AB Tasty is thrilled to announce that Wandz.ai, the real-time adaptive customer experience platform, is officially joining our family. This partnership is more than just a handshake; it’s a leap forward for digital experience optimization everywhere, and it’s a game-changer for personalization.
Why Wandz? Because Digital Journeys Are Messy—and We’re Here for It
Everyone in the digital space knows that online journeys are rarely straightforward.
Visitors pop in mid-funnel, juggle multiple tabs, bounce between devices, and most of them remain anonymous. In fact, 90% of your website visitors don’t log in or leave a data trail. But here’s the twist: when brands adapt to these unpredictable behaviors, conversion rates can skyrocket.
Wandz was built for this challenge. Wandz technology captures real-time intent signals—every click, scroll, and session pattern—and instantly adapts the experience for each visitor, even if they’re flying under the radar. Think of it as a digital guide that knows what your customers want before they do. The key to personalizing for your visitors is also understanding your users’ intent. That’s how you’ll know what to offer them next.
What’s in It for You, Personally?
With Wandz joining AB Tasty, we’re not just adding new features—we’re unlocking a whole new level of personalization and engagement for your brand.
Real-Time, Adaptive Personalization: Wandz’s AI engine processes 3.7 trillion data points every month, serving 1.5 billion users worldwide, and generates predictions in just 20 milliseconds. That’s not just fast—it’s lightning fast.
Proven Results: Leading brands in the digital e-commerce space have already seen up to 15% revenue lift, 13.6% higher conversion rates, and 65% more content engagement thanks to Wandz’s adaptive approach.
Full Transparency: No black-box mysteries here. Every data point is transparent, accessible, and actionable—so your teams can make informed decisions with confidence.
The Power of Predictive and Generative AI—Now in Your Hands
By bringing Wandz’s AI into the AB Tasty platform, we’re giving you the tools to move from reactive to proactive. Imagine forecasting behaviors, segmenting intelligently, and building models tailored to your unique customer journeys—all while optimizing every touchpoint in real time.
With generative AI, you can create and refine personalized experiences at scale, ensuring every interaction feels relevant and unique. Predictive AI keeps fine-tuning performance and outcomes, so you’re always ahead of the curve.
What’s Next? Smarter, More Adaptive Experiences for All
This isn’t just an acquisition—it’s a partnership for the future. By combining Wandz’s talent and technology with AB Tasty’s global reach and culture of innovation, we’re setting a new standard for adaptive personalization and customer experience.
Soon we’ll be rolling out these new AI-powered capabilities across all our clients. Whether you’re in marketing, product, or development, you’ll have the tools to analyze, strategize, and optimize like never before—transforming simple interactions into adaptive experiences that drive real business results.
Welcome to the Next Chapter of Digital Experience
So, what’s new at AB Tasty? Only the most advanced, adaptive, and engaging digital experiences on the market. We can’t wait to see what you’ll create with the combined power of Wandz and AB Tasty.
Stay tuned—this is just the beginning. The future of customer experience is adaptive, and we’re excited to help you lead the way.
At AB Tasty, we know that data is the foundation of every great digital experience.
Getting accurate analytics shouldn’t feel like a guessing game. But with privacy changes, ad blockers, and browser updates, even the best teams have struggled to get clean, reliable data from their websites. We’ve seen it firsthand, and we knew something had to change.
That’s why we revamped our Google Analytics 4 (GA4) connector. It’s designed to make your data more trustworthy—without adding complexity for your team.
Designed for Today’s Data Challenges
Modern websites face a host of obstacles when it comes to data collection: privacy settings, ad blockers, and evolving browser behaviors can all impact the reliability of analytics. Our new GA4 connector is built to address these realities head-on, ensuring your data remains consistent and actionable.
Server-to-Server Integration for Unmatched Reliability
By sending events directly from AB Tasty’s servers to Google Analytics, we bypass the common pitfalls of browser-based tracking. This means your analytics are less susceptible to blockers and delays, and you can trust the numbers you see.
What’s Different?
The real shift is under the hood. Instead of sending data from the browser (where it can get blocked or delayed), our connector sends events straight from AB Tasty’s servers to GA4. This cuts out the usual noise and means your numbers in AB Tasty and GA4 finally match up.
We’ve made a significant enhancement to how data flows between AB Tasty and GA4. Instead of sending two separate hits—one to AB Tasty and another to GA4— to each platform, we now collect events once in AB Tasty, enrich them, and seamlessly send that unified data to GA4.
This streamlined process ensures that what you see in AB Tasty is exactly what appears in GA4—delivering near-instant updates and even greater accuracy across your reports.
Easy Set Up
You don’t need to be an engineer to get started. With our connector, setup is straightforward—just add your GA4 Measurement ID and API Secret in AB Tasty, and you’re good to go. No need for complex engineering or code changes, so your teams can focus on what matters: driving results.
Built for Scale, Backed by Experts
This connector is more than a technical upgrade—it’s a reflection of AB Tasty’s commitment to innovation and customer success. Our Data and DevOps teams have prioritized both reliability and scalability, with a target of less than 7% data discrepancy between AB Tasty and GA4. We’re setting a new benchmark for the industry.
Competitive Advantage: Why AB Tasty Leads the Way
AB Tasty is the first to address client-side tracking while following Google best practices with server-to-server hits sending.
