Until recently, A/B testing has often been a time-consuming process for marketing teams and involved a certain amount of guesswork. But by integrating AI tools into the testing process, brands can iterate at scale, analyze data fast, and drive customer engagement like never before.
Join the AI revolution
If you think AI now seems to be everywhere, you’re probably right. It’s safe to say that AI is currently creating seismic upheaval in the marketing technology landscape. One of the chief reasons for this is AIs ability to analyze large amounts of data incredibly quickly and find patterns in that data. And that’s something that happens to make it ideal for A/B testing.
The use of AI agents for A/B testing is literally a gamechanger for marketing teams, making it much easier to scale their testing and experimentation programs. Coming up with ideas to test, designing those tests, analyzing results, and implementing changes can take hours of your time. But a lot of this can be accomplished in a matter of clicks with AI, leaving your team more time to focus on high-level tasks.
This lets you to accelerate your testing program to a scale that is literally not humanly possible. And because everything AI does is driven by hard data, it also takes the guesswork out of testing and experimentation. It gives you the confidence that everything from generating ideas to analyzing reports is based on verifiable visitor trends on your website. It can also provide you with valuable insights that a human might otherwise miss.
All of this opens up a world of enhanced personalization and continuous optimization that marketers have until recently only been able to dream about. AI agents are now set to redefine A/B testing and drive unprecedented growth for those that make them part of their testing program.
Introducing Evi, your evidence-based marketing agent
Evi is AB Tasty’s AI-powered marketing agent designed for evidence-based decision making. It transforms complex data into clear, actionable strategies for repeatable, measurable results, ensuring every step you take is grounded in evidence.
Evi helps brands scale their experimentation by facilitating fast test launching without running out of ideas. But Evi is also designed to enhance human creativity and collaboration, not to replace them. Instead, Evi empowers marketing teams, helping them move from ideas to iteration quickly and confidently.
With Evi, your team can:
Greatly accelerate the testing process, speeding up your workflow with automated code generation and content suggestions
Extract deeper insights, all driven by actual website data and feedback using built-in AI analysis
Generate and prioritize test ideas based on your objectives and recent activity patterns
But don’t just take our word for it. Over 1,000 brands are already using Evi to constantly scale their testing and experimentation programs, resulting in noticeably accelerated campaign performance. By using Evi, they’ve reported:
33% more campaigns created
53% more campaigns launched
73% faster experimentation
The pressure now on companies to integrate AI into their testing programs can mean they end up with multiple AI tools for specific tasks with varying degrees of compatibility. By using Evi across your entire testing workflow, you guarantee the same consistent level of quality, the same context, and the same great results.
Features that transform how you test, learn, and grow
Evi’s six different AI agents will help you test with confidence, learn faster, and understand your users better than ever before.
Evi Ideas
Unsure about what you should be testing next? Evi Ideas will scan pages of your website and generate ideas for new tests based on hard data that will actually impact your testing roadmap.
Evi Hypothesize
Struggling to craft a strong hypothesis for your experiments? Evi Hypothesize uses an automated checklist of essential elements to help you turn fuzzy thoughts into a sharp, well-structured hypothesis that has clear objectives.
Evi Content
Still waiting for the development team to build your experiment? Evi Content will let you turn your vision into reality in just a few clicks. No matter how good you are at coding, Evi Content will let you instantly transform concepts into actual buildable experiments.
Evi Analysis
Tired of spending hours staring at colorful charts and wondering what they all mean?Evi Analysis will analyze your campaign data and deliver clear, actionable insights. It highlights winning variations and breaks down why they drive transactions so you can feel confident in your next move.
Evi Feedback
Feel like you’re drowning in feedback but don’t know what to do with it all? Evi Feedbacktakes the heavy lifting out of Net Promoter Score (NPS) and Customer Satisfaction (CSAT) campaigns. It analyses customer responses right within your reports, quickly identifying key themes and sentiment trends.
Evi Explore
Want to know if your tests will actually drive revenue?Evi Explore, powered by our own patented metric, RevenueIQ, lets you see what each test is worth before you launch. This gives you the confidence to make faster, more profitable decisions based on real revenue projections, rather than simply relying on traditional metrics like conversion rate or average order value (AOV).
Finally, AI you can trust
And you can rest assured that Evi only uses the right data for the right task. This guarantees that your data is secure, transparent, and under your control at all times.
Proprietary intelligence: Evi is exclusively trained on AB Tasty’s proprietary data. This ensures that it delivers relevant, experiment-ready outputs.
Your inputs are yours and yours alone: Key features like Evi Ideas and Evi Content only process the prompts and screenshots that you supply, ensuring they remain private.
Secure by design: The Evi Analysis feature runs entirely on AB Tasty’s own servers. No data is sent to external services.
Evi from AB Tasty grounds every step in evidence, notices what you don’t, and never gets it wrong, transforming how you optimize the digital experience.
Understanding your customers’ paths? Not easy. Each person arrives with their own reason for visiting your site and takes their own route through your pages.
So how do you gain real insights to improve usability and spot buying trends?
Start with building a customer journey map.
In this blog, we’ll walk you through what a customer journey map is, how to build a customer journey map, which templates work best for your customer journey map, and how to put them into action. Let’s get started!
What is a customer journey map?
A customer journey map is a visual tool that shows how customers interact with your business or website—from start to finish.
It helps you spot where things aren’t working and improve the overall experience.
Think of it as a story told visually. It maps out:
What customers do
What they think
How they feel
At the heart of the map are touchpoints—specific moments where customers interact with your brand. Maybe they’re researching a product, making a purchase, waiting for delivery, or requesting a return.
Each touchpoint can be positive, neutral, or negative from the customer’s perspective. Your job? Make more of them positive.
Customer journey mapping requires a mix of hard data, customer feedback, and creative thinking. No two maps are the same—and that’s the point. Every business is different.
7 Reasons Why Use Customer Journey Maps
Customer journey mapping isn’t just a nice-to-have—it’s a strategic tool that drives real business results.
Here’s why it matters:
1. See Through Your Customers’ Eyes
Journey maps help you step into your customers’ shoes. You’ll understand their motivations, expectations, and frustrations at every stage—not just what they do, but why they do it.
That empathy translates into better decisions, smarter strategies, and experiences that actually resonate.
2. Spot and Fix Pain Points Fast
Every journey has friction. Your checkout process might be too complicated, your search function delivers the wrong results, or customers can’t find help when they need it.
Customer journey mapping reveals these bottlenecks so you can address them before they cost you customers.
3. Build Loyalty That Lasts
When customers feel understood and valued, they stick around. By removing barriers and meeting needs at every touchpoint, you strengthen the emotional connection between your brand and your audience. That connection drives repeat purchases and long-term loyalty.
In fact, a 5% increase in customer retention can lead to a 25% increase in profits.
4. Personalize at Scale
Not all customers are the same—and your experience shouldn’t treat them that way. Journey maps highlight individual preferences and behaviors, enabling you to tailor messaging, product recommendations, and support to each person.
Personalization increases purchase likelihood and makes customers feel like you actually get them.
5. Align Your Entire Team
Customer journey mapping breaks down silos. When marketing, product, sales, and support all work from the same map, everyone understands the customer’s perspective and how their work impacts the overall experience.
That shared understanding leads to better collaboration, faster problem-solving, and a more cohesive brand experience.
6. Make Smarter, Data-Driven Decisions
Journey maps aren’t just pretty visuals—they’re strategic tools backed by real data.
They guide decisions about where to invest, what to test, and which initiatives will have the biggest impact on customer satisfaction and business growth.
7. Drive Innovation and Stay Ahead
Customer needs evolve. Markets shift. New competitors emerge.
Regularly reviewing and updating your customer journey map helps you spot emerging trends, changing preferences, and new opportunities before your competitors do. It keeps your brand agile, innovative, and ready to adapt.
The Heart of Customer Journey Mapping: Buyer Personas
Buyer personas are fictional characters based on real customer data. They represent your audience in a way that’s relatable and actionable.
Most projects create between three and seven personas—and each one gets its own customer journey map. Why? Because different customers have different needs, goals, and pain points. A persona helps you walk in their shoes and design experiences that truly resonate.
