Making it Count: Developing a custom digital metric framework that works

Key Insights

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  NPS often obscures diverse customer experiences by aggregating different user segments into a single score.

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  Custom metric frameworks combining behavioral, attitudinal, and quality-of-experience data yield richer insights than standardized metrics.

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  Separating attitudinal (feelings) and behavioral (actions) metrics avoids the risk of conflating different dimensions of user experience.

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  Quantitative data should be supplemented with qualitative verbatims analyzed via sentiment analysis for fuller context.

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  Business leadership prefers simple headline metrics, so complex multi-dimensional data must be distilled carefully, often accompanied by storytelling.

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  Existing UX metrics frameworks like NASA TLX, SUS, SuperQ, and Google HEART offer valuable components but may need adaptation for specific digital contexts.

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  Designing useful metrics starts by clarifying goals, then defining quantity, signals, timeframe, and scope explicitly.

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  High conversion rates alone can be misleading without considering total volume of conversions and user behaviors in context.

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  Customer sentiment is complex and may not align directly with retention or recommendation behavior, so metrics must capture nuance.

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  Short, targeted surveys on key user journeys help balance depth of insight with user willingness to respond.

Notable Quotes