AB Tasty’s early investment means clients benefit from a proven, reliable solution today. Whether you’re looking to solve existing analytics challenges or simply want the peace of mind that comes with trustworthy data, AB Tasty’s GA4 connector is here to help you succeed.
The Bottom Line
For brands that rely on data accuracy, the stakes are high. Data accuracy drives smarter decisions, better customer experiences, and stronger business outcomes.
FAQs
What is the new GA4 connector from AB Tasty?
The GA4 connector is an enhanced integration that allows you to send enriched event data directly from AB Tasty’s servers to Google Analytics 4, ensuring more reliable and accurate analytics.
How does the new connector improve data accuracy?
By sending a single, enriched event from AB Tasty to GA4, the connector eliminates discrepancies and delays that can occur with separate browser-based hits. This ensures that your data in both platforms matches and is updated in near real-time.
Why is server-to-server integration important?
Server-to-server integration bypasses common issues like ad blockers, privacy settings, and browser limitations that can interfere with client-side tracking. This means your analytics are more complete and trustworthy.
Is the connector difficult to set up ?
It’s very easy! Setting up the GA4 connector is straightforward. All you need to do is add your GA4 Measurement ID and API Secret in AB Tasty—no complex engineering or code changes required.
Let’s be honest: proving ROI in digital experimentation has often felt like trying to solve a Rubik’s Cube, blindfolded.
For years, teams have been stuck in the same old debate: “This test boosted conversion rate, but AOV dropped!” or “AOV is up, but conversions are down!” Which is better? Who’s right? And most importantly, how do you convince your CFO that your work is actually making money?
The Problem: Conflicting Metrics and Stalled Decisions
Picture a scenario familiar to many: one campaign variation boosts conversion rate but lowers AOV, while another does the opposite. Which is the real winner? Without a unifying metric, teams get stuck in endless debates, unable to confidently declare a result or justify next steps. As a result, a significant share of tests end up in limbo, and existing ROI dashboards suffer from low trust and adoption.
In fact, last year, 8% of A/B test campaigns with a transaction goal ended up in the dreaded “no decision” zone.
The Solution: RevenueIQ
Now, imagine a world where you don’t have to choose between conversion rate and AOV. Where you don’t have to explain why one number went up while the other went down. Where you can walk into any meeting and say, “Here’s a monthly revenue projection of exactly how much revenue this campaign is generating.”
That’s the world RevenueIQ is building.
RevenueIQ is AB Tasty’s new, patented metric—a result of years of R&D and statistical expertise. It takes all the messy, contradictory data and boils it down to one simple, business-focused number: monthly revenue projection. No more “unclear winners.” No more “conversion vs. AOV” dilemmas; just a clear, actionable view of financial impact.
Key Benefits of RevenueIQ:
Always a Clear Revenue View: RevenueIQ provides a direct view of revenue per visitor and per month, making it easy to see the financial impact of every campaign.
Eliminates “Unclear Winners”: Even in complex scenarios, RevenueIQ provides a definitive view of which variation delivers the most revenue. This means no more inconclusive campaigns and a significant reduction in “undecidable” tests.
Delivers faster results: Combining the two key metrics into a single revenue metric gives actionable insights more quickly than analyzing them separately
ROI Projections Before Going Live: Teams can now project the revenue impact of a campaign before full rollout, complete with confidence intervals for best- and worst-case scenarios. This transparency helps avoid surprises and supports more strategic decision-making.
Strong Differentiation: RevenueIQ is powered by a unique, patented Bayesian engine, ensuring robust, trustworthy results. It’s not just another metric—it’s the business truth.
Revenue IQ is able to give a confidence interval around the revenue prediction, allowing for better business decisions. With a clear best-case and worst-case scenario, business decisions are easier than just having one number without knowing its accuracy.
The best thing? No competitor currently offers an equivalent.
How RevenueIQ Works
RevenueIQ is deeply integrated into the AB Tasty platform. When a campaign runs, users see not just conversion rates or AOV, but a clear revenue uplift per visitor and per month. The system visually identifies the winning variation, quantifies the potential monthly revenue gain, and provides confidence intervals to show the range of possible outcomes.
For example, if a variation is projected to generate an additional €4,000 per month, RevenueIQ will also display the probability of this outcome and the range (e.g., €2,700–€6,000). This approach is both rigorous and transparent, helping teams make decisions with confidence.
Curious to know more details? Please read our RevenueIQ Whitepaper for a full scientific explanation written by our Data Scientist, Hubert Wassner.
Not a data scientist, but still want to know more? Read our RevenueIQ article that goes into more detail about the practical use of RevenueIQ.
The Impact: Confidence, Adoption, and Differentiation
With RevenueIQ, AB Tasty is setting a new standard for ROI proof in digital experimentation. The result is a simple, credible, and actionable narrative for QBRs and renewal discussions—one that restores confidence, drives adoption, and differentiates AB Tasty in a crowded market.
Revenue IQ lowers the risk of making business mistakes by focusing on revenue.
For teams tired of inconclusive debates and complex metrics, RevenueIQ offers a new way forward: clear, credible, and actionable proof of business impact.
FAQs about RevenueIQ
What is RevenueIQ?