Personas aren’t perfect replicas of real people. They’re broad representations that guide smarter decisions.
Who Benefits from a Customer Journey Map?
Short answer: everyone.
Customer satisfaction drives loyalty more than ever. People are more informed, more demanding, and more willing to shop around.
A well-designed customer journey map helps you:
Highlight problems customers face
Build stronger relationships with your brand
Keep customers at the center of every decision
Once your map is ready, your entire team—from marketing to product to support—can use it to stay aligned and customer-focused.
Bringing Your Whole Business Together
Customer journey mapping isn’t just for your customer-facing teams. It brings everyone together.
When you map out touchpoints, departments that don’t usually interact with customers start to see how their work affects the experience. That’s powerful.
For example:
How easy is it for someone to find return instructions on your site?
How fast do they get a response when they need help?
What happens after the purchase?
Traditional marketing often stops at checkout. But the customer journey doesn’t. Post-purchase experience matters just as much—and your map should reflect that.
How to Map the Customer Journey Visually?
A customer journey map gives you a clear picture of your customers’ experiences from their point of view.
To create one, focus on two things:
Defining customer goals – What are they trying to accomplish?
Understanding their nonlinear journey – Customers don’t move in straight lines
By mapping every interaction, you’re identifying opportunities to delight your customers and craft smarter engagement strategies.
According to Aberdeen Group, 89% of companies with multi-channel engagement strategies retained their customers—compared to just 33% of those without one.
You can build your map using:
Excel sheets
Infographics
Diagrams
Illustrations
Customer journey maps also help with:
Retargeting with an inbound mindset
Reaching new customer segments
Building a customer-first culture
All of this leads to better experiences, more conversions, and stronger revenue.
There are four main types of customer journey maps. Each highlights different behaviors and serves different goals.
1. Current State Template
Shows what customers currently do, think, and feel. Great for spotting pain points and making incremental improvements.
2. Future State Template
Focuses on what customers will do, think, and feel. Useful for planning new products, services, or experiences.
3. Day in the Life Template
Similar to the current state map, but broader. It looks at how customers behave with your brand and your competitors. Perfect for uncovering unmet needs.
4. Service Blueprint Template
Starts with a simplified current or future state map, then adds the internal processes, people, and tech behind the experience. Helps you see the full picture—front and back.
How to Create a Customer Journey Map in 7 Steps ?
Creating customer experience journey maps takes time, but the payoff is worth it. Here’s how to do it.
Step 1: Create Buyer Personas
Start with a clear objective. Who is this map for? What are you trying to learn?
Building personas is the most time-consuming part—but also the most important. You’ll need:
AB Tasty is a best-in-classexperimentation platform that helps you test variations, personalize experiences, and convert more customers—fast. With AI and automation built in, you can optimize the digital experience with confidence.
Once your map is live, review and update it regularly. Customer journeys evolve—and so should your map.
How to Collect Journey Mapping Data?
Great customer experience journey maps are built on solid data—not assumptions. You’ll need a mix of qualitative insights (the “why” behind behavior) and quantitative metrics (the “what” you can measure).
Here’s how to gather both:
1. Qualitative Data: Understanding the “Why”
Qualitative research helps you uncover motivations, emotions, and pain points that numbers alone can’t reveal.
Customer Interviews
Have real conversations with your customers. Ask about their experiences, what frustrates them, and what they love. These in-depth discussions provide rich, nuanced insights.
Surveys
Use open-ended questions to gather feedback on specific parts of the journey. Keep them short and focused to get honest, actionable responses.
User Testing
Watch how people interact with your website or product in real time. Tools like usability tests reveal where users get stuck, confused, or frustrated.
Mystery Shopping
Experience your own customer journey firsthand. Walk through every step—from discovery to purchase to support—and see what works and what doesn’t.
Support Transcripts
Review customer service conversations to identify recurring issues and common questions. These transcripts are goldmines for understanding pain points.
2. Quantitative Data: Tracking the “What”
Quantitative data gives you measurable, trackable insights that help you validate assumptions and monitor progress over time.
Website Analytics
Tools like Google Analytics show you how customers navigate your site, where they drop off, and which pages drive the most engagement.
See exactly how users interact with your pages—where they click, how far they scroll, and where they hesitate. Tools like Hotjar and Contentsquare make this easy.
Conversion Funnels
Track how customers move through key stages of the journey and identify where they abandon the process.
Customer Satisfaction Scores
Metrics like Net Promoter Score (NPS) and Customer Satisfaction (CSAT) measure loyalty and satisfaction at different touchpoints.
CRM Data
Your CRM system (like Salesforce or HubSpot) holds valuable information about customer interactions, purchase history, and behavior patterns.
Social Media Listening
Monitor what customers say about your brand on social platforms. This reveals sentiment, trends, and unfiltered feedback.
Email Campaign Metrics
Analyze open rates, click-through rates, and conversion rates to understand how customers engage with your messaging.
Support Ticket Volume
Track common issues and complaints to identify systemic problems in the customer journey.
Best Practices for Journey Map Data Collection
Combine Both Types of Data
Qualitative insights explain why customers behave a certain way. Quantitative data shows you what they’re doing. Together, they give you the full picture.
Test Your Assumptions
Don’t rely on guesses. Validate your hypotheses about customer behavior through research and real data.
Involve Stakeholders
Gather input from marketing, sales, product, customer service, and leadership. Each team has unique insights that make your map more accurate and actionable.
Keep It Current
Customer behavior changes. Markets evolve. Your journey map should too. Update it regularly to stay relevant and effective.
Customer Journey Map Examples
Customer journey maps come in all shapes and sizes. Some look like works of art. Others are simple sketches. What matters is clarity.
Here are some real-world examples of customer journey mapping in action:
1. David Jones: Simplifying Account Access
David Jones, a major Australian retailer, mapped their customer journey to understand how shoppers interacted with their account features during the buying process.
Through testing and personalization, they made it easier for customers to access their accounts, track orders, and manage preferences.
Website performance has never mattered more. Google Core Web Vitals now directly influence organic rankings, mobile conversions continue to dominate, and users expect instant experiences.
In this context, many digital teams ask the same question:
“Will an experimentation or personalization tool slow down my site?”
It’s a valid concern. After all, any third-party script has the potential to impact performance if it’s not engineered carefully.
In this article, we’ll break down what actually affects performance in an experimentation platform — and how AB Tasty has built a performance-first architecture that avoids common pitfalls.
1. The Real Reasons Experimentation Tools Can Slow Down a Website
Not all experimentation platforms behave the same. When performance issues appear, they usually come from a few well-identified causes.
1.1 Heavy, all-in-one tags
Some tools load everything upfront — all features, all experiments, for every visitor — even when most of that code is never used.
This leads to:
Slower execution in the browser
More JavaScript to download and process
Increased pressure on the main thread
Wasted network bandwidth on unused code
The result: a slower page and unnecessary work for the browser.
1.2 “Anti-flicker” scripts that block the page
To prevent visual flicker, many vendors solve flicker by hiding the page (e.g., opacity: 0) until the experiment loads.
While this may avoid a brief visual change, it comes at a cost:
The page cannot render immediately
First visual elements appear later (LCP, FCP)
It hurts SEO rankings
Users may face a noticeable “white screen,” especially on slower connections
The page looks stable — but it loads later than it should.
1.3 Limited optimization for modern websites
Modern websites are no longer simple static pages. Single-page applications, server-side rendering, and hydration flows all require precise timing.
When experimentation scripts are not adapted to these architectures:
They may re-run unnecessarily
They can interfere with rendering
They introduce delays that affect performance
2. AB Tasty’s Philosophy: Performance by Design, Not by Patch
At AB Tasty, we believe an experimentation platform should contribute to user experience — not compromise it. That’s why performance is woven directly into our architecture.
This gives CRO and technical teams full visibility and control over experimentation performance.
Conclusion: You Can Experiment Without Sacrificing Speed
A fast digital experience and an experimentation program are not mutually exclusive.
With its modular architecture, modern rendering logic, and performance-first philosophy, AB Tasty enables brands to run impactful campaigns without jeopardizing SEO or UX.
