In today’s digital landscape, data-driven choices are essential for staying competitive, with experimentation as a critical driver of innovation. To support this, we recently hosted a webinar with experts from Google Cloud and AdSwerve, focusing on how Google Analytics 4 (GA4) and BigQuery can enhance experimentation strategies. GA4 is essential for all marketing teams, providing advanced analytics that, when combined with BigQuery’s data consolidation capabilities, enables more effective testing, personalization, and digital optimization.
Meet the panel
Taige Eoff, Cloud Data AI Lead at Google, has been at Google for twelve years, leading data and AI initiatives for cloud marketing. Taige focuses on developing scalable solutions that support partners like AB Tasty and AdSwerve in optimizing digital experiences.
Alex Smolin, Senior Optimization Manager at AdSwerve, brings extensive experience in media, data, and technology. As a certified Google Premium Partner, AdSwerve provides data-driven brands with solutions ranging from A/B testing to advanced analytics.
Mary Kate, our roundtable host and Head of Growth Marketing for North America at AB Tasty, leads efforts to help companies create impactful digital experiences through AB Tasty’s suite of experimentation, personalization, product recommendations, and site search tools.
AB Tasty’s integration with GA4 & BigQuery
Connecting AB Tasty with GA4 gives marketing teams insights into visitor behavior through advanced analytics on CPA, conversion rate, bounce rate, SEO, and traffic. This integration allows teams to use data from either tool to measure the impact of experiments pre- and post-rollout, generating data-backed hypotheses and fostering innovation.
Google BigQuery, a fully managed cloud data warehouse solution, offers rapid data storage and analysis at scale. With its serverless, cost-effective structure, BigQuery allows businesses to analyze large datasets efficiently, making it easier to make well-informed decisions.
With Google BigQuery, users can effortlessly execute complex analytical SQL queries and leverage built-in machine-learning capabilities.
Why is data from GA4 foundational to any CRO program?
In experimentation, data is the catalyst that drives actionable insights. Data flows in from multiple sources, and businesses generate detailed reports by working with partners to integrate tracking and tagging. But the question then becomes: what comes next? That’s where experimentation enters. Using data from tools like GA4, teams can transform hypotheses into tests, uncovering which changes impact user engagement or conversions most effectively.
GA4’s role extends further by providing a consistent framework for testing across platforms. When integrated with BigQuery, GA4 allows teams to cross-reference test outcomes with other data points, revealing not just what worked but why it worked. As Alex noted, “We gather good data, run good tests, and then verify results across disparate sources like BigQuery to see if what we tested had the expected downstream impact.”
Data accessibility and agility are also important. Trends evolve quickly, with viral content or market shifts requiring rapid adaptability. “Having partners like Google, with all data in one place, and a platform like AB Tasty, where experiments can be quickly set up, is essential for staying competitive” Alex emphasized.
“Having partners like Google, with all data in one place, and a platform like AB Tasty, where experiments can be quickly set up, is essential for staying competitive.”
Alex Smolin, Senior Manager Optimization at Adswerve
How BigQuery powers scalable experimentation
With the growing volume of data, businesses need a way to consolidate and interpret it to drive impactful decisions. BigQuery, as Taige explained, is a robust cloud warehouse that streamlines data for meaningful insights, making it a key player in the experimentation ecosystem.
“Think of BigQuery as a filing cabinet for your organized data,” Taige noted. By consolidating disparate data sources, teams can create a unified view that informs testing and optimization efforts. Through this approach, tools like GA4 and BigQuery enable accurate decision-making that scales with the business. With BigQuery as the backbone, AB Tasty and AdSwerve can build on this structure to optimize user experiences through precise experimentation.
Beyond just data storage, BigQuery integrates with various Google Cloud tools and supports a wide range of use cases—from standard reporting to advanced machine learning. For marketers, this means fewer technical bottlenecks and quicker access to the data needed to stay agile. As Taige explained, “You may not need deep technical skills to access BigQuery’s benefits; the right partnerships and data structure can give you a powerful, accessible foundation.”
Leveraging BigQuery’s built-in AI and machine learning models
BigQuery offers an array of AI models for specific use cases—from translation and personalization to customer segmentation. These models add value by automating processes, such as localization or customer behavior prediction, allowing for smoother, more targeted marketing.
BigQuery’s flexibility means that companies can incorporate custom or third-party models, ensuring compatibility with a variety of AI solutions. This adaptability helps organizations innovate and iterate on experimentation programs, expanding what they can achieve with data.
Simplifying data access for marketing efficiency
For marketing teams, BigQuery’s role as a centralized data hub allows seamless data consolidation from platforms like Google Ads, Salesforce, and GA4. This integration ensures that marketers aren’t slowed down by fragmented data sources, freeing them to focus on insights and execution. As Taige highlighted, “The peace of mind that BigQuery provides comes from knowing that all data is consolidated and accessible, allowing teams to be nimble and creative.”
With BigQuery, marketers can view performance metrics, analyze customer journeys, and refine strategies—all within a unified environment. This lets teams optimize campaigns in real time as new data insights emerge.
Next-Generation capabilities enabled by Google Cloud
Looking ahead, digital is paving the way for more advanced experimentation capabilities. The conversation shifts to AI and machine learning, bringing new opportunities for personalization and optimization. As Mary Kate pointed out, while AI-driven insights can revolutionize customer experiences, many brands are still years away from realizing the full potential of these tools.
True value will come not from adopting every new tool but from understanding the foundational data supporting AI and asking the right questions about how these technologies can serve customer needs. Taige added, “If you don’t have a data strategy, you won’t have an AI strategy.” While AI amplifies data power, it requires organized, high-quality data to work effectively.
By consolidating and centralizing data through BigQuery, teams gain real-time insights and can make informed decisions. This data foundation enables the current wave of omnichannel strategies and sets the stage for future AI applications. Businesses that adopt this holistic approach—consolidating data, optimizing channels, and preparing teams for AI—will unlock new experimentation opportunities and drive impactful customer experiences.
With GA4 and BigQuery, businesses have the tools to streamline data consolidation and power next-generation experimentation. Ready to join your data and experimentation? Discover how AB Tasty can help bring data-driven optimization to life.
In the vast and competitive world of e-commerce, simply having great products isn’t enough. Your online store is like a stage, and how you present your products can make or break the show. Enter e-merchandising—the art and science of guiding your customers through a shopping journey that’s as smooth as silk and as engaging as a blockbuster movie.
Whether you’re looking to captivate first-time visitors or inspire returning customers, the right merchandising strategies can transform your site from a digital storefront into an experience that keeps customers coming back for more.
Ready to dive in? Here are five e-commerce merchandising strategies, with real-world examples, to help you create a shopping experience that truly shines.
1. Branding and Homepage Messaging: Your Digital First Impression
“Don’t judge a book by its cover” is a great mantra to apply to our personal lives, however, this proverb doesn’t apply to the e-commerce world.
Your homepage is more than just a landing page—it’s the welcome mat to your online store, and it needs to speak volumes. From the moment someone lands on your site, they should know who you are, what you stand for, and how you can make their life better.
Why it matters:
First impressions count. A compelling homepage can turn curious browsers into engaged shoppers.
Returning visitors want to see something fresh and relevant, not the same old same old.
Pro tips:
Tell your story boldly: Your brand story should be front and center. Use a powerful tagline or headline that captures your essence.
