection and collection as required by the law 

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Understanding Your Customers’ Digital Expectations 

If you’re optimizing a digital product, you may not see customers face-to-face, but there are still several ways for you to better understand and improve the customer experience you provide. 

Usability Testing

What it is: Usability testing is defined as getting customers to test and evaluate a product, feature, or prototype. 

How it works: In usability testing, the facilitator asks people who fit the brand’s ideal customer profile to go on the website and accomplish specific tasks while they talk aloud about their experience. 

How to leverage it: This is a great way to develop a deeper understanding of your customer’s experience on the site because they share first-hand feedback about the overall digital experience. When they can’t find what they’re looking for or get confused by something, they will call this out. You will be able to identify where your customers get stuck and improve it so that they can continue to seamlessly navigate through your site.

If you’re unsure how to properly conduct user testing, there are tools and services available to help you. 

Reviews and Social Listening 

What it is: Reviews and social listening are conducted by analyzing and monitoring what your customers are saying about your brand on various social channels and review platforms. 

How it works: If you want to set yourself up for success, you can use an app that’s dedicated to sifting and collecting information on the web. Apps such as these can aggregate information online regarding your name, demographic, industry, or relevant hashtags. 

How to leverage it: Aside from gaining insight into areas for improvement and customer satisfaction, you can also leverage reviews and social listening to ensure positive brand perception. Brand perception refers to the thoughts and feelings people associate with your brand. Once brand perception is established, it can be difficult to change. 

Session Recordings 

What it is: Session recordings are recordings of actions taken by visitors as they browse your website. Unlike usability testing, users do not talk about their experiences while browsing the site. 

How it works: With the use of a digital analytics tool, you can capture and replay how people use your site and interact with the elements within it. 

How to leverage it: The primary goal of a session recording is to help you identify trends or patterns in customer behavior that can help you better understand them and find out which areas of the site need improvement.

Surveys

What is it: Surveys are a great and simple way to obtain data from your users. Unlike the first two methods, surveys usually provide more quantitative data relating to customer behavior. 

How it works: Another advantage of using a survey is that it can be sent from almost any device. Surveys are usually created as a form and sent to customers to gather information or feedback. 

Another option could be to send surveys to your customer service teams. Service teams interact the most with customers. They often speak to customers about their pain points or struggles throughout the customer journey. 

How to leverage it: With surveys, you can ask very specific and tailored questions depending on what you’re trying to learn about customer behavior or customer experience. Survey results can inform decision-making or hypothesis testing. 

Heat Map Analysis 

What it is: Heat maps show you the part of your site that customers find most relevant or eye-catching. They are presented as data visualizations with different color gradients that represent the level of frequency, density, or intensity of values in a data set. To put it simply, they are a snapshot of how your customers interact with elements or pages in your website. 

How it works: You can still create heat maps by hand or through Excel spreadsheets. However, thanks to the evolution of technology, there are also digital experience tools specifically designed to generate heat maps for users. 

How to leverage it: Heat maps can tell you how to get your customers to take action because they detect what does and doesn’t work for your website. By looking at heat maps, you’ll develop ideas for experimenting with CTA buttons and the position of website elements. With heat maps, you can also see: 

• What content site visitors and customers fail to notice 
• How visitors interact with links, navigation, and buttons 
• What issues they experience on different devices 
• How they get distracted by certain elements 

How To Understand And Meet Digital Customer Expectations 

Once you are able to get a better understanding of your customer’s expectations, you can then take the necessary steps to meet (and exceed) those expectations. You can boil it down to three simple steps.

Step #1: Listen and Respond When Your Customers Speak

First and foremost, listen to your customers early and often. Use surveys to get customer feedback on different aspects of their online experience.

Provide numerous avenues for customers to get in touch with you, such as email, chat, and phone. Few things are more frustrating than not being able to easily communicate with a company when there’s a problem.

If your customers have to go spelunking deep into your menus to find contact information, they’re going to come away feeling frustrated.

When contact your company, and you do nothing about the problem, they’re going to feel even more frustrated. Thus, they will probably communicate their experience to others.

You need to have a systematic process in place to escalate issues raised by customers.

Step #2: Talk Regularly To Customer Service

Ask your service reps to provide some input. They interact with customers on a daily basis, and they probably have the best sense regarding the expectations of your customers.

A customer usually files a complaint when the brand doesn’t meet their needs or expectations.

Additionally, the more communication there is between customer service and the rest of the team, the more likely it is that you can fix inefficiencies.

Fixing the inefficiencies will make customers happy, which, in turn, makes your support reps happy. Ultimately, when it helps increase conversions, it makes your revenue happy.

Step #3: Improve Upon Problem Areas

By consistently listening to your customers and your customer support reps, you create feedback loops. This allows you to identify both the areas in which you’re doing well and the ones that tend to cause problems for your customers.