If performance is a concern for your engineering or CRO teams, we’d be happy to share:
Performance benchmarks
Technical documentation
Best practices for Core Web Vitals
Case studies from top global brands
Experiment boldly — with a platform engineered for speed.
FAQs
Does A/B testing slow down your website?
Yes, but AB Tasty minimizes it. Our tag delivers < 100ms load time, < 500ms execution, and < 10ms from cache—making us 2x faster than Kameleoon. Plus, we block releases if Core Web Vitals degrade by > 2%.
Does A/B testing affect Core Web Vitals?
It can — but AB Tasty minimizes this impact through dynamic imports, optimized rendering logic, and non-blocking execution.
Do I need anti-flicker for A/B testing?
Most of the time, no. Anti-flicker masking can degrade SEO and create a poor user experience.
Is AB Tasty fast?
Yes — benchmarks from independent sources consistently show AB Tasty among the fastest experimentation tags on the market.
Booking a flight is an exercise in high-stakes decision-making. For the customer, it’s a significant purchase filled with dozens of micro-decisions, from dates and times to seat selection and baggage allowances. For an airline, it’s a complex, multi-stage transaction where the smallest point of friction can lead to an abandoned booking and a substantial loss of revenue. Unlike a simple e-commerce purchase, the path from searching for a flight to completing a booking is a long-haul journey in itself.
In this environment, relying on assumptions is a recipe for failure. The color of a CTA button, the order of ancillary services, or the way fees are presented can have an outsized impact on conversion rates. This is why a culture of systematic experimentation isn’t just a “nice-to-have” for airlines; it’s the most effective way to navigate the complexities of the user journey, de-risk critical design decisions, and build a digital experience that turns lookers into bookers, and bookers into loyal customers. It’s about replacing guesswork with the certainty of data, ensuring every change is a step toward a smoother, more profitable customer experience.
The high-friction world of airline UX
An airline website is not a typical e-commerce store. It’s a sophisticated platform balancing user needs, complex business rules, and ancillary revenue goals. A seamless User Experience (UX) here requires a deep understanding of the unique pressures and priorities of the travel booker. Key considerations include:
Clarity in search and filtering: The journey begins with a search. Users need to effortlessly filter by dates, stops, airlines, and times. As Spanish travel agency Iberojet discovered, even the initial presentation of search options can have a major impact. They questioned the order of their homepage tabs: “Holiday Packages” vs. “Travel Circuits and Long-Distance Trips.” By running a simple A/B test that swapped the order based on user browsing history, they increased clicks on the “Search” button by a staggering 25%. This shows that getting the very first interaction right is critical.
Transparency in pricing: Nothing erodes trust faster than hidden fees. A modern airline UX presents all costs—from baggage fees to seat selection charges—in a clear and upfront manner. The goal isn’t to hide the costs, but to integrate them so seamlessly into the flow that the user feels informed, not ambushed.
A mobile-first imperative: More and more travelers are booking complex trips entirely on their mobile devices. This demands a responsive, thumb-friendly design where every step, from entering passenger details to selecting a seat on a detailed map, is intuitive on a small screen.
Intuitive ancillary upsells: Baggage options, seat upgrades, and travel insurance are crucial revenue drivers. However, if presented aggressively or confusingly, they become a major point of friction. The best experiences integrate these upsells as helpful, well-timed suggestions rather than mandatory hurdles. A cluttered page that forces users to opt-out of multiple insurance offers feels frustrating, whereas a clean interface that clearly explains baggage options at the right moment feels helpful.
De-risking design with systematic experimentation
Every proposed change to a booking flow is a hypothesis. Does this new layout simplify seat selection? Does this revised copy clarify baggage rules? Experimentation is the process of testing these hypotheses with real users before committing to a full rollout.
A/B testing
This is the workhorse of experimentation. It involves testing one change at a time (e.g., a green “Book Now” button vs. a blue one) to see which performs better against a specific goal, like booking completion rate. It’s simple, direct, and provides clear answers to specific questions. A great example from the vacation package industry comes from Smartbox. They hypothesized that a more prominent “Add to Cart” button would drive more sales. By testing a bright pink CTA against their original aqua one, they saw a 16% increase in clicks. The principle is the same for airlines: small visual changes can yield significant results.
Multivariate testing
This approach allows you to test multiple changes at once. For example, you could simultaneously test two different headlines, three different banner images, and two different CTA buttons to see which combination performs best. This is ideal for redesigning a complex section, like the ancillary services page, where multiple elements interact. Its power lies in not only identifying the best-performing individual elements but also understanding how they influence one another.
Personalization experiments
Not all travelers are the same. A frequent flyer logged into their loyalty account has different needs than a first-time visitor booking a family vacation. Personalization involves tailoring the experience to different user segments. For example, Best Western Hotels & Resorts ran a personalization campaign targeting anonymous visitors looking for a multi-night stay. By showing them a pop-up with a special offer available only to loyalty members, they increased program sign-ups by 12%. Airlines can use the same logic to offer targeted promotions to frequent flyers, pre-fill information for logged-in users, or simplify the interface for new customers.
Navigating the challenges of airline experimentation
While incredibly valuable, running experiments on a high-traffic airline website comes with its own set of challenges:
Minimizing disruption: A poorly implemented test can introduce bugs or slow down the site, directly impacting revenue. Rigorous quality assurance and phased rollouts are essential to avoid disrupting the booking process for thousands of users.
Complex technical environment: Airline websites are often a web of internal systems, third-party APIs (for everything from payment to loyalty programs), and global distribution systems. Implementing a test that touches multiple systems requires careful planning and deep technical expertise. A test on the seat selection page, for instance, might rely on an external API for the seat map; if that API is slow, it could invalidate the test results.
Measuring long-term impact: While it’s easy to measure the immediate impact of a test on bookings, measuring its effect on long-term loyalty or repeat business is more difficult. This requires a mature analytics setup and a commitment to tracking user cohorts over time to see if a winning variation today leads to more valuable customers tomorrow.
Recommendations: Building a culture of continuous improvement
To successfully navigate the turbulence of the online travel market, airlines should treat their website not as a static brochure, but as a dynamic product that is always evolving.
Embrace an ongoing process: Experimentation should not be a one-off project. It’s an iterative, continuous loop of hypothesizing, testing, learning, and improving. The insights from one test should fuel the ideas for the next, creating a powerful engine for growth.
Reduce guesswork with data: Use data-driven insights to inform every UX decision, from the grand redesigns down to the smallest copy change. A powerful example of this comes from Evolve Vacation Rental. By analyzing user intent from different traffic sources, they tested changing a CTA from “Start for Free” to “See if You Qualify.” This simple, intent-aligned copy change drove a 161% increase in conversions, demonstrating the immense impact of data-driven copywriting.
Balance optimization with brand: While optimizing for conversion is critical, it must be balanced with the airline’s brand promise and regulatory requirements. The goal is a journey that is not only efficient but also reassuring, trustworthy, and compliant.
By adopting a disciplined, data-driven approach to UX and experimentation, airlines can move beyond simply selling tickets. They can design digital journeys that are smoother, more intuitive, and build the kind of trust that keeps passengers coming back.
Ready to find your better? If you’re looking to build a data-driven experimentation program that drives revenue and builds customer trust, we’re here to help. Talk to one of our experts today to start your journey.
The travel and hospitality industry operates in one of the most competitive digital landscapes.
With customers comparing prices, experiences, and options across multiple platforms in seconds, every element of your website can make or break a booking. That’s where feature experimentation, personalization, a/b tests, and rollouts come in—giving travel brands the power to test, learn, and optimize their digital experiences with confidence.
The Power of Experimentation
Experimentation isn’t just about testing button colors or headlines. It’s about de-risking innovation, understanding your guests, and optimizing every experience—from the first website visit to post-stay engagement. With AB Tasty, travel and hospitality brands can:
Validate ideas before full rollout
Personalize journeys for every traveler segment
React quickly to market changes and guest feedback
Drive measurable business impact—fast
Let’s look at how leading brands are using AB Tasty to solve real challenges and unlock growth. In this article, we’ll explore five travel and hospitality use cases that demonstrate how experimentation and personalization strategies are driving measurable results.
