Great product
November 20, 2024
Great product

Score 7 out of 10
Vetted Review
Verified User
Overall Satisfaction with Optimizely Web Experimentation
At Zoom, we use Optimizely Web Experimentation to optimize user acquisition, conversion, and engagement on our website and product flows. It helps us test and iterate on pricing pages, onboarding journeys, and feature visibility to address key business challenges like increasing paid upgrades, improving activation rates, and driving monetization strategies for our freemium and Pro plans.
Pros
- Easy analysis of data
- Easy stat sig
- Eeasy trends of data
Cons
- It’s difficult to go from results to the different details about the test.
- The most organization of tests is difficult to scan through
- Stat sig doesn’t seem to be accurate
- Increased Conversions/Revenue: Successful experiments on pricing page layouts and onboarding flows have led to measurable increases in free-to-paid upgrades, directly boosting revenue from Zoom Pro subscriptions
At Zoom, we primarily use Optimizely Web Experimentation in conjunction with Optimizely Feature Experimentation. This combination allows us to test and optimize both web interfaces and in-product features simultaneously. For example, while testing pricing page designs on the website, we also experiment with feature visibility and functionality within the product to ensure a cohesive experience across touchpoints, ultimately driving higher upgrade and engagement rates.
Using multiple Optimizely products together, such as Web Experimentation and Feature Experimentation, has allowed us to align web and in-product experiments, creating a seamless customer experience. This has led to higher conversion rates, as we can optimize the entire user journey from the website to product usage. It has also improved decision-making efficiency by providing unified insights across channels, accelerating our ability to deliver impactful changes that drive revenue growth.
Using Optimizely Web Experimentation as an all-in-one platform has streamlined our workflow at Zoom, allowing us to design, launch, and analyze experiments without relying on multiple tools. This has saved time, reduced errors, and improved collaboration across teams. The integrated analytics provide clear, actionable insights, enabling us to quickly iterate on experiments and make data-driven decisions that directly improve conversion rates and user engagement.
Optimizely is more user-friendly and cost-effective, ideal for experimentation-focused teams, while Adobe Target excels in advanced personalization and seamless integration within the Adobe ecosystem, making it better suited for large enterprises.
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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