Test, test, test: Use A/B testing to find out what messaging resonates most with your audience.
Show, don’t tell: Include social proof like testimonials and customer reviews to build instant credibility.
Real-world example: Homepage
JOTT, a French clothing retailer, noticed that their homepage was experiencing a higher bounce rate than expected. Realizing that first impressions were crucial, they ran a no-code A/B test using AB Tasty’s experience platform to see if rearranging the homepage layout would improve engagement.
By moving product categories to the above-the-fold section and pushing individual product displays lower down, they achieved a 17.5% increase in clicks on the product category blocks. This optimization reduced bounce rates and guided more users deeper into their shopping journey, enhancing overall engagement.
2. Group Merchandise into Collections: Curate Like a Pro
Ever walked into a store and felt overwhelmed by choice? The same thing can happen online. Grouping your products into well-thought-out collections can turn chaos into clarity, making it easier for customers to find what they’re looking for—and maybe even discover something they didn’t know they needed.
Why it matters:
Curated collections simplify the shopping experience, helping customers quickly find what they’re after.
They also encourage customers to explore more, potentially increasing their basket size.
Pro tips:
Get creative with collections: Don’t just stick to the basics. Think outside the box—consider seasonal themes, trending items, or even influencer picks.
Use data wisely: Analyze purchase patterns to create collections that reflect what customers are actually buying.
Spotlight special collections: Use banners or pop-ups to draw attention to limited-time offers or new arrivals.
Real-world example: Collections
Balibaris, a leading French men’s fashion brand, revamped its e-commerce strategy by intelligently reorganizing its product displays to better match customer preferences and behavior. By dynamically sorting products and emphasizing best-sellers and seasonal items, Balibaris saw a significant increase in conversion rates compared to the previous year, even without special promotions. This strategic move not only enhanced the online shopping experience but also boosted overall sales while freeing up the digital team to focus on more impactful projects.
3. Showcase Products with Visual Merchandising: Let Your Images Do the Talking
In the world of e-commerce, a picture is worth a thousand clicks. Visual merchandising isn’t just about slapping up a few product photos; it’s about creating an emotional connection that makes customers want to reach through the screen and grab that item. High-quality images, videos, and even virtual try-ons can bring your products to life and help customers see how they’ll fit into their lives.
Why it matters:
Stunning visuals can make or break a sale. They help customers imagine the product in their own lives.
Lifestyle images and videos build an emotional connection, making customers more likely to hit “Add to Cart.”
Pro tips:
Go high-def: Invest in top-notch photography that shows your products from every angle.
Tell a story: Use lifestyle images or videos to show how your products can be used in real life.
Mix it up: Consider adding videos or 360-degree views to give customers a more immersive experience.
Real-world example: Visual Merchandising
Galeries Lafayette, one of France’s most iconic department stores, sought to enhance the online shopping experience by testing the impact of different product image styles. They compared standard packshot images to premium images featuring models wearing the products.
The results were striking: the premium images not only increased clicks by 49% but also boosted the average order value (AOV) by €5.76, adding a potential €114,000 in profit. This shift towards higher-quality visuals resonated with customers, leading Galeries Lafayette to prioritize premium images across their site, significantly improving user engagement and sales.
4. Implement Effective Site Search: Help Shoppers Find Their Perfect Match
When a customer knows what they want, nothing should stand in their way—especially not a clunky search function. A well-oiled site search is like a personal shopper, helping customers find exactly what they’re looking for, faster.
Why it matters:
Customers who use search are often more ready to buy, so it’s crucial that they find what they’re looking for quickly and easily.
An effective search can turn casual browsers into buyers by surfacing relevant products.
Pro tips:
Optimize filters & facets: Let customers narrow down their search results with relevant filters like size, color, and price.
Smart error detection: Make sure your search can handle typos and synonyms—because we all make mistakes.
Autocomplete magic: Help customers out by suggesting popular search terms as they type.
Never show a dead end: Avoid zero-results pages by offering suggestions or related products instead.
Real-world example: Site Search
VAN GRAAF, an international fashion retailer, recognized the need to elevate their online search functionality to meet the high standards of their physical stores. By integrating AB Tasty, VAN GRAAF significantly improved the customer journey on their e-commerce site. The results were impressive: online orders from search increased by 30%, conversion rates rose by 16%, and the average order value (AOV) saw a 5% boost. Additionally, the share of sales from search grew by 4.3%. This transformation not only enhanced the shopping experience but also reduced the time the team spent managing search functionalities, allowing them to focus on other critical optimizations.
5. Cross-Sell and Up-Sell Products in Your Shopping Cart: The Power of Suggestion
You’ve done the hard work of getting a product into a customer’s cart—now’s your chance to suggest a few more. Cross-selling and up-selling are subtle yet powerful ways to increase the value of each sale by offering customers items that complement what they’ve already chosen.
Why it matters:
Personalized recommendations can boost your average order value and make customers feel like you really “get” them.
It’s a win-win—customers discover more great products, and you see a bump in sales.
Pro tips:
Personalize everything: Use AI to suggest products based on what’s already in the cart or what similar customers have bought.
Bundle it up: Show products that are frequently bought together as a bundle to encourage more sales.
Test placement: Experiment with where you place these suggestions—product pages, the shopping cart, or even during checkout.
Real-world example: Cross-sell and Up-sell
Figaret, a high-end French shirtmaker, significantly boosted its online sales by integrating personalized product recommendations. By strategically placing recommendation blocks on product pages and in the shopping cart, Figaret achieved remarkable results: 6% of visitors used these recommendations, contributing to 10% of the site’s total revenue. Additionally, these users spent on average 1.8 times more than those who didn’t engage with the recommendations. This approach not only enhanced customer engagement but also drove substantial revenue growth.
Measuring Success in E-merchandising: Are You Hitting the Mark?
You’ve put in the work, but how do you know if your e-merchandising strategies are actually working? Measuring success isn’t just about looking at sales numbers; it’s about understanding how each element of your strategy contributes to the bigger picture.
Key Metrics to Watch:
Website traffic: Keep an eye on where your visitors are coming from and what they’re doing on your site.
Conversion rate: This is the percentage of visitors who actually make a purchase—one of your most important metrics.
Sales data: Analyze overall sales, average order value, and revenue from specific merchandising strategies.
Average basket size: Track how many items customers are purchasing per transaction to gauge the effectiveness of your cross-selling and up-selling efforts.
Pro tips:
Set benchmarks: Compare your metrics against industry standards to see where you stand.
Use analytics tools: Platforms like Google Analytics or Matomo can give you insights into how visitors interact with your site.
Keep iterating: Don’t settle for good—strive for better. Regularly review your data and tweak your strategies to keep improving.
Conclusion: Trial and Better—The Heart of E-Merchandising Strategies
E-commerce merchandising isn’t a “set it and forget it” task—it’s a continuous journey of trial, error, and improvement. The best strategies evolve over time as you learn more about your customers and the market. So don’t be afraid to experiment, take risks, and, most importantly, keep pushing for better. Every tweak, test, and change you make is a step towards creating an online store that not only meets but exceeds customer expectations.
Ready to take your e-commerce merchandising to the next level? Download our comprehensive guide on e-merchandising best practices or schedule a free demo with AB Tasty today. Your journey to better starts now.
