Measuring ROI of Customer Centricity-Historical Correlations
A common challenge of chief customer officers and other customer executives is the need to prove the ROI of customer centricity. For better or for worse, business executives are primarily interested in increasing revenue, decreasing costs, and mitigating risk. To effectively demonstrate value, customer executives need to show how their customer initiatives impact one or more of these key factors.
One of the easiest and most powerful ways for customer executives to demonstrate value is to examine historical trends of loyalty and revenue/profits, especially for key customers. Assuming that you have a history of loyalty survey data (or even satisfaction survey data), correlate the incremental revenue (or better yet, if you have it, the incremental profit) of a customer with improving loyalty measures over time. Some local improvements may be due to a change in customer leadership or an improved sales relationship, making it necessary to examine multiple customers in aggregate and by segment. Start with the key accounts, as these accounts are supposedly enjoying the greatest attention and perhaps unwittingly becoming the most loyal.
It may also be helpful to examine the opposite; what is the incremental loss as loyalty erodes? If you plot for each of your customers their revenue (or profits) and their loyalty score over time and notice a downward trend, the negative proves the loyalty-profit correlation in reverse, and elevates the opportunity for increasing investment to stop the bleeding.
There may not be perfect correlations. Satisfaction and loyalty are subjective measures of an emotional state and although loyalty correlates well with increased revenue it isn’t as strong as customer engagement, which measures actual customer behavior. As well, without concerted efforts across the board, some of your employees or processes may be destroying the loyalty you are working so hard to create and measure.
Are there holes in the customer or loyalty data? Do you have loyalty information from end users but not decision-makers? Or poor loyalty survey participation? How about poor participation by certain key accounts? Or worse, an inability to measure revenue/profit of an individual customer or segment? Spend some time filling these holes in your data and analytics capability so you can conduct this analysis again in the following quarter.
In examining historical correlations in this fashion, JetBlue found that a one-point improvement in their overall NPS score equates to between five and seven million dollars in additional revenue. The goal isn’t necessarily to prove that a specific customer initiative will raise revenue by 30 basis points. Instead, the goal is to show an upward trend correlating increasing loyalty with increasing revenue/profits. Demonstrating this trend and correlation is a significant step for CCOs in proving the ROI of customer centricity, which validates the need for additional investment in activities to drive loyalty and customer engagement.