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Taboola is responsible for billions of daily recommendations, and we are doing everything we can to make those recommendations fit each viewer’s personal taste and interests. We do so by updating our Deep-Learning based models, increasing our computational resources, improving our exploration techniques and many more. All those things though, have one thing in common – we need to understand if a change is for the better or not, and we need to do so while allowing many tests to run in parallel. We can think of many KPI’s for new algorithmic modifications – system latency, diversity of recommendations or user-interaction to name a few – but at the end of the day, the one metric that matters most for us in Taboola is RPM (revenue per mill, or revenue per 1,000 recommendations), which indicates how much money and value we create for our customers on both sides – the […]