Conversion optimisers should pick a VWO alternative by who runs the tests: marketers changing pages in a visual editor, or product teams shipping experiments through code and feature flags. Decide that first, because the tools built for each group work in different ways, then check how each one reports results you can trust.
Who this testing list is for
Conversion rate optimisers and product teams who run A/B tests on landing pages and apps: the marketer trying to lift sign-ups on a campaign page, and the product manager testing a new onboarding flow. Both want a result they can act on, but they work in very different places.
VWO sits in the experimentation and optimisation category. I've described each alternative from its own website and haven't run tests through them, so use this as a shortlist rather than a ranking.
Marketer-led or code-led testing?
Marketer-led page testing. Convert, Crazy Egg, Optimizely, Unbounce and Webtrends Optimize lean towards marketing and website teams: split tests, personalisation, heatmaps and landing pages.
Product experimentation and feature flags. GrowthBook, Kameleoon, Split and Statsig describe experimentation, rollouts, feature flags or product analytics.
Something different. PostHog describes a tool that diagnoses problems, fixes bugs and generates pull requests without being prompted, so read its site closely to see how it fits a testing workflow.
VWO alternatives compared
In no particular order, with each vendor's own description boiled down to a few words.
| Tool | Approach | Good at |
|---|---|---|
| Convert | A/B testing tool | Testing, personalisation and advanced goals |
| Crazy Egg | Visitor behaviour and testing | Heatmaps, recordings, surveys and A/B tests |
| GrowthBook | Warehouse-native experimentation | Open source experiments, feature flags and analytics |
| Kameleoon | AI experimentation platform | Building and rolling out experiments with AI |
| Optimizely | Marketing and digital team platform | Content, testing and personalisation for marketing teams |
| PostHog | Problem diagnosis tool | Diagnosing problems, fixing bugs and generating pull requests |
| Split | Feature management and experimentation | Seeing whether a software change helped or hurt |
| Statsig | Product development platform | Experiments, feature flags, analytics and session replays |
| Unbounce | Landing page builder | Building and A/B testing landing pages |
| Webtrends Optimize | A/B testing and personalisation | Testing and personalising the user experience |
Ten VWO alternatives, in alphabetical order
Unranked, one line each, so you can match a tool to the people who'll run your tests.
Convert
Best for: Optimisers who want split testing, personalisation and advanced goals, with fast support and monthly terms.
Crazy Egg
Best for: Website owners who want to see what visitors do through heatmaps, recordings and surveys, with A/B testing as well.
GrowthBook
Best for: Data teams wanting open source, warehouse-native experimentation with feature flags and product analytics.
Kameleoon
Best for: Optimisation groups that want to build, test and roll out experiments in one place on an AI platform.
Optimizely
Best for: Marketing and digital teams that create content, test and personalise it, and need to show business impact.
PostHog
Best for: Product groups that want a tool that diagnoses problems, fixes bugs and generates pull requests without being prompted.
Split
Best for: Developers using feature flags who want alerts on whether a software change is making things better or worse.
Statsig
Best for: Product teams wanting experimentation, feature management, product analytics and session replays in one toolkit.
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Unbounce
Best for: Marketers building landing pages with AI, templates or drag and drop, then A/B testing them.
Webtrends Optimize
Best for: Businesses that want A/B testing and personalisation, with licensing scaled to their traffic.
Keep search engines in mind while a test runs
One rule matters for every tool here. Google Search Central's guidance on website testing says that showing one set of content to Googlebot and a different set to people is cloaking, which is against Google's spam policies, whether you're running a test or not.
In plain terms, every variant should be served to bots the same way it's served to people. Don't build a rule that hides a test from crawlers or shows them something special, and ask any vendor how it handles bots before you launch a test on pages that bring in search traffic.
Mistakes that waste a test
- Stopping a test the day it looks ahead. Let it run long enough to cover a full weekly cycle.
- Testing tiny changes on pages with little traffic, then reading noise as a result.
- Running two tests on the same page at once without a plan for how they interact.
- Forgetting mobile. Check every variant on a phone before it goes live.
Most bad test results I hear about come from one of these, not from the tool itself. A good testing tool won't save a test that's set up badly, and a simple one won't spoil a test that's planned well, so spend as much time on the plan as on the software.
My advice for teams moving off VWO
Work out who'll run tests day to day, then choose from that group only. If it's a marketer, a visual editor and clear reports matter more than anything else. If it's a product team, look for feature flags and a link to your data warehouse or analytics. Run one real test in your top two options before moving your whole testing plan, and check the result screen makes sense to the people who'll act on it.
For a wider view of testing, see my list of A/B testing tools, and if you want to see what visitors do before you test, these heatmap tools for websites help.
Do you make A/B testing or experimentation software? Tool makers can ask to be considered for a featured place on this list.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
What's the difference between A/B testing and feature flags?
A/B testing shows different versions to different visitors and compares results. Feature flags let developers switch a feature on or off for chosen users without a new release, and many product teams run experiments through them.
Can A/B testing hurt my search rankings?
It can if search engines are treated differently from people. Google Search Central's testing guidance says showing Googlebot different content from humans is cloaking and against its spam policies, test or not. Serve every variant the same way to bots and people.
Do I need a developer to run tests?
That varies by tool, so ask each vendor. Marketer-led tools are described around page testing, while product experimentation tools talk about feature flags and releases, which usually involve developers.
How long should an A/B test run?
Long enough to cover your normal weekly pattern and gather enough visitors to trust the result. Ending early because one version looks ahead is the most common way to get a false result.