Once you’ve identified the problem areas, you can begin systematically and strategically using CRO methods to make improvements.

By focusing on reducing friction in the most problematic areas, you can make a significant impact relatively quickly.

Lay the Right Foundation, Meet Customer Expectations

The digital space is constantly changing and evolving, and your customers are changing along with it. In order to survive and thrive, brands need to consistently deliver great customer experience. They have to be customer-centered, data-informed, and insight-driven.

Customers have different expectations for different brands. However, when brands learn to listen to their customers, they can meet and exceed these expectations. They will then be in a position to lay the right foundation for successful customer relationships.

In a landscape where products and services can be very similar, your understanding of your customers and their expectations can be a real differentiator that separates you from competitors. 

If you start with the fundamentals, you can create seamless customer experiences.

And when you do that, you’ll create customers for life.

The post How to Understand and Meet Digital Customer Expectations appeared first on The Good.

As a brand, it’s important to understand customer sentiment: how your customers feel about you. Once you uncover their thoughts, you can make ethical optimizations to your business and website experience that create more positive sentiment.

In this guide, we explain customer sentiment and how to analyze it. We also explain how ethics are intertwined with sentiment and how our proprietary model helps you identify ethical activities that have the best chance of moving the needle.

What is Customer Sentiment?

Customer sentiment refers to the emotions customers feel toward your brand, products, or services. It helps you understand whether your customers’ feelings are positive, negative, or neutral, as well as why they feel that way.

Generally speaking, if your customers have positive sentiment, they are more likely to buy and become repeat loyal customers. Customers who think of your brand negatively are less likely to buy.

What affects sentiment? Your products are the biggest factor. If people love your products, they’ll probably think well of your brand. But your service quality, personal interactions, charity work, company values, website experience, and other factors can influence sentiment.

Sadly, there is a discrepancy between companies’ opinions on customer sentiment and how customers actually feel. A NICE CXone report discovered that 50% of businesses believe their customers have a positive sentiment toward their brand, but only 15% of customers agree.

What’s interesting about sentiment is that it’s infectious. It can spread from one customer to others. For instance, suppose a customer has a delightful experience with your brand. They will undoubtedly share their experience with others, which will improve those people’s sentiment.

If you gather enough feedback from customers about their feelings, you can take steps to address any issues and build a better brand experience. But to get this feedback, you have to ask the right questions.

Direct vs. indirect feedback

Customer sentiment relies on direct and indirect feedback. Both are valuable. Their differences lay in how you get them.

Direct feedback refers to statements your customers make to you directly. This includes emails, phone calls, customer support tickets, live chat, or in-person conversations. Generally, these only happen when customers aren’t happy, though direct praise isn’t uncommon.

Indirect feedback refers to statements your customers make publicly, but aren’t intended for you. This includes conversations with friends and social media conversations. With the right tools, you can find and listen to these statements.

Some communications straddle the line between direct and indirect. A Twitter complaint, for example, is directed at the brand, but the tweeter relies on the pressure of a public conversation to make their point or get a response.

Measuring customer sentiment

We have lots of ecommerce metrics to measure how people feel, such as customer satisfaction (CSAT), customer effort score (CES), ease of doing business (EODB), or Net Promoter Score (NPS®).

While those metrics are valuable, they don’t attempt to understand why customers feel the way they do. To learn why, we have to approach it qualitatively.

More than 90% of communication is nonverbal, but that presents a challenge when you’re dealing with written communication, which lacks visual and acoustic aid. The words people use are only a fraction of their feelings.

This is referred to as the Iceberg Principle. Like an iceberg’s mass, which sits mostly under the water, your audience’s sentiment is similarly obscured. It’s your job to decipher the true meaning.

Customer sentiment is based on words, so we have to either a) have to have conversations with our customers, or b) peer into their conversations with their friends, family, and followers. A star rating will tell you whether a customer had a good or bad experience, but it doesn’t give you any information in regards to fixing the bad and leaning into the good.

Sentiment analysis, therefore, will put you on the path toward improving the experiences of all of your future customers. According to the Customer Service Trends for 2022 report, 64% of consumers stop doing business with a brand after only two or three bad experiences, so it’s important to make sentiment-improving changes quickly.

Sentiment analysis is the process of trying to understand your customers’ and potential customers’ feelings about your brand, products, and overall experience. Furthermore, it helps you look beyond their words at the tone of their comments. You can do this manually or with a customer sentiment analysis tool.

Let’s use a basic example. Suppose a customer leaves a product review that simply says, “It’s fine.” At face value, that’s a good review. “Fine” certainly isn’t negative, but even through the text we can see that the customer isn’t really happy with their purchase. Maybe the product isn’t what they wanted, but not worth initiating a return.

