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Most businesses evaluate customer value based solely on upfront ticket sales. The New York Red Bulls tested that assumption and discovered that evaluating total matchday engagement offers a far more accurate picture of fan value.
Most advice on building a culture of experimentation focuses on evidence. Run more tests, raise your standards, get the statistics right, and the organization will come along.
TL;DR: Finding and exploiting bugs is getting cheaper, and the attackers now include software with superhuman abilities. You cannot fix your vendors' security. You can control how many of them hold your data, and where they run. The best security is by removing attack surface areas.
If you build healthcare-related software, you’ve probably been told to make sure that personal health information is kept out of third-party tools. It’s a huge undertaking but necessary considering the consequences of a data leak.
Most consumer subscription businesses share a simple instinct: more engagement is better. More minutes watched, more books read, more sessions started.Mary Alfheimspent years inside that instinct, leading product analytics at Prime Video, working at HBO when HBO Max launched and leading data and ana
Search for banana on Walmart and look at the ads. There are almost none. Hardly any advertiser sells bananas, or fresh food of any kind, so the pages that shoppers visit most for groceries are some of the emptiest for sponsored products.
The registration page was leaking. VidaXL's B2B buyers were getting to the signup step and leaving before they created an account, and the analytics could show exactly where it happened. What the analytics could not show was why.
Most conversations about experimentation start at the A/B test.Michal Lenik's starts much earlier.
Most experimentation stories start with a bold redesign. This one starts with a search box.
Every new AI model brings its own response style, its own strengths, its own sharp edges when it meets your application.
Running experiments one at a time is safe. Every test enrolls the whole user base and nothing overlaps. It’s also slow. Any test using the whole user base blocks everything behind it. Even with access to the entire user base, many experiments need to run forat least 2 weeksto balance out day-of-week
Show: The Experimentation Edge with Ashley Stirrup. Guest:Gaurav Sethi, Group Product Manager, PayPal. Publishing: September 30, 2026. Length: 00:31:21
Guest:Ashraf Karim, Sr VP, Connected Customer Experiences & Technology, ServiceNow. Host: Ashley Stirrup. Show: The Experimentation Edge. Publishing: September 29, 2026
Guest:Wanli Lau, Sr Director, Data Science & Analytics, Twilio. Host: Ashley Stirrup. Show: The Experimentation Edge. Publishing: September 24, 2026
MCP server, Slack app, and contextual bandits
Most experimentation programs keep score the obvious way. Count the wins, divide by the tests, report the win rate. Will Guyeskey thinks that is the wrong scoreboard.
If you have a fairly robust deployment pipeline, it’s probably tightly controlled. For instance, you have pull requests, CI checks, and production approvals. But it’s still possible that a change can reach productionwithoutgoing through any of these steps. It happens when you flip a feature flag.
Feature flagging platformswere built to helpengineering teamsship faster while reducing risk. But in regulated industries likefintechorhealthtech, every change you make with a flag is also a production change, and auditors will always ask about it.
Companies that run successful experimentation programsunderstand their business better, improve the product and customer experience faster, and drive smarter decision-making company-wide.
Guest:Anuradha Tempe, Lead Product Manager, Samsung Electronics America. Host: Ashley Stirrup, CMO, GrowthBook. Show: The Experimentation Edge.
The traditionalCI/CD pipelinetreated deployment and release as the same event. You merge to main, and the code hits production while every user experiences the changes at once. If something goes wrong, you find out the hard way.
You can put 50% of your users on a new checkout flow in about thirty seconds using a feature flag. But that doesn’t mean you’ve run an A/B test.
Guest:Joe Yevoli, Director of Growth, Charlie Health. Host: Ashley Stirrup, CMO, GrowthBook. Show: The Experimentation Edge.
GrowthBook Cloud now supports an EU data region. When you set up aManaged Warehouse, chooseAWS eu-west-1 (Ireland)and your event data is ingested and stored in the EU.
Guest:Mi Tian, Head of Applied Science, Zalando. Show: The Experimentation Edge with Ashley Stirrup. Company: Zalando, the Berlin-based e-commerce platform operating in around 30 European markets with over 60 million monthly active users.
Guest:Whitney Perez, Director of Product Management, Realtor.com. Host: Ashley Stirrup, CMO, GrowthBook. Show: The Experimentation Edge.
Guest:Rich Liebling, Senior Director of Engineering at Learneo. Host: Ashley Stirrup. Show: The Experimentation Edge, presented by GrowthBook.
DORA’s researchidentifies trunk-based developmentas a capability that drives software delivery performance. It’s not just a habit that high performers happen to share. Here, they work in small batches and merge into a shared “trunk” at least once a day to deploy continuously.
DORA’s researchidentifies trunk-based developmentas a capability that drives software delivery performance. It’s not just a habit that high performers happen to share. Here, they work in small batches and merge into a shared “trunk” at least once a day to deploy continuously.
When it comes to feature flagging, it’s easy to build a simple server-side, on/off feature flagging system, but that simple project can quickly grow into a full platform as your requirement list grows. Use this checklist to assess your mid-term needs.
Running an experiment is the easy part. The hard part is knowing whether it was worth running at all.
Feature flagsare one of the few tools you can use to change production behavior in seconds, without deploying code. As powerful as that sounds, it also comes with its own risks.
Getting your firstexperimentationwin is one thing. ScalingA/B testingto hundreds of experiments a year across many teams is a distinct discipline with its own challenges. Programs that add velocity without changing how they operate often run into similar problems: teams rerun the same tests without
Three hundred million people play a Supercell game every month. Clash of Clans, Clash Royale, Brawl Stars, Hay Day, Boom Beach: some of the most successful mobile games ever made, built by a company of about a thousand people in Helsinki. A player base that size could justify thousands of A/B tests
Most companies say they value experimentation. Far fewer have built a culture where a failed test is treated as a win.James Falzone, Director of Product Management atKargo, leads a team that does, and on The Experimentation Edge, he made a case for why that distinction is the whole game.
Dimension splits can surface what your Average Treatment Effect hides, or fool you with noise. How to avoid cherry-picking your results, correct for multiple tests, and steer clear of bad controls.
Winnings compound your metrics. Learnings compound your experimentation program. Introducing GrowthBook Learnings.