A company launches a Recommendation activity for returning users. Metrics indicate low engagement with recommended items. What should be the next step?

The correct answer is A. Adjust the recommendation algorithm. When a Recommendation activity shows low engagement with recommended items, the root cause is that the recommendations themselves aren't resonating - meaning the algorithm is the problem to fix. Adjusting the algorithm (A) directly targets the issue by improving relevance, person

Optimization and Analysis

Question

Options

AAdjust the recommendation algorithm
BIncrease the sample size
CExpand the test duration
DEnd the activity

How the community answered

(46 responses)

A
83% (38)
B
2% (1)
C
4% (2)
D
11% (5)

Explanation

When a Recommendation activity shows low engagement with recommended items, the root cause is that the recommendations themselves aren't resonating - meaning the algorithm is the problem to fix. Adjusting the algorithm (A) directly targets the issue by improving relevance, personalization, or ranking logic.

Why the distractors are wrong:

B (Increase sample size) - Sample size addresses statistical confidence, not relevance. More users seeing bad recommendations won't improve engagement.
C (Expand test duration) - More time doesn't fix a flawed algorithm; it just prolongs poor performance.
D (End the activity) - Ending prematurely discards a viable channel; the activity has potential, it just needs tuning.

Memory tip: Think "diagnose before you quit." Low engagement = wrong recommendations = fix the engine (algorithm), not the experiment parameters.

Topics

#Recommendations#algorithm adjustment#engagement metrics#optimization

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