Optimizely vs Eppo
Feature checklists rarely decide anything. What decides it is the pricing metric, who has to write the tests, and which limitation you can live with.
Entry price
Quote on request
Quote onlyQuote on request
Quote onlyWhat drives the bill
The metric that actually scales your invoice.
Enterprise annual contracts, commonly in the tens of thousands and up. Priced by traffic and modules.
Quote-based, generally aimed at companies with a data team and a warehouse already in place.
Free tier
No free tier.
Free tier available for small teams.
Open source
Self-hostable
No-code authoring
Languages
Platforms
Fits teams
Adoption
Widely used
Optimizely · since 2010
Established
Eppo (Datadog) · since 2020
Strengths
- The most capable visual editor for non-technical experiment authoring.
- Deep personalisation and audience-targeting features.
- Established statistics with sequential testing, so peeking is handled correctly.
- Statistically rigorous — sequential testing, CUPED and diagnostics are core, not add-ons.
- Metrics defined once in the warehouse and reused across every experiment.
- dbt integration fits existing analytics engineering workflows.
Limitations
- Expensive, with a suite-oriented sales motion that pushes adjacent products.
- Client-side testing causes flicker and is increasingly blocked by browsers and blockers.
- Heavyweight for teams that only need a handful of experiments.
- Requires a warehouse and a data team; not usable by a product manager alone.
- Feature-flagging capability is lighter than dedicated flag platforms.
- Now part of Datadog, which changes the strategic picture.
Best for
Large marketing organisations running continuous experimentation on high-traffic sites.
Data-mature organisations where experiment results must withstand scrutiny.
All of these integrate with: Segment, Snowflake, Slack.
Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.