colleagues. Demonstrating the link between something as ambiguous as loyalty and something as specific as revenue or profit can be extremely difficult.
MEASURING CUSTOMER LOYALTY
Based on more than 20 years of experience conducting primary research in the information technology (IT) industry, TNS Prognostics has found that one of the most effective and widely applicable methods of measuring customer loyalty for our clients involves three of the elements listed above: referenceability, repurchase intentions, and future purchase levels. Many of the customer surveys we conduct for our clients include a question about each of those three elements, and the answers to those questions are then combined to create the Prognostics Customer Loyalty Index (ProCLI). We have found the ProCLI measure to be both internally reliable and stable over time, with a Cronbach’s alpha (a tool for measuring the reliability of scales) of .77 and an average test-retest correlation of .64 over the last three years (all with p < .06).
The questions used to create the ProCLI are included in an annual benchmarking survey conducted by TNS Prognostics. The benchmarking survey targets a wide range of business customers in the IT industry and uses a standardized questionnaire. The results of this annual benchmarking survey provide a rich source of historical customer loyalty data for a wide range of companies in the IT industry.
INVESTIGATING LINKS
The first step in our effort to uncover potential links between customer loyalty and financial data was to gather and organize historical customer loyalty data from the TNS Prognostics benchmarking survey. Our next step was to gather historical financial performance data for the target companies. Annual revenue growth, which is widely reported in public financial reports and less dependent on costs that may be unrelated to customer loyalty, was selected as our primary financial performance metric. We then had 2002 customer loyalty data alongside revenue growth data for 2001-2002 and 2002-2003, which provided the core information for our analysis.
We began by correlating the customer loyalty data to the financial data to measure the strength of their relationship. ProCLI and its three individual components (referenceability, repurchase intentions, and future purchase levels) were correlated to the revenue growth percentage for both time periods (2001-2002 and 2002-2003), and our analysis uncovered a significant relationship between several of the customer loyalty measures and revenue growth over the following year (2002-2003).
CORRELATING GROWTH
The most compelling finding was the strong correlation between ProCLI and revenue growth over the following year. (See Exhibit 1.) The analysis showed a significant positive relationship between ProCLI and next year’s revenue growth (r = .79, p < .01), indicating that the companies with more loyal customers in 2002 tended to experience higher revenue growth the following year. More specifically, the companies in our dataset show an average 12.5% gain in annual revenue growth for every 10% increase in customers who are loyal. The relationship also holds true across companies of various sizes, as the magnitude of the correlation remains fundamentally unchanged even when controlling for differences in annual company revenue (r = .80, p < .01).
Based on this data, there is clearly a strong relationship between the ProCLI of the companies’ customer bases and the revenue growth of those companies over the next year. Given that our analysis was based on correlations, we cannot draw definitive conclusions about the causal nature of the relationship between customer loyalty and financial performance. Our findings certainly do not change the fact that customer loyalty is just one of the important factors that influence financial performance.
INVESTING IN LOYALTY
Completing the link between financial performance and customer loyalty requires an understanding of the specific issues that drive customers to be loyal or disloyal. Without this understanding, a company cannot determine the specific actions that are likely to lead to the greatest loyalty improvements. Measuring ProCLI over time can help a company understand how loyal its customers are, but ProCLI by itself does not reveal the factors that cause a company’s customers to be loyal. At one company, for example, improving the quality of service/support might drive the greatest improvement in customer loyalty, while at another it may be product quality.
When companies know exactly which issues drive the loyalty of their customers, they are in an excellent position to take action and make real improvements. Equipped with an understanding of key loyalty drivers (such as specific aspects of the service/support engagement), companies can begin to take action by assembling cross-functional teams that develop specific initiatives designed to make improvements in high-impact areas.
All too often companies fail to take action. Improving customer loyalty can require a significant investment of both time and money, and many companies are hesitant to make that investment without knowing how much they expect to get back in return. For the companies included in our analysis, we found that a 10% increase in customer loyalty was associated with an additional 12.5% increase in annual revenue growth. Armed with that type of direct link to financial performance, companies are in a much better position to build a powerful business case for investing in customer loyalty.
For more information from TNS Prognostics, please go to www.prognostics.com.
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