Metrics question

Amazon's Monthly Active Users (MAU) have been steadily increasing for the past six months, indicating robust user engagement. Nevertheless, the average sales per user has consistently declined during this period. What might be the reasons behind this trend?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Root-cause / metrics diagnosis: can you separate a numerator (sales) from a denominator (MAU) problem and generate testable hypotheses.

Restate the metric: average sales per user is declining while MAU rises, so the denominator is growing faster than the numerator.
Hypothesis 1: mix shift, new users are lower-intent (browsing, not buying) than the existing base, diluting the average.
Hypothesis 2: existing high-spend users are actually spending less, a real engagement problem masked by new-user growth.
Hypothesis 3: external factors, like a promo period ending, pricing changes, or seasonality (e.g. post-holiday dip).
Segment the data by user cohort (new vs returning, tenure) to isolate which hypothesis is driving the trend.
Recommend the next step: cohort-level average sales trend, not just the blended average, before proposing a fix.

Leads with the mix-shift explanation, since MAU growth diluting a per-user average is the most common cause of this exact pattern.
Proposes cutting the data by cohort tenure, e.g. 'sales per user for accounts older than 6 months' to isolate real engagement decline.
Considers non-obvious causes like a pricing/discount change or a shift toward lower-AOV categories (e.g. more grocery, less electronics).
Avoids jumping to a fix before confirming which segment is actually declining.

Treating this as one root cause instead of laying out 2-3 testable hypotheses.
Not noticing that rising MAU with flat total sales can look like decline purely from mix shift.

Chapters of the AI PM course that teach what this question tests.