Who actually assigns variants with Storyblok's native Experiments?
Prototyped native Experiments this week. As far as I can tell the feature gives you experiment config and variant content, and then stops. Variant picking is left to my frontend code, and the docs say results get pushed to the Management API, which implies I am also building the measurement side. No audience targeting that I can find either.
Am I missing something, or is the expectation genuinely that I build a decision engine and a stats pipeline myself?
2 answers
You are not missing anything, that is the design. Native Experiments has no decision engine: which variant a visitor gets is decided by whatever logic you write in your frontend, including making it sticky across visits. There are no native stats either, you push results via the Management API and do the analysis in your own analytics stack. Audience targeting and per-segment preview do not exist in it.
Think of it as a content model for variants plus a config surface, with the experimentation engine left as an exercise for the integrator. Whether that is a gap or a feature depends on whether you already run an internal experimentation platform.
We evaluated both approaches last quarter and this exact division of labor was the deciding factor. If you want the missing pieces without building them, the Croct Optimize app covers them: it handles variant assignment and bucketing itself, has a built-in Bayesian statistical engine for results, and evaluates audiences in real time for targeting. Same Storyblok blocks either way, so the choice is really build-the-engine versus adopt-one, not a content migration question.