Is Customer Satisfaction Worth the Effort? How Linkage Analysis Validates the Impact on Your Bottom Line

Linkage analysis measures the impact of customer satisfaction on the bottom line. By linking satisfaction survey information with customer behavior, it is possible to validate the benefits of measuring and managing satisfaction. Linkage analysis also guides the allocation of resources.

The cornerstone of a successful business (or non-profit) is customer loyalty. Loyalty can be defined by many factors, all measurable in a survey, including: satisfaction, perceived value, future purchase/renewal intent, and advocacy (e.g., net promoter score). Many organizations, including Rockbridge clients, invest substantially in measuring loyalty and in making improvements in services based on customer feedback.

As management invests in surveying customers and acting on the information, questions arise as to the economic benefits to the organization. Questions management may ask include:

• Does satisfying customer needs really matter?
• What is the return on investment (ROI) of making improvements that increase customer satisfaction?
• In what areas should investments be made?
• What is the impact of reducing service or value?

Linkage analysis answers these questions by correlating customer satisfaction survey data with customer behavior. It involves a form of “quasi-experiment” that tracks customer behavior into the future after satisfaction is measured.

This kind of analysis involves a series of steps:

1. When customers are surveyed regarding their satisfaction, information is retained so their behavior can be tracked in the future (note that this is done anonymously to ensure adherence to confidentiality guidelines).


2. After a certain period of time has elapsed, usually 6 to 12 months, customer information is obtained from the CRM system and merged with the satisfaction data – information can include: did the customer renew or cancel a relationship/membership? Did the customer make additional purchases or stop purchasing? How much did the customer purchase? How did purchases compare with past purchases?


3. A statistical model is created that predicts and explains behavior with the customer satisfaction information. For example, for one online retailer, a 1 point change in satisfaction translated into $264 in annual purchasing per customer. The modeling phase may explore the behavioral impact of individual quality dimensions as well as overall satisfaction/loyalty.


4. A financial model is created to identify the ROI of improvements in quality. This model includes parameters input by our client, such as: profit margins, number of customers, planned investments, and planning horizons. A more sophisticated model will include information on a “discount rate” that takes into account the opportunity costs of investment in measuring the ROI.

A linkage analysis is used to answer key questions that management has about their efforts to improve customer satisfaction. The most profound finding is whether a statistically significant linkage actually exists. Showing that there is a positive relationship is critical in building support for efforts to improve quality. Another finding is the actual dollar gain in profit from improving quality. By comparing this with investments made to improve quality, management can gauge whether it is worthwhile to invest in the customer experience or to use the investments elsewhere.

A linkage analysis also helps identify the kinds of investments to make. A common output for a linkage analysis is a planning spreadsheet that allows managers to input hypothetical assumptions about investment costs and improvements in specific areas to determine the ROI. If the investments are high and the returns minimal, the model will show that it is better to invest in a different area of customer satisfaction or in a different part of the organization altogether.

• Linkage analysis may also be used to assess the impact of reductions in satisfaction. To illustrate, one client was in the habit of offering continuous promotions to drive business, but decided to abandon the practice. The Return-on-Quality simulator made it possible to compare the reduction in sales with the increase in profit margin, showing the decision was a wise one. Another example is weighing cost savings from reduced variety of options or less comprehensive service with the impact on sales.

Linkage analysis is a valuable task that brings reality into the satisfaction measurement process. It provides reassurance to the organization that its emphasis on the customer contributes positively to the bottom line. And, it provides the basis for making smarter decisions about investments in quality improvement.

For more information, contact Gina Woodall, SVP at 703-757-5213 ext. 11 or gwoodall@rockresearch.com, or Charles Colby, President, at 703.757.5213 ext. 12 or ccolby@rockresearch.com.

This content was provided by Rockbridge Associates. Visit their website at www.rockresearch.com.

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