# Safe to change traffic allocation on a running experiment?

Asked by Aksel Berg on 2025-04-16. Tags: ab-testing, methodology.

We are one week into a headline experiment and variant B is showing an early
lead. In the tool we used previously I could ramp a promising variant from
50 to 80 percent mid-flight without any warnings, and we did so regularly to
limit revenue exposure.

I do not see an obvious way to do the same in Croct. Is this supported, and
if not, what is the recommended procedure when a variant looks strong early?
Budget-wise I would rather not keep half the traffic on a likely loser for
another two weeks.

## 1 answer

### Answer from hannah_cro (2025-04-17)

It is deliberately discouraged rather than missing. Changing the traffic
distribution, or adding and removing variants, during a running experiment
invalidates the statistics. The problem is a Simpson's paradox style
time-window bias: visitors who arrived before the change and after the
change are different populations (different days, campaigns, weekday mix),
and once the split changes those populations are weighted unevenly across
variants. A tool that lets you ramp mid-flight without warnings does not
make the bias go away, it just never surfaces it in the results.

The supported paths are:

1. End the experiment and roll out the current winner to 100 percent.
2. Start a fresh experiment with the new split if you still want to keep
   measuring.

Both can be done from the dashboard without code changes, so pausing an
experiment or rolling out a winner does not need a developer. If B really
is ahead, the honest move is to let it finish cleanly and then roll it
out, which also limits your exposure without biasing the numbers.