They said “Fine,” but in actuality, they had a negative experience. Even the most basic customer feedback can help you discover potential optimizations.

The Intersection of Ethical Website Design and Customer Sentiment

Now that you understand customer sentiment, you’re probably wondering how to improve it.

There is a general correlation between higher sentiment and more conversions. It’s not a linear relationship, however. While customers who like your brand are more likely to buy, increasing sentiment doesn’t always improve conversions and boost sales.

There are definitely some things you can do to improve customer sentiment and will make people more likely to purchase. Social proof, for example, makes customers feel better about their purchase and improves conversions.

However, some sentiment-improving activities won’t impact your conversion rate. Having a blog or offering a freemium model of pricing makes people feel good, but doesn’t necessarily move users down the conversion funnel.

As you would expect, activities that produce negative sentiment, such as poor imagery, hidden prices, and slow-loading pages, can hurt your conversion rate.

However, we have to consider the ethical ramifications of any initiative, even if they lead to more sales. Some sentiment-reducers can actually boost sales, like popups, false claims, and blatantly copying your competitors. These initiatives work in the short term, but they often have long-term, irrecoverable effects on your brand.

If you’re confused, don’t worry. Here’s a model we put together that shows common site elements and how users interpret them based on our research and testing.

The top left quadrant represents activities that will improve customer sentiment, but won’t boost your conversion rate. These are not a priority.

The bottom left quadrant represents activities that will reduce customer sentiment and reduce your conversion rate. They frustrate users and detract them from making a purchase. Avoid them at all costs. If you have any of these issues, don’t bother testing. Just fix them.

The bottom right quadrant represents activities that might improve your conversion rate, but are still unethical. They work, but that could affect your brand image over time. They also might have non-customer-related consequences. False claims, for example, could cause legal trouble.

We know that no one intends to create dark patterns or act unethically toward their site visitors, but it does happen. For instance, there is a fine line between “urgent language” and misleading users. These are elements to stay away from and potentially test to determine if it improves sentiment and purchases.

The top right quadrant is the intersection of ethics and good design: activities that improve sentiment and conversions. These represent opportunities that deserve your attention.

What we do at The Good focuses on this top right quadrant. We approach optimization with an understanding of what drives positive sentiment. This helps us develop better outcomes for our clients. A client may have a lot of ideas but we may not test all of them for data-backed reasons or because we know it won’t move the needle towards purchase.

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How to Find Ethical Initiatives That Increase Customer Sentiment and Conversions

In order to find initiatives for testing, we first focus on that top right quadrant. This is the sweet spot where optimizations have a reasonable chance of improving conversions and increasing customer sentiment.

• Post-purchase incentives
• Shipping incentives
• Imagery with product in-situ
• Brand value alignment
• Social proof
• Search improvements
• Quality tiles
• Priming
• Buy-now-pay-later
• Urgent language

Does this mean that those initiatives will definitely improve sales and sentiment? No. Nothing is guaranteed because all brands, products, and audiences are different. But these are great topics to inspire your experiments.

Furthermore, there are probably some ethical activities that improve sentiment and conversions that are unique to your business. Maybe your customers want a product builder on your site. Maybe they want you to get involved with a related charity. Or maybe they want special, nonstandard product filtering.

If you aren’t sure what your customers want, you’ll have to go out and get that information. Here are some actionable ways to determine customer sentiment and learn how to improve it.

As you hunt for your own optimization, plot them in our sentiment-ethics model, then focus on the ones that fall into the top right quadrant.

1. Collect reviews and survey responses

If you aren’t already, someone on your team should be reading every customer review that comes in. This includes reviews on individual products and general brand reviews on Google, Yelp, Facebook, and Trustpilot. If you don’t have reviews coming in naturally, start requesting them as part of your post-purchase experience.

Don’t focus on the bad reviews from unhappy customers. Positive customer experiences can validate what you know works in your website experience and marketing campaigns.  

Additionally, use online surveys to collect your customers’ opinions. These are typically longer than a simple product review request, so your response rate will be lower, but they give you the opportunity to ask probing questions. Plus, surveys aren’t public, so only you see the answer. You can encourage your customers to be brutally honest.

Who should take your customer satisfaction survey? It depends on what you want to know. If you want to know what you’re doing right, talk to your most active customers. If you want to know what you’ve done wrong, ask customers who only purchased once.

Most importantly, make your customer surveys easy for customers to complete. Send a link to a simple form. Include multiple choice questions they can complete quickly, but also add comment boxes so they can provide unique feedback in their own words.

2. Conduct customer interviews

User interviews are one-on-one conversations with existing users or potential users in your target audience. The purpose is to get direct feedback on how they feel and what you can do better in your brand experience, including your ecommerce site.

