On the podcast I talk with Dan about how to design experiments that answer the right questions, common A/B testing pitfalls to avoid, and how a simple checklist might just save your complex experiment.Top Takeaways? Conclusions from tests sometimes go stale faster than you realize? Minimizing the cost of running tests will improve decision making? Check your sanity — or don’t live and die by statistical significanceAbout Dan Pannasch?‍? Senior Product Manager at RevenueCat? Dan saw what experimentation looked like across a portfolio of app businesses when his previous company TelTech’s success led to an acquisition by IAC. He joined RevenueCat in May 2022 and leads the Experiments project.? “You could change the color [of the buy button in A/B testing and] release it in the new application. And if you can't tell which one won [with users], then you learned that it doesn't matter. You didn't learn which one won, but you did learn that it doesn't matter for you right now.”? Twitter | LinkedInLinks & Resources‣ Join the RevenueCat team‣ Sub Club interview with Blinkist’s Jaycee Day‣ RevenueCat’s Experiments toolFollow us on Twitter‣ David Barnard‣ Jacob Eiting‣ RevenueCat‣ Sub ClubEpisode Highlights[2:18] Experimentation: What is app experimentation and why should you do it? The right decision making, considering impact on variables, and risk mitigation are everything when it comes to user experience.[9:04] Taking a page from DuoLingo’s playbook: Product strategy and intuition naturally limits possibilities — and it’s not the place for A/B testing. Microdecisions within deliverables are testable, and then it’s just cost-benefit analyses. [14:04] The early days: The cost-benefit analysis should pervade every stage of the process, from early growth and beyond. Trying to design the perfect A/B test isn’t always possible when customers are begging you for.[19:20] Paywall plays: Where you put the paywall is a tough decision. But there are strategies for implementation and risk mitigation.[24:35] Testing 101: Be sure to write down the hypothesis before testing so that you can measure impact. Unexpected results — where you learn the most about variables — depend on it.[28:05] Follow it up: Dan shares his thoughts on user follow ups to boost quantitative data with qualitative data. Sometimes talking to users can be very powerful.[31:13] Sanity check: How to do a testing plan, as done by Dan during his time as a PM at TelTech. Plus, an explanation of statistical significance.[39:53] Impact and intuition: To understand user experience impact and product intuition, it’s critical to ensure the design aligns with the value proposition.[42:22] Actual testing: There are pitfalls and screw-ups to watch out for when testing (and even before).[46:33] Analyzing the results: Dan provides his overview for analyzing the results after running the experiment. Second and third order effects are important but not always immediately obvious. [48:41] The Experiments product: RevenueCat’s new tool enables easy A/B testing for two offerings. The data helps you analyze the full subscription lifecycle to understand which variant is producing more value for your business.[55:55] Bugs: No product will ever be perfect, but Experiments offers app developers the tools and confidence to make sure it’s at least most of the way there.