1. Creating Urgency with Countdown Timers
The Challenge: A major theme park operator had been using countdown timers on their season pass pages during promotional periods, but they had never actually tested whether these timers were driving purchases—or just taking up space.
The Experiment: The team ran an A/B test to measure the true impact of countdown timers on their season pass sales page. The timer was designed to create urgency and encourage faster purchasing decisions during limited-time offers.
The Results: The test confirmed what many marketers assume but rarely prove: urgency works. The variation with the countdown timer delivered a +7.2% increase in transaction rate, with particularly strong performance on desktop, where the majority of purchases occurred.
Key Takeaway: Don’t assume your tactics are working—test them. Even widely used conversion techniques like countdown timers deserve validation through experimentation.
2. Smarter Sorting with Algorithmic Recommendations
The Challenge: A travel booking platform was sorting their listing pages by ascending price—a logical approach, but one that didn’t always surface the most relevant offers for customers. Lower prices don’t always mean better value, and the team suspected they were leaving revenue on the table.
The Experiment: Using feature experimentation, the team tested a new “Recommended” sorting algorithm that factored in product relevance and historical performance data, rather than price alone.
The Results: The smarter sorting approach delivered impressive gains:
+2.8% revenue uplift
+4.6% increase in average order value (AOV)
Key Takeaway: How you present options matters as much as what options you present. Algorithmic sorting that considers relevance and performance can guide users toward better choices—and better business outcomes.
3. Turning Dead Ends into Opportunities with Personalized Alternatives
The Challenge: When travelers searched for a route with no available flights, they hit a frustrating dead end: a cold “no flights available” message. This led to drop-offs, lost revenue, and a poor user experience.
The Experiment: Instead of showing an error message, the team implemented a personalized experience that displayed smart alternatives—nearby airports, flexible date options, or connecting routes.
The Results: The personalized approach transformed a point of frustration into a conversion opportunity:
+35% increase in flight search modifications
+14% improvement in conversion rate
Key Takeaway: Every dead end is an opportunity in disguise. Personalization can rescue frustrated users and turn potential abandonment into completed bookings.
4. Testing Discount Framing: Percentages vs. Monetary Values
The Challenge: A travel company was presenting discounts as percentages (e.g., “Save 15%”), but they weren’t sure if this framing was maximizing customer response. Would travelers respond better to seeing the actual monetary savings?
The Experiment: The team tested a variation that displayed monetary savings instead (e.g., “Save up to $1,500 per couple”) across all devices.
The Results: The monetary framing significantly outperformed the percentage version:
+41% increase in revenue
+18% more clicks on the homepage promotional link
Key Takeaway: How you frame value matters. For high-ticket travel purchases, concrete monetary savings can feel more tangible and compelling than abstract percentages.
5. Elevating Trust Signals for Higher Conversions
The Challenge: A travel operator had key trust signals—their Price Promise guarantee and 24/7 customer support—displayed in a banner on their homepage. However, the banner was positioned too low on the page, limiting its visibility and impact on user confidence.
The Experiment: The team tested moving the trust signal banner higher on the page to make these reassurances more prominent earlier in the customer journey.
The Results: The simple repositioning delivered remarkable results:
+35% increase in transaction rate
Key Takeaway: Trust is everything in travel. Make sure your credibility signals are visible early in the user journey—don’t bury them below the fold.
Why Experimentation Matters for Travel & Hospitality
These five use cases illustrate a fundamental truth: assumptions are expensive. Whether it’s the effectiveness of urgency tactics, the optimal way to sort listings, or how to frame a discount, the only way to know what works is to test it.
Experimentation gives travel and hospitality brands the ability to:
Validate ideas before full deployment – Reduce risk by testing changes with a subset of users first
Make data-driven decisions – Move beyond gut feelings to measurable results
Personalize at scale – Deliver the right experience to the right user at the right time
Iterate quickly – Learn fast, fail fast, and continuously improve
In an industry where margins are tight and competition is fierce, the brands that embrace experimentation will be the ones that thrive.
Ready to Start Experimenting?
The travel and hospitality industry is perfect for optimization. From booking flows to search results, from promotional messaging to trust signals, every touchpoint is an opportunity to improve the customer experience and drive business results.
At AB Tasty, we have dedicated CSMs specialized in travel and hospitality to help you on your experimentation journey. Looking to see which clients are already onboard? Check out our customers page!
The question isn’t whether you should be experimenting—it’s how quickly you can start.
Schedule a demo today. Start experimenting tomorrow.
Why should travel and hospitality brands invest in an experimentation platform?
Travel and hospitality brands need to optimize complex journeys: search, comparison, booking, and post-booking. AB Tasty provides a unified experimentation and personalization platform that lets you: – Test changes to search, listing, and booking flows with A/B and multivariate testing
– Roll out new features safely using feature flags and progressive rollouts
– Personalize experiences for different traveler segments (families, business, frequent flyers, etc.)
How does AB Tasty help optimize booking funnels on travel websites and apps?
AB Tasty lets you experiment across every step of the funnel from homepage to booking flows. With client-side and server-side experimentation, you can optimize both front-end UX and back-end logic (like ranking algorithms or pricing rules) without compromising performance.
Can AB Tasty support feature experimentation, not just marketing A/B tests?
Yes. AB Tasty goes beyond traditional marketing tests with Feature Experimentation & Rollout. You can use feature flags to control who sees new features, run server-side experiments on your booking engine, search logic, and algorithms, and use progressive rollouts to launch features gradually, monitor impact, and roll back instantly if needed
How does AB Tasty help personalize experiences for travelers?
AB Tasty’s personalization capabilities enable you to tailor journeys based on behavior, context, and profile data. This includes showing different content or offers to first-time visitors vs. loyal customers, surfacing relevant destinations, hotels, or packages based on previous searches or bookings, and more!
Is AB Tasty suitable for high-traffic, seasonal travel campaigns?
Yes. AB Tasty is built to handle the seasonality and peaks that are typical in travel and hospitality. You can confidently test urgent campaigns—like flash sales or early-bird offers—during your busiest periods while keeping control over performance and user experience.
Can non-technical teams in travel and hospitality use AB Tasty?
Yes. AB Tasty is designed for marketing, product, and development teams:
Marketers can use the visual editor and ready-made widgets to launch tests and personalization without code
Product teams can design and analyze experiments on flows, features, and UX
Developers can implement feature flags, server-side tests, and complex rollouts
This collaborative approach helps travel brands move faster while keeping control and governance over what goes live.
Customer experience optimization (EXO) used to be your secret weapon. Go the extra mile, win the customer. Simple. But the game has changed, and now everyone’s optimizing. It’s no longer about gaining an edge; it’s about staying relevant in a market where a solid customer experience strategy isn’t just nice to have, it’s the baseline for survival.
What does that actually mean? It means shaping every interaction a customer has with your brand across all touchpoints, from website browsing and mobile app experiences to in-store interactions, chatbot conversations, and tablet interfaces. Every touchpoint matters because these interactions don’t just influence purchasing decisions; they shape loyalty, trust, and whether someone comes back or walks away for good.
Why Does EXO Matter Now More Than Ever ?
Deliver solid experiences, and you’ll build a reputation that sticks. Conversion rates climb. Customer loyalty strengthens. But here’s the catch: you can’t stop moving. Stand still, and you’ll get overtaken. Fast. So what does it take to stay ahead?
You need to:
Figure out what your customers actually want – not what you think they want
Find the sweet spot between their needs and what you offer
Keep evolving your interactions on an ongoing basis
That’s where superior experiences live. That’s where business success happens.
Optimization isn’t a one-time project. It’s the bare minimum. To stay competitive and stay ahead, the work never stops.
You need a continuous feedback loop:
Test hypotheses
Gather behavioral data
Analyze results
Iterate improvements
This is how you maximize customer experience and hold onto your edge. Not through one big launch. Through brave, ongoing iteration.
Why Must You Optimize Your CX Strategy Continuously ?
Technology shifts every second, and customer attitudes evolve even faster. The only way to keep pace is by adapting continuously. Your optimization practices need to respond to customer demands in real time—unlocking value, building loyalty, and staying relevant.