For e-commerce success, added revenue from existing customers can be more efficient than constantly pursuing new ones. Returning buyers are a vital piece of this strategy. We recently sat down with industry experts to discuss how optimizing customer experiences can drive upselling and cross-selling opportunities. They shared practical approaches for boosting average order value (AOV) while nurturing customer loyalty and retention.
Our speakers, each experts in testing, optimization, and conversion rate, provided insights into how brands can increase revenue through personalized, thoughtful customer engagement.
Meet the experts
Nicole Story: Co-Founder & Director at Hookflash Analytics, leading experimentation in testing, optimization, and personalization.
Gerred Blyth: Chief Product Officer at Giftory, with a background in interaction design and e-commerce.
In this article, we’ll explore actionable strategies from the webinar to help you personalize to existing customers and drive growth through upselling and cross-selling—not just new customer acquisition.
1. Optimizing the cart for upsells
Upselling at the cart and checkout stages can significantly increase AOV, but it requires a carefully planned approach. As Colette Carlson explains: “Before implementing anything, it’s crucial to understand how you’re going to measure success and ensure that your conversion rate is solid. When it comes to the cart and checkout process, if those aren’t optimized, adding upsell and cross-sell strategies will only introduce more noise.” Shoppers who have reached the cart are already primed to convert, so it’s important not to disrupt their momentum with irrelevant or poorly timed offers.
“Before implementing anything, it’s crucial to understand how you’re going to measure success and ensure that your conversion rate is solid. When it comes to the cart and checkout process, if those aren’t optimized, adding upsell and cross-sell strategies will only introduce more noise.”
Collette Carlson, Director of Optimization at Astound Digital
Coordination with internal teams is also important when designing upsell strategies. For instance, if an upsell is introduced at checkout, the process should be seamless – will the original product be automatically removed from the cart if the customer selects an upgrade, or will they need to make the changes manually? Likewise, if you’re offering a bundle or cross-sell, is your system prepared to handle it without disrupting the customer experience?
Effective upsell offers are relevant to the customer’s purchase. Suggesting complementary items or upgrades can boost AOV, as 80%of consumers are more likely to complete their purchase with brands offering personalized experiences. From upsell testing experience at Giftory, Jared advises against pushing unrelated or overly expensive items, which can confuse or deter customers altogether.
Using product recommendation algorithms can streamline upselling. Automating this process ensures that customers receive relevant suggestions without the need for manual curation, creating a smoother experience for your team and the customer. AB Tasty’s product recommendation engine allows upsells based on several criteria, including most recent products, associated products, similar or more expensive items, complementary items, and top promotions.
2. Strategic product recommendations for cross-selling
To effectively cross-sell, brands must identify the right moment in the customer journey. If you offer relevant products at key points without disrupting the experience, similar to upselling. But first, establishing cross-selling metrics can lead to stronger effectiveness.
The primary metrics will vary depending on what you’re testing—whether it’s an algorithm change, a new carousel design, or a different recommendation format. There are some essential KPIs to consider:
Engagement: Track how often customers interact with cross-sell offers, such as clicks or add-to-basket rates.
Conversion rate: Measure how many customers who engage with offers complete their purchases.
Average order value (AOV): Gauge how effectively cross-sell strategies are increasing the total order value.
Items per order: Monitor if cross-sell efforts lead to additional products being added to the cart.
Overall revenue: This ultimate metric reflects the total impact of your cross-sell strategy.
Once these metrics are in place, refine your strategy by determining where cross-sell offers should appear. For example, adding a cross-sell option in the mini cart or as a pop-up at checkout can add complexity, so testing can help avoid disrupting the customer experience.
Testing cross-sell algorithms in action
Nicole Story shared a valuable example of testing product recommendation carousels. Inspired by Amazon’s success, many brands rushed to implement carousels on their websites, but forgot the importance of context. Placing multiple carousels on the homepage often leads to irrelevant suggestions and a poor experience.
Nicole’s team tested various algorithms by tailoring product recommendations to the customer’s journey. On product detail pages (PDPs), carousels that showed “related product suggestions” outperformed those with generic recommendations. The tests revealed that adjusting algorithms based on context and customer behavior was far more effective than placing standard carousels throughout the site.
As Nicole explains: “Simply introducing product recommendations and checking that box off the roadmap isn’t going to deliver real value. The key is continuous optimization and discovering what works across the entire customer journey—that’s where the real value lies.”
“Simply introducing product recommendations and checking that box off the roadmap isn’t going to deliver real value. The key is continuous optimization and discovering what works across the entire customer journey—that’s where the real value lies.”
Nicole Storey, Co-Founder & Director at Hookflash Analytics
Relevance is everything
Cross-sell strategies must be highly relevant to what the customer is already doing. As Gerred Blyth from Giftory mentioned, “We have high expectations as customers and irrelevant offers can break that trust.” Customers expect brands to know their preferences and behaviors, so it’s important that recommendations feel personalized and timely.
3. Experimentation and testing for long-term loyalty and CLV
Continuous experimentation is critical for building long-term customer loyalty and increasing customer lifetime value (CLV). Instead of relying on a single strategy, brands should constantly test and improve their approach. Colette points out that starting by analyzing existing order data can uncover natural cross-sell patterns. This provides valuable insights into which products are frequently purchased together.
For first-time visitors, bombarding them with upsell offers might backfire. Instead, let them become familiar with your brand and key products before introducing additional offers. In contrast, repeat customers may be more open to cross-sells that align with their previous purchases.
Upselling with product recommendations
According to our data a customized UX can boost revenue and increase basket size by up to 10%. Product recommendations can be seen as a form of personalization and, as our panel pointed out in the webinar, experimenting with different formats—such as carousels, quizzes, or other interactive tools—can help identify what resonates with your audience and drives engagement.
We use AI to analyze visitors’ site interactions and purchase behavior, delivering targeted recommendations, each with a specific goal. This means you can better understand which products to offer, to whom and when during the customer journey:
Product Page: Guide users to explore more products or categories.
Last Seen Products: Help users quickly resume their browsing.
Add to Cart: Encourage users to add complementary items to their basket.
Cart Page: Suggest additional items to increase order value.
Homepage: Showcase personalized content and help users navigate the site.
Our panel also discussed how different types of algorithms are necessary depending on your vertical. You can divide your algorithms into three distinct types and choose how you prioritize:
Convert: These recommendations would offer top sellers, top trending products, top converting products, top reviewed products etc.
Upsell: This could suggest most recent products viewed, associated products, similar products, compatible products etc.
Personalize: This could suggest last visited products, last bought products, user affinity or similar or associated to cart products
If you work for a beauty site, customers will replenish their favorite products, whereas home and decor might recommend accessories or similar products. While personalization drives relevance, maintaining control over the recommendation process means you can speak directly to your customer’s needs.
Giftory: fostering loyalty with timely engagement
Giftory is beginning to focus on lifetime customer value. Their approach involves using cross-sell and upsell strategies similar to a CRM initiative, introducing customers to a broader range of products both during and after their purchase. They gather data on why customers buy gifts, such as birthdays or anniversaries, and use that information to send timely product recommendations in the future.
By reaching out to customers at the right moment, such as 11 months after an anniversary purchase, Giftory can re-engage them with relevant offers without overwhelming them with constant promotions. This creates a personalized experience that encourages long-term loyalty and repeat business.
