Question: A product team evaluates a classifier on four customer segments: commuters, students, households, and enterprise clients. Why might the team combine the four accuracy scores with a weighted average instead of a simple average, and how does that choice affect the usefulness of the final metric?

Sample answer: A simple average gives each segment the same influence, even if the segments differ a lot in traffic, revenue, or strategic importance. A weighted average lets the team assign more importance to the segments that matter most to the product, such as the largest user group or the highest-value customers. This makes the single summary score match the real business objective more closely. It also prevents a very small segment from hiding poor performance on the segment that matters most, or from causing the overall score to swing too much because of a small number of examples.

Key points:

• A simple average treats all segments equally.
• A weighted average lets each segment contribute according to traffic, revenue, or priority.
• The resulting score is more representative of the team’s actual business goal.
• Weighting keeps a small segment from dominating the overall metric.

Rubric: The response must explain the difference between simple and weighted averaging, describe how weights can reflect segment size or importance, and connect the choice of averaging method to alignment with business goals.