Which metric helps infer whether customers find the product useful and whether actual usage meets expectations by features?

• A. Usage-Index, by features
• B. Net promoter score
• C. Cumulative flow
• D. Burn-down chart

Answer: (A)

The main idea here is to measure whether customers actually find the product useful and whether how they use it matches what was expected, at the level of individual features. A metric that does this is the Usage-Index by features. It combines how often a feature is used with how useful users perceive that feature to be. With this, you can see which features deliver value in practice and whether real usage aligns with your expectations for each feature.

If a feature has high usage and high usefulness, you’re seeing strong validation that it meets customer needs. If usage is high but usefulness is low, that signals friction, misinterpretation, or a need to adjust how the feature is presented or integrated into workflows. If usage is low but usefulness is high, adoption barriers may exist—perhaps discoverability, onboarding, or marketing needs improvement. This kind of metric directly informs prioritization and refinement focused on value delivery.

Net Promoter Score gauges overall willingness to recommend, which reflects customer sentiment but not how features are used or how useful they are. Cumulative flow tracks the movement of work items through a process, not customer value or feature-specific usage. A burn-down chart shows progress toward completing a sprint, not whether customers find the product useful or how feature usage measures up to expectations.

So, the most relevant metric for inferring usefulness and actual feature usage relative to expectations is the Usage-Index by features.