4. Subscription models for upsell and retention
Offering subscription products to upsell can improve both immediate revenue and CLV. The challenge is to find the right balance: How can you encourage customers to subscribe without overwhelming them, while also ensuring the offer feels relevant and valuable over time?
Before launching a subscription model, look at your data to understand customer behavior. Consider the difference between a one-time purchaser and a subscriber. While offering a small discount for subscribing may lower the initial AOV, the long-term benefits of recurring revenue from a loyal subscriber can make up for it.
Testing and data-driven strategy
Launching a subscription model requires more than just adding an upsell feature—it involves a data-informed approach. Starting small with a minimum viable product (MVP) allows you to test how customers respond and fine-tune the offering. Metrics like renewal rates, engagement, and overall CLV will help guide decisions about whether to scale the program.
As Gerred advises: “Walk before you run. Start with the first test—an MVP. It doesn’t have to be the final version you’ll roll out, but that initial test will help you understand the value and prove the benefits. From there, you can evolve and continuously improve. It’s easy to feel overwhelmed when you hear about advanced strategies and algorithms, but you don’t need to get there all at once.”
“Walk before you run. Start with the first test—an MVP. It doesn’t have to be the final version you’ll roll out, but that initial test will help you understand the value and prove the benefits. From there, you can evolve and continuously improve. It’s easy to feel overwhelmed when you hear about advanced strategies and algorithms, but you don’t need to get there all at once.”
Gerred Blyth, Chief Product Officer at Giftory
Offering personalized options, such as different subscription tiers or flexible renewal cadences (monthly, bi-monthly, quarterly), can make the experience more appealing to a wider range of customers. Testing, refining, and adapting based on customer feedback will ensure that the model evolves in a way that meets both business goals and customer expectations.
Wrapping up
Just as you approach CRO with care and precision, cross-selling and upselling require a high level of attention.
Upselling and cross-selling don’t have to be complex when you have the right tools and the right strategy. If you want the expert’s opinion – watch the webinar below:
In today’s mobile-first world, where smartphones dominate more than half of global web traffic, optimizing for mobile has never been more crucial. Mobile usage surpassed desktop in the US in 2022 and in the UK in 2023, signaling a clear shift in consumer behavior. Brands are now urged to design with mobile in mind first, adapting for desktop as needed, rather than the reverse. This shift may seem daunting for teams, but it’s a necessary evolution to meet the expectations of today’s users.
Whether your customers are researching products or making purchases, their mobile experience can make or break their journey with your brand. While it’s clear that more shopping is done on mobile devices than on desktop, the real question remains: how significant is mobile shopping overall? Today’s mobile-savvy consumer isn’t just using their device for convenience, but to blend their in-store and online shopping into one seamless experience. In fact, nearly 80% of shoppers globally use their smartphones to browse a retailer’s website while shopping in-store, and 74% use the store’s app. However, only 33% of consumers prefer making purchases on their phones, with 49% reporting a smoother experience on desktop or tablet. This highlights just how important it is for brands to enhance their mobile offerings for a seamless experience across all devices.
To delve into the complexities of mobile optimization Mary Kate, AB Tasty’s Head of Growth Marketing for North America, teamed up with Allie Tkachenko, a UI/UX Strategist at WPromote, for a webinar on mastering mobile. AB Tasty’s platform enables brands to deliver personalized customer experiences, while Wpromote helps design and optimize engaging web experiences that convert. They emphasize a key message: mobile optimization isn’t just about resizing for a smaller screen – it’s about creating an intuitive, seamless journey that aligns with today’s mobile-first consumer’s behaviors and expectations.
It’s critical that mobile websites excel in areas like speed, navigation, and user-friendliness. Let’s dig into three actionable strategies from the webinar to help your brand stay ahead and deliver an improved mobile experience for your customers.
1. Maximizing limited space
One of the biggest challenges in mobile design is maximizing limited screen space without overwhelming users. The key is to keep crucial content above the fold—on mobile, this means placing essential elements like navigation bars, CTAs, and product highlights in a prominent position, visible without scrolling. This is particularly important on search landing pages, the homepage, and other high-traffic areas. A well-organized and streamlined navigation system that helps users quickly find what they need can lead to higher engagement and reduced bounce rates.
While desktops offer ample space to break down navigation into detailed categories, mobile design requires a more simplified structure due to space constraints. Consider grouping categories under broader buckets like “Top Categories” or similar, allowing users to easily explore the site without feeling overwhelmed by too many options. Another key strategy is leveraging responsible design, such as implementing sticky navigation bars or menus that stay visible as users scroll. This approach, widely adopted across industries, ensures easy access to important links and minimizes the effort required to navigate the site.
AB Tasty in action
The UX team at Clarins wanted to make their product more visible on their category pages. In the original layout, filtering and sorting functions were stacked, removing space from the second row of products appearing. After testing a column layout for the filtering and sorting menus, the team saw a significant improvement—bounce rates decreased, and clicks to products increased by 34%.
The “Thumb Zone” refers to the area of the screen that is easiest for users to reach with their thumbs, typically the lower portion of the screen. Since most users interact with their phones one-handed, placing critical CTAs, buttons, and interactive elements within this zone is important for accessibility and ease of use.
Consider this: a navigation bar that starts at the top of the page but shifts responsively to the bottom as the user scrolls. This keeps it in an expected spot initially, avoiding any disruption to the user’s flow, and then moves it to a more reachable area as they continue browsing.
Another thing to keep in mind is sizing. Whether it’s buttons, images, form fields, or menu links, the size of these elements plays a huge role in usability. You can’t just shrink them to save space—you have to ensure they’re “tappable” so users can easily interact. While reachability is key, think about what doesn’t need to be within reach, like informational banners or logos. You can place those outside the thumb zone, saving prime space for interactive elements.
Brands that prioritize the thumb zone in their mobile designs see improved user engagement and lower frustration levels. This small shift can make a significant difference in usability and customer satisfaction.
AB Tasty in action
The team at Club Med, a leading travel and hospitality brand, observed that their original mobile site displayed a navigation bar at the top of the page, which would disappear as users scrolled down. To increase user engagement with different category offerings, they created a variation of the mobile homepage with a sticky navigation bar which remained at the bottom of the screen while scrolling.
The results of the A/B test revealed a 12% increase in click rates, a 12% increase in access to the transaction funnel, and a 2% decrease in the bounce rate for users showing the variation with the sticky navigation bar. This approach effectively makes information more physically accessible.
Optimizing the thumb zone
Bottom Navigation
Sizing
Reachability
3. Improving processes
Lengthy forms and cumbersome checkout processes are major obstacles to conversion in mobile digital experiences. Mobile users expect a seamless, fast journey, and frustration with complex forms often leads to abandoned carts. Streamlining these processes—especially form fills and checkouts—can reduce friction and improve conversions. We’ve all experienced the annoyance of having to redo a form, fearing progress might be lost, which can lead to users abandoning the process entirely. Key areas for optimization include simplifying checkout by offering guest checkout options and exploring one-click payment methods.
Search and product discovery also present unique challenges on mobile devices due to limited screen space. With condensed menus and site navigation, users often rely heavily on the search function. Optimizing your search results pages to help users quickly find specific products can drastically improve the user experience. The space constraints of mobile mean that every element, including search results, should guide users efficiently to what they’re looking for.
