Optimizing Optimizely: How we use Full Stack for product development

Optimizing Optimizely: How we use Full Stack for product development

To put it simply, Optimizely Full Stack decouples the deployment of code from the delivery of features the code represents. That allows you to quickly release new features to audience segments, test the performance of the changes, analyze their impact, and either release them more widely or roll them back, all from an intuitive drag-and-drop dashboard. No need […]

Optimizely’s Vision for Product Development Teams

Optimizely’s Vision for Product Development Teams

Earlier this week, Optimizely’s Chief Product Officer Claire Vo and Jon Noronha, our VP of Product Management, presented via a live webinar on Optimizely’s vision for product development teams and previewed our upcoming roadmap.  They explained how product development teams need to be able to balance velocity with proving value. Here are some of the […]

Stop Launching.
Start Rolling Out.

Stop Launching. <br/> Start Rolling Out.

Splashy, big-bang launches were once the most common way software companies released new software. Product and engineering worked tirelessly to get a new product or feature ready while marketing and PR feverishly prepped launch materials. They often even put together extravagant launch parties to celebrate the occasion. But for every successful big bang launch, there […]

Product Experimentation Pitfalls, Post #5: Failing to Scale Across Teams

Product Experimentation Pitfalls, Post #5: Failing to Scale Across Teams

This is the final post in our Product Experimentation Pitfalls blog series, written by Optimizely’s Director of Product Management, Jon Noronha. See here for more information on this 5-part series.    So far in this series, I’ve highlighted several pitfalls on the path to product experimentation. We’ve seen how some common mistakes can slow down […]

Product Experimentation Pitfalls, Post #4: Measuring and Driving Experiment Velocity

Product Experimentation Pitfalls, Post #4: Measuring and Driving Experiment Velocity

This is the fourth post in our Product Experimentation Pitfalls blog series written by Optimizely’s Director of Product Management, Jon Noronha. See here for more information on this 5-part series.  So far in this series, we’ve talked about the hidden challenges that can stop experimentation from getting off the ground, like getting tricked by statistics, or choosing […]

Product Experimentation Pitfalls, Post #3: Getting Tricked by Statistics

Product Experimentation Pitfalls, Post #3: Getting Tricked by Statistics

This is the third post in our Product Experimentation Pitfalls blog series written by Optimizely’s Director of Product Management, Jon Noronha. See here for more information on this 5-part series.  Analyzing an A/B test is deceptively simple. You count up how many conversions happened in each variation, you divide by the number of users exposed […]

Product Experimentation Pitfalls, Post #2: Experimenting Without Enough Traffic

Product Experimentation Pitfalls, Post #2: Experimenting Without Enough Traffic

This is the second post in our Product Experimentation Pitfalls blog series written by Optimizely’s Director of Product Management, Jon Noronha. See here for more information on this 5-part series.  An experiment is like a metal detector. When there’s valuable treasure close to the surface, it’s an incredible tool that can lead you straight to the gold. […]