How to choose scalable customer experience metrics

How to choose scalable customer experience metrics


Part of a new MEX series highlighting compelling case studies which catch our eye. Follow @mexfeed or by signing-up for the weekly email newsletter.

Our case study of the week is this long-form article from Ericsson’s research team, offering a blueprint for scaling customer experience measurement to massive networks while retaining individual-level detail.

This is a macro challenge in the world of experience design, as large companies struggle to balance the depth of insight from small scale, but time consuming qualitative approaches against impersonal trends in larger data sets.

A true understanding of customers as individuals – and the ability to respond to them as such – requires a mix both approaches, but the key is knowing which to rely on and when.  It was a theme which also emerged in episode 27 of the MEX podcast, my conversation with Alex Genov, Head of UX Research at Amazon-owned online retailer Zappos.

Jörg Niemöller, Nina Washington and George Sarmonikas of Ericsson explain the dangers of amplifying reliance on a single metric, like the popular ‘net promoter score’ (NPS), and examine how to develop a range of metrics appropriate to specific aspects of the user experience.

“…individual users are never truly objective, and a subjective individual user might not always feel satisfied – even when experiencing good service. Understanding why this is the case is essential to developing customer experience awareness and gaining the insights required to make the right decisions to actively manage the user’s perception.”

Their tools include this 6 point checklist for determining the nature of customer metrics:

  1. Scope: Does the score reflect an insight at the individual user level, for a group of users, or for an entire organisation?
  2. Outreach: How many users are included?
  3. Subjectivity: Does the insight reflect an objective fact or a subjective perception?
  4. Predictive: Is the insight directly measured or the result of a predictive model?
  5. Latency: How quickly does the score need to reflect an experience?
  6. Frequency: How often is an update of the score needed?
In addition, they offer a 22 point model for understanding a customer’s complete journey, from pre-acquisition to churn management, developed as part of a TM Forum working group:
TM Forum's Experience Lifecycle Model
I’ve selected it as our case study of the week for reasons of both process and content:
  • It draws on a collaborative, cross-industry process under the auspices of TM Forum. The balance and refinement afforded by that iteration is evident.
  • The content they share is detailed and practical, providing sufficient explanation to begin formulating a measurement strategy appropriate to your own challenges.

Part of a new MEX series highlighting compelling case studies which catch our eye. Follow @mexfeed or by signing-up for the weekly email newsletter.

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