When teams work together, everything clicks. Living and breathing this approach means your teams collaborate seamlessly:
Marketing teams understand user behavior
Product teams prioritize features that matter
Tech teams implement changes efficiently
They share the same mission. They work from the same experimentation roadmap. And when they do resources unlock, improvements roll out at the right time and, most importantly, your business stays on the road to success.
Why Is Digital Customer Experience Optimization Essential?
At the core, every business—no matter the product or sales channel—tries to satisfy customers. Customer centricity isn’t new.
But customer experience optimization really took flight when technology advanced and brand touchpoints multiplied. Add in the fact that data is everywhere—collectible, analyzable, actionable—and suddenly you have the means to understand your customers better than they understand themselves.
Still not convinced it matters? The numbers tell the story. According toPwC’s Customer Experience Survey and Future of CX research:
One in three consumers will walk away from a brand after just one bad experience
73% of consumers say their experience with a brand is a major factor in purchasing decisions
Customers will pay up to 16% more for products and services from brands that deliver better experiences
Think about your own habits. Pause for a moment. Think about your own online shopping:
Which brands do you gravitate toward? Which ones leave you cold?
Do they see you as a person—or just another transaction?
It only takes a second to realize: optimizing customer experiences isn’t just important. It’s essential.
How to improve digital customer experience: 10 Proven Strategies
Improving digital customer experience isn’t a one-and-done project—it’s an ongoing commitment to making every online interaction better. Whether you’re optimizing your website, mobile app, or omnichannel strategy, these proven tactics will help you deliver seamless, personalized experiences that keep customers coming back.
1. Map the Digital Customer Journey
Start by understanding every touchpoint your customers encounter—from discovery to purchase and beyond.Customer journey mapping helps you identify pain points, friction, and opportunities to improve the experience.
Use tools and frameworks to visualize each phase of the journey, then prioritize the touchpoints that matter most to your audience. Resources likeAB Tasty’s Digital Customer Journey Kit offer practical guidance for mapping and optimizing these paths.
Advanced segmentation—including emotional and behavioral insights—can help you address different customer needs and motivations more effectively. Learn how AI-powered personalization works in AB Tasty’s EmotionsAI case studies.
3. Optimize UX Across All Devices
Your website and app should be intuitive, visually appealing, and easy to navigate—especially on mobile. Mobile optimization is non-negotiable, as more customers interact with brands on smartphones than ever before.
Streamline navigation, simplify checkout processes, and remove any friction points that slow users down. A well-optimized UX directly impacts conversion rates and customer satisfaction.
4. Test, Learn, and Iterate Continuously
A/B testing and experimentation are essential for digital customer experience optimization. Continuously test different layouts, messaging, CTAs, and features to discover what resonates best with your audience.
Use the results to refine your digital experiences over time. Remember: even small improvements can lead to big wins in engagement and conversions.
5. Ensure Omnichannel Consistency
Provide a unified, seamless experience whether customers engage via desktop, mobile, app, social media, or chat. Omnichannel customer experience builds trust and makes transitions between channels effortless.
Consistency in branding, messaging, and service quality across all digital touchpoints is critical for customer retention and loyalty.
6. Leverage AI and Automation
AI-powered tools can transform how you deliver digital experiences. Use AI to automate personalization, product recommendations, and customer support—boosting both efficiency and satisfaction.
Automation frees up your team to focus on higher-value activities while ensuring customers get fast, relevant responses at every stage of their journey.
7. Collect and Act on Customer Feedback
Regularly gather feedback through surveys, reviews, and direct interactions. Use tools like Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES) to measure digital CX performance.
More importantly, act on what you learn. Customer feedback is one of the most valuable resources for continuous improvement.
8. Simplify Processes and Reduce Friction
Make every process—from sign-up to checkout to support—as simple and fast as possible. Reducing friction means removing unnecessary steps, providing clear guidance, and ensuring smooth, intuitive flows.
Speed and ease of use are non-negotiable for modern customers. The easier you make it, the more likely they are to convert and return.
9. Use Data and Analytics to Drive Decisions
Data-driven insights are critical for shaping exceptional digital customer experiences. Track user behavior, conversion funnels, and engagement metrics using tools like Google Analytics and heatmaps.
Analyze performance regularly, identify trends, and use these insights to inform your optimization strategy.
10. Foster a Customer-Centric Culture
Improving digital CX isn’t just the job of one team—it requires cross-functional collaboration. Share data, insights, and goals across departments to align everyone around the mission of delivering better experiences.
When customer experience becomes an organization-wide priority, the results speak for themselves: higher satisfaction, stronger loyalty, and sustained growth.
3 Key Ingredients to Supercharge Your Customer Experience Optimization Strategy
1. Optimize Your User Experience (UX)
Know your customer journey—and dial it up. When a customer lands on your site, they’re on a mission: searching for products, comparing options, learning more about features, and making purchase decisions.
Each step they take is part of a path—one filled with opportunities and pitfalls. The more you understand that journey and remove friction along the purchase funnel, the better your site performs.
Here’s how to make it happen:
Gather data about customer behavior and preferences
Run experiments using A/B testing to find the optimal setup
Test everything – calls-to-action, landing page configurations, product images, navigation structure, form length
Not sure if your CTAs have the best wording? Test them. Trying to nail the perfect landing page? Run an experiment. Debating whether product images should be cropped or full body? We can examine that too.
Ultimately, you’re aiming for one thing: more conversions. Driving UX optimization on an ever-changing customer pathway keeps you ahead.
2. Improve Your Personalization Efforts
Know your customers—and tailor to their needs. Personalizing digital brand interactions builds loyalty and drives repeat business. In the experience economy, you’re not just selling a product—you’re selling the interaction, the purchase moment, the entire journey.
The user experience when acquiring and consuming your product is just as important as what it does. So personalizing these digital exchanges is key to long-term retention.
To understand customers on a personal level:
Build a solid data foundation to collect behavioral insights
Identify their needs through analytics and feedback
Deliver personalized experiences that keep shoppers returning
As with your customer journey, responding to ever-changing desires can be challenging. Knowing your customers intimately is crucial. Get it right, and the impact is huge. So don’t leave any stone unturned when exploring improvement opportunities.
3. Implement Server-Side Testing and Feature Management
Bring in the tech teams to expand your optimization activities. This is where we bring in the heavy hitters.
While A/B testing can be rapidly implemented by marketing teams, server-side experimentation requires the buy-in and expertise of tech teams and developers. Collaboration between the two is essential to deliver seamless customer experiences.
Think of it this way:
The front-end (client-side) lures customers in with compelling design
The back-end (server-side) runs smoothly to ensure effortless shopping
For instance: presenting a promotional offer (front-end) only delivers results if the payment gateway runs glitch-free and page loading times are fast (back-end).
Lukas Vermeer, director of experimentation at Vista, champions testing both sides:
“A lot of the value from experimentation comes from two things: One is not shipping the bad stuff—a huge value point. The other is figuring out strategically, going forward, what you should invest in.”
If your business has reached a certain level of maturity, maximizing bothclient and server-side testing ensures your optimization efforts work as hard as they possibly can.
Customer Experience Optimization Across Industries
E-Commerce Optimization
Drive transactions and boost conversion rates through continuous experimentation. Test and optimize:
Not every website is for purchasing right then and there. Sometimes site visits are the first step on a longer journey.
Optimize for lead generation on big-ticket purchases—automotive, bedroom furniture, holiday rentals—by focusing on:
Site layout and navigation
Call-to-action placement
Access to product information
Store locator functionality
Contact forms and lead capture
Travel and Hospitality
Travel offers a range of solutions—from individual bookings (hotels, transport) to comprehensive packages. When bundling items together, finding that pricing sweet spot is key.
Server-side testing is particularly relevant here. It helps you:
Curate product offerings based on user preferences
Experience optimization isn’t optional anymore—it’s how you stay competitive. Every test you run, every insight you uncover, every iteration you make moves you closer to experiences that truly resonate.
The path forward is clear: map your customer journeys, personalize boldly, test continuously, and let data guide your decisions. Whether you’re optimizing e-commerce checkout flows, refining B2B lead generation, or perfecting travel booking experiences, the principles remain the same—understand your customers deeply, remove friction relentlessly, and never stop improving.
