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Making it Count: Developing a custom digital metric framework that works
Summary
NPS, SUS, HEART, CSAT, CES, CLI—the list of ambiguous acronyms goes on and on. Companies are under more pressure than ever to measure and quantify their results and their interactions with customers, but finding the right metric and the right approach is a challenging process that risks leaving key factors behind as you commit to one sole standard. However, what if there is another way to measure digital transformation and how people see your services? This is what this presentation will focus on. You will learn how to navigate the pitfalls of standardized metrics—with their pros and cons—and learn how to build and implement a custom metric framework that incorporates the best aspects of Net Promoter Score, Customer Effort Score, System Usability Scale, and other, into one cohesive and modern whole aimed at developing the actionability and traceability of your operations and customer services. Attendees takeaways include: how to develop a custom framework without losing benchmarking capability, identifying gaps and needs from this framework that is not focused solely on operational numbers, and how to wade through the murky waters of digital experience quantification. Bring your best questions and leave with actionable insights that you can put in use immediately.
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
"A user-centered measurement should not be one dimensional because people are complex."
"NPS scores can rise overall, yet new and existing customers might have completely different views that get obscured."
"A metric is usually the result of a relation between two measures, not interchangeable with a measure itself."
"Customers tend to inflate negative feelings in surveys, but that doesn't always reflect their actual behavior."
"We aim to keep the reporting simple for stakeholders while incorporating multiple data points in the background."
"Combining behavioral and attitudinal data helps us understand not just what users do, but how they feel about it."
"We use sentiment analysis on verbatims to quantify positive, neutral, and negative customer feedback over time."
"Designing a metric starts with the goals, not the metric itself."
"Conversion rate alone isn’t sufficient; total conversions and traffic volume also matter."
"Including human stories alongside numbers helps business leaders grasp the complexity behind the metrics."
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