Welcome to Nerd Alert, a series of special episodes bridging the gap between marketing academia and practitioners. We’re breaking down highly involved, complex research into plain language and takeaways any marketer can use.
In this episode, Elena and Rob explore how sophisticated advertising algorithms can skew A/B test results, potentially leading marketers to draw misleading conclusions about ad performance.
Topics covered:
- [00:45] "Where A-B Testing Goes Wrong”
- [02:00] Divergent delivery in online advertising platforms
- [03:00] How user types and targeting policies impact tests
- [04:10] Pizza party analogy explaining divergent delivery
- [05:40] Marketing Architects' approach to testing
- [06:50] Using synthetic audiences for more controlled testing
To learn more, visit
marketingarchitects.com/podcast Resources:
Braun, M., & Schwartz, E. M. (2024). Where A-B Testing Goes Wrong: How Divergent Delivery Affects What Online Experiments Cannot (and Can) Tell You About How Customers Respond to Advertising. Journal of Marketing.
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