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its technically possible to recreate our hashing algorithm with SQL, but it would only work for extremely simple use cases and will likely introduce a lot of variance into your test results. The odds of making a mistake are very high. The main issue is that you usually only want to include a user in the analysis if they actually see the experiment. So if you only run an experiment on a few pages, or a user doesn't visit your site while your experiment is running, you will add a lot of noise by including them in your analysis. Also, you usually only want to include metric conversions that happen AFTER viewing the experiment. To do that, you don't just need the hash value, but also the date they say the experiment. The other issue is with how the hash value maps to a variation. If you always do 50/50 tests on 100% of traffic it's easy (hash<0.5 is control), but if you ever run 3-way tests or use a different traffic split it will be difficult to model in SQL. That's why we recommend firing a dedicated event when someone views an experiment with a timestamp and the variation they saw. It's much more reliable.