Admittedly, user interviews are expensive and time-consuming. Someone on your team has to conduct each one. And sometimes you don’t come away with any valuable feedback. If you need feedback at scale, opt for social listening or satisfaction surveys.

But customer interviews have the potential to provide a surprising amount of information, especially if the interviewer has experience pulling information out of your customers. A skilled interviewer can probe deeply to extract powerful insights.

Analyzing your feedback from interviews is challenging because the information is qualitative and unstructured. You (or someone on your team) will need to go through them one by one and divide customer comments into categories that help optimize the website. In some cases, you might look for answers to specific questions, such as “Why don’t our users take the quiz?”

3. Monitor customer service calls and live chat

When customers contact you directly, it’s important to measure their sentiment. Since 96% of customers don’t complain when there’s a problem, you have to take the ones that do complain seriously.

Suppose a customer calls to complain about missing shipment tracking information. Perhaps they didn’t receive the shipping confirmation email. Or maybe there’s something wrong with the tracking field in the email itself.

In this case, the customer support representative should summarize the encounter in a shared document or CRM. Then, review these notes regularly to look for repeat complaints. If you see sentiment patterns, have someone fix the issues so future customers don’t suffer the same problems.

4. Conduct customer sentiment analysis with AI

Sentiment analysis (sometimes called opinion mining) is a process that uses conversational artificial intelligence, natural language processing, and machine learning to determine the sentiment behind text. It attempts to extract those intangible bits of communication and identify customer issues.

These kinds of tools can analyze any type of text: social media posts, review sites, news articles, blogs, support tickets, live chat transcripts, and more.

After reviewing the comments, the AI will unpack the text to understand its structure and classify the words as positive, neutral, or negative, thereby turning qualitative information into quantitative data that can be analyzed at scale.  

How does it work? The algorithms turn words into vectors, then use the distance between those points to understand their relationship. For instance, a sentiment analysis AI would group “Honda” and “Ford” together because they are related. (This TEDx talk explains everything.)

Sentiment analysis can detect emotions, like anger, happiness, frustration, or disappointment at different stages of the customer journey. It can even deduce what customers think of your product. Suppose customers complain that a product “breaks right away” or “isn’t very durable” or “fell apart in my hands.” In this case, the AI would classify all of those comments as “low quality” to give you a comprehensive picture.

Fortunately, you don’t need to build this yourself. There are plenty of pre-built sentiment analysis SaaS tools your data team can use, such as Talkwalker, Reputation, Repustate, Brand24, or SentiSum.

5. Interact with your audience on social media

A proper social media presence is more than just blasting out content into the void. Smart brands engage with their audience to create genuine relationships and extract valuable social media feedback.

In a 2020 Bain & Company study, 54% of companies reported using technologies for analyzing customer sentiment from social media platforms. This is expected to exceed 80% in 2023.

The benefit to these interactions is that you can hear from all customers, not just recent ones. You can even learn what non-customers think of your brand and website experience.

When a social media user mentions your brand, document their comments. Try to determine why they made those comments and how you can fix the problem for that customer and future customers.

If your brand gets a lot of social media activity, consider using a social listening platform to monitor conversations at scale, such as Sprout Social, Falcon.io, or Hootsuite. These tools let you track brand mentions, hashtags, and any keywords you like.

The Best Results Come From Tailored Insights

Best practices only take you so far. At a certain point, you have to run methodical experiments to determine what moves the needle for your brand and ecommerce site.

At The Good, our experts can help you develop accurate insights tailored to your specific site and user goals. We’ll find ways to increase conversions and customer sentiment without violating ethics, mistreating your users and customers, or causing long term damage to your brand.

Our years of experience let you focus on the initiatives that will have the greatest impact. You may have a lot of ideas, so we work collaboratively with you to test ideas that move the needle towards purchase while surfacing improvement opportunities that your team can implement. 

Learn more about our Conversion Growth Program. Let’s accelerate your business growth with our done-with-you optimization program that has proven results and no long-term commitments.

FAQs About Customer Sentiment and Ethical Design

What is customer sentiment?

Customer sentiment refers to the overall attitude, opinion, and emotions of customers towards a product, brand, or service. It can be positive, negative, or neutral and can have a significant impact on a company’s success or failure.

What is a sentiment example?

An example of negative customer sentiment in ecommerce is when customers leave negative reviews about a product they purchased online, citing issues such as poor quality, incorrect sizing, or slow shipping times. This negative sentiment can discourage potential customers from making a purchase, leading to a decrease in sales and revenue for the ecommerce business.

How do you measure customer sentiment?

Customer sentiment can be measured through various methods such as surveys, feedback forms, social media monitoring, online reviews, and sentiment analysis tools. These methods allow businesses to gather data and valuable insights about customer opinions, emotions, and attitudes towards their products or services.

