Item: Optimizely Feature Experimentation
Rating: 7
Author: Sergio Palomino

Overall Satisfaction with Optimizely Feature Experimentation

Use Cases and Deployment Scope

As the responsible of the experimentation and optimization center of excellence, I work with my team to support product owners in launching experiments through Optimizely. We use the tool to test new features before rolling them out to all users. This allows us to make data-driven decisions, reduce risk, and improve the customer experience. Our main use cases are in product and development, focusing on A/B testing and progressive rollouts.

Pros and Cons

Pros

Works well with Adobe Analytics, making it easier to track experiment results.
Easily test features without needing "a lot" of engineering effort.
Supports feature flags and gradual rollouts, which helps reduce risk when we make the roll out within out different shops

Cons

Calculating economic impact in base to our parameters of the winner ab test
Can improve in the pre analysis before launching the tests
Could improve is in the speed of results reporting

Return on Investment

Converted visitor share
Incremental net revenue
Add to cart visitor share

Usability

I rated it an 8 because, overall, it's a robust and dependable tool, particularly for rollouts and A/B testing.

Alternatives Considered

Adobe Analytics and Adobe Target

not too much experience on that to answer this question

Key Insights

Do you think Optimizely Feature Experimentation delivers good value for the price?

Yes

Are you happy with Optimizely Feature Experimentation's feature set?

Yes

Did Optimizely Feature Experimentation live up to sales and marketing promises?

Yes

Did implementation of Optimizely Feature Experimentation go as expected?

Yes

Would you buy Optimizely Feature Experimentation again?

Yes

Other Software Used

Adobe Target, Adobe Analytics

Likelihood to Recommend

Optimizely is great for gradual rollouts, we use it to release features to a small group, monitor impact, and scale safely. It also works well for quick A/B tests, letting us validate ideas fast with minimal dev effort. It’s less ideal for content-heavy or visual experiments where non-tech users need more hands-on contro

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Optimizely Feature Experimentation review