A/B testing and personalization: do you trust your data and results?

Modern digital marketing strategies depend on understanding, analyzing, and acting on large volumes of data. In 2020, Gartner added the concept of customer data ethics to its Hype Cycle for the first time, demonstrating that it is now a major concern for brands, consumers, and regulators.

In this guest article, Frontastic technology partner Kameleoon gives useful insights into the topic A/B testing and the right usage of visitor data.

A/B testing and personalization

A/B testing and personalization solutions use visitor data to enable brands to make good decisions to improve user experience and deliver a personalized customer journey. Given its importance, the quality of this data is crucial for the success of a project. Data must be collected, processed, and analyzed correctly to deliver real insights and value.

But how can marketers be certain that the results of experiments are reliable?

Jean-Noël Rivasseau, Kameleoon’s founder and CTO is able to give answers to this question. He has built a feature-rich A/B testing and personalization platform that combines high performance, reliability, and security. The product is dedicated to meeting the changing technical, functional, and business needs of the biggest global digital brands when it comes to experimentation and personalization.

What are the top criteria when choosing an A/B testing and personalization technology provider?

Kameleoon’s founder and CTO. At Kameleoon Jean-Noël has a clear opinion on this.

“Brands invest in an A/B testing and personalization solution so they can make decisions based on reliable data and consequently roll out the best possible online experience to their visitors in real-time. So the most important criteria is the solution’s reliability when it comes to delivering trustworthy results. Without this, you can’t have faith that your optimization practices are actually going to provide real improvements.”

This may seem obvious but this point is often overlooked by decision-makers. Is your supplier collecting data correctly? How are they processing it? Is your reporting tool reliable?

These technical questions are vital since they carry big risks for brands. Data loss, skewed reporting, and thus biased decision making — all of which have a financial impact. It’s very important for brands to have complete trust in their solution since it functions as a decision-making tool that has a direct impact on increasing conversion rates and therefore sales and revenues.

What does a “reliable” solution have to deliver?

A reliable solution is one with a high degree of uptime, and that delivers A/B test and personalization results that cannot be disputed. This reliability depends on several upstream factors within the tool supplier, such as the skills of the team involved, the technology leadership, and whether it is based on a robust, scalable architecture. It is important to think ahead — some decisions made several years ago may have a long-term impact, leading to an accumulation of technical debt that becomes unmanageable over time.

Besides technology choices, it is crucial to have the right people in place at your supplier to manage the tool’s underlying processing engine, and who have the experience and skills to successfully administer security.

How can data be managed?

Where data collection is concerned, servers have to manage a large number of requests per second. Second, the chosen system has to be completely scalable and flexible.

For data processing, technology choices make the difference when it comes to guaranteeing reliability to clients. We build trust, any incidents that may occur have to be communicated in real-time.

Finally, in the event of an error, processes have to lead to very short response times, limiting the impact on clients. All these measures enable maximum reliability to clients.

Conclusion: What do brands have to understand to enable long lasting growth?

Brands must understand the constraints that are inherent to digital marketing. For example, the restrictions on cookie lifespan imposed by browsers, the flicker effect, and script performance are all elements that have a huge impact on experiment results.

From this point of view, not all testing and personalization solutions are equal.

“The first element, which we believe to be the most critical is that our visitor-data collection and processing technology enables us to adapt to the constant changes of Apple’s Intelligent Tracking Protection (ITP) changes and to other browser restrictions. The second element is that we have a 100% anti-flicker script to ensure that a visitor has the same quality of experience, whether they are shown version A or version B in an experiment. Finally: the ultra-optimized size of our script enables us to provide brands with maximum execution speed, ensuring an optimal visitor experience.” Kamaleoon Founder and CTO Jean-Noël Rivasseau

Find out more about ITP in this blog post by Kamaleoon.

In summary, you should choose a testing solution as you would a SatNav or GPS: if the route directions are wrong and if the results are too slow, then you’re better off not using it at all. That’s why the reliability of data along with the performance and availability of a good platform is so important.

You want to find out more about A/B testing with Kamaleoon? Request a free demo now!

Kameleoon is an AI-driven personalization and A/B testing platform that enables entrepreneurs and marketeers of digital products to quickly and automatically tailor their website and user experience to the needs of each individual visitor.

Over 450 major companies trust Kameleoon and make it the leading SaaS platform for AI-driven personalization in Europe.

Find out more on www.kameleoon.com or LinkedIn.

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