Article

5min read

Why AB Tasty Delivers 4x Faster

Hello! I’m Léo, Product Manager at AB Tasty. I’m in charge of AB Tasty’s JavaScript tag that is currently running on thousands of websites around the world. As you can guess, my roadmap is full of topics around data collection, privacy, and… performance.

It’s why I’m so excited to give an update on our performance, and how we’ve worked hard to be the best. We’re now providing loading times up to 4 faster than other solutions on the market. 

In a world where every second counts, slow-loading pages are the fast track to lost revenue. At AB Tasty, we know that speed isn’t just about convenience; it’s about delivering the smooth, reliable experience that today’s consumers expect. 

That’s why we’re thrilled to be recognized by ThirdPartyWeb.today for having one of the lowest impacts on web performance among top experimentation and personalization platforms. This acknowledgment affirms our commitment to speed, scalability, and brand satisfaction.

But what does this actually mean for brands using AB Tasty?

Let’s dive into how prioritizing performance can improve your SERP rankings, customer experience (CX), and overall campaign effectiveness.

Why Web Performance Impacts Your Bottom Line

Imagine clicking on a page that seems to take forever to load. Chances are, you’d be out of there faster than you could say “conversion rate.” And you wouldn’t be alone: slow page load times can lead to increased bounce rates, missed opportunities, and, ultimately, frustrated visitors.

Good performance translates into smoother customer journeys, which leads to better engagement and, most importantly, higher conversion rates.

ThirdPartyWeb.today: The Performance Benchmark 

ThirdPartyWeb.today is an independent performance data visualization initiative that analyzes the impact of various platforms on page speed. It ranks tools according to their performance cost, drawing data from nearly 4 million websites to create an unbiased performance benchmark. For brands aiming to deliver a seamless experience without sacrificing speed, ThirdPartyWeb.today provides a reliable guide for evaluating the performance impact of their tools.

Being recognized as one of the most performance-friendly Experience Optimization platforms by ThirdPartyWeb.today means our clients know they’re partnering with a technology designed with speed in mind.

What Makes AB Tasty the Fastest?

Our tech teams have worked tirelessly to make AB Tasty not only an intuitive experimentation and personalization platform, but one that prioritizes high performance. Here’s a quick look at the innovations that make AB Tasty so fast and reliable:

  1. Modular Architecture with Innovative Dynamic Importing and Smart Caching Technology
    Our platform is built with a modular architecture, where only essential code is loaded for each campaign. This keeps file sizes lean, reducing load time and resource consumption. Our proprietary smart caching technology ensures that visitors only need to load the data they haven’t accessed before. By minimizing redundant data calls, we significantly reduce load times across all devices. We also provide worldwide API endpoints and have a global CDN presence with multiple Edge locations and regional Edge caches for fast response times no matter where you and your site visitors are.

  2. Performance Center
    AB Tasty’s dedicated Performance Center allows you to monitor your campaign performance in real-time. This tool gives you full transparency into what’s happening behind the scenes, so you can make adjustments as needed to keep things running smoothly. It provides recommendations to help you monitor and improve tag weight. Learn all about it here.


  3. Single-Page Application (SPA) Compatibility
    AB Tasty’s platform is SPA-compatible without requiring custom code, making it easier for developers to integrate AB Tasty into their tech stack. AB Tasty is running on a native Vanilla TypeScript framework. Our tag is compatible with modern JS frameworks, including React, Angular, Vue, Meteor or Ember. The tag is unique for all environments and doesn’t require any additional implementation. Many of our customers have left their previous provider due to challenges with SPA pages. In these tools, changes are often not “sticky” or flicker when there is a dynamic content load. SPA tests in these environments often require custom code for each test, which makes testing more complicated and less user-friendly.

  4. Flicker-Free Experiences
    AB Tasty’s tag uses a blended approach of both synchronous and asynchronous scripts to eliminate flicker, while maintaining optimised performance. Other solutions will prescribe “anti-flicker” snippets to eliminate flicker, which is not a recommended practice. It means hiding the body’s content while the tag loads, which ultimately delays the rendering of the site. This causes a worse user experience, increases your Largest Contentful Paint (LCP) metric, and may ultimately lead to increased bounce rates and decreased conversions. In contrast, AB Tasty’s synchronous tag uses 3kb of render-blocking to allow the tag to execute quickly before the page loads, as opposed to blocking the visibility of the page for the full package size.

And that translates to…

First loading time < 100ms
Caching loading time < 10ms
Execution time < 500 milliseconds
Minimal Lighthouse Core Web Vitals impact

Cheers to Our Product and Tech Teams

This wouldn’t be possible without the dedication of our Product and Tech teams (thanks team!). We’ve dared to innovate, pushing the limits of what’s possible with web performance in the experimentation and personalization space.

The Bottom Line

When brands choose AB Tasty, they’re choosing a platform that prioritizes both innovation and performance. By minimizing impact on web performance, we’re helping brands deliver faster, better experiences that delight customers and drive results.

Curious to learn more about? Contact us today to discover what else sets us apart.

Subscribe to
our Newsletter

bloc Newsletter EN

We will process and store your personal data to respond to send you communications as described in our  Privacy Policy.

Article

9min read

Test, Optimize, and Upsell

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

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: