Klaviyo Data Science EP 25 | Using A/B testing to optimize your strategy
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Description
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into… Thinking big-picture with A/B testing We’ve discussed A/B testing multiple times on this podcast, for good reason. But there’s an important angle we have yet to cover: in the life of a researcher or marketer, there’s no such thing as an A/B test. There’s an entire system of A/B tests run for specific purposes over time. What is the best way to construct a system of A/B tests to help you learn, improve, and grow over time? How does that translate into tenets to hold while building software to help people run A/B tests? We’ve brought on three members of the data science team at Klaviyo, and you’ll hear about A/B tests in a variety of ways, including: Real data-driven trends observed by successful A/B testers on Klaviyo Why up-front thinking and vision translate into long-term success Why dad jokes might be far more powerful than you think “The more experimental you can be, the more creative you can be, the more you can learn about your customers to really deliver authentic experiences and see return on your investment.” - Woody Austin, Senior Machine Learning Engineer Check out the full show notes on Medium for more information!
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