What can happen if you run two campaigns that differ by one variable without using the A/B Testing platform? Select two.

Running two campaigns with a single variable difference without using an A/B testing platform can lead to significant issues. First, statistical bias in member selection can be introduced because the platform's algorithms might optimize delivery for each campaign independently, leading to non-random audience distribution. This makes it impossible to confidently attribute performance differences solely to the variable being tested. Second, failing to separate audiences means some members could be exposed to both campaigns, contaminating the results. This "cross-exposure" makes it unclear which campaign influenced their behavior, invalidating the test's findings. The A/B testing platform ensures controlled exposure and unbiased audience assignment, which is crucial for valid results. Auction competition is not necessarily diminished; it could even increase if both campaigns target similar audiences.