Lastly, page load speed plays a vital role in retaining users. A slow-loading site can deter users, leading them to abandon your site altogether. Reducing load times is crucial for keeping users engaged. Understanding your audience and continuously optimizing these processes will help ensure your site meets their needs and encourages conversions.
AB Tasty in action
Travel insurance company, DirectAsia, needed users to fill out a form to generate an insurance quote. The team observed that customers were not completing the forms as smoothly as expected. To address this, they implemented a variation in the test where bolded check marks appeared to validate each completed field. This change created a sense of progress for users as they navigated the form and alleviated any uncertainty about needing to go back to correct errors.
As a result of this test, DirectAsia achieved a 1.97% increase in quote generations and a 7.78% increase in transaction rates. By reassuring users throughout the form-filling process, DirectAsia successfully guided more customers through their quote generation form.
Optimizing mobile processes
Checkout
Search and discovery
Speed & image loading
Wrapping up
Mobile optimization is about much more than making your website look good on a smaller screen; it’s about crafting a seamless, user-friendly experience that enhances the customer journey. Whether you’re focusing on improving site speed, optimizing design for better accessibility, or streamlining complex processes, the suggestions above provide a solid foundation for mastering mobile optimization. By understanding the nuances of mobile behavior and catering to the needs of your users, your brand can create a frictionless experience that drives conversions and fosters customer loyalty.
Stay ahead in the mobile-first era by ensuring your website design and processes align with the expectations of today’s consumers. AB Tasty can help achieve this goal by providing innovative tools and data-driven testing to enhance your mobile strategy. As mobile usage continues to grow, so does the importance of providing a smooth, engaging, and conversion-focused experience.
If you want to get all the details. – watch the webinar below.
The future of digital experience optimization has arrived and it’s driven by AI.
Are you ready for it?
AI can often be a sensitive subject, as loud voices in the room will boast how AI can replace people, careers, or even entire sectors of society. We’re scaling back the dystopian imagery and instead finding ways where AI can be your sidekick, not a supervillain.
There are two sides to the coin with AI: it can help optimize your time and boost conversions, but it can also be risky if not used properly. We’ll dig into the ways AI can be a helpful tool, as well as some considerations to take.
The positive impact of AI on your customer experience roadmap
In one of our last pieces about AI in the CRO world, we discussed 10 generative AI ideas for your experimentation roadmap. Since the publication of this article, we’re back with even more ideas and concrete examples of successful campaigns.
1. Display reassurance messages to visitors who value it
Some shoppers value their privacy and data safety above all else. How can you comfort these visitors while they’re shopping on your website without interfering with other visitors’ journeys? While salespeople can easily gauge these preferences in face-to-face interactions, online shoppers deserve the same personalized experience when they shop independently.
Let’s see an example below of how you can enhance the digital customer experience for different shoppers at the same time:
MAAF, a French insurance provider, knows just how complex buying auto insurance can be for visitors. Some shoppers prioritize safety and reassurance messages, while others don’t. With AI systems that segment visitors based on emotional buying preferences, you can detect and cater to this type of profile without deferring to other shoppers. “Intuitive” profiles are receptive to reassurance messages, while “rational” profiles tend to see these extra messages as a distraction.
The team at MAAF used advanced AI technology to overcome this exact challenge. Once the “intuitive profiles” were identified, they were able to implement personalized messages ensuring their commitment to their customers’ data protection. As a result, they saw an increase of 4% in quote rates for those directed to the intuitive segmentation, and other profiles continued on their journey without extra messaging.
2. Segment your audience based on their shopping behavior
With so many online shoppers, how can you possibly personalize your website to give each shopper the best user experience? With AI-powered personalization software.
Some online shoppers have a need for competition. Don’t we all know someone who loves to turn everything into a competition? These “competitive” shoppers are susceptible to social-proof messaging and are influenced by the opinions of other customers while searching for the best product. One of the best ways to personalize a listing page for competitive shoppers is to show ratings from their peers.
Meanwhile, what works for competitive shoppers, will not work effectively for speedy shoppers. Shoppers with a need for immediacy will appreciate a clear, no-frills browsing experience. In other words, they don’t want to get distracted. Let’s look at the example below.
This website implemented two different segments targeting online shoppers with a need for “competition” and “immediacy.” These two segments brought in a 9% increase in conversion rates and a 2% increase respectively. The campaign was a success, but how did it work?
Using AB Tasty’s AI personalization engine, EmotionsAI, this online shop identified its visitors’ main emotional needs and directed them toward a product listing page best suited for them. EmotionsAI turns buyer emotions into data-driven sales with actionable insights and targeted audiences.
Want to learn more about EmotionsAI? Get a demo to see how AI can impact your roadmap for the better!
3. Automate and personalize your product recommendations
European backpack designer, Cabaïa, used an AI-powered recommendation engine to generate personalized recommendations for their website visitors based on user data collected. The team at Cabaïa previously managed product recommendations manually but wanted to shift their focus to improving the digital customer experience.
AI recommendation tools put the right product in front of the right person, helping boost conversions with a more tailored experience. Since implementing this AI-powered recommendation engine, they’ve had +13% revenue per visitor, increased conversions by 15%, and raised their visitor’s average cart size by 2.4%.
4. Innovate your testing strategy with emotional targeting
According to an online shopper study (2024), traditional personalization is no longer enough. Personalizing based on age, location, and demographics just isn’t as precise anymore.
The team at Groupama, a multinational insurance group, wanted to take A/B testing a step further and better adapt their approach to fit their customers’ unique emotional needs. By using an AI-powered emotional personalization engine, they were able to identify two large groups of website visitors: emotionals and rationals.
They created an A/B test based on these customer profiles. One variation catered to the “emotional” buyers by showing reassuring messaging on the insurance quote to protect their data, and the other catered to “rationals” that displayed the insurance quote without any extra messaging that allowed them to have a distraction-free buyer journey. Within 2 weeks, Groupama saw an instant win with a 10% increase in quote submissions.
5. Simplify the customer journey and build buyer confidence
Like many financial services, purchasing insurance is inherently complex. Consumer behaviors and expectations in insurance are quickly changing.
As a leading insurer in Singapore, DirectAsia has embraced innovative technologies to better serve their customers. By pioneering new technology, Direct Asia was able to segment their visitors based on emotional needs.
The team at DirectAsia identified that the ‘safety’ segment (buyers needing reassurance) was the top unsatisfied emotional need for visitors on both desktop and mobile devices. With these insights, DirectAsia ran an experiment on ‘safety’ visitors, displaying two banners to reassure them and move them further down the form to the quote page.
The banners led to + 10.9% in access to the quote page for one, and +15% in access to the quote page for the other.
The potential risks of AI on your customer experience roadmap
Artificial intelligence has been evolving (very quickly!) over the past few years and it can be tempting to run full speed ahead. However, it’s important to find the right AI that works for you and helps you achieve your goals. Is AI powering something you need, impacting your business, or is it just there to impress?
With that in mind, let’s consider some precautions to take while using AI:
Unfactual or biased information on data reports, website copy, etc.
When researching or asking for data sources, it’s important to keep in mind that artificial intelligence can get it wrong. Just as humans can make mistakes and have biased opinions, AI can do the same. Since AI systems are trained to produce information following patterns, AI can unintentionally amplify bias or discrimination.
Lack of creativity, dependence, and over-reliance
Excessive reliance on AI can reduce decision-making skills, creativity, and proactive thinking. In competitive industries, you need creativity to stand out in the market to capture your audience’s attention. Your roadmap could suffer if you put too much faith in your tool. After all, you are the expert in your own field.
