Testing · head to head
Eppo vs Kameleoon
Eppo
Testing
Warehouse-native experimentation and feature flagging, now sold as Datadog Experiments
- From
- On request
- Rated
- -
Kameleoon
Testing
A/B testing and feature experimentation with a hybrid client and server-side engine
- From
- On request
- Rated
- -
The short version
- Each has a real cost: Eppo datadog acquired Eppo in May 2025 and is folding it into Datadog Experiments, so you are now buying a component of an observability suite rather than an independent product, and roadmap priorities will follow Datadog’s bundle strategy.; Kameleoon no rate card is published. Reported entry pricing around several hundred euros a month for the limited prompt-based tier comes from third parties rather than Kameleoon, so any budget you build before contacting sales is a guess.
- They diverge on capability: Eppo covers Warehouse-native analysis, Kameleoon covers Visual A/B test editor.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Eppo and Kameleoon actually diverge.
Identical on both: starting price (On request), pricing model (quote), free tier (No), user rating (Not yet rated), category (Testing).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Eppo
- Warehouse-native analysis
- Sequential testing
- CUPED variance reduction
- Feature flagging
- Metric governance
- Contextual bandits
- Experiment scorecards
- Heterogeneous effect analysis
Only in Kameleoon
- Visual A/B test editor
- Server-side experimentation
- Feature flags
- Anti-flicker engine
- AI personalisation
- EU data hosting
- Shared audiences
- Statistics options
What people use each for
The jobs each tool is most often brought in to do.
Eppo
- A company whose experiment results have repeatedly disagreed with the analytics team’s own numbers because the two systems define revenue differentlynot Kameleoon
- A product organisation with low traffic on a key surface that needs variance reduction to reach a decision in weeks instead of monthsnot Kameleoon
- A team that must keep user-level event data inside its own warehouse for regulatory reasons and cannot ship it to a third-party analytics vendornot Kameleoon
- An existing Datadog customer consolidating product analytics, feature flags and experimentation onto one vendor agreementnot Kameleoon
Kameleoon
- A European retailer whose legal team requires EU-hosted experimentation data and has ruled out US-only vendorsnot Eppo
- A team running both marketing page tests and product feature rollouts that wants one results engine rather than two disagreeing onesnot Eppo
- A media site where client-side flicker on a test variant is visibly damaging the reading experiencenot Eppo
- An organisation re-tendering experimentation after Optimizely or VWO pricing changes and wanting an independent European vendornot Eppo
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Eppo
- Datadog acquired Eppo in May 2025 and is folding it into Datadog Experiments, so you are now buying a component of an observability suite rather than an independent product, and roadmap priorities will follow Datadog’s bundle strategy.
- No pricing is published anywhere, before or after the acquisition; the site offers only a demo request, so cost cannot be estimated without a sales process and is likely to be quoted alongside a wider Datadog contract.
- Because analysis runs in your warehouse, Eppo shifts compute cost onto your Snowflake or BigQuery bill; a large experiment programme with frequent recomputation raises a line item that does not appear in the Eppo quote at all.
- Results are only as fresh as the pipeline feeding the warehouse, so teams used to near-real-time dashboards from an event-based tool will wait hours for updated numbers, which slows down the fast iteration loops some product teams rely on.
- It assumes a mature data stack with a warehouse, defined metrics and analysts who can maintain them; an organisation without that has to build the data foundation first, which makes the real adoption cost far larger than the licence.
Kameleoon
- No rate card is published. Reported entry pricing around several hundred euros a month for the limited prompt-based tier comes from third parties rather than Kameleoon, so any budget you build before contacting sales is a guess.
- Web experimentation, feature experimentation and personalisation are licensed as separate capabilities, so the unified platform story costs materially more than the entry configuration most buyers are first quoted.
- The partner and agency ecosystem is concentrated in France and continental Europe; a buyer in North America or Asia will find fewer implementation specialists and less community knowledge than for Optimizely or VWO.
- The integration catalogue is smaller than the market leaders, so a stack built on less common analytics or CDP tooling may need custom work that a larger vendor would cover natively.
- Client-side visual testing still carries the structural problems of the approach, including performance cost and single-page-application fragility; the anti-flicker engine reduces the symptom but does not remove the dependency on the DOM staying stable.
Pricing, plan by plan
Eppo
On request- Eppo, now Datadog Experiments$undefined/year
- Warehouse-native experiment analysis
- Feature flagging and assignment
- Sequential testing and CUPED variance reduction
Kameleoon
On request- Kameleoon$undefined/year
- Priced on monthly tested users and features licensed
- Web experimentation, feature experimentation and personalisation licensed separately
- Free trial of the prompt-based experimentation feature, with data not retained afterwards
Which should you pick?
Choose Eppo if
- You need warehouse-native analysis.
- You work on Web, Cloud.
- You also want sequential testing.
Choose Kameleoon if
- You need visual a/b test editor.
- You work on Web, iOS, Android.
- You also want server-side experimentation.
Questions people ask
- Is Eppo or Kameleoon better?
- Neither clearly leads. Eppo starts at On request and Kameleoon at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Eppo or Kameleoon?
- Eppo starts at On request and Kameleoon at On request.
- Does Eppo or Kameleoon run on more platforms?
- Eppo runs on Web, Cloud. Kameleoon runs on Web, iOS, Android.
- What is Eppo best used for?
- Eppo is most often used for a company whose experiment results have repeatedly disagreed with the analytics team’s own numbers because the two systems define revenue differently, a product organisation with low traffic on a key surface that needs variance reduction to reach a decision in weeks instead of months, a team that must keep user-level event data inside its own warehouse for regulatory reasons and cannot ship it to a third-party analytics vendor, an existing datadog customer consolidating product analytics, feature flags and experimentation onto one vendor agreement. Of those, a company whose experiment results have repeatedly disagreed with the analytics team’s own numbers because the two systems define revenue differently and a product organisation with low traffic on a key surface that needs variance reduction to reach a decision in weeks instead of months are not what Kameleoon is typically brought in for.
- What can Eppo do that Kameleoon cannot?
- Eppo covers Warehouse-native analysis, Sequential testing, CUPED variance reduction, Feature flagging. Kameleoon covers Visual A/B test editor, Server-side experimentation, Feature flags, Anti-flicker engine.
Answered from the vendors’ own pages
Eppo: Is Eppo still a separate product?
It is still sold and supported, but Datadog acquired it in May 2025 and it is branded as Datadog Experiments. Buy it expecting a Datadog product roadmap.
Kameleoon: Does Kameleoon publish pricing?
No. Pricing depends on monthly tested users and which capabilities you licence, and requires a sales conversation.
Eppo: What does it cost?
Nothing is published. There is no pricing page, only a demo request, and pricing is now likely bundled into a Datadog agreement.
Kameleoon: Can I keep data in the EU?
Yes. EU hosting and a GDPR-first consent model are among the main reasons European buyers shortlist it.
Eppo: Does it need a data warehouse?
Yes. Warehouse-native analysis is the whole architecture. Without Snowflake, BigQuery, Redshift or Databricks there is no product.
Kameleoon: Does it do feature flags as well as A/B tests?
Yes, through server-side SDKs, sharing audiences and results with the visual testing side.
Eppo: Does it include feature flags?
Yes. Assignment and measurement come from the same system, which is the main reason teams pick it over pairing a flag tool with a separate analysis tool.
Kameleoon: How does it compare with Optimizely?
Similar capability at a smaller scale. Kameleoon's advantages are European data residency and an independent vendor; Optimizely's are ecosystem size and partner availability.
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