
Operations
Part of Reading ecommerce conversion optimization with a skeptical eye
Conversion tools compared: what a buyer trial actually reveals
A buyer trial of Optimizely, VWO, AB Tasty, Convert and Kameleoon shows what each tool does, what each costs, and where a store gets stuck on setup.
What to take away
- Run one identical task list through every finalist before you sign anything.
- Test assignment, event reconciliation, rollback and raw export, not the visual editor.
- Ask for the exit cost in writingcode removal, data return and notice period.
- Score governance and accessibility separately from convenience.
- Re-run the trial after any pricing, ownership or API change.
Ecommerce conversion optimization tools split into four jobs: experimentation, analytics, personalization and session review. Most stores need one from each group, not five from one. Write the job down before you take a demo.
The five tools compared here: Optimizely, VWO, AB Tasty, Convert and Kameleoon. All five run web experiments. They differ on pricing model, data handling and how much engineering they assume.
Optimizely, VWO, AB Tasty, Convert and Kameleoon, tool by tool
Optimizely runs web and feature experimentation with a rollout layer, so a winning variant can ship as a flag. Pricing is quoted per traffic and seats. Enterprise agreements typically run into the thousands of dollars a month. Suits teams with engineering support.
VWO covers web, mobile and server-side testing plus surveys and heatmaps. It publishes a free plan and paid tiers priced by monthly visitors; paid plans typically start in the low hundreds of dollars a month. Suits mid-market stores that want testing and research on one bill.
AB Tasty pairs testing with personalization and AI-ranked variations, and its Flagship product handles feature flags and releases. Pricing is quoted, scaled by traffic and campaign volume. Suits retailers with steady traffic and a merchandising team.
Convert sells experimentation with a privacy and compliance posture, built on consent-aware tracking and a server-side option. Larger accounts are quoted; published entry plans in this category typically start in the low hundreds of dollars a month. Suits regulated or consent-sensitive catalogs.
Kameleoon combines A/B testing, feature flags and predictive targeting from one SDK, so web and server-side tests share a definition. Pricing is quoted by monthly visitors and seats. Suits teams already running feature flags in production.
Vendors repackage tiers often. Get the current number from the vendor in writing, with the traffic tier and seat count attached.
What it does
- Optimizely
- Web and feature experiments with rollout flags
- VWO
- Web, mobile and server-side tests, surveys, heatmaps
- AB Tasty
- Tests, personalization, AI-ranked variations, Flagship flags
- Convert
- Consent-aware experiments and server-side tests
- Kameleoon
- Tests, feature flags and predictive targeting from one SDK
Pricing model
- Optimizely
- Quoted per traffic and seats
- VWO
- Free plan plus published tiers
- AB Tasty
- Quoted by traffic and campaigns
- Convert
- Quoted above entry tiers
- Kameleoon
- Quoted by visitors and seats
Who it suits
- Optimizely
- Teams with engineering support
- VWO
- Mid-market stores
- AB Tasty
- Retailers with steady traffic
- Convert
- Consent-sensitive catalogs
- Kameleoon
- Teams already running feature flags
What the trial should check
- Optimizely
- Who removes the flags after the test
- VWO
- Snippet load cost and consent handling
- AB Tasty
- Whether audience rules match in editor and report
- Convert
- Events for visitors who decline the first consent layer
- Kameleoon
- SDK version pinning across web and server
As of 2026, a single low-traffic tool typically costs about $100 to $500 a month. A mid-market stack of testing plus personalization commonly runs $1,000 to $5,000 a month. Monthly visitors, seats, server-side events and support drive the range.
One trial, every finalist
Give each tool the same synthetic store task, and work through it in order.
- Run a customer-level A/B test across repeat sessions.
- Delay an event on purpose.
- Cancel an order mid-flow.
- Break a variant.
- Remove a user's access.
- Export the record.
- Disable the integration.
Watch what happens, not what the deck says.
| Check | What you are looking for |
|---|
One trial, eight checks
- Assignmentidentity stays in one variant
- Exposuresee who received the change
- Metricskey event reconciles with order
- Qualityimbalance, missing data, broken variants
- Releasepause, roll back, keep evidence
- Accessleast privilege, recover ownership
- Exportraw data, config, definitions
- Exitcode out, business records stay
A feature earns credit only when an intended user finishes the task safely. Save the tested plan and its date.
What the trial usually exposes
Assignment bugs and missing exports are the two failures that end trials early. A visual editor that feels smooth will not compensate for either.
Map data fields, recipients, regions, retention and deletion. Inspect consent and identity behavior. Check accessible authoring and variant output. Then price licenses, implementation, traffic, seats and support together.
Ask each vendor for the exit cost in writing: who removes the code, how long the notice period runs, and how you get your data back. Vendor decks tend to leave that line out.
Test the operating burden
The GOV.UK technology selection guidance asks for adaptable choices, data control, security review and whole-life cost. Those questions transfer to ecommerce conversion optimization tools. They are not endorsements of any product.
The GOV.UK open standards guidance ties open standards to interoperability and less supplier dependence. Test whether ecommerce conversion data and definitions move between systems, including Optimizely, VWO, AB Tasty, Convert and Kameleoon. Keep the page's UK public-service context in view.
Test the operating burden
- Give every tool the same source sample
- Assign identical roles and required output
- Set the same failure case and export task
- Measure setup time and recurring labor
- Measure specialist help and correction work
- Measure shutdown effort
Keep the evidence beside the decision
Record rejected options and the chosen path. The constraint that ruled a tool out may change next year.
Use the same definitions in the interface, the export, the meeting note and the correction log. Close unused reports and permissions when the decision cycle ends. Set the next review date and name the change that triggers an earlier one.
Common questions
What is the best CRO tool?
There is no universal winner. Pick the smallest set that passes your research, experiment, data, access and exit tests, then re-test it when pricing or ownership changes.
What do these tools cost?
As of 2026, entry plans typically start between $100 and $500 a month. Optimizely, AB Tasty and Kameleoon quote enterprise pricing; VWO and Convert publish entry tiers.
Can a tool guarantee valid experiments?
No. People stay responsible for design, implementation, assumptions, analysis and the decision that follows. A platform can make a bad test easier to run.
Who should own the account?
The store. Keep administration, recovery, billing and data in your own hands. Keep code, records, exports and vendor revocation in your own hands. Do not leave these with the agency.
How often should we re-run the trial?
After any pricing, ownership, API, privacy or security change, and at least once a year. A current product page does not promise the same function or price next year.