RevenueIQ is a proprietary, patented metric developed by AB Tasty that provides a clear, unified view of how much revenue your digital experiments generate—expressed as revenue per visitor, per month.
How trustworthy are RevenueIQ’s numbers?
RevenueIQ is powered by a patented Bayesian engine, ensuring robust, transparent, and reliable calculations. All projections include confidence intervals, so you always see the full picture.
How does RevenueIQ handle complex or ambiguous test results?
RevenueIQ always provides a clear winner based on revenue impact, even in cases where traditional metrics are inconclusive (due to their lack of integration). This means fewer “stuck” campaigns and more decisive action.
How is RevenueIQ different from what competitors offer?
No competitor currently offers a metric like RevenueIQ. While others may provide “all-purpose” statistics for each individual metric, only RevenueIQ gives you a patented, unified view of revenue per visitor, per month—making it a true differentiator.
Let’s face it: launching a new feature can feel a bit like walking a tightrope. You want to wow your users with something fresh, but you also know that even the best-tested releases can have surprises lurking in the shadows.
What if you could take the nerves—and the guesswork—out of your next launch? That’s exactly what Progressive Rollout is here to do.
The Problem: Risky Feature Releases and Manual Workarounds
Picture this: your team has spent weeks (maybe months!) building a new payment system, a revamped booking flow, or a shiny loyalty program. You’re excited. But you’re also worried. What if something breaks? What if a bug slips through and impacts thousands of users at once?
This is the reality for most product and engineering teams. The stakes are high, and the pressure to “get it right” is real. That’s why so many teams look for ways to release new features gradually—starting with a small group, then expanding as confidence grows.
But here’s the catch: most teams don’t have a dedicated tool for this. Instead, they put together workarounds using feature toggles or A/B tests. These methods can work, but they’re clunky, manual, and often lack the visibility and reassurance everyone craves during a launch.
The Solution: Progressive Rollout
Progressive Rollout is our answer to this all-too-common problem. It’s a feature designed not just for the tech wizards, but for everyone involved in a product launch—product managers, developers, and even business stakeholders.
How does it work? With Manual Progressive Delivery, you can schedule your feature release in stages. Maybe you want to start with 10% of your users, then move to 20%, 40%, and so on. You decide the pace and the audience.
Our platform handles the rest, automatically exposing more users to your new feature at each step. And at every stage, you get clear notifications and a visual overview, so you always know exactly what’s happening.
What Makes Progressive Rollout a Game-Changer?
1. It’s Actually Easy to Use Let’s be honest: many “enterprise” tools are intimidating. Progressive Rollout is different. The interface is clean, intuitive, and designed so that anyone can set up a rollout in just a few clicks. No advanced segmentation or manual math required. Whether you’re a seasoned developer or a product manager new to experimentation, you’ll feel right at home.
2. Full Control, Full Reassurance One of the biggest anxieties during a rollout is not knowing what’s happening. With Progressive Rollout, you get a crystal-clear view of your rollout plan: who’s getting the feature, when, and how much of your audience is included at each step. Email notifications keep you in the loop, so you’re never caught off guard. This transparency isn’t just a nice-to-have—it’s a must for teams who want to move fast and stay safe.
3. Flexible for Any Scenario Want to give early access to your VIPs or most loyal users? Easy. Need to roll out to everyone, but in controlled increments? No problem. You can import user lists, target specific segments, or just roll out to “all users” in stages. Progressive Rollout adapts to your needs, not the other way around.
Fun Fact: Most Teams Aren’t Doing This—Yet
Here’s something surprising: despite the clear benefits, most teams aren’t using dedicated progressive rollout tools. They’re still relying on toggles and A/B tests, or even manual processes. Why? Because until now, the tools have been too complex or not user-friendly enough. Progressive Rollout changes that, making safe, staged launches accessible to everyone.
The Bottom Line: Launch With Confidence
Progressive Rollout isn’t just another feature—it’s peace of mind for your next big launch. By making gradual releases easy, transparent, and accessible, we help you reduce risk, improve user experience, and focus on what matters: delivering value to your customers.
Picture this: You’ve just launched a new product line, or maybe you’re gearing up for a themed campaign–think “Back to School” or a limited-edition collection. You want your customers to discover the right products, right away. But traditional recommendation engines are stuck waiting for data to trickle in, leaving you with generic suggestions and little control over what’s shown. For merchandisers, that’s not just frustrating – it’s a missed opportunity.
That’s exactly why we built AB Tasty’s Semantic Proximity Algorithm. Instead of relying on yesterday’s sales numbers, this new approach lets you craft relevant, business-driven product recommendations from day one. Whether you’re working with a fresh catalog or pivoting to a new campaign, you get the flexibility and control you need – no waiting, no guesswork, just smarter recommendations tailored to your goals.
From Algorithm to Merchandiser Mindset
Most recommendation engines are just that – algorithms. But AB Tasty’s Semantic Proximity Algorithm is a paradigm shift: it allows your catalog to think like a merchandiser. Instead of passively waiting for data, it actively understands your products, your campaigns, and your business goals – giving your catalog a brain and putting you in the driver’s seat from day one.
Why Rethink Product Recommendations?
