Your customer segments change completely when you re-run the pipeline monthly. Is that acceptable?

hard

Answer

$No, because a segmentation the business acts on has to be stable enough to plan around, and instability means you are describing sampling noise rather than structure.$
$First check whether the instability is algorithmic: k-means with random initialization on data with no strong separation gives different partitions every run, which a fixed seed hides without fixing.$
$Measure it properly with the adjusted Rand index between consecutive runs, and if agreement is low the structure is weak.$
$Options are to reduce k until the solution is stable, initialize from the previous month's centroids so segments evolve rather than being reinvented, or move to a model with an explicit assignment probability so you can see which customers are genuinely borderline.$
$Report the stability number alongside the segments.$

Check yourself — multiple choice

Yes, clusterings always differ
No — measure agreement with the adjusted Rand index, reduce k if it is low, warm-start from last month's centroids, and report stability alongside the segments
Fix the random seed and move on
Re-run until you like the result

Instability signals weak structure; measure it, reduce complexity, and warm-start so segments evolve.

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214 interview questions in this topic.