Allon Korem
Expert in advanced A/B Testing methodologies. Worked at Google and Wix.com.
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Say goodbye to black-boxed solutions. Bell offers outsourced advanced analytics services by experienced statisticians, specializing in: A/B Testing, Media Mix Modeling and Geo Tests.
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What our customers say
“One of the problems with testing is the ‘curse of knowledge’ – you know what you know, and you don’t know what you don’t know. Bell’s team, led by Allon, helped by unlocking the testing black box, helping us to find issues with our AB Tests flow, resolve them and ultimately gain much more out of our testing.”
"Bell transformed our approach to A/B testing. Bell not only revamped our testing methodology but ensured it was well-implemented. Their workshops and close guidance empowered our teams to make confident, data-driven decisions. The education and support provided by them significantly elevated our internal tools and testing accuracy."
Trusted by the best
Bell's Team
Oryah Lancry-Dayan
Expert in research planning, data analysis and statistical methodology.
Mali Tsadok
Expert in conducting advanced statistical analyses and A/B testing.
Gouni Jacobi
Expert in Geo Testing, and Recommender Systems.
Prof. David Steinberg
Expert in the statistical design of experiments. Awarded the George Box Medal in 2013; and the Walter Shewhart Medal in 2017.
Israel Ben Baruch
Product leader and Google expert who’s driven conversion growth through thousands of experiments and a proven methodology.
Latest Insights
Dive into the advanced analytics trends, tips, and tricks by our gorgeous team
10/90 vs 10/10 in A/B Testing: How to Split Users When Unequal Allocation Is Required
When business constraints limit A/B testing treatment exposure, analysts must choose between the statistical integrity of a balanced design (e.g., 10/10) and the speed of an unbalanced design (e.g., 10/90). The unbalanced 10/90 split, which uses full traffic to dramatically accelerate the experiment, comes with risks like inflated false positives from skewed metrics, Sample Ratio Mismatch, and resource contention bias. Read on as we examine this critical trade-off to help you balance speed with statistical validity.
Geo Testing: Unlocking True Incrementality in Marketing and Product Experiments
Our “Geo Testing: Unlocking True Incrementality” webinar explored how teams can measure real-world impact when A/B testing isn’t possible - using geographic experiments and synthetic controls to reveal true incremental lift in marketing and product initiatives.
Correct me if I'm wrong: Navigating multiple comparison corrections in A/B Testing
In this post, we will dive into the various methods for addressing multiple comparisons, examining their strengths and weaknesses, and providing guidance on when each method is most appropriate to use.