I wonder if anyone came up with better ideas on having a fixed number of random sample? There are several ideas (e.g. Fixed number Random Sample) and discussions, but nothing seems working very well for me. In general, when you have a big database or list and you need to run it via webhook, or a data management campaign, or some testing, it would be tremendously helpful to be able to throttle and queue it. Thus only fixed number of records will be treated a day. That is what I came up with:
- I tested flow steps: random sample 10% > action; wait 1 day; random sample 10% > action, wait 1 day, etc. This did NOT work, only the first flow step was executed.
- I tested recurrent daily smart campaign with random sample in the flow step, so only 10% will be treated every time the campaign runs (there was a reference to exclude those who have been treated). This somewhat worked, but the size of batches varied from zero to several dozen thousands, so it didn't help a lot.
- Basically, the only consistent way is splitting into lists manually (might be too painful or not viable at all with big numbers).
- Shall I try to run a recurrent daily smart campaign with a random sample in the smart list? (No advanced filters, but can make it a try).
With randomizing and splitting into lists, I found helpful the following:
- If I need to have 0.1% random sample (less then 1%, while the filter accepts only 1-100), you can do 1% random sample, add to a static list, then do one more 1% random sample of the list.
- I've done quite a lot of randomizing based on last name characters and creation date.
(Do you know an average percentage of people in US who have last name starting with R? Well, I do )
What do I miss? Are there better scalable solutions for randomizing and throttling?