Don’t Rush to Rely on the Magic “One Number” Loyalty Score

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The philosopher’s stone, in Latin philosophi lapis, is a legendary substance
that supposedly could turn inexpensive metals such as lead into gold and/or create an elixir that would make humans younger. It was a longtime
“holy grail” of Western alchemy.

—Wikipedia

The philosopher’s stone was first mentioned in the writings of Zosimos of Panopolis, a third-century mystic and alchemist. Eventually, the philosopher’s stone was thought to represent the force behind the evolution of life and the universal binding power that unites minds and souls. The lore of its amazing properties became the basis, parenthetically, for the first Harry Potter novel and film.

The search for a marketing “Holy Grail”—a measure that would attach real behavioral outcomes to sales, communication and promotional programs—has also been with us for quite some time. Decades ago, marketers began using single-number scores in an attempt to understand the effectiveness of print and television advertising. More recently, the concept of a single metric, which, based on recommendations given to a product or service, can tell corporations and executives how to predict future customer behavior, has been widely endorsed and promoted as a latter-day marketing “philosopher’s stone.”

Just as it’s unlikely that a stone can have magical superpowers, there are flaws, inconsistencies, contradictions and challenges with the thesis that referral and recommendation, or a metric created from it, can consistently decode optimum customer loyalty behavior. I don’t doubt the appeal of ultimate simplicity in the idea of a single measure, but I believe businesses instead should be asking, “Look, is increasing recommendation really the best way to drive business success? Is it going to have more of an impact than reducing customer loss? Is it more powerful than increasing customer volume, cross-sale or share purchased? Is it the best way to go—and in all circumstances?”

Real-world challenges
Recommendations are a key goal, but are they the main thing? Most customer management research practitioners argue that, while recommendation and referral are important (as is an unwillingness to recommend or refer), much more needs to be understood about customer decision and behavior dynamics.

Recommendation is certainly one of the principal outcomes of loyalty behavior, and certain pundits seem to be preaching from bully pulpits that recommendation is a prime indicator—in fact, the single or only predictor—of the construct, itself. There are numerous, serious limitations to this concept. It should be quickly recognized and understood that it’s possible, for example, to incentivize customers, and they will refer once compensated to do so. If companies do that—and it can easily be accomplished—what happens to the value of the metric? It’s very, very strongly compromised.

Is increasing recommendation really the best way to drive business success?

There are many more problems with putting too much emphasis on recommendation and referral. One of these problems is that if other information is available about customer behavior, as it often is through targeted research, the over-focus on a single number suggests that these insights will receive less consideration and relevance. For example, if a company discovers that it has a high incidence of unresolved customer complaints, that serious loyalty-leveraging situation can get brushed aside as executives seek to create ever-higher positive recommendation levels

Also, companies using a single net recommendation “score” should understand that it can be obtained in multiple ways. In other words, a 40 percent recommendation score could be the result of 65 percent positive recommendation minus 25 percent negative recommendation or a 45 percent positive recommendation minus 5 percent negative recommendation. Yet these two net scores represent entirely different customer referral scenarios. Though the first scenario might have some cause for concern because of the level of negative recommendation, the second scenario is far more serious because of the lower level of positive scores, suggesting that many customers are potential candidates for churn.

Additionally, the use of alternative customer research methods to identify key drivers of loyalty—such as multi-question indices and models and probability allocation (assigning probabilities to events, including purchase activity or informal communication)—have been found by numerous customer loyalty research methodologists to correlate much more closely with actual customer behavior than willingness to refer or recommend. While I understand that these approaches lack the appeal of one-number simplicity, I believe they represent far greater accuracy and “actionability.”

Finally, we’ve evolved to a time where most marketers live in a one-to-one customer communications, measurement, management world. Linkage must be made between individual customer-detailed expressions of loyalty and customers’ lifetime value. So, perhaps the biggest challenge with a net recommendation score is that it’s usually presented on a grouped, rather than specific customer, basis. Customer-level information systems can help leverage profile and loyalty research data, enabling marketers to understand behavior on an individual basis; but an aggregated score offers no such flexibility. At the end of the day, this may be one of the measure’s more serious drawbacks.

Magic versus actionability
So marketers really have to understand what brands and products customers would consider (known as the evoked set); what they’re currently using; what their level of favorability is; and what their likelihood of saying positive and negative things about the product is. And if they then build recommendation into that kind of construct, they will have something that’s more actionable.

Here’s the bottom line. It would be attractive to have a single metric, but its analytical limitations can be dangerous. Marketers want to know more about their customers’ perceptions and actions. They need to understand why levels of loyalty behavior are occurring, not just what is occurring, on as sub-segmented a basis as possible. Again, referral and recommendation are important outcomes of loyalty but are not just the end goal, or Holy Grail, in and of itself. Magic and potions may work for Harry Potter; however, marketers must understand customer behavior in the real world.

1 COMMENT

  1. Michael a very intersting article. There has been a lot of publicity recently surrounding the Net Promoter Score and there are plenty of advocates in support. I tend to agree though, that it is a ‘roll-up’ and an indicator of the portfolio of customers, willingness to support a firm.

    Hidden underneath are detractors or those whose needs may be changing and who might therefore seek alternative providers.

    I think that to be of real value one needs to drill down to the underlying reasons for customer attitudes, and then to act on these insights to improve the customer experience and optimise investments.

    I’m a long standing fan of Prof. Stephan Haeckel who talks about the ‘customer-back’ and ‘knowing earlier’ firms. He was first to coin the phrase – ‘the Adaptive Enterprise’. I’ve called it the ‘Heads-up Enterprise’ in the little blog:

    http://www.customerthink.com/blog/the_heads_up_enterprise

    Having the right sensing, analytical and action management capabilities + the leadership and culture to do the right things, are all essential to helping firms adapt based on customer and market feedback.

    The single number is really only the tip of the iceberg. If it were easy wouldn’t we all have done it by now?

    Or to mix my metaphors, it will take a lot more than alchemy to turn base metal into gold.I forsee a lot of hard work and dogged determination being required.

    Jeremy Cox

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