Traditional recommendation algorithms are built on analytics data – think Google Analytics or similar tools. These models can be effective, but only if you have enough historical data. What happens when you launch a new product line, a new brand, or want to activate a campaign around a specific theme (“Back to School,” “Harry Potter,” etc.)? Merchandisers are often left with little control, unable to quickly tailor recommendations to their business needs or campaign goals.
This is the challenge that inspired us to create the Semantic Proximity Algorithm: a tool that empowers merchandisers to launch relevant, business-driven recommendations instantly, even with zero historical data.
The Semantic Proximity Algorithm: A New Approach
AB Tasty’s Semantic Proximity Algorithm takes a fundamentally different approach. Instead of relying on analytics data, it leverages advanced Natural Language Processing (NLP) to analyze the attributes of your product catalog – such as product name, description, category, price, and even custom metafields. This allows the algorithm to identify products that are semantically related, regardless of whether they have ever been purchased together.
Key benefits include:
Fast ROI: Campaign launches, upsell, cross-sell
Instant setup: No need to wait for analytics data to accumulate. Recommendations are ready as soon as your catalog is integrated.
Total flexibility: Merchandisers can select and combine any catalog attributes to build strategies and adapt recommendations on the fly for seasonal events or business needs.
Full control and transparency: Preview and iterate on recommendations before going live, ensuring relevance and quality.
Adaptable for all expertise levels: The algorithm is as simple or as advanced as you need. SMBs can start with just product names, while advanced users can leverage dozens or even hundreds of attributes for highly customized strategies.
Previously, recommendation engines were blind – waiting for clicks, sales, and data to slowly trickle in before making generic suggestions.
AB Tasty’s Semantic Proximity Algorithm delivers instant, intelligent recommendations. As soon as your catalog is integrated, the algorithm “thinks” like a merchandiser – making smart, relevant suggestions based on product meaning, not just past behavior. No more waiting, no more guesswork -just instant, business-driven recommendations that adapt as quickly as you do
Unique on the Market
No direct competitor offers this level of semantic attribute selection and flexibility. While some platforms provide basic attribute filtering, none allow merchandisers to select and combine multiple catalog attributes to fine-tune recommendations. Most competitors still rely mainly on analytics and sales data, with only limited semantic analysis capabilities.
This is a true differentiator for AB Tasty, empowering clients to adapt their recommendation strategies to their unique business challenges – without being held back by data limitations.
How Does It Work in Practice?
The Semantic Proximity Algorithm is designed to be both powerful and user-friendly. Merchandisers can choose which attributes to use for each recommendation strategy – whether that’s product name, description, category, price, or even custom fields like Shopify metafields. This means you can tailor recommendations for specific campaigns, themes, or business objectives.
For example, during a seasonal campaign, you might want to recommend products that share a common theme in their description or category, even if they’ve never been purchased together before. Or, you might want to upsell higher-value editions of a product by prioritizing price as an attribute. The algorithm allows you to preview and iterate on these strategies instantly, making it easy to adapt to changing business needs.
Upsell, Cross-sell, and Beyond with Product Recommendations
The flexibility of the Semantic Proximity Algorithm opens up new possibilities for both upsell and cross-sell strategies. For upsell, you can recommend alternative products that are not only similar but also more profitable. For cross-sell, you can suggest complementary items that enhance the customer’s purchase – think of the classic “chewing gum at the checkout” scenario, but tailored to your specific catalog and business logic.
This approach is especially valuable for businesses with large or complex catalogs, or those looking to launch new products and campaigns quickly. It’s also ideal for expert merchandisers who want granular control over their recommendation logic, as well as for SMBs seeking a fast, easy-to-implement solution.
Fun Facts & Unique Highlights
Did you know? This is the first AB Tasty algorithm that works directly from your product catalog–no analytics setup required.
Unique on the market: No competitor allows merchandisers to select and combine multiple catalog attributes (including custom metafields) to fine-tune recommendations.
Instant preview: You can see and iterate on your recommendation strategies before going live – perfect for adapting to seasonal campaigns or special events.
Scalable: The algorithm can handle catalogs with hundreds or even thousands of attributes per product.
Conclusion
AB Tasty’s Semantic Proximity Algorithm ushers in a new era for product recommendations: faster, more flexible, and more intelligent. Whether you’re an SMB looking for simplicity or an enterprise seeking advanced personalization, this innovation lets you transform the customer experience and maximize revenue from day one.
FAQs
Is this just another “black box” AI?
No. You control which attributes are used, can preview results, and iterate. It’s transparent and customizable.
What if the recommendations don’t make sense?
You can filter and combine attributes, set thresholds, and preview results before going live. Early feedback has led to rapid improvements.
Does it work with custom fields?
Yes! Any attribute in your catalog, including custom metafields, can be used.
When it comes to digital optimization, you need more than just another tool—you need a partner who understands that every test is a step toward something bigger.
Here’s why AB Tasty stands out as the best choice for teams ready to go further.
1. Built for Everyone: Usability That Empowers Your Whole Team
Your team shouldn’t need a developer for every test.
AB Tasty’s visual editor and theme builder work for everyone—whether you’re a marketer launching your first campaign or a developer building complex experiments. Our intuitive interface means less time wrestling with code and more time testing bold ideas.
