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:

SELECT
  *
FROM
  __variations
WHERE
  -- 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
ORDER BY
  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

config.yml

? Smth like

minimum_days = 6

by default

We can definitely make that configurable. Just created an issue on GitHub for it. https://github.com/growthbook/growthbook/issues/58

Great! Will try it out!