Data and privacy risks
Protecting your data should always be a top concern, especially in the digital experience world. You will want a trusted partner who uses AI with safeguards in place and a good history of data privacy. With the fast-developing capabilities of AI, handling your data correctly and safely becomes a hurdle. As a general best practice, it’s best not to upload any sensitive data into any AI system – even if it seems trustworthy. As these systems often require larger quantities of data to generate results, this can lead to privacy concerns if your data is misused or stored inappropriately.
Hallucinations
According to IBM, AI hallucinations happen when a large language model (LLM) thinks it recognizes patterns that aren’t really there, leading to random or inaccurate results. AI models are incapable of knowing that their response can be hallucinogenic since they lack understanding of the world around us. It’s important to be aware of this possibility because these systems are trained to present their conclusions as factual.
Conclusion: Using AI in the Digital Customer Experience
As with any tool or software, AI is a powerful tool that can enhance your team – not attempt to replace it. Embracing the use of AI in your digital customer experience can lead to incredible results. The key is to be aware of risks and limitations, and understand how to use it effectively to achieve your business goals.
Welcome to a world where chocolate isn’t just a treat but an experience—a world crafted by Hotel Chocolat, a British group with nearly 31 years of rich history. At the heart of their journey lies a realization: loyalty isn’t bought with discounts—it’s earned through authentic connections and shared values.
Recently, they shared this ethos at the CX Circle event by Contentsquare featuring Mel Parekh, Head of E-commerce at Hotel Chocolat. Mel took the stage to unravel the complexities of customer loyalty—a subject that has never been more critical in the fast-evolving world of eCommerce. The discussion centered around how Hotel Chocolat has navigated the challenges of a changing world while staying true to its brand values using the power of experimentation.
The Secret Ingredient: Authenticity and Quality
Hotel Chocolat stands out in the chocolate industry for its commitment to authenticity and quality. While most chocolate brands are content to source their cocoa, Hotel Chocolat went all-in, growing their own on the lush Rabot Estate in Saint Lucia. This direct control over their supply chain ensures that they use only the highest quality ingredients while helping craft a brand that’s as genuine as the cocoa it cultivates.
Hotel Chocolat has witnessed a constant change in the e-commerce landscape. They’ve learned to adapt to these changes while staying true to their brand identity. One of their key initiatives has been to clearly define who they are as a brand and to create compelling reasons for customers to return to their site time and time again.
A Changing Landscape
It’s no secret that the world of eCommerce is in constant flux. Prices are rising across the board—from raw materials to operating costs—and the competition for customers is fiercer than ever. In this environment, retailers must do more with less, finding innovative ways to stand out.
As customers increasingly engage with various digital platforms and experiences, the range of choices available to them has become almost overwhelming. In this crowded marketplace, standing out from the competition requires more than just eye-catching design elements.
Moreover, the explosion of data in recent years has made it possible for even smaller companies to leverage insights that were once only accessible to larger players. However, the real challenge lies in capturing this data, interpreting it effectively, and, most importantly, implementing it in ways that drive meaningful results. Hotel Chocolat has embraced this data-driven approach, using insights to refine their strategies and create a more personalized experience for their customers with both Contentsquare and AB Tasty.
Building Lasting Relationships with Customers in a Phygital World
Loyalty is the cornerstone of Hotel Chocolat’s strategy in this new era. As a premium brand, they understand that their customers aren’t just looking for a product; they’re looking for an experience that resonates with their values and desires. This understanding has led Hotel Chocolat to focus on building a brand that not only meets customer expectations but exceeds them by offering a unique, personalized experience.
One of the key strategies they’ve implemented is their “phygital” approach, which blends the digital and physical worlds to create a more personalized, engaging shopping experience. This approach is centered on three key principles:
Instant: Reducing delay or lag to ensure a smooth customer experience.
Connected: Creating a more personal connection with each customer.
Engaging: Giving customers a sense of control over their shopping journey.
Make the Experience Personal
With over 120 different chocolate recipes, Hotel Chocolat faced this challenge: how do you help customers find the perfect product without overwhelming them? Their solution was gamification—a method that makes the shopping experience more fun and interactive. In Spring 2023, they launched the “Chocolate Love Match,” a quiz that matches customers to one of six flavor profiles. This not only narrows down the selection from 120 options to 20 or 30, making it easier to shop but also helps customers find the perfect gift for friends and family based on their flavor preferences.
The personalization doesn’t stop there.
Hotel Chocolat also leverages machine learning and tools like AB Tasty to improve their customer experience further. For instance, they’ve been experimenting with “Add to Bag” personalized recommendations. This initiative is crucial, especially as acquisition costs rise, making it more important than ever to maximize the value of each customer interaction.
Using AB Tasty, they tested two variations: one that showed products frequently bought together and another that displayed recently viewed items for easy access. Both approaches tested positively, resulting in a 5.31% increase in average order value and a 2.87% boost in revenue.
Embracing Data for Optimization
Hotel Chocolat has also focused on optimizing its digital presence, particularly their website. Working with AB Tasty, they undertook a redesign of their homepage, recognizing that the layout and user experience across devices play a critical role in customer engagement. The goal was to create a more visually appealing and intuitive experience that could better connect with customers online—especially when you can’t taste or smell the products.
The results speak volumes. By optimizing the homepage, they saw a 10% reduction in bounce rate, a 1.67% increase in visiting time, and significant improvements in conversion rates—up 0.54% overall and a substantial 7.24% on desktop. This uplift was largely due to better highlighting the most attractive elements on the homepage, such as category tiles that drive higher conversion and revenue.
Loyalty from a Brand Perspective
Mel Parekh left us with three takeaways for building a brand that stands the test of time:
Embracing Change: It shows that your brand is up-to-date and ready to adapt. Staying agile ensures that your brand remains relevant and continues to serve your customers, no matter the circumstances.
Listening and Understanding Customers: If loyal customers aren’t heard and understood, they’ll lose their preference for your brand and start considering others.
Sticking to Your Values: Clearly reward loyal customers for their loyalty, and make sure to differentiate between who is loyal and who isn’t.
Conclusion
Loyalty isn’t just about offering a great product; it’s about creating connections that resonate. Hotel Chocolat has perfected this recipe by blending their commitment to quality with a data-centric culture. Experimentation and data from AB Tasty have allowed them to be able to improve in all areas – whether that is personalization, gamification of their loyalty scheme, or the link between their online and physical shops. Experimentation has improved more than just their CRO but has helped define who they are and what they stand for.
Any marketer will tell you that Digital Optimization is crucial to ensure successful e-commerce operations and yield the best possible return on investment (ROI). This practice includes both A/B testing and website personalization: every website presents a unique set of features and designs, which must, in turn, be optimized through A/B testing.
Building a great website is, unfortunately, not simply a matter of following best practices. Even within a single industry, users will hold varied expectations based on your brand, communication style, target audience, funnel, etc. And while browsing the same website, users’ expectations can vary, with some knowing exactly what they want and others needing to explore, check your returns policy, learn about your sustainability initiatives, and so on.
We have all heard the hype about how AI has been revolutionizing how marketers approach experimentation. Generative AI offers new opportunities for optimizing every aspect of the user journey, allowing marketers to:
streamline testing,
create new online experiences,
and create new types of user segments for more precise personalized experiences that drive conversions.