Real autonomy, real speed.Teams choose AB Tasty because their previous platform kept them dependent on developers for basic changes. With AB Tasty, they launched campaigns faster and gave their marketing team the independence they needed to iterate quickly.
Widgets that work, right out of the box. Our widget library comes from 12+ years of real-world testing. These aren’t just features—they’re battle-tested components that help teams launch more campaigns with confidence. While newer platforms struggle with bugs and limitations, our widgets deliver reliability when you need it most.
The result? Teams report launching more experiments, faster, with fewer roadblocks.
2. Honest Pricing: What You See Is What You Get
No surprise costs. No hidden fees. Just transparent value.
What starts as your solution stays your complete solution—no extra charges for essential features down the line.
Predictable partnerships. Many platforms lure teams in with low initial costs, then surprise them with steep price increases or essential features locked behind add-ons. We believe in honest pricing from day one, so you can plan your growth without budget surprises.
Long-term value that makes sense. When you calculate total cost over time—including all the features you’ll actually need—AB Tasty delivers better value. We’re smarter for the long haul.
Our CSMs are dedicated to helping you win, not upselling you. They’re your advocates, your strategic partners, and your go-to team for navigating complex challenges. No conflicts of interest, no hidden agendas—just genuine support.
Local expertise when you need it. Whether you’re based in the UK, France, or anywhere else we serve, you get local support that understands your market, your timezone, and your specific needs. Responsive, knowledgeable, and always ready to help.
Technical reliability you can count on. We handle complex environments—React, SPAs, multi-brand setups—with confidence. Teams praise our ability to navigate technical challenges that trip up other platforms. When your setup is complicated, we make the solution simple.
4. Technical Excellence: Speed, AI, and Innovation That Works
The fastest tag performance in the industry. Speed matters. Our script loads at 482ms—significantly faster than major competitors. That means better user experience, higher conversion rates, and tests that don’t slow down your site.
AI that’s transparent and ready now. Our Engagement Level and EmotionsAI aren’t black boxes or future promises—they’re transparent, advanced tools you can use today. While others demo concepts, we deliver production-ready AI that helps you understand and optimize for real user behavior.
Built for modern web experiences. Single Page Applications and dynamic content work out-of-the-box with AB Tasty. No manual workarounds, no technical debt—just seamless experimentation on the modern web.
5. Proven Reliability: Trust Built Over Time
Platform stability when it matters most. Experimentation requires trust—in your data, your results, and your platform. We deliver consistent reliability while others struggle with bugs, lost test goals, and API limitations that disrupt your work.
Recognition from the experts. Industry analysts consistently recognize AB Tasty for experiment design, pricing flexibility, community support, and market presence. But the real validation comes from our customers—teams who’ve switched to us and never looked back.
Real client wins, real results. Multiple teams have moved from other platforms to AB Tasty for better usability, superior support, and genuine value. They stay because we help them accomplish more together.
The Best Choice for Teams Ready to Go Further
What makes AB Tasty the best digital optimization partner isn’t just one thing—it’s how everything works together. Intuitive tools that empower your whole team. Transparent pricing that respects your budget. Support that genuinely cares about your success. Technical excellence that delivers results. And proven reliability you can count on.
We’re not just another platform. We’re your collaborators, your advocates, and your partners in every bold test you want to try.
Other tools might promise quick wins or flashy features. We deliver something better: a partnership that grows with you, technology that works when you need it, and a team that believes in your potential.
Try, learn, iterate—then go again. That’s how teams grow, and that’s how we help you get there.
Ready to experience the difference? Let’s build something better—together.
If you’ve ever wondered what to test next, struggled to get developer time, or felt overwhelmed by reporting dashboards, you’re not alone.
These are the frustrations experimentation teams face daily. That’s why we built AB Tasty AI—a suite of AI designed not to add hype to your workflow, but to genuinely help you move faster, test smarter, and get real business impact from your experimentation program.
With AB Tasty AI, those roadblocks disappear. Our AI guides you through ideation, building, personalization, and analysis—so you can focus less on the “what ifs” and more on the results that matter.
Let’s walk through how it works.
AI that crushes your “We’re guessing what to test next” problem
Step 1: Ideation generation
Every experimentation program begins with the same hurdle: what should we test next?
In many organizations, idea generation depends on gut feelings or endless whiteboard sessions that rarely produce actionable outcomes. That’s where AB Tasty AI steps in.
Our platform scans your pages and surfaces data-backed test ideas that are proven to make an impact. Instead of guessing, you get a prioritized list of opportunities aligned with your business goals. It’s like having an intelligent co-pilot who not only brainstorms with you but also brings evidence to the table.
AI that eliminates your “Our hypotheses are hunches” frustration
Step 2: Develop a hypothesis
A test idea is only as strong as the hypothesis behind it. Yet many teams struggle to move from fuzzy thinking to clear, structured hypotheses with measurable objectives.
AB Tasty AI eliminates the guesswork by helping you sharpen your hypotheses. You can turn casual “what if we tried this?” conversations into formal statements that define the change, predict the impact, and set up the right metrics for evaluation.
This structured approach not only improves your test quality but also boosts team confidence and stakeholder trust.
AI that annihilates your “I can’t build what I’m thinking” roadblock
Step 3: Start building
One of the biggest blockers in experimentation is the dependency on developer resources. Great ideas often languish in backlogs because the dev team is focused on other priorities.
