A/B Testing: The Hero of Data Analytics
Digital marketing is a fast-paced landscape where flexibility and experimentation are paramount to success. Enter A/B and Multivariate testing — a powerful practice wielded by data analysts (and other marketers) to optimize as many variables as possible for digital products.
On this episode of the Marketing Roundtable podcast, hosts Tatiana Knies-Smith and Rachel Rhodes sit down with two analytics experts to dive deeper into the intricacies of A/B testing, BrainDo’s unique approach, and where the practice is headed.
Let’s dive in.
A familiar face returns! BrainDo’s own Principal and co-founder, Brian Cosgrove, previously guest starred on an episode dedicated to data science and analytics as a larger discipline.
Now he’s back to dive deeper with us, alongside VP of Analytics Engineering, Peter Song.
Peter started his career in web development, but quickly realized that the world of data analytics was calling his name. Over the years, Peter amassed a stellar skillset that touches everything from tracking tools configuration to CCPA/GDPR compliance. Process-oriented by nature, Peter enjoys putting his ideas to the test and seeing the results in concrete performance metrics. He’s also a dedicated, life-long skateboarder.
So with these two brilliant minds together around … well, the roundtable … we jumped right into defining just what A/B testing really is.
Specifically in the context of a front-end interface for a website or an app, Peter explains that A/B testing involves comparing a control against another experience to optimize customer interaction and enhance conversion rates. This method can be as simple as contrasting two designs or as complex as testing multiple elements — like headlines, images, and call-to-action buttons.
“It’s about tweaking the design to make it effective, more user-friendly,” Brian emphasizes, highlighting its role in optimizing user experience.
Popular tools used for digital interface measurement, or clickstream data, include Google Analytics, Adobe Analytics, and Amplitude. For A/B testing, tools like Optimizely, Adobe Target, and Visual Website Optimizer help teams orchestrate these tests and provide specialized reporting about the outcome of the tests. But, of course, there are countless nuances to consider with each of these tools before recommending one to a company. Luckily, Peter and Brian have the expertise and skills to navigate those decisions with BrainDo’s clients.
Recalling him once referring to BrainDo as being platform-agnostic, Rachel asks Peter to elaborate on what that means for us as client partners.
“Being platform-agnostic means we work with any type of analytics platform and have the expertise within that,” Peter states, underscoring the importance of adaptability in analytics. The software tools ecosystem is constantly changing, and some tools can be adapted to facilitate different types of experimentation. He continues, “We’re not just a Google shop, or an Adobe shop. We have skill sets in all of these platforms.”
Flexibility is crucial in today’s diverse digital ecosystem — especially as a consultancy working with organizations that possess their own histories and comfort levels with different platforms. BrainDo adapts its best practices and techniques for orchestrating these tests by meeting clients with the tools they have, or by otherwise making the best recommendation possible.
Of course, any conversation around the future of A/B testing in data analytics wouldn’t be complete without touching on artificial intelligence (AI)! According to Brian, these technologies will replace A/B testing practices to eventually automate the optimization of digital products.
However, the effectiveness of AI in this space heavily relies on the quality of the data. “If your data is not of high quality, the AI is not going to be effective,” he points out, stressing the significance of reliable data capture for AI-driven optimization to be effective.
Just like anything else in marketing, AI and automation may provide a powerful toolset, but are best paired with a discerning (read: human) eye for detail to ensure everything is running efficiently and meeting intended objectives without sacrificing both written and unwritten guidelines for the design.
Watch the full podcast episode now to explore how we establish processes for A/B testing, how to personalize tests for different user groups, common caveats we’ve seen, and so much more!
The Marketing Roundtable is available to watch on YouTube or listen to on every major podcast platform. Check it out today to learn more about A/B testing in the world of data analytics from two incredible experts, or browse other episodes for more digital prowess: