Optimizely Web Experimentation is a Winner at 99% Significance
December 11, 2024
Optimizely Web Experimentation is a Winner at 99% Significance

Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Optimizely Web Experimentation
We use Optimizely Web Experimentation as part of our growth and innovation for our digital channels - increasing top of funnel conversion and connecting it to downstream revenue generation impact. We also utilize it on our product org as a design validation and pseudo-feature testing tool. We've got a robust program that delivers 100-150 tests a year and have a high win rate, with testing informing our product roadmap and winning results handed off to product to prioritize and code for production release.
Pros
- Powerful Stats Engine that drives conclusivity of outcomes and helps generate trust in results when shared to leadership and stakeholders.
- Customizable metrics with various tags, properties, and attributes that allow users flexibility in what and how they architect their Optimizely analytics.
- Flexibility for different levels of tech expertise, I live in the tool as an expert JavaScript and front-end developer, someone else might use solely the visual editor to click and make changes without knowledge of how to code.
Cons
- The results view is dense and difficult to package easily for leadership, and when filtering by segment it's hard to read comparative outcomes without clearing or swapping filters
- The organization of experiments and statuses is a cluttered list and the search is limited in use - would love to see that improve with time
- There are so many other MarTech products out there, would love to see more dedicated integrations so we don't have to invest in something like Zapier or Tray to build hacky automations
- We've generated an estimated $12M in revenue (not even annualized impact) and are looking to grow that impact by 20-50% for FY25.
- We've successfully validated bad ideas and avoided development costs in the realm of the hundreds of thousands of dollars.
We have product recommendations live on our website that we tested the implementation of against existing product feeds on our PDPs, leading to a 200% click conversion rate uplift. Using both tools in concert is how we validated the value of the added tool and plan to scale that implementation to create more value in future.
We have built a robust experimentation program, and now in the current state we are seeking to use that as the backbone of our personalization program which we are only now beginning to build. Part of the growth of our experimentation program has been fully utilizing all of the different types of tests, such as A/b testing, multivariate testing, multi-armed bandit testing, and using the stats accelerator in order to quickly generate outcomes. And we are able to use that experience now to help forge the methodology for our personalization program. And the best way for us to know that we are successful is being able to view results on a test by test basis as well as connect those outcomes to larger reporting based out of our data warehouse.
None of them have a best in class stats engine and live within an ecosystem of marketing technology products the way that Optimizely does, so the scalability of using any one of those tools is limited as compared to using Optimizely Web Experimentation.
Do you think Optimizely Web Experimentation delivers good value for the price?
Yes
Are you happy with Optimizely Web Experimentation's feature set?
Yes
Did Optimizely Web Experimentation live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Optimizely Web Experimentation go as expected?
I wasn't involved with the implementation phase
Would you buy Optimizely Web Experimentation again?
Yes

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