What sequence should you follow to investigate declining engagement?

• A. Review metrics, form hypotheses, run experiments, measure results.
• B. Randomly change product.
• C. Increase marketing spend only.
• D. Delay actions.

Answer: (A)

Investigating declining engagement works best as an evidence-driven loop: start by reviewing the relevant metrics to understand what’s happening and where the drop is strongest, then form testable hypotheses about possible causes, followed by running controlled experiments to test those ideas, and finally measuring the results to determine what actually helped (or didn’t) and to guide the next steps. This sequence creates a clear diagnostic path—from data to explanation to evidence-based action—and helps you quantify impact rather than guess.

Think of metrics as the signal that points you to where to look. Forming hypotheses turns that signal into testable causes—like onboarding friction, feature changes, or seasonal effects. Experiments, preferably controlled or A/B tests, give you causal evidence about whether a change improves engagement. Measuring results closes the loop by confirming the effect size and informing the next iteration.

Briefly, other approaches skip essential parts of this process: random changes lack a purposeful basis and can mislead you; simply increasing marketing spend might boost some numbers but doesn’t diagnose or fix underlying engagement issues; delaying actions loses valuable learning time and can let the problem grow worse.