Basic A/B testing — split traffic, track conversions, compare — is genuinely simple. Statistically rigorous results at enterprise scale, with feature-flagging and team workflows layered on, is a different, deeper product.
VIBE SCORE 97/100
The parts this build actually needs, each rated on its own — the average is the Vibe Score above.
| Landing page | 99 |
| CRUD database | 95 |
Two real costs, not just "free": the AI agent's own usage, and hosting once it's running. Both are estimated from this app's own effort rating and component list — see the assumptions on the method page.
| AI agent — with a subscription (Claude Pro/Max, Cursor, etc.) | $0 marginal |
| AI agent — pay-per-use API, no subscription | $43–$86 one-time |
| Hosting, once it's running | $0/mo (free tier) |
| Domain name, if you want your own | ~$12/yr |
Optimizely's pricing varies — check the source link on this page to compare against your own build cost.
Borderline. Basic A/B testing — split traffic, track conversions, compare — is genuinely simple. Statistically rigorous results at enterprise scale, with feature-flagging and team workflows layered on, is a different, deeper product.
Optimizely's pricing varies by plan — check the source link on this page for current numbers.
Getting statistical significance genuinely right (avoiding false positives from peeking early, correctly handling multiple simultaneous tests) takes real statistical care beyond a raw percentage comparison Feature flagging at organization scale, with gradual rollouts and instant kill-switches, is real infrastructure beyond a simple A/B split Enterprise permission and approval workflows across large marketing teams are organizational tooling, not a testing feature