Uneven A/B testing — 90% to one branch, 10% to the other
Set a 50/50 distribution in or Assign Manager 50/50 for two operators — but you see 90% of leads going one way and 10% the other. This is not a bug or a misconfiguration — it is statistically normal f
Set a 50/50 distribution in A/B Router — Random Distribution or Assign Manager 50/50 for two operators — but you see 90% of leads going one way and 10% the other. This is not a bug or a misconfiguration — it is statistically normal for small samples.
Why this happens
Any random distributor works like flipping a coin for each lead. Over thousands of flips, the ratio evens out to 50/50. Over a dozen, it may turn out to be 7/3, 8/2, or even 10/0. This does not mean “the coin is biased” — it means “there have not been enough flips.”
In simple terms: to reliably display a 50/50 distribution, you need at least 200–500 leads through the A/B step. With 20 leads, you may see 14/6 (a “70/30” ratio), and this will be within the normal range. With 1000 leads, a difference between 50/50 and 51/49 is already informative.
The same applies to Assign Manager
If Assign Manager — chat distribution is set to 50/50 for two operators, but one received 8 chats out of 10 — with a sample size of 10, this is normal. After 200 chats, the difference will even out. If an operator complains about overload, let 100+ leads pass through the distribution before changing the settings.
How to check that everything is okay
Open analytics
For A/B Router — Steps Conversion — funnel by flow steps (you can see how many passed through each branch). For Assign Manager — Chats — conversation analytics (chat distribution among operators).Wait for enough volume
Wait until at least 200 leads have passed through A/B Router. If you get 30 leads per day, that is a week of waiting. Until then, do not draw conclusions about a “broken” distribution.Compare the numbers
If, with 200+ leads, the distribution differs significantly from the configured one (for example, you set 50/50 but got 70/30), then it makes sense to take a closer look at the config. Until then, it is statistics, not a bug.
To build an A/B sample faster
Test hypotheses where there is a lot of traffic. In cold tests with 5 leads per day, any A/B will be “unbalanced” — you will spend a week and not get an answer. If there is a new launch with a large flow, it is better to test hypotheses there.
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