We’re excited to announce our very first blog series, written by Jon Noronha, the Director of Product Management at Optimizely.
Hot on the heels of the release of Feature Management, we’re launching a 5-part blog series, using stories, research, and data to help you avoid common product development experimentation pitfalls. Whether your team has experiments running like a well-tuned engine or you’re just learning about adopting testing into your product development cycles, you’re likely to have a few ‘aha moments’ as you’re reading these posts.
In this new series, Jon will share past experiences, lessons learned, and important advice from having worked in the experimentation space for years, including a long stint leading experimentation on the Bing search product at Microsoft. What you’ll quickly realize is that no one becomes an experimentation expert overnight, everyone has their own trials and tribulations, but with the right tools and resources, goal alignment, and a pinch of patience, you can cross the finish line developing better products at a more rapid speed.
Here’s a sneak peek of what’s to come in the series:
One of the biggest trends software development today is product experimentation. Instead of designing a product, building it, launching, and praying, more and more teams are looking for ways to iterate gradually and validate their ideas with data. Techniques like A/B testing, feature flagging, and gradual rollouts are quickly going from niche to mainstream.
But like any trend, product experimentation is a good idea that can easily go wrong. For every game-changing A/B test, there’s a trail of testing mistakes that led well-meaning teams down the wrong path. That’s exactly why I want to share some common ways I’ve seen A/B testing go wrong, along with some tips for avoiding these pitfalls in your own experimentation program.
- Choosing the Wrong Metrics
- Experimenting Without Enough Traffic
- Getting Tricked by Statistics
- Testing Too Few Variations
- Failing to Scale Your Experimentation Platform
Stay tuned for the first post ‘Choosing the Wrong Metrics’ next week. Check back here on the Optimizely blog or subscribe below to get a notification as soon as the new post is released!