What is ethical website design?

Ethical website design involves creating websites that prioritize the privacy, security, and well-being of users. It includes transparent data collection practices, accessibility for all users, and user-centered design that prioritizes usability and functionality. Ethical website design also avoids the use of manipulative tactics to exploit or deceive users.

What is customer sentiment analytics?

Customer sentiment analytics in ecommerce involves analyzing customer feedback, reviews, and social media mentions to understand customers’ emotions, attitudes, and opinions about a company’s products or services. This helps ecommerce businesses identify areas for improvement and make data-driven decisions to enhance the customer experience and ultimately drive sales.

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The post Drive Business Growth at the Intersection of Positive Customer Sentiment & Ethical Website Design appeared first on The Good.

A/B testing is the standard experimentation methodology for digital marketing. It provides statistical significance and a high level of confidence. The challenge, however, is that it requires a decent amount of web traffic. If you don’t have enough traffic, outliers, and anomalies can influence your results, thereby obscuring the truth.

Fortunately, A/B testing isn’t the only conversion optimization process you can use to make smart decisions. There are other tools that will arm you with sound insight so you can improve your conversion goals

In this article, we discuss the different types of testing that business owners with smaller sites and low traffic can utilize to optimize for conversions. But first, it’s important to understand why you can still test even if your site doesn’t get many visitors.

The Confidence/Tolerance Relationship

Confidence is an important part of statistical analysis. It refers to the level of certainty we have that the results of a test accurately represent the real world, expressed as a percentage. Note: Confidence rate should not be confused with the success rate of the experiment.

If a test yields a confidence rate of 95%, we can be pretty sure that the results of the test align with the results in the real world. 50% confidence means the results could be accurate, but there’s an equal chance they could be totally off base.

Testing based on small sample sizes because you have low traffic tends to yield low confidence values. This means it’s hard to tell if the results of your test represent what will happen in the real world. This is true for macro conversions like sales or micro conversions like category browsing, filtering, or adds-to-cart.

But whenever we discuss confidence, we also have to think about tolerance.

Tolerance is your ability to deal with the consequences of being wrong. If you implement a change to your business based on the results of the test, but the results turned out to be inaccurate, could you deal with the consequences?

For instance, suppose you test product page variations. At the end of the test, page variation #1 produced more conversions. But after pushing all of your traffic to that variant, you learn that the test was inaccurate and conversions ultimately fell, which represents lost revenue.

In a case like this, the reduced conversions represent the cost of learning. Can you tolerate that cost? Or would it cause irreparable harm to your business?

Some organizations have very little tolerance. An aircraft manufacturer that is conducting stress tests needs 99.99% confidence that the results they’re getting from the test they’re running are correct. If a bolt breaks on their plane in the sky, it is a high-risk situation. So they have a very low tolerance for error.

In ecommerce, we have a higher tolerance for error. Some companies may find that 75% confidence is sufficient, while others might only need some confidence to move forward.

When you optimize conversions for a small site with low traffic, you’re simply reducing the confidence of your testing. But if your tolerance is high, confidence is less important.

CRO for small businesses is unique because you have a high tolerance for the consequences of a bad experiment. If you’re only getting three conversions per day, a 30% or 50% drop doesn’t really mean much. Your job, therefore, is to determine what your tolerance is, and based on that, decide what kind of validation methods meet your needs.

Rapid Testing: Validation Beyond A/B Testing

The confidence vs. tolerance balance begs the question: How do we test different tactics on a site without much traffic if we can’t use A/B testing?

In the absence of data to validate statistical significance, we have to lean into rapid testing. When it comes to CRO for small businesses, this is the bread and butter.

Rapid testing is the practice of getting quick answers from people who aren’t site users, but still match your customer profile. The goal is to get feedback quickly on isolated elements. This type of testing is fast, efficient, and doesn’t require a large user base.

That said, there are two downsides to rapid testing. First, testing quickly means you give up some statistical certainty. Second, you aren’t testing your actual customers, so results are less reliable (but not unreliable).

Nevertheless, when we talk about CRO for small businesses, rapid testing is your best option. Let’s look at the different types of rapid testing that help you optimize a website with low traffic.

1. Preference testing

Preference testing is when you present two or more variants to users who match your target audience and ask for feedback on which variant is more likely to make a user perform a specific action or feel a certain way.

For example, you might show three ad designs to a number of people who match your target audience and ask, “Which of these is more likely to make you click the blue button and why?”

One of the best use cases for preference testing is display ads. If a company has eight versions of an ad and wants to narrow it down to two or three to test in the market against each other, preference testing helps to quickly cut out the worst performers and provides a great gut check with an audience that matches some of the criteria of the test market audience.

