Customer satisfaction is a term that is bandied about freely within the corporate world. Managers are measured on it; employees are paid bonuses on it; and firm strength is based, in part, on it. Satisfaction is one of the most common metrics used to measure customer sentiment.
But measuring customer satisfaction has always been complicated. Many firms have long had difficulty determining the best way to effectively capture customer sentiment. In 2003, Fred Reichheld introduced the concept of a Net Promoter Score, a simple, and therefore popular, way to measure satisfaction. The Net Promoter Score required the measurement of only one question: “How likely are you to recommend (your company) to a friend or colleague?”
This single question enabled firms to easily measure customer satisfaction. They interpreted the results by subtracting the detractors (those who rate the firm 0-6 on a 10 point scale) from the promoters (those who rate the firm a 9 or 10), to determine the net promoters. The simplicity made adoption of the methodology swift as companies around the globe began asking the “one question” they needed to fully understand satisfaction.
Fast forward more than a decade. Academics are beginning to do rigorous testing of the Net Promoter Score and are challenging this measure’s ability to predict future customer behavior and loyalty. In a recent Harvard Business Review article, authors Matthew Dixon, Karen Freeman and Nicholas Toman compare several traditional measures of customer satisfaction, including the popular Net Promoter Score, to a new measurement methodology and found that the Net Promoter Score wasn’t as effective at predicting future customer behavior.
Furthermore, research conducted by Keiningham, Cooil, Aksoy, Andreassen, and Weiner found that the single question regarding a customer’s likelihood to be an advocate for a brand was lacking as an indicator of future loyalty behavior.
How Can CMOs Better Understand Customer Satisfaction?
Enter the CEO and the CMO. Representatives from both roles indicate that while they are attempting to measure customer satisfaction, they don’t adequately understand it.
A recent survey of more than 1700 global CEOs found that one of their top priorities is to generate greater consumer insight, with an obvious focus being what consumers think of their firms’ products and services. A single measure, while being simple, can’t possibly provide the texture, the granularity, and the nuance necessary to be able to fully understand customer sentiment and translate it into superior profitability.
If traditional methods of measuring customer satisfaction aren’t effectively forecasting future customer behavior, then the obvious question is: How can CMOs better understand and leverage satisfaction?
Drawing on recent knowledge from select CEOs and CMOs I’ve interviewed, I offer suggestions for successfully generating and comprehending customer satisfaction data to drive business growth.
Tip #1: Simple may be too simple. Fully understanding customer satisfaction requires a more comprehensive model.
R. Sukumar, the founder and CEO of Optimal Strategix Group, suggests a more comprehensive approach to understanding customer sentiment.
“We propose that CMOs take into account several factors, including the customer’s role, their influence on the purchase decision, what matters most to customers in their purchase decision, customer expectations, and their ultimate satisfaction,” Sukumar says.
“There are multiple factors that drive customer sentiment and ultimately, the customer’s likelihood to purchase,” Sukumar continues. “A composite evaluation of customer drivers of purchase, loyalty, and repeat purchase, along with the drivers of satisfaction, can then allow for a full understanding of the customer experience throughout their journey. This enables CMOs to then implement programs throughout the purchase funnel that are more likely to drive profitable growth.”
“Our engagement with customers happens over numerous interactions and a variety of media such as in-store service, the web, email, the telephone, etc.,” he told me. “To fully understand how customers think about us, we have to measure our performance across vehicles. This also means looking at performance throughout the purchase conversion funnel to identify issues. Not surprisingly, customer sentiment can vary and this coarseness helps us refine and perfect the customer’s experience across the continuum of engagement.”
Tip #2: True customer insight requires first knowing which attributes matter to the customer and then determining how the firm is performing on those attributes. If a customer’s experience occurs over multiple interactions and various media, then each needs to be measured to drive insight precision.
Firms measure a variety of attributes related to satisfaction. For example, an apparel retailer might measure satisfaction related to quality, price, value, store experience, and service at checkout. However, to get the greatest insight, it is critical to first understanding which of these attributes matter most to the customer, and then to understand how the firm performs on these attributes.
David Norton, the previous CMO of Caesar’s Entertainment – a company known for its sophisticated approach to customer knowledge – suggests that “granular understanding should be based on the important and relevant attributes that consumers have.”
Regarding choosing which attributes are measured, Optimal Strategix’s Sukumar believes “If a company treats all customer satisfaction attributes the same, then the firm can be led astray. For example, if the appearance of the entrance of the store is rated low in terms of importance to a customer, the company might chase a problem they don’t have. A low satisfaction rating on something that isn’t important suggests that the firm can likely ignore it.”
If CMOs spend more time focusing on measuring and analyzing the attributes that are most important to their customers, they will likely gain a better overall understanding of satisfaction.
Tip #3: Advanced statistical methods and expertise are necessary to be able to move beyond measuring customer satisfaction to actually understand and leverage it to drive business growth.
Depth of customer insight is related to the sophistication of methodology chosen. Firms that use more contemporary and advanced statistical techniques are likely to generate more accurate and predictive insight.
“Leveraging advanced techniques and more rigorous methodologies is required to generate the insight needed to drive growth,” Norton notes. “Simplicity has its place, but not when it comes to generating true customer insight.”
Sukumar believes methodologies, such as tradeoff techniques, key driver analyses or path analyses, enable a superior understanding of what matters to customers during their experience with products or services. This leads to the ability to quantify the incremental value that a company’s improvement in each attribute can deliver for the product, brand, and entire firm.
“Historically, the goal with customer satisfaction measures was to simply do quantitatively better than the prior year,” Sukumar says. “However, the value of a more sophisticated statistical technique is that it can help predict which attribute will generate the greatest profitable growth with the least investment. The former goal demonstrates how customer satisfaction has been divorced from business performance.”
Satisfying customers, who can ultimately convert to evangelists, should be the goal of every CMO. Unfortunately, the standard methodology for generating insight is insufficient. Moving beyond just measuring customer satisfaction, to actually understanding and learning from it, should be a new approach to crafting a sophisticated learning program.
By using a comprehensive satisfaction model, understanding which attributes matter most to customers, and leveraging advanced statistical techniques, CMOs will be better positioned to drive ultimate business growth for their companies.
Kimberly A. Whitler is an instructor at Indiana University who is researching the role and contribution of the CMO.