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AB Testing vs. Multi-Armed Bandits: What You Need to Know
Imagine a world where your AB tests run themselves—faster, smarter, and more dynamic than a simple 50/50 split that takes weeks to measure.
Today’s episode breaks down how multi-armed bandit algorithms could change when and where you use AB testing. But don’t be fooled—there are no free lunches and no cure-alls.. We’ll show you why understanding your use case, keeping the stakes low, and having human oversight are the keys to getting the most out of these powerful algorithms.
In this Episode:
Today’s episode breaks down how multi-armed bandit algorithms could change when and where you use AB testing. But don’t be fooled—there are no free lunches and no cure-alls.. We’ll show you why understanding your use case, keeping the stakes low, and having human oversight are the keys to getting the most out of these powerful algorithms.
In this Episode:
- The potential of multi-armed bandit algorithms to supplant traditional AB testing
- Critically assessing the limitations and complexities involved in applying bandit algorithms to real-world data and marketing contexts.
- The role of these algorithms in personalizing customer interactions and automating low-risk experiments.
View all episodes
By EppoImagine a world where your AB tests run themselves—faster, smarter, and more dynamic than a simple 50/50 split that takes weeks to measure.
Today’s episode breaks down how multi-armed bandit algorithms could change when and where you use AB testing. But don’t be fooled—there are no free lunches and no cure-alls.. We’ll show you why understanding your use case, keeping the stakes low, and having human oversight are the keys to getting the most out of these powerful algorithms.
In this Episode:
Today’s episode breaks down how multi-armed bandit algorithms could change when and where you use AB testing. But don’t be fooled—there are no free lunches and no cure-alls.. We’ll show you why understanding your use case, keeping the stakes low, and having human oversight are the keys to getting the most out of these powerful algorithms.
In this Episode:
- The potential of multi-armed bandit algorithms to supplant traditional AB testing
- Critically assessing the limitations and complexities involved in applying bandit algorithms to real-world data and marketing contexts.
- The role of these algorithms in personalizing customer interactions and automating low-risk experiments.