With AB Tasty AI, you can instantly transform ideas into buildable experiments—no coding required. Whether you want to tweak a button, test a new layout, or launch a more complex variation, our AI makes it possible to build, preview, and launch without waiting weeks for a developer.
This shift not only accelerates testing velocity but also democratizes experimentation, empowering marketers, product managers, and designers to run with their ideas.
AI that ends your “Our personalization feels robotic” paralysis
Step 4: Understand your audience
Many brands struggle with personalization that feels forced, generic, or robotic. Visitors sense it, and the results often disappoint.
AB Tasty AI introduces EmotionsAI Insights, giving you a window into the emotional triggers that shape customer behavior. Instead of relying only on demographic or behavioral data, you get deeper visibility into what truly motivates your audience.
It’s personalization with empathy—designed to feel natural, human, and meaningful.
AI that solves your “I don’t know why visitors convert” mystery
Step 5: Personalize the customer journey
Understanding emotional drivers is just the start. With EmotionsAI Segments, you can act on those insights by creating experiences tailored to specific motivations.
For example, one group of visitors might be motivated by security and reassurance, while another thrives on novelty and excitement. AB Tasty AI combines emotional, behavioral, and contextual data to reveal these distinctions, allowing you to craft experiences that resonate at a deeper level.
The result? More conversions, stronger loyalty, and a customer journey that feels less like a funnel and more like a personalized conversation.
AI that crushes your “I don’t understand this report” problem
Step 6: Analyze your reports
Once experiments are running, the next challenge is often reporting. Traditional dashboards can be dense, and interpreting results takes time—especially if stakeholders want quick answers.
AB Tasty AI simplifies the process with natural language analysis. You can ask plain-English questions like “Which variation performed best with mobile visitors?” and get clear, actionable answers instantly.
This not only saves hours of manual analysis but also democratizes data, empowering non-technical teams to explore results with confidence.
Why AB Tasty AI Stands Out
The market is full of AI solutions, many of which promise more than they deliver. AB Tasty AI is different. We’ve designed it to remove the real blockers experimentation teams face every day:
No more guessing what to test
No more hunch-based hypotheses
No more dev backlog bottlenecks
No more robotic personalization
No more confusing reports
No more lost learnings
In short, AB Tasty AI moves your experiments from start to success.
FAQs about AI in digital experimentation
What type of AI does AB Tasty offer?
AB Tasty offers practical, experimentation-focused AI that supports the full testing journey. This includes AI for idea generation, hypothesis creation, no-code experiment building, emotional personalization (EmotionsAI), natural language reporting, and more.
How does AB Tasty AI help with personalization?
AB Tasty AI uses EmotionsAI to uncover visitor motivations and segment audiences based on emotional, behavioral, and contextual data. This allows businesses to create experiences that feel more human and relevant.
Can AB Tasty AI help non-technical teams run experiments?
Yes. AB Tasty AI empowers marketers, product managers, and designers to launch tests without relying on developers, thanks to its no-code experiment builder.
What makes AB Tasty AI different from other AI solutions on the market?
AB Tasty AI is designed to deliver practical, business-ready solutions. While many AI tools focus on hype, AB Tasty AI helps teams move from “what if” to “what works” by providing tangible results at every stage of the experimentation cycle.
If you’ve ever run an A/B test, you know the thrill of watching those numbers tick up and down, hoping your new idea will be the next big winner. But behind every successful experiment is a secret ingredient: the statistical model that turns your data into decisions.
With so many options – Bayesian, Frequentist, CUPED, Sequential – it’s easy to feel like you’re picking a flavor at an ice cream shop you’ve never visited before. Which one is right for you? Let’s dig in!
The Scoop on Statistical Models
Statistical models are the brains behind your A/B tests. They help you figure out if your shiny new button color is actually better, or if you’re just seeing random noise. But not all models are created equal, and each has its own personality – some are straightforward, some are a little quirky, and some are best left to the pros.
Bayesian Testing Model: The Friendly Guide
Imagine you’re asking a friend, “Do you think this new homepage is better?” The Bayesian model is that friend who gives you a straight answer: “There’s a 92% chance it is!” Bayesian statistics use probability to tell you, in plain language, how likely it is that your new idea is actually an improvement.
Bayesian analysis works by updating what you believe as new data comes in. It’s like keeping a running tally of who’s winning the race, and it’s not shy about giving you the odds. This approach is especially handy for marketers, product managers, and anyone who wants to make decisions without a PhD in statistics. It’s clear, actionable, and – dare we say – fun to use.
At AB Tasty, we love Bayesian. It’s our go-to because it helps teams make confident decisions without getting tangled up in statistical spaghetti. Most of our clients use it by default, and for good reason: it’s easy to understand, hard to misuse, and perfect for fast-paced digital teams.
Pros of Bayesian Testing:
Results are easy to interpret (“There’s a 92.55% chance to win!”).
Great for business decisions (and no need to decode cryptic p-values).
Reduces the risk of making mistakes from peeking at your data.
Cons of Bayesian Testing:
Some data scientists may prefer more traditional methods.
Can require a bit more computing power for complex tests.
