Running too many experiments simultaneously is counterproductive: you're unlikely to complete them all, and if you change multiple variables at once, you can't isolate which experiment is actually having an effect; best practice is one experiment at a time, with limited exception for experiments in completely separate life domains (e.g., work productivity and health simultaneously).