Here’s the truth: your competitors are already optimizing. The question isn’t whether to start—it’s how fast you can move and how brave you’re willing to be with your experiments.
Digital experimentation has matured. Where A/B testing was once handled by a handful of specialists, today it’s a team sport — involving marketing, product, UX, engineering, and data. Organizations now need platforms that connect these roles, reduce friction, and enable collective decision-making.
This is where AB Tasty stands apart. More than an experimentation tool, it is a collaborative ecosystem, designed to help companies run impactful tests at scale while empowering every contributor in the process. From idea generation to final reporting, AB Tasty removes silos and strengthens alignment — a critical ingredient for a successful CRO program.
A Platform Built for Cross-Functional Workflows
Modern experimentation involves teams with different expertise and expectations. AB Tasty addresses this diversity through a unified platform that brings everyone together.
1. Clear Governance and Team-Based Visibility
Large organizations often struggle with visibility: too many tests, too many markets, too much noise. AB Tasty’s advanced RBAC system solves this by assigning precise roles and allowing teams to create custom folders and views. A French editor only sees French campaigns; a central CRO manager sees everything; a developer accesses only what they need.
This structure reduces operational clutter and protects the integrity of local workflows, while still enabling global oversight.
2. Collaboration at Every Step of the Experiment Lifecycle
Where AB Tasty excels is its ability to facilitate teamwork throughout the entire testing process.
Before a Campaign
Teams use the Ideas Backlog to surface opportunities and prioritize them together, while the Learnings Library accelerates strategy by making past learnings accessible across markets—and ensures those insights are continuously built upon. Unlike static archives, the Learnings Library is designed to be iterative: every experiment, whether a win or a “failed” test, adds to a living repository that evolves with each new insight, helping teams refine and improve their strategies over time.
During a Campaign
The no-code visual editor empowers marketers, while developers leverage VS Code. Comments can be added anywhere — in the editor, creation flow, or reports — with tagged users notified instantly. Preview and QA links make cross-team collaboration effortless.
After a Campaign
AB Tasty’s segmentation features and its powerful Data Explorer allow analysts to go deep, while marketing teams can still interpret results intuitively. Reports can be shared externally via secure links or exported automatically to Notion, BI systems, or Slack channels. Visibility becomes effortless and organization-wide.
After a campaign concludes, the true value of the Learnings Library comes into play. Instead of letting critical insights disappear with team turnover or get buried in forgotten files, the Learnings Library transforms every campaign’s results—both qualitative and quantitative—into a permanent, searchable company asset.
Teams can capture not just what happened, but why. This means that even as teams and agencies change, the knowledge stays put—enabling new hires to hit the ground running and decision-makers to build on a growing foundation of proven insights, campaign after campaign.
3. Deep Integrations Strengthen Collective Intelligence
Collaboration is not limited to the experimentation platform itself. AB Tasty integrates with tools teams already use daily:
Slack: receive notifications when campaigns go live or when new learnings are added
Notion: synchronize campaign KPIs and reports automatically into team workspaces
BigQuery, Looker, Metabase: power custom dashboards
GA4, Contentsquare, FullStory: enrich analysis with behavioral and analytics data
And with Microsoft Teams coming soon, AB Tasty is extending its collaborative reach even further.
4. A True “One Platform” for Experimentation, Personalization, and Feature Rollouts
Cross-team alignment is reinforced by AB Tasty’s unique combination of client-side experimentation and Feature Experimentation & Rollout (FE&R). Product teams and engineers can gradually deploy new features, run server-side tests, and secure releases through progressive rollout and rollback automation. Meanwhile, marketing and CRO teams continue to run client-side tests on the same unified platform.
Everyone operates within the same environment, driving shared KPIs and shared business outcomes. And this collaborative foundation is amplified by Evi — AB Tasty’s evidence-based AI agent.
5. How Evi Enhances Collaboration Throughout the Experiment Lifecycle
Evi acts as a shared intelligence layer that supports every role involved in experimentation — ensuring alignment, speed, and evidence-based decisions at every step.
Before launching a test
Evi Ideas generates new experiment opportunities
Teams align faster on hypotheses grounded in evidence
Evi Content creates consistent messaging across markets
During the campaign
Evi provides contextual guidance directly in the workflow
Teams can iterate faster and reduce dependency loops
After the campaign
Evi Analysis turns raw results into clear, actionable insights
Everyone sees the same interpretation of data
Learnings become easier to share and apply across markets
Result: A more autonomous, aligned, and collaborative experimentation program — powered by shared intelligence rather than siloed expertise.
AB Tasty continues to strengthen its collaborative features, with upcoming developments. Stay tuned! These improvements move AB Tasty closer to its long-term vision: a platform that not only enables experimentation but also unlocks organizational intelligence.
Conclusion: Collaboration Is the New CRO Advantage
Companies win with experimentation when they democratize it — when insights circulate openly, when accountability is shared, and when tools empower collaboration instead of slowing it down.
AB Tasty doesn’t just enable experimentation; it turns it into an organizational capability. A place where teams align faster, learn continuously, and make decisions grounded in evidence rather than intuition.
In a world where speed and cross-functional execution define competitive advantage, AB Tasty provides the collaborative foundation businesses need to accelerate growth.
Danielle Harvey shares how travel customers are using different channels, why testing doesn’t always have to end in success, and how travel companies can integrate AI to provide a more engaging customer experience.
Currently Vice President, Industries, Partnerships & Emerging Products at Quantum Metric, Danielle Harvey, has a long experience in the travel industry. She also spent 11 years at one of the world’s largest hotel brands, Wyndham Hotels & Resorts, driving a data-driven approach to optimizing customer experience. With roles including digital acquisition, voice of the customer, CRM, experimentation, and digital analytics, she has a unique understanding of the travel customer journey.
Danielle Harvey spoke with AB Tasty’s Head of Marketing and host of The 1000 Experiments podcast, John Hughes, about the importance of connecting channels in the travel industry, using testing to understand the customer journey, and how brands can best harness the power of AI.
Here are some of the key takeaways from their conversation.
Let customers do what they want where they want
COVID forced the travel industry to undergo an accelerated digital transformation. And travel customers now want a seamless cross-channel experience when booking. This is especially true when people frequently use different platforms at different stages of their buying journey and make multiple visits to your website before making a booking.
“We did some benchmark data and 75-80% of traffic in travel is on mobile at this point, but only about 25% of bookings are. It’s a heavy research channel, a day-of-travel channel, but not necessarily where people are comfortable purchasing yet,” says Danielle.
Enabling customers to transact in their channel of preference and connecting different channels therefore becomes vital. This provides immediate benefits for the customer but also operational efficiencies for providers.
Omnichannel may have been little more than a buzzword a few years ago. But with the true adoption of digital technology and improved methods of data collection, connecting those experiences is becoming more of a reality.
“A lot of travel can still be pretty siloed, but your customers don’t care,” explains Danielle. “They expect that your teams are speaking to each other, that there’s an overarching strategy.”
10 essential ideas to help travel brands win bigger.
Even flat and failed tests can be learning experiences
Testing and experimentation don’t always have to be successful to provide you with valuable information to help you improve the customer experience. An example that Danielle gave was testing customer ratings and reviews on a website.
“Some of the most interesting testing I did was around reviews. Because the assumption was that if you get those out there on the site, they should really have an impact,” says Danielle.
But when almost a quarter of the people researching travel will typically visit your website as least five times before booking, it’s likely that they’re getting much of their information from other sources.
“It was always interesting that whenever we tried testing reviews, they didn’t really move the needle. So, your website is often not the only place people are going to go for information,” notes Danielle.
But this flat result helped drive the realization that while adding reviews might not have a direct financial impact, they were important for transparency. And at the same time, they made things easier for the customer.
And just because a test has failed, that doesn’t mean it shouldn’t help to inform your strategy going forward. The key is to try and understand what happened and learn from that.
“Over time, I would typically see a 50/50 win to fail rate. But my focus on failed tests was always what do we learn from this, digging into the reason why it failed and then building a pipeline of testing and experimentation off of that,” says Danielle.