This guest blog post was written by Rodolphe Dougoud, Project Lead at fifty-five—a leading data company that helps brands harness the potential of Generative AI and mitigate associated risks effectively with a comprehensive and pragmatic AI strategy, among other services.
Below, we’ll explore these three perspectives in depth, with real-life examples gleaned from AB Tasty’s new algorithm, Emotions AI, and fifty-five’s work with its clients around GenAI.
AI in Action for Experiences that Matter
Streamline testing
When thinking about A/B testing, you might immediately picture creating an experiment and launching it live on a website. However, the most time-consuming phases of the A/B testing process generally come before and after that: finding new features to try out in order to create a testing roadmap and analyzing the results of these tests. Here, AI can increase test velocity by helping to reduce bottlenecks hindering both of the aforementioned stages.
Test ideation
Your roadmap must not only be top-down but also bottom-up: pay close attention to insights from your UX designers, based on benchmarks from your competitors and industry trends, and data-driven insights based on your own analytics data. Here, AI can facilitate the process by analyzing large datasets (e.g., on-site Analytics data) to find insights humans might have missed.
Result analysis
Similarly, it’s essential to analyze the results of your tests thoroughly. Looking at one KPI can sometimes be enough, but it often represents only one part of a bigger story. An aptly-calibrated AI model can find hidden insights within your testing results.
While we generally know what data we want to access, the actual querying of that data can be time-consuming. Applying a GenAI model to your dataset can also allow you to query your data in natural language, letting the model pull the data for you, run the query, and create instant visualizations for major time gains.
Content creation
While not necessary for most tests, creating new content to be included in the testing phase can take a long time and impact your roadmap. While GenAI cannot produce the same quality of content as your UX team, a UX designer equipped with a GenAI tool can create more content faster. The model used can be trained with your design chart to ensure it integrates with the rest of your content. Overall, adding a GenAI tool as a complement to your design arsenal can yield substantial gains in productivity and, therefore, reinforce your testing roadmap timeline.
Create new online experiences
Marketers should not hesitate to experiment with AI to create unique and interactive experiences. Generative AI can create personalized content and recommendations that can engage users more effectively.
Consider, for instance, fifty-five’s recent work with Chronodrive, a grocery shopping and delivery app. We used AI to address a common user challenge (and, frankly, near-universal issue): deciding what to make for dinner.
With our innovative solution, taking a picture of the inside of your fridge will allow the app to create a recipe based on the ingredients it identifies, while a photo of a dish – taken at a restaurant or even downloaded from social media – will generate a recipe for said dish and its associated shopping list.
Artificial Intelligence opens new creative options that weren’t available with previous LLM models. Chronodrive’s solution may not be applicable to most companies, but every business can think back on their typical user’s pain points and conceptualize how GenAI could help ease them.
Create new types of user segments for more precise personalized experiences
When a customer enters a store, a salesperson can instantly personalize their experience by checking if they want to be helped or just want to browse, if they are discovering the brand or are already sold on it, if they require guidance or know precisely what they want… A website, on the other hand, necessitates extra effort to present the user with a similarly personalized experience.
Online, segmentation thus becomes indispensable to deliver the most satisfying user experience possible. Even during testing phases, deploying A/B tests on user segments makes achieving significant results more likely, as increased precision helps mitigate the risk of obtaining neutral results.
AI can analyze a wide array of user interactions on a given website to determine which elements drive the most conversions, or how different users respond to specific stimuli. This analysis can allow brands to classify users into new segments that could not have been available otherwise. For instance, fifty-five applied AI to split Shiseido’s website users between low and high-lifetime value segments. This allowed Shiseido to run differentiated A/B tests and personalize their website depending on the expected lifetime value of the user, resulting in a 12.6% increase in conversions.
Going even further, what if AI could read your emotions? AB Tasty’s new AI algorithm, Emotions AI, can automatically segment your audience into 10 categories based on emotional needs.
If a user needs to be reassured, the website can emphasize its free return policy
If they need clarity, the website can highlight factual information about your product
And if they need immediacy, the website can hide any unnecessary information to instead focus on its main CTAs
The model estimates the needs of the user by taking into consideration all of their interactions with the website: how long they wait before clicking, whether they scroll through an entire page, where their mouse hovers, how many times they click, etc. This enables stronger personalization, both during testing phases and when deploying online features, by letting you know exactly what your users need.
Want to Learn More?
If you would like to dive deeper into current experimentation trends, watch our webinar replay here, where fifty-five and AB Tasty explored key CRO case studies and more. And if you have any questions or insights you’d like to share, please leave a comment – we would love to hear from you!
Transaction testing, which focuses on increasing the rate of purchases, is a crucial strategy for boosting your website’s revenue.
To begin, it’s essential to differentiate between conversion rate (CR) and average order value (AOV), as they provide distinct insights into customer behavior. Understanding these metrics helps you implement meaningful changes to improve transactions.
In this article, we’ll delve into the complexities of transaction metrics analysis and introduce our new tool, the “Report Copilot,” designed to simplify report analysis. Read on to learn more.
Transaction Testing
To understand how test variations impact total revenue, focus on two key metrics:
Conversion Rate (CR): This metric indicates whether sales are increasing or decreasing. Tactics to improve CR include simplifying the buying process, adding a “one-click checkout” feature, using social proof, or creating urgency through limited inventory.
Average Order Value (AOV): This measures how much each customer is buying. Strategies to enhance AOV include cross-selling or promoting higher-priced products.
By analyzing CR and AOV separately, you can pinpoint which metrics your variations impact and make informed decisions before implementation. For example, creating urgency through low inventory may boost CR but could reduce AOV by limiting the time users spend browsing additional products. After analyzing these metrics individually, evaluate their combined effect on your overall revenue.
Revenue Calculation
The following formula illustrates how CR and AOV influence revenue:
Revenue=Number of Visitors×Conversion Rate×AOV
In the first part of the equation (Number of Visitors×Conversion Rate), you determine how many visitors become customers. The second part (×AOV) calculates the total revenue from these customers.
Consider these scenarios:
If both CR and AOV increase, revenue will rise.
If both CR and AOV decrease, revenue will fall.
If either CR or AOV increases while the other remains stable, revenue will increase.
If either CR or AOV decreases while the other remains stable, revenue will decrease.
Mixed changes in CR and AOV result in unpredictable revenue outcomes.
The last scenario, where CR and AOV move in opposite directions, is particularly complex due to the variability of AOV. Current statistical tools struggle to provide precise insights on AOV’s overall impact, as it can experience significant random fluctuations. For more on this, read our article “Beyond Conversion Rate.”
While these concepts may seem intricate, our goal is to simplify them for you. Recognizing that this analysis can be challenging, we’ve created the “Report Copilot” to automatically gather and interpret data from variations, offering valuable insights.
Report Copilot
The “Report Copilot” from AB Tasty automates data processing, eliminating the need for manual calculations. This tool empowers you to decide which tests are most beneficial for increasing revenue.
Here are a few examples from real use cases.
Winning Variation:
The left screenshot provides a detailed analysis, helping users draw conclusions about their experiment results. Experienced users may prefer the summarized view on the right, also available through the Report Copilot.
Complex Use Case:
The screenshot above demonstrates a case where CR and OAV have opposite trends and need a deeper understanding of the context.
