How to Choose the Ideal Tool to Help Build Experimentation Culture in Your Organization

In today’s fast-paced digital landscape, companies that experiment, learn, and adapt quickly are the ones that create a competitive advantage. But creating a true experimentation culture, not just running a few isolated A/B tests, requires more than a strategy. And it requires the right tools. What you need is a purpose-built experimentation engine designed to…

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Transforming Experimentation Insights Into Actionable Outcomes

Running experiments, tracking outcomes, and making tweaks based on what you learn are important for entire organisations that want to deliver a top-tier user experience. But, despite widespread adoption, a critical gap persists: reporting. All too often, the results are locked behind walls of metrics or are so granular that their organisational impact goes unnoticed…

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Datadog Buys Eppo for $220M: Our Take on the Future of Experimentation

Datadog’s recent acquisition of Eppo for $220 million marks a significant moment in the rapidly evolving field of experimentation. First, we’d like to congratulate the teams at both Datadog and Eppo. This move underscores a broader industry trend that we’ve seen building momentum: experimentation is moving from a specialized discipline within tech giants to a…

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The Top Three Experimentation Mistakes Businesses Make

Effective experimentation enables organisations to optimise their products, services, and processes. But even teams with a solid grasp of A/B testing often stumble down a few blind alleys that undermine their experimentation efforts. These are the three key mistakes we see when people are running experiments. Mistake 1: Overcomplicating Experimentation Experimentation is about learning how…

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Experimentation Made Smarter

This December, we focused on simplifying the process of setting up and running tests to empower your teams to experiment with more confidence. Our December 2025 platform update makes your experimentation experience smoother, faster, and more flexible than ever.  Enhanced Group Sequential Testing (GST) We made lots of usability improvements to our GST engine so…

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Optimizing A/B Testing for Low-Traffic Sites or Apps

A/B testing is incredibly valuable for businesses looking to refine their websites and apps, and understand the user experience better. But experimentation is significantly more challenging when it comes to low-traffic sites and apps. We are referring to folks with a few thousand visitors/users per month. Drawing statistically significant conclusions from user experience usability testing…

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Making Experimentation More Intuitive and Powerful: ABsmartly September Features Update

This autumn, we’re excited to introduce several powerful improvements to help make your experimentation workflow smoother, more intuitive, and even more effective. At ABsmartly, we’re constantly refining our platform so your team can focus on what matters—running effective experiments and making revenue-impacting decisions. Improving Our Unique Group Sequential Testing (GST) Engine We’ve worked hard to…

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The Danger of Not Looking Beyond Numbers in Experimentation

Numbers often serve as the foundation of decision-making in the nuanced field of data analysis and A/B testing. However, the real challenge—and opportunity—lies in interpreting these numbers correctly, particularly by understanding the reasons behind them. This approach helps uncover genuine insights that can drive meaningful improvements rather than being misled by surface-level data. I hope…

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