/conv/ - Conversion Rate

deciding between multivariate and a/c testing usually comes down to ur traffic volume. multivariate testing lets u see how different combinations of elements work together, but it requires massive amounts of data to reach significance. if u are running small-scale experiments, stick to simple a/c tests on single variables to avoid the noise.
>testing everything at once is a recipe for inconclusive results
the main benefit of multivariate is identifying interaction effects between a headline and an image. however, most people settle for sequential testing because it is much faster to implement and interpret. multivariate is basically just a way to burn budget if you don't have millions of monthly visitors . if you want to automate ur process, you can use simple scripts to track variations via the data layer:

window.dataLayer.push({'experiment_variant': 'variant_b'});

don't try to overcomplicate your testing roadmap by ignoring your actual traffic constraints. focus on high-impact changes first before moving into complex multi-variable setups.