Frequentist Testing Model: The Classic Statistician
If Bayesian is your friendly guide, Frequentist is the wise professor. This is the classic approach you probably learned about in school. Frequentist models use p-values to answer questions like, “If there’s really no difference, what are the chances I’d see results like this?”
Frequentist analysis is all about statistical significance. If your p-value is below 0.05, you’ve got a winner. This method is tried and true, and it’s the backbone of academic research and many data teams.
But here’s the catch: p-values can be tricky. They don’t tell you the probability that your new idea is better; they tell you the probability of seeing your data if nothing is actually different. It’s a subtle distinction, but it trips up even seasoned pros. If you’re comfortable with statistical lingo and want to stick with tradition, the Frequentist model is a good choice. Otherwise, it can feel a bit like reading tea leaves.
Pros of Frequentist Testing:
Familiar to statisticians and data scientists.
Matches legacy processes in many organizations.
Cons of Frequentist Testing:
Results can be confusing for non-experts.
Easy to misinterpret, leading to “false positives” if you peek at results too often.
CUPED Testing Model: The Speedster (But Only for the Right Crowd)
CUPED (Controlled Experiment Using Pre-Experiment Data) is designed to go fast by using data from before your experiment even started. By comparing your test results to users’ past behavior, CUPED can reduce the noise and help you reach conclusions quicker.
But here’s the twist: CUPED only shines when your users come back again and again, like on streaming platforms (Netflix) or big SaaS products (Microsoft). If you have an e-commerce site, CUPED can actually steer you wrong, leading to misleading results.
For most e-commerce teams, CUPED is a bit like putting racing tires on a city bike, not the best fit. But if you’re running experiments on a platform with high user recurrence, it can be a powerful tool in your kit.
Pros CUPED Testing:
Can deliver faster, more precise results for high-recurrence platforms.
Makes the most of your existing data.
Cons of CUPED Testing:
Not suitable for most e-commerce or low-frequency sites.
Can lead to errors if used in the wrong context.
More complex to set up and explain.
Sequential Testing Model: The Early Warning System
Sequential testing is your experiment’s smoke alarm. Instead of waiting for a set number of visitors, it keeps an eye on your results as they come in. If things are going south – say, your new checkout flow is tanking conversions – it can sound the alarm early, letting you stop the test and save precious traffic.
But don’t get too trigger-happy. Sequential testing is fantastic for spotting losers early, but it’s not meant for declaring winners ahead of schedule. If you use it to crown champions too soon, you risk falling for false positives – those pesky results that look great at first but don’t hold up over time.
At AB Tasty, we use sequential testing as an early warning system. It helps our clients avoid wasting time and money on underperforming ideas, but we always recommend waiting for the full story before popping the champagne.
Pros of Sequential Testing:
Helps you spot and stop losing tests quickly.
Saves resources by not running doomed experiments longer than necessary.
Cons of Sequential Testing:
Not designed for picking winners early.
Can lead to mistakes if used without proper guidance.
Which Statistic Model is Best for A/B Testing?
If you’re looking for a model that’s easy to use, hard to misuse, and perfect for making fast, confident decisions, Bayesian is your best bet – especially if you’re in e-commerce or digital marketing. It’s the model we recommend for most teams, and it’s the default for a reason.
If you have a team of data scientists who love their p-values, or you’re working in a highly regulated environment, Frequentist might be the way to go. Just be sure everyone’s on the same page about what those numbers really mean.
Running a streaming service or a platform where users log in daily? CUPED could help you speed things up – just make sure you’ve got the right data and expertise.
And if you want to keep your experiments safe from disasters, Sequential is the perfect early warning system.
Conclusion: The Right A/B Testing Model for the Right Job
Choosing a statistical model for A/B testing doesn’t have to be a headache. Think about your team, your users, and your goals. For most, Bayesian is the friendly, reliable choice that keeps things simple and actionable. But whichever model you choose, remember: the best results come from understanding your tools and using them wisely.
Ready to run smarter, safer, and more successful experiments? Pick the model that fits your needs—and don’t be afraid to ask for help if you need it. After all, even the best chefs need a good recipe now and then.
Running hundreds of experiments each year is a sign of a mature, data-driven organization – but it also comes with challenges.
How do you ensure that every test is running smoothly, and that critical issues don’t slip through the cracks?
At AB Tasty, we’ve listened to our clients’ pain points and are excited to announce the launch of Experiment Health Check: a new feature designed to make experimentation safer, smarter, and more efficient.
The Challenge: Keeping Experiments Healthy at Scale
For leading brands running over 100 campaigns a year, experimentation is at the heart of digital optimization.
But with so many campaigns running simultaneously, manually checking reports every day to spot issues is time-consuming and inefficient. Worse, problems like underperforming variations or sample ratio mismatches (SRM) can go unnoticed, leading to lost revenue or inconclusive results.
Our Solution: Experiment Health Check
Experiment Health Check is an automated monitoring system built directly into AB Tasty. It proactively alerts you to issues in your experiments, so you can act fast and keep your testing program on track.
Key Features:
Automated Alerts: Get notified in-product (and by email, if you choose) when an experiment encounters a critical issue, such as:
Centralized Dashboard: Super-admins can view all alerts across accounts for a global overview.
