Hard things about Sales - and how A/B testing can help
summary
Sales teams face difficult, practical problems that resist intuition; Pavel Dmitriev outlines how to bring experimentation and A/B testing and machine learning into sales to make decisions data-driven. He discusses concrete techniques for running and scaling randomized experiments in sales contexts (drawing on experience from Outreach and Microsoft products like Bing, Skype, and Windows) to evaluate interventions and improve outcomes.
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chapters (15)
- 0:00Sales is the Engine that Propels Innovation
- 0:37Sales is Hard
- 3:07Sales Playbooks are Based on Myths and Anecdotes o not Data, and are Hard to Change
- 5:34Summary
- 6:10The Sales Process Optimization Challenge
- 6:54Sales Sequence
- 9:00A/B testing for Sales
- 11:04Obstacles to A/B Testing Adoption in Sales
- 12:02What to test?
- 14:11Can A/B Testing Help Answer Strategic Questions?
- 16:09How to Measure Success?
- 18:44It's a lot of work!
- 19:33Four Parts of an Effective A/B Testing Program
- 21:35Takeaways
- 24:09Global Big Data Conference
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