More feature flags related terms

Behavioral targeting


Behavioral targeting is a digital marketing strategy that leverages user data such as browsing history, search queries, and online behavior to deliver advertising content more likely to resonate with an individual's interests and preferences. This approach aims to increase the relevance of ads presented to users, thereby improving engagement rates, conversion rates, and ultimately, the effectiveness of advertising campaigns.



Key Benefits


Behavioral targeting represents a shift towards more user-centric advertising strategies, where the focus is on delivering relevant, personalized content to enhance engagement and effectiveness. By leveraging detailed insights into user behavior, marketers can craft campaigns that not only meet business objectives but also provide value to the audience, creating a win-win scenario for both advertisers and consumers.


Bayesian methodology updates beliefs based on prior knowledge and new evidence, offering flexibility and clear interpretability. It's valuable for understanding uncertainty and predicting events in fields like machine learning and decision-making.

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Bucket testing

Bucket testing, also called A/B testing, compares two versions of a webpage or app to see which performs better, aiding data-driven decisions for enhancing user experience and achieving business goals through iterative improvements.

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Confidence interval

Confidence intervals in A/B testing provide a range of plausible values for the true difference in performance metrics between variations, guiding decision-making and interpretation of results.

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