Customizable Notifications: Choose which alerts to display and how you want to receive them.
Why It Matters
Proactive, Not Reactive: No more waiting until the end of a test or sifting through reports to find problems. Experiment Health Check surfaces issues as soon as they’re detected.
Saves Time: Focus on insights and strategy, not manual monitoring.
Peace of Mind: Most clients will rarely see alerts – only about 2% of campaigns encounter SRM issues – so you can be confident your experiments are running smoothly.
What’s Next?
Experiment Health Check is available to all AB Tasty clients as of June 2025.
Simply activate it in your dashboard to start benefiting from automated experiment monitoring. We’re committed to evolving this feature with more alert types and integrations based on your feedback.
What if you could describe your vision and watch it come to life? What if understanding your visitors’ emotions was as simple as a 30-second scan? What if your reports could tell you not just what happened, but why it mattered?
That’s where AI steps in – not to replace your creativity, but to amplify it.
At AB Tasty, we’ve built AI tools that work the way teams actually think: curious, collaborative, and always moving forward. Here are nine features that help you test bolder, learn faster, and connect deeper with the people who matter most.
Insight: If you’re already an AB Tasty customer, you’ve already got access to some of our most popular AI features! But don’t stop scrolling yet, there’s more to discover.
1. Visual Editor Copilot: Your vision, our AI’s creation
Visual Editor Copilot turns your ideas into reality without the endless clicking. Just describe what you want – “make that button green,” “add a fade-in animation,” or “move the CTA above the fold” – and watch our AI bring your vision to life.
No more wrestling with code or hunting through menus. Your creativity leads. Our AI follows.
EmotionsAI Insights gives you a free peek into 10 emotional profiles that reveal what your visitors actually feel. Not just what they click – what moves them.
See the missed opportunities hiding in plain sight. Understand the emotional drivers that turn browsers into buyers. It’s personalization that goes beyond demographics to tap into what people really want.
3. Engagement Levels: Segment traffic for affinity and engagement
Our engagement-level segmentation uses AI to cluster visitors based on how they connect with your site. New visitors get the welcome they deserve. Returning customers get the recognition they’ve earned.
It’s traffic segmentation that makes sense – grouping people by affinity, not just attributes.
4. EmotionsAI: The future of personalization
EmotionsAI is personalization with emotional clarity. In just 30 seconds, see what drives your visitors at a deeper level. Turn those insights into targeted audiences and data-driven sales.
Your visitors have unique needs and expectations. Now you can meet them where they are – emotionally and practically.
5. Recommendations and merchandising
Recommendations and Merchandising turns the right moment into new revenue. Our AI finds those perfect opportunities to inspire visitors – whether it’s a complementary product or an upgrade that makes sense.
You stay in control of your strategy. AI accelerates the performance. The result? A delightful experience that drives higher average order value.
6. Content Interest: No more struggling to connect
Content engagement AI identifies common interests among your visitors based on their browsing patterns – keywords, content, products. Build experiences that feel personal because they actually are.
It’s not about pushing content. It’s about finding the connections that already exist and making them stronger.
7. Report Copilot: Meet your personal assistant for reporting
Report Copilot is your personal assistant for making sense of data. It highlights winning variations and breaks down why they drove transactions – so you can feel confident in your next move.
No more staring at charts wondering what they mean. Get clear insights that move you forward.
8. Drowning in feedback? Feedback Analysis Copilot saves you time
Feedback Analysis Copilot takes the heavy lifting out of NPS and CSAT campaigns. Our AI analyzes responses right within your reports, identifying key themes and sentiment trends instantly.
High volumes of feedback? No problem. Get the insights you need without the manual work that slows you down.
9. Struggling to craft the perfect hypothesis for your experiments?
Hypothesis Copilot helps you craft experiments that start strong. Clear objectives, richer insights, better structure – because every great test begins with a rock-solid hypothesis.
No more struggling with the “what if” – start testing with confidence.
AI That Amplifies Human Creativity
These aren’t just features – they’re your teammates. AI that understands how teams really work: with curiosity, collaboration, and the courage to try something new.
Every tool we build asks the same question: How can we help you go further?
Whether you’re crafting your first experiment or your thousandth, these AI features meet you where you are and help you get where you’re going. Because the best optimization happens when human insight meets intelligent tools.
Ready to see what AI-powered experimentation feels like? Let’s test something bold together.
FAQs about AI in digital experimentation
How is AI used in digital experimentation and A/B testing?
AB Tasty offers clients multiple AI features to enhance A/B testing by automating test setup, analyzing emotional responses, segmenting audiences, and generating data-driven recommendations—all aimed at faster insights and better personalization.
What are the benefits of using AI in website optimization?
AI reduces guesswork, accelerates testing, improves personalization, and turns raw data into actionable insights. It empowers teams to learn faster and create better digital experiences.
How does AI help marketing and product teams test and learn faster?
AB Tasty empowers marketing and product teams with AI tools like Report Copilot and Hypothesis Copilot to streamline data analysis and test planning, helping teams move from idea to iteration quickly and confidently.
What AI features does AB Tasty offer for experimentation and personalization?
AB Tasty offers features like Visual Editor Copilot, EmotionsAI, Content Interest segmentation, and Report Copilot to streamline testing, personalization, and reporting.
