What is the value of running a true A/B test with campaign experiments?

Analysis of Correct Answer(s)

• In an A/B test, trial campaigns run at the same time as the original campaign, controlling for external factors (e.g. seasonality) that may otherwise bias results.
  • This statement accurately captures the core value of a true A/B test. By running the control group (original campaign) and the test group (trial campaign) concurrently, A/B testing ensures that both groups are exposed to the same external factors. This includes variables like seasonality, economic shifts, competitor activities, news events, or even day-of-week effects. If tests were run sequentially (e.g., original campaign in January, trial campaign in February), any observed difference could be due to these external factors rather than the campaign change itself. Concurrent testing allows marketers to isolate the impact of the specific variable being tested, thereby providing a more reliable and unbiased assessment of its performance. This eliminates confounding variables and provides a clear causal link between the change and the results.

Analysis of Incorrect Options

• A/B tests can help marketers understand if their trial campaign drove user action that wouldn’t have occurred otherwise.

  • While A/B tests do help attribute user action to a campaign, this statement describes a result of A/B testing rather than its unique mechanism for achieving valid results. The primary value proposition of an A/B test is controlling for external variables through concurrent execution, which is what enables accurate attribution and understanding of "what wouldn't have occurred otherwise." Without that control, the attribution would be unreliable. Therefore, it's not the most precise or complete description of the fundamental value.

• An A/B test is designed to test multiple variables at one time, allowing advertisers to learn and quickly adjust their campaigns based on findings.

  • This option describes a multivariate test (MVT), not a standard A/B test. A true A/B test (or A/B/n test) is designed to test one primary variable or a single, distinct version against another (e.g., Version A vs. Version B). The goal is to isolate the impact of that specific change. Testing multiple variables simultaneously without proper experimental design often leads to complex interactions that are difficult to interpret or requires a significantly larger number of variations, which is characteristic of MVT.

• An A/B test runs one campaign at a time, allowing a true ramp-down period between each testing timeframe to declutter results.

  • This describes sequential testing or "before and after" comparisons, which is precisely what A/B testing aims to avoid. The core principle of A/B testing is concurrent execution of different variations to ensure both groups are subject to the same external conditions. Running one campaign at a time makes results susceptible to bias from changing external factors (e.g., seasonality, market trends, competitor actions) that occur between the test periods. A "ramp-down period" is not a standard practice in A/B testing methodology; instead, the focus is on simultaneous operation.