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An overall review and critique of net scores, Part 2

Last week, I discussed some of the issues we need to be aware of when considering the use of net scores. Before moving forward, let’s be clear – there are no bad metrics as long as they meet a number of criteria:

  1. The metrics need to resonate within your organization – They need to be understood, accepted, and embedded in the culture.
  2. The metrics must create an impetus for action – Score-keeping in and of itself is neither strategic nor imperative; for metrics to be valuable, they must facilitate action in a way that provides guidance on where, how, and how much to change.
  3. The metrics must link to business outcomes – This seems obvious, but it is a step that many companies overlook. It is tempting to use conventional wisdom as our proof point; in other words, if it makes sense that loyal customers (or satisfied customers, or Promoters, or committed customers, etc.) buy more, then that should be proof enough. Not so – to borrow a quote from Ronald Reagan, we should trust but verify. Making certain our metrics link to hard business outcomes ensures that the action we take today will yield the results we are looking for tomorrow.

While we have clients that have adopted a variety of metrics – including net scores and multi-metric indices – most clients have preferred to focus on Top 2 box scores or means. Here is some food for thought on the topic of Top 2 box and mean scores:

  •  Top 2 (or Bottom 2) box scores are intuitively easy to understand; for example, an 80% top two box on an Excellent-Poor scale means that 80% of customers score us as either Excellent or Very Good. Moreover, we immediately know that 20% of the customers rate us Good, Fair or Poor. Of course, this presents a challenge in that we don’t know how the 20% are dispersed across Good, Fair and Poor – this is meaningful, as you would likely interpret a customer rating you “Poor” differently than one rating you “Good.”
  •  Means offer the advantage of considering all scale points, but are harder to interpret – for example, if I score a 4.2 mean on an Excellent – Poor scale, how do I interpret this? In addition, while the mean considers all scale points, it does not address the distribution – in other words, even when we know the mean, we don’t know anything about how the scores are dispersed across the scale (we need the standard deviation for that).
  • When Top 2 performance gets to the point that it’s too large to be meaningful, many clients migrate to a top-box score metric. “Excessive” top 2 box scores are also an indicator that we may want to revisit the model to ensure that we are using the best metrics to predict future behavior.

For programs that have an underlying predictive analytic model (i.e., one that shows how customer sentiment drives customer purchasing behavior), it is important to consider how your metrics of choice align with the statistical model. In most cases, means and Top 2 box scores are suitable metrics to use that complement more complex predictive models.

Ultimately, we would advise our clients that the best metrics offer actionability while communicating a core central message in a motivational way.

Mark Ratekin
Sr. Vice President, Resource Management and Consulting Services

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