It’s important to note that the Report Copilot doesn’t make decisions for you; it highlights the most critical parts of your analysis, allowing you to make informed choices.
Conclusion
Transaction analysis is complex, requiring a breakdown of components like conversion rate and average order value to better understand their overall effect on revenue.
We’ve developed the Report Copilot to assist AB Tasty users in this process. This feature leverages AB Tasty’s extensive experimentation dashboard to provide comprehensive, summarized analyses, simplifying decision-making and enhancing revenue strategies.
What is the future of experimentation? Bhavik Patel highlights the importance of strategic planning and innovation to achieve meaningful results.
A thought leader in the worlds of CRO and experimentation, Bhavik Patel founded popular UK-based meetup community, CRAP (Conversion Rate, Analytics, Product) Talks, seven years ago to fill a gap in the event market – opting to cover a broad range of optimization topics from CRO,data analysis, and product management to data science, marketing, and user experience.
After following his passion throughout the industry from acquisition growth marketing to experimentation and product analytics, Bhavik landed the role of Product Analytics & Experimentation Director at product measurement consultancy, Lean Convert, where his interests have converged. Here he is scaling a team and supporting their development in data and product thinking, as well as bringing analytical and experimentation excellence into the organization.
AB Tasty’s CMO Marylin Montoya spoke with Bhavik about the future of experimentation and how we might navigate the journey from the current mainstream approach to the potentialities of AI technology.
Here are some of the key takeaways from their conversation.
The evolution of experimentation: a scientific approach.
Delving straight to the heart of the conversation, Bhavik talks us through the evolution of A/B testing, from its roots in the scientific method, to recent and even current practices – which involve a lot of trial and error to test basic variables. When projecting into the future, we need to consider everything from people, to processes, and technology.
Until recently, conversion rate optimization has mostly been driven by marketing teams, with a focus on optimizing the basics such as headlines, buttons, and copy. Over the last few years, product development has started to become more data driven. Within the companies taking this approach, the product teams are the recipients of the A/B test results, but the people behind these tests are the analytical and data science teams, who are crafting new and advanced methods, from a statistical standpoint.
Rather than making a change on the homepage and trying to measure its impact on outcome metrics, such as sales or new customer acquisition, certain organizations are taking an alternative approach modeled by their data science teams: focusing on driving current user activity and then building new products based on that data.
The future of experimentation is born from an innovative mindset, but also requires critical thinking when it comes to planning experiments. Before a test goes live, we must consider the hypothesis that we’re testing, the outcome metric or leading indicators, how long we’re going to run it, and make sure that we have measurement capabilities in place. In short, the art of experimentation is transitioning from a marketing perspective to a science-based approach.
Why you need to level up your experiment design today.
While it may be a widespread challenge to shift the mindset around data and analyst teams from being cost centers to profit-enablement centers, the slowing economy might have a silver lining: people taking the experimentation process a lot more seriously.
We know that with proper research and design, an experiment can achieve a great ROI, and even prevent major losses when it comes to investing in new developments. However, it can be difficult to convince leadership of the impact, efficiency and potential growth derived from experimentation.
Given the current market, demonstrating the value of experimentation is more important than ever, as product and marketing teams can no longer afford to make mistakes by rolling out tests without validating them first, explains Bhavik.
Rather than watching your experiment fail slowly over time, it’s important to have a measurement framework in place: a baseline, a solid hypothesis, and a proper experiment design. With experimentation communities making up a small fraction of the overall industry, not everyone appreciates the ability to validate, quantify, and measure the impact of their work, however Bhavik hopes this will evolve in the near future.
Disruptive testing: high risk, high reward.
On the spectrum of innovation, at the very lowest end is incremental innovation, such as small tests and continuous improvements, which hits a local maximum very quickly. In order to break through that local maximum, you need to try something bolder: disruptive innovation.
When an organization is looking for bigger results, they need to switch out statistically significant micro-optimizations for experiments that will bring statistically meaningful results.
Once you’ve achieved better baseline practices – hypothesis writing, experiment design, and planning – it’s time to start making bigger bets and find other ways to measure it.
Now that you’re performing statistically meaningful tests, the final step in the evolution of experimentation is reverse-engineering solutions by identifying the right problem to solve. Bhavik explains that while we often focus on prioritizing solutions, by implementing various frameworks to estimate their reach and impact, we ought to take a step back and ask ourselves if we’re solving the right problem.
With a framework based on quality data and research, we can identify the right problem and then work on the solution, “because the best solution for the wrong problem isn’t going to have any impact,” says Bhavik.
What else can you learn from our conversation with Bhavik Patel?
The common drivers of experimentation and the importance of setting realistic expectations with expert guidance.
The role of A/B testing platforms in the future of experimentation: technology and interconnectivity.
The potential use of AI in experimentation: building, designing, analyzing, and reporting experiments, as well as predicting test outcomes.
The future of pricing: will AI enable dynamic pricing based on the customer’s behavior?
About Bhavik Patel
A seasoned CRO expert, Bhavik Patel is the Product Analytics & Experimentation Director at Lean Convert, leading a team of optimization specialists to create better online experiences for customers through experimentation, personalization, research, data, and analytics. In parallel, Bhavik is the founder of CRAP Talks, an acronym that stands for Conversion Rate, Analytics and Product, which unites CRO enthusiasts with thought leaders in the field through inspiring meetup events – where members share industry knowledge and ideas in an open-minded community.
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 on what it takes to build and run successful experimentation programs.
We’re excited to share that AB Tasty is now available on the Shopify app store. This means it’s easier to use AB Tasty’s leading experimentation and personalization solutions directly on Shopify sites.
The launch marks an important milestone for the partnership between AB Tasty and Shopify, providing a more seamless user experience and keeping experience optimization accessible with easy-to-use solutions.
What this means for Shopify merchants
Brands using Shopify can enhance their commerce sites with AB Tasty to boost conversions and optimize experiences. Set-up is simple: search for AB Tasty in the Shopify App Store and install the tag in just three steps.
Once a site is equipped with AB Tasty, you can easily access your favorite features, run tests, and personalize content throughout the shopping funnel from homepage to cart page.
Building better experiences on your Shopify sites is also easy with AB Tasty’s ready-to-use widget library including interactive features like the scratch card. Or you can create your own custom widget.
When it’s time to check on how your campaigns are performing, track your success with analytics that automatically link Shopify transactions(transaction rate, total number of transactions, average basket, items per transaction, average item price per transaction, etc.) and other transaction data (like currency, coupons, payment method, etc.) to your AB Tasty campaigns. Quickly identify what campaigns work for your audience and where you can make adjustments.
How does it work?
When you are ready to get started, connect AB Tasty with your Shopify site in three steps.
Install the AB Tasty app directly from the Shopify app store.
Enable the extension with your AB Tasty identifier.
Hit save.
Now you can get to work building better experiences for your visitors. Really, that’s it.
Over 100 brands already use AB Tasty & Shopify to optimize their sites
Learn more about how Embark Veterinary’s e-commerce teams use AB Tasty’s experimentation solution to test product copy and increase revenue per session and conversion rate.
At AB Tasty, we’re your optimization partners helping ignite change from the inside out. That’s why we’re continuously improving the experience of our customers, from new integrations to strengthened partnerships and beyond.
To connect AB Tasty to your Shopify site, get started here.