Use AI to improve the customer experience
AI-powered tools can create time efficiencies for travel providers and provide valuable context about customer intent. And many travel brands are using AI to help their employees service the customer faster.
“We’re doing some cool stuff at Quantum where an AI chat component will send a summary to a support agent who can immediately see what the customer was trying to do, rather than putting the burden on the customer to repeat themselves,” explains Danielle.
Integrating AI can also be extremely valuable for people involved in testing and experimentation.
“A lot of the excitement around AI, especially in things like personalization, is that you don’t need to come up with ideas yourself and test them, but ideally some of that is automated for you,” says Danielle.
If you launch a test and don’t specifically track certain behaviors, for example, it’s often hard to know how a user might interact with it. By using AI to auto capture data, you can watch what users did and use heat maps to see where they were engaging.
There’s also an increasing focus from both customers and travel providers on self-service. But many brands are still hesitant to have a lot of AI facing the customer. The key is finding the right balance.
“The unique thing with travel and hospitality is there is always a human element. You don’t want to digitize it completely,” advises Danielle. “You’re ideally delivering a nice experience as well.”
What else can you learn from our conversation with Danielle Harvey?
The long-haul effect: How the travel customer journey differs from that of e-commerce.
Voice of the customer: The importance of turning qualitative feedback into quantitative data.
On brand: Some of the challenges involved in testing across different brand websites
Experience over things: Why travel will continue to be a priority for many people going forward even though it might look different.
About Danielle Harvey
Danielle Harvey is Vice President, Industries, Partnerships & Emerging Products at Quantum Metric. Passionate about the travel industry, she spent 11 years prior to this leading digital and analytic teams at Wyndham Hotels & Resorts and has also worked for the Avis Budget Group.
About 1,000 Experiments Club
The 1,000 Experiments Club is an AB Tasty-produced podcast hosted by John Hughes, Head of Marketing at AB Tasty. Join John as he sits down with the experts in the world of experimentation to uncover their insights into what it takes to build and run successful experimentation programs.
The Problem: The High Cost of Experimentation Amnesia
In digital optimization, we often obsess over velocity—how fast can we test? But this focus masks a deeper, more expensive problem: Experimentation Amnesia.
At AB Tasty, an analysis of over 1.5 million campaigns revealed a startling trend. While thousands of tests are launched daily, the specific context—why a test won, what surprised us, and the strategic lesson learned—often evaporates the moment the campaign ends.
It vanishes into a 250-slide PowerPoint deck that no one opens again. It disappears into a Slack thread. Or, most painfully, it walks out the door when your CRO Manager or agency partner moves on to their next opportunity.
If you are running tests but not archiving the insights in a retrievable way, you aren’t building a program; you’re just running in circles. It’s time to shift your focus from Execution to Knowledge Management.
The Hidden Cost of “One-and-Done” Testing
The digital industry is notorious for its high turnover. On average, internal digital teams change every 18 months and agencies rotate every two years.
In traditional workflows, knowledge is tied to people, not platforms. When a key manager leaves, they take their “mental hard drive” with them.
This is the “Knowledge Drain.” It is the silent budget killer of CRO programs.
Every time you repeat a test because you couldn’t find the previous results, you are paying double for the same insight. Every time you lose the context of a winning test (i.e., you know that it won, but not why), you lose the ability to iterate and double your gains.
This is why the most mature experimentation teams are moving away from simple testing tools and adopting Program Management platforms that secure their knowledge.
The Solution? AB Tasty’s new Learnings Library.
We designed this feature to serve as a centralized, searchable repository that lives directly where your experiments do. It acts as the institutional memory of your digital team, ensuring that every test—whether a massive win or a “flat” result—contributes to a permanent asset library.
Context is King: Why AI Can’t Replace the Human “Why”
In an era where everyone is rushing to automate everything with AI, you might ask: “Why can’t an AI just write my test conclusions?”
While AI is powerful for analyzing raw numbers, it lacks business context. An AI can tell you that “Variation B increased transactions by 12%.” But it cannot tell you why that matters to your strategy.
Was that 12% expected?
Was it a shocking surprise that disproved a long-held internal belief?
Did it cannibalize another product line?
AB Tasty’s Learnings Library is designed to capture Qualitative Intelligence. It prompts your team to manually qualify results with human tags like “Surprising” or “Expected.” It asks for the narrative behind the numbers.
This human layer is critical. A “failed” test (one that produced no uplift) is often more valuable than a win, provided you document the lesson. By recording, “We learned that our users do not care about social proof on the cart page,” you create a defensive asset. You prevent future teams from wasting budget on that specific hypothesis again.
Visual History: The Power of “Before and After”
One of the biggest friction points in reporting is visual documentation. How much time does your team spend taking screenshots, cropping them, pasting them into PowerPoint, and trying to align the “Control” vs. “Variation” images?
Our Learnings Library automates this friction. It should allow you to upload your screenshots and automatically generate a Comparison View—a visual “Before and After” slide that lives alongside the data.
This visual history is vital for continuity. Two years from now, a spreadsheet number won’t spark inspiration. But seeing the exact design that drove a 20% increase in conversions? That is instant clarity for a new Designer, Developer, or Strategist.
Conclusion: Stop Renting Your Insights
If your testing history lives in the heads of your employees or on a local hard drive, you are effectively “renting” your insights. The moment that employee leaves, the lease is up, and you are back to square one.
It is time to own your knowledge.
Don’t let your next great insight slip through the cracks. Start building your library today.
FAQs: Learnings Library
What is AB Tasty’s Learnings Library?
Our Learnings Library is a centralized digital repository that archives the results, visual history, and strategic insights of every A/B test run by an organization. Unlike static spreadsheets, it connects data (uplift/downlift) with qualitative context (hypotheses and observations), transforming individual test results into a permanent, searchable company asset
How does staff turnover impact A/B testing ROI?
Staff turnover creates a “Knowledge Drain.” When optimization managers leave without a centralized system of record, they take valuable historical context with them. This forces new hires to “restart” the learning curve, often leading to redundant testing (paying for the same insight twice) and a slower velocity of innovation.
Should I document “failed” or inconclusive A/B tests?
Yes. A “failed” test is only a failure if the lesson is lost. Documenting inconclusive or negative results creates “defensive knowledge,” which prevents future teams from wasting budget on the same disproven hypotheses. A robust Learning Library treats every result as a data point that refines the customer understanding.
How do I stop my team from re-running the same A/B tests?
The most effective way to prevent redundant testing is to implement a searchable timeline of experiments that includes visual evidence (screenshots of the original vs. variation). This allows any team member to instantly verify if an idea has been tested previously, under what conditions, and what the specific outcome was.
What is the best platform for scaling a CRO program?
Scaling a program isn’t just about running more tests; it’s about running smarter tests. Unlike competitors that focus on “gadget” features (like AI text generation), AB Tasty invests in Program Management infrastructure. By combining execution with a native Knowledge Management system, AB Tasty allows your program to compound its value over time, rather than resetting every year.
Let’s be honest… Most KPI dashboards are where good intentions go to die. They’re meticulously built, packed with charts, and then they’re mostly ignored. Teams are drowning in data but starved for real insight. Why? Because the framework is broken. It’s either tracking metrics that don’t matter, it’s too slow to be useful, or it’s so complex that nobody knows what the numbers are actually telling them.
This creates a frustrating cycle. Marketing, product, and engineering teams work hard on new ideas, but they can’t prove their impact. The result is a culture of guesswork, not growth. But it doesn’t have to be this way. At AB Tasty, we see optimization as a journey of constant learning, where every experiment moves you forward. A great KPI framework is your guide on that journey. It’s not a static report; it’s a dynamic tool that turns raw data into a clear story of progress, aligns your teams around shared goals, and gives you the confidence to make the next move. It’s time to build a framework that your teams will not only use but will champion.
Step 1: Identify KPIs that are actually key
The biggest trap in measurement is vanity. We track clicks, pageviews, and time-on-page because they’re easy to see and feel like progress. But do they connect to the bottom line? Often, they don’t. A truly effective framework starts by asking the big questions first. What are the core outcomes that drive our business forward?