Another good application for preference testing is any marketing asset with small amounts of copy. Whenever you ask people to evaluate multiple options, it’s important to keep the options simple so they can take it all in. This is especially true when you’re testing language.

For example, you might present test participants with three headlines and ask, “Which one makes you more interested in the product?” Here, the amount of information that they have to retain in order to make a decision is small. If you want to test a lot of copy, break it into smaller chunks and administer multiple tests.

2. Tree testing

Tree testing is a usability testing method that helps evaluate the effectiveness of a website’s information architecture. It involves presenting users with a simplified, text-only version of the site or app’s hierarchical structure, often in the form of an accordion-shaped tree diagram, and asking them to complete specific tasks by navigating through the tree. It’s used to optimize site navigation, menus, and categories.

The goal of tree testing is to assess whether users can easily find the information they are looking for and identify any issues or potential improvements in the organization of content. It allows you to measure things like how long it takes for someone to find something, and how likely they are to think they can discover something there.

3. Card sorting

Card sorting is a generative type of research useful for earlier-stage work like product categorization and menu organization, which makes it especially applicable to CRO for small businesses.

In card sorting, participants are given a set of cards, each representing a piece of content or functionality, and asked to organize them into categories or groups based on their understanding or perception of how they relate to each other.

There are two main types of card sorting. In open card sorting, participants create their own categories or groups and name them based on their interpretations of the content or features.

In closed card sorting, participants are provided with predefined categories and asked to place the cards into the appropriate groups.

The results of card sorting exercises help designers and developers understand how users perceive the relationships between content or features, informing the design of navigation menus, categories, and overall information architecture to improve usability and user experience.

4. AI-based eye-tracking studies

Traditional eye-tracking studies involve tracking the gaze and movement of a user’s eyes as they interact with a website to understand how users consume information and identify areas that draw attention or cause confusion.

AI-powered eye-tracking studies replace the need for real people by using machine learning models trained on large datasets of human eye movements. These models simulate human eye-tracking behavior and then predict the likely gaze patterns and attention distribution of users when presented with a new website.

By leveraging AI, you can gather valuable insights into user behavior and attention more quickly and cost-effectively. No traffic is necessary, which makes it especially powerful for CRO for small business. While AI eye tracking is not a perfect representation of how real people use your site, it’s a great way to evaluate which option from a group is more likely to get attention.

5. Recall testing

Recall testing is where you show users a design for a short period of time (usually five or 10 seconds) and ask what they remember seeing on the page. You would conclude the one they remember to be more memorable and eye-catching.

For example, to test an add-on in the cart, you can show one version of the cart page design to 50 users, and another design version to a separate group of 50, and the better ability to recall they saw an enticing add-on would be a good indicator of a better placement or a more eye-catching placement.

6. Click testing

Click testing is similar to heat testing, but instead of showing where users move their mouse, it shows you where they clicked when you ask them to perform a specific task. This can be especially helpful when testing complicated interfaces like product configurators.

When we worked with Fully, we tested wireframes of their product configurators. We used click testing to instruct users to “Show us where you would click on the page if you wanted to update the color of the metal base.”

We assumed the participants would click the word “frame” on the right-hand panel that had an accordion-style menu. Instead, they clicked on the image, assuming the configurator was interactive since the picture was taking up 80% of the screen. This taught us we either needed to make the image clickable or make using the menu more obvious.

7. Preference test with open-ended responses

This type of test is similar to a regular preference test, except that participants are asked open-ended questions after completing their prompts. They might be asked, “What did you like about this design and why?” or “Which one are you more likely to pick and why?”

In some cases, getting an open-ended response enables you to hear the why behind a user’s action, thus providing you with insight into how you’re making users feel along the journey.

Other Optimization Tools for Low Traffic Sites

While rapid testing is the best way to validate your optimizations if you lack traffic, you’ll need some tools to generate testing ideas and gather qualitative data. The following knowledge-building tactics will help you understand foundational elements of your website, like traffic sources and demographics.

1. Surveys

Surveys are structured questionnaires designed to collect data from a specific population, providing valuable insights into attitudes, opinions, or experiences to inform decision-making or hypothesis testing.

People generally aren’t willing to complete long surveys, so ask the questions that are the most impactful to your business. In some cases, you may need to incentivize people to participate.

2. Usability testing

Usability testing is a research method that involves observing real internet users as they interact with a product or interface to evaluate its usability, functionality, and overall user experience, informing design improvements and enhancements.

A usability test requires a facilitator, participant, and a series of tasks for the participant to complete. The facilitator watches the participant complete the tasks or views a recording of the session later.

3. Reviews and social listening

Reviews and social listening involve monitoring and analyzing customer feedback and conversations on various platforms, such as review sites and social media, to gain insights into brand perception, customer satisfaction, and potential areas for improvement.

