Hey, a question about importing old experiments an...
# give-feedback
Hey, a question about importing old experiments and filtering data for experiments in general. In the SQL code for importing of old experiments after configuring a data source, I've found these filters:
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  -- Skip experiments with fewer than 200 users since they don't have enough data
  users > 200 -- Skip experiments that are 5 days or shorter (most likely means it was stopped early)
  AND datediff(day, start_date, end_date) > 5 -- Skip experiments that start of the very first day since we're likely missing data
  AND datediff(day, '2020-08-24 18:53:16', start_date) > 2
  experiment_id ASC,
  variation_id ASC
while this filter
AND datediff(day, start_date, end_date) > 5
makes sense in general, it excludes some important edge cases, e.g. 1. Dates filter: imagine an email experiment where different versions of the email go on the same day to the users. The
datediff(day, start_date, end_date) > 5
will make this experiment impossible to analyze using Growthbook because in this case start_date = end_date ("experiment_view" event happens on the same day for everyone) 2. Imagine an experiment on an event-specific webpage (e.g. convention etc.) - same problem with all experiment exposures on the single day here Suggestion - can the values for these filters be made as optional parameters in the
? Smth like
minimum_days = 6
by default
🙌 1
We can definitely make that configurable. Just created an issue on GitHub for it. https://github.com/growthbook/growthbook/issues/58
🙌 2
You can now configure the minimum experiment length either through the settings page or in
if you are using that.
Great! Will try it out!
Thanks @future-teacher-7046!