Forget the firehose of data for a moment and focus on your ultimate destination. Are you trying to:
Increase customer lifetime value?
Improve user retention and reduce churn?
Boost average order value?
Drive qualified leads for the sales team?
Once you have your high-level business objective, you can work backward to identify the Key Performance Indicators (KPIs) that directly influence it. These are your true north stars. If your goal is to grow revenue from your e-commerce platform, your key indicators aren’t just traffic numbers. They’re metrics like purchase rate, average order value (AOV), and overall revenue.
This is why we’ve built our platform with these meaningful goals in mind. Right out of the box, you can set up goals in AB Tasty that cut straight to business impact. These include:
Transaction goals, such as AOV, purchase rate, and revenue.
Action tracking, which measures critical user interactions like clicks, scroll depth, and element visibility.
Browsing behavior, to understand revisits, bounces, and pageviews in a meaningful context.
By starting with KPIs that are directly tied to business outcomes, you create a shared language. Your product team’s experiments with the checkout flow, marketing’s new campaign, and the CRO team’s homepage tests all point toward the same measurable goal. You’re no longer just running tests; you’re driving tangible progress.
Step 2: Measure what makes you unique with custom metrics
Standard metrics are a great starting point, but your business isn’t standard. Your user journey has unique steps, critical interactions, and “aha!” moments that generic KPIs will never capture. Maybe it’s a customer using your product configurator, engaging with a new video series, or filling out a multi-step form. These are the interactions that define your unique customer experience, and you need to measure them.
This is where the grit comes in. It takes determination to go beyond the easy-to-track metrics and measure what truly matters. Custom metrics allow you to translate your unique business logic into trackable data points. They answer specific questions like:
“Did users who interacted with our new sizing guide convert at a higher rate?”
“How many people clicked on the ‘request a demo’ button after watching our new feature video?”
“What percentage of users completed all three steps of our new onboarding flow?”
You shouldn’t have to change your user experience to fit your analytics tool. Your tool should adapt to you. That’s why in AB Tasty, you can create Custom Trackings that are directly linked to the DataLayer on your site. This lets you build metrics based on your specific data. You can also create custom trackers with JavaScript, giving your team the flexibility to measure virtually any interaction. It’s even possible to use these custom tracking events to replicate goals from other platforms, like GA4, ensuring consistency across your entire analytics stack.
When you measure what makes you unique, you get insights that your competitors can’t see. You start understanding the why behind the what, turning your data from a simple report into a competitive advantage.
Step 3: Leverage real-time reporting to act fast
The pace of digital is relentless. An insight that’s a week old is already history. For optimization to be effective, the feedback loop between action and insight needs to be as short as possible. If your team has to wait days or weeks for a report on their latest experiment, they’ve already lost momentum. The opportunity to pivot, iterate, or double down on a winner has passed.
A culture of improvement requires a flow of constant learning. This is where real-time reporting becomes essential. When you can see the impact of your changes as they happen, you empower your teams to be proactive, not reactive. They can spot a problem with a new release within minutes, not days. They can see a winning variation pull ahead and make a confident decision to roll it out to all users, capturing its value immediately.
We know that speed is critical. That’s why AB Tasty offers real-time reporting that automatically activates when you push a campaign live. During the initial, most critical phase of a test (up to 1,000 unique visitors or the first 12 hours), your data for every goal and variation is updated every five minutes. We also provide a Live Hits monitoring tool so you can track event data at any moment. This closes the gap between an idea and its outcome, allowing your teams to make smarter, faster decisions fueled by up-to-the-minute data.
Step 4: Understand confidence to make confident decisions
You’ve run a test, and variation B is outperforming the original by 5%. Is it time to celebrate and deploy it to everyone? This is where many teams get stuck. They see a positive lift but are paralyzed by uncertainty. What if it’s just random chance? How “sure” do we have to be?
This is the final, crucial piece of the framework: understanding the story your statistics are telling you. You don’t need to be a data scientist to make a good call, but you do need tools that present statistical confidence in a clear and actionable way.
At AB Tasty, we use Bayesian statistics, which provides direct and intuitive probability statements. Instead of just a confusing p-value, we give you two key things:
The chance to win: This is a straightforward probability that tells you how likely it is that a variation is better than the original. A 98% chance to win means there’s a 98% probability that the variation is the true winner.
A 95% confidence interval: Think of this as a “range of likely outcomes.” If the confidence interval for the gain is [+2%, +8%], we are 95% confident that the true, long-term uplift from this variation is somewhere between 2% and 8%. The remaining 5% represents the margin of error.
This approach removes the ambiguity. It equips your team with the conviction they need to make decisions. It’s not about being 100% certain; it’s about understanding the probability and the potential impact, allowing you to make a calculated business decision. It’s the insightfully sharp wisdom that turns a good idea into proven progress.
Conclusion: Find your better
A KPI framework is so much more than a dashboard. It’s a reflection of your strategy, a tool for alignment, and the engine of your experimentation culture. When you focus on what matters, measure your unique journey, act on insights in real-time, and make decisions with confidence, you create a powerful cycle of continuous improvement.
You stop guessing and start knowing. Your teams feel empowered because they can see the direct impact of their brave ideas. You build a culture that doesn’t just celebrate the wins but learns from every single test. You start your journey to “Find your better.” Your data is already telling this story. It’s time to build the framework that lets you read it.
Frequently Asked Questions (FAQ)
What’s the difference between a KPI and a metric?
Think of it this way: a metric measures a process, but a KPI measures performance against a key business objective. For example, “website traffic” is a metric. But “conversion rate from organic traffic,” when your goal is to increase online sales, is a KPI. All KPIs are metrics, but not all metrics are KPIs.
How many KPIs should we track?
Less is more. A framework with 25 KPIs is a list, not a focus. Aim to identify 3-5 primary KPIs for each major business objective. This forces you to prioritize what truly drives the business forward and keeps your teams from getting lost in the noise.
How do we get our teams to actually use the framework?
Adoption comes from ownership and accessibility. Involve marketing, product, and data teams in the creation process so the KPIs reflect their reality. Then, make the dashboard highly visible and easy to understand. Most importantly, celebrate the insights the framework generates, not just the successful tests. Frame it as a tool for learning, and your teams will embrace it.
What kinds of KPIs are available out of the box in AB Tasty?
You can set up goals at both an account and campaign level. The primary goal types include:
Action Tracking: Clicks, dwell time, element visibility, scroll rate.
Page Tracking: Visits to a specific page or group of pages.
Browsing Behavior: Revisit rate, bounce rate, pageviews per session.
Transaction: Average order value (AOV), purchase rate, total revenue.
DataLayer Goals: Tracking based on variables in your site’s data layer.
Can we create custom metrics?
Yes. You can create Custom Trackings linked directly to your DataLayer, allowing you to build metrics from your unique business data. You can also create custom trackers using JavaScript, which can be used to track specific interactions or even replicate goals from other platforms like GA4.
Is reporting in real-time?
Yes. Real-time reporting activates automatically when a campaign goes live. During the initial phase (the first 1,000 unique visitors or 12 hours), data for each goal and variation are updated every five minutes. We also provide a Live Hits monitoring tool to track event data at any time.
How does AB Tasty report on statistical confidence?
We provide two key figures to make decisions easier. The first is a 95% confidence interval, which gives you a likely range for the true value of the gain. The second is the Chance to Win, which is a direct probability that one variation is better than the other. We use a Bayesian statistical model because it provides these intuitive, actionable results that are easier for teams to understand and act on.
What’s the difference between client-side and server-side testing?
Client-side testing happens in the user’s browser and is ideal for marketing and CRO teams to quickly test visual changes, copy, and layouts without needing developer support. Server-side testing happens on the web server, which is better for product and engineering teams to test more complex functionality, new features, and omnichannel experiences. AB Tasty’s unified platform supports both, allowing teams to work from a single place.
How do we measure the impact of personalization on KPIs?
The key is to always test your personalization efforts. Run an A/B test where Group A sees the standard experience and Group B sees the personalized experience. By comparing the KPIs for both groups—such as conversion rate, AOV, or engagement—you can directly attribute any uplift to your personalization strategy and prove its ROI.