If you’re serious about social listening, it’s smart to use a dedicated app that aggregates all of the information on the web regarding your name, industry, demographic, and even relevant hashtags. Notice how this dashboard is tracking everything that has to do with British Airways.

4. Session recording

Session recording is a digital analytics tool that captures and replays user interactions with a website or application. The primary goal of a session replay is to provide you with insights into user behavior and help to identify areas for improvement. With a tool like Hotjar, you can literally watch people use your site.

5. Heat map analysis

Heat maps are data visualizations that use color gradients to represent the density, frequency, or intensity of values in a dataset, making it easier to identify patterns, trends, or outliers. It will show you the parts of your site your visitors find most relevant and eye-catching, and what they didn’t notice at all.

CRO for Small Business isn’t Impossible

While it’s true that conversion rate optimization is more reliable when you have a lot of traffic, that doesn’t mean it’s impossible if your site sees few visitors. You may have less confidence in your tests, but you also have a higher tolerance for being wrong.

That gives you a unique advantage when it comes to CRO for small business, as long as you’re willing to use some of the testing methodologies we explained above, instead of standard A/B testing in your conversion optimization process.

If you’re a small business, you’re the perfect size for a CRO Audit from UserInput by The Good. This audit taps into some of the tactics mentioned in this week’s article to provide a personalized action plan to help you design better shopping experiences and improve your most important metrics.

Want to stop guessing how your customers view your brand?

ASK THEM

The post CRO for Small Businesses: Optimizing Low Traffic Sites for Conversions appeared first on The Good.

Marketing and development teams spin off “new and improved” technology faster than any one person can possibly keep up with. That makes it easy to get confused about which tools to use in a particular situation.

I know exactly how that goes. I have often detected an unhealthy focus on tools or tactics over strategy among the marketing teams I interact with. In fact, I’m guilty of being tempted to chase after the next big breakthrough myself.

We must be careful not to become disciples of the technology meant to serve us. We too often give in to the erroneous idea that collecting the best tools and platforms means we’ve created an effective and functional strategy that leads to maximum conversions.

I’m not knocking the value of a smoothly operating A/B testing tool or an innovative platform that allows you to conduct user testing sessions in real time. I love technology and the insight it affords digital marketing managers.

Here’s the rub, though: without a sound conversion funnel, your expensive tools may be more dangerous than valuable. Your aim isn’t to spend more money on tools; it’s to use them to bring in revenue.

In this article, let’s explore some of the steps to developing an effective conversion strategy for your business. Keep this checklist on hand to make sure your team is working strategy first, tools second.

8-Point Checklist to Develop an Effective Conversion Strategy and Drive ROI

Here are eight steps you can use as a strategic cheat sheet for developing your conversion strategy. Don’t look at this as a necessarily ordered list. Rather, it is a checklist you can leverage to make sure the most critical strategic considerations are included in your plan.

1. Begin with the end in mind

You need to know where you want to go before you can find the right path to get there. None of the tactics matter until you are crystal clear about where you want to end up. Not only does destination inform direction, but it provides a built-in monitor to keep you on track.

Your conversion strategy should include an A/B testing roadmap that aligns with what you want to discover and improve. Your objectives for an A/B testing roadmap might include:

• Improving conversion rate to purchase
• Increasing average order value
• Increasing new user product engagement

If you have lofty goals for one year’s time, break that down into monthly goals so you can determine whether you’re on track. The last thing you want is to get to the end of the year and realize you missed the mark over and over again.

2. Do your research and refer to it often

Cross-industry studies show that, on average, less than half of an organization’s structured data is actively used in making decisions — and less than one percent of its unstructured data is analyzed or used at all. That is a whole lot of flying blind! Oddly enough, the root of the problem isn’t the lack of data. Rather, the dilemma results from too much data.

The more you have of something, the lower the perceived value. Give yourself a good shake. Pull the data you need, then use it rigorously to inform decisions.

When doing your research, ask yourself:

• What data is important to my goals?
• How am I measuring that data?
• What does this data tell me about my conversion rate and customers?
• How can this data fuel my decisions going forward?

3. Clearly identify your ideal customer

The better you know who you’re speaking with, the easier it is to communicate. Industry jargon, for instance, may be imperative in marketing materials aimed at a supplier but would confuse and alienate retail customers.

At The Good, we see this fundamental mistake get replayed over and over: the strategic plan defines ideal customer personas, but those detailed perspectives don’t make it into the marketing copy.

Twenty-something copywriters love to speak to twenty-something readers. That’s fine if that’s an accurate picture of the audience. But it’s not so fine if your ideal clients are fifty-something professionals who don’t share the same interests as your writers. Every part of your marketing must address the needs of your customers, not of your staff.

When identifying your target audience, don’t limit yourself to demographic details like age and location. Dig deeper to find out what makes them tick and consider things like:

• Their biggest challenges and struggles
• What gets them up in the morning
• Why they might need a product like yours
• How they spend their spare time
• Their interests
• Their goals and dreams

This will help you build up a three-dimensional image of a customer and ensure every piece of your marketing strategy and every message you send resonates with them.

4. Know and amplify your unique selling proposition (USP)

How are you different from your competitors? Why should someone choose you over them? Company leaders who know and hone in on the company’s USP invariably beat out companies that fail the USP test.

Even if you supply a commodity, there’s something different about you that will appeal to your ideal customers. Does your location and inventory allow you to guarantee on-time deliveries? Does your customer service team staff the phones and chat lines 24/7 and make sure everyone who comes to them leaves with a smile? Do you back your products with no-question returns and extended warranties?

Dig deep to uncover and fine-tune your USP. Then bring it up and brag about it every chance you get. See those guys with the “We’re the Best at Everything” banner? No, they aren’t. And their generic, fuzzy USP claims don’t fool (or attract) anyone.

Take Dossier, for example, whose value proposition is that it sells luxury perfumes at budget prices. Or what about Good Dye Young, which promotes inclusivity and champions vibrant self-expression in its USP.

5. Establish appropriate key performance indicators (KPIs) for an effective conversion strategy

Take a close look at the sales funnel your web traffic experiences, from the moment they find out about you to when they visit your website, browse your inventory, load up a shopping cart, and proceed to payment and checkout — and beyond. There are critical junctures along that path, and a close look will identify them. Better yet, travel the road yourself and note the points where the road forks.

Your KPIs will measure and report on what happens at the most telling of those locations.

Key metrics you need to know include:

• Click-through rates
• Average order value
• Conversion rate on each page
• Abandoned cart rate

Shrewd KPI selections beyond the basics, though, can help you test and adjust quicker and more accurately.

6. Uncover the stuck points that are getting in the way of reaching your goals and hitting KPIs

Conversion rate optimization (CRO) is largely a process of clearing rocks (sometimes boulders) from the sales path you’ve set out for your visitors. The more “stuck points” there are along the way, the more difficult it will be for prospects to become customers and for customers to become repeat customers.

It can help to create a customer journey map that illuminates the most common route customers take through your website and the desired action you want them to take at each stage. Once you’ve identified who your ideal customers are, you can map out the rest of the journey by:

• Defining the different stages of the customer journey (awareness, consideration, decision)
• Defining the steps in each stage of the journey in relation to your ideal customer (e.g. how do they usually become aware they need a product like yours? Social media? Via a search engine?)
• Identifying and implementing key touchpoints at each stage of the journey (e.g. publishing blog posts that educate your ideal customer on why they need a product like yours, adding testimonials to product pages, and including a CTA)
• Understanding and tackling customer objections (what’s stopping customers from moving from one stage of the journey to the next? How can you solve it?)

7. Build your effective conversion strategy around your biggest problems first

Determine which areas of your website are most affecting sales. Sometimes your strategy will need to focus on highly visible changes to your website design (making your site more mobile responsive, for instance), and sometimes it will require subtler adjustments that seem trite but are still bottlenecking sales.

There are several actionable ways you can discover where the sticking points are in your site:

• Heat mapping shows you where visitors click and where they spend the most time on each page
• User testing invites visitors to share feedback about the user experience
• Google Analytics shows you where visitors are dropping off

Once you have a better understanding of where the friction points are on your site, you can begin to map out areas for improvement and identify what you should prioritize.

Furniture brand Fully used heat mapping to identify how customers were using the navigation function on the site and used the results to make it easier for visitors to find what they were looking for.

8. Design a built-in testing protocol

Consistent testing tells you what’s working and what’s not working. After each test run, make necessary adjustments and test again. Did KPIs move in the right direction? Good. Try to make them even better next time. Did KPIs turn the wrong way? Great. You discovered something that won’t work. Make adjustments and try again.

Don’t look at testing (A/B tests are the most-known type, but there are more) as an add-on, occasional marketing rite. Make testing integral to your functional strategy design. Always be testing.

Start building your effective conversion strategy today

To develop an effective conversion strategy, you need to know your business inside out. You need to know who you’re targeting, what your unique selling point is, and even how your competitors do business.

Then, it’s a case of using the data you have available to make informed decisions.

There’s always the hit and hope option, but that will no doubt lead to disappointment. Instead, use cold, hard data to identify how your customers use your website, where the sticking points are, and what you can do to improve.

This information will drive your conversion strategy so you can hit the goals you’ve set for your ecommerce business (however lofty they may be!).

Ready to get started? Check out our services page for help building your conversion strategy.

The post An 8-Point Checklist For Building An Effective Website Conversion Strategy appeared first on The Good.