Sure, your company has satisfied customers. If you didn’t, you wouldn’t be in business (at least not for long). But here’s a question few companies ask: How loyal are they? Will they recommend your products and services to others? Will they stick with you through thick and thin? Or will they run at the first sign of a price increase or some other change that rubs them the wrong way? The mere presence of customers (even those who’ve stuck around long enough to make multiple purchases) isn’t enough. You need to be able to measure their loyalty so you can use it to predict the health of your company.
Too many companies spend a ton of time and effort getting a customer to make a purchase, and then they just hope for the best. The problem with that approach is that operating in the blind in terms of loyalty makes it likely the company’s leadership will make ill-advised decisions that will come back to bite them. When they measure customer loyalty, they will be able to not only make the most of that loyalty but also to make better strategic decisions for the company.
Good customer management comes from good customer measurement. Customer loyalty is an important analytic for determining how well a company or product is positioned to grow or shrink based on future earnings. The “best” metric for determining customer loyalty depends on the industry, company and type of product or service, but for most organizations, measuring customers’ intent to repurchase a given product or service and their willingness to recommend the company to others provides a solid base.
Find out if they’re likely to buy from you again. Probably the first way to gauge customer loyalty is to compute the percentage of customers who are repurchasing, reusing or returning to a product or service. This data can be collected from past sales or from surveying customers about their past or future intent.
Repurchase habits are measured differently depending on the type of product or service offered. For example, for rental car companies, the repurchase rate is a good indicator of loyalty as certain customer segments rent multiple times per year and have many companies to choose from. For software companies, a similar measure of repurchase loyalty is the maintenance contract renewal rates.
Collecting actual repurchase rates and building a repurchase matrix can take years, especially for products that aren’t purchased frequently. To speed up the process and gauge customers’ loyalty before they defect, a company should survey its customers and ask their intent to repurchase. For best results, keep the surveys short.
Gauge word-of-mouth promotion with the Net Promoter Score. The Net Promoter Score (NPS) is a popular way of measuring customer loyalty through understanding word-of-mouth marketing. It is based on a single question: “How likely are you to recommend [product or service] to a friend or colleague?”
NPS is calculated by following a three-step process. First, customers are asked how likely they are to recommend a company’s product or service to a friend or colleague. The next step is to compute the proportions of “promoters,” “passives” and “detractors.” Promoters are customers who are most likely to speak about and recommend a company’s product or service. Passives are generally satisfied with its product or service but are less likely to recommend it to others. Detractors are not only the least loyal, but also the most likely to actually discourage friends and colleagues from purchasing or using the company’s product. The final step is to compute NPS by subtracting the percentage of detractors from the percentage of promoters.
Getting access to competitive data can be difficult for some industries and products. Even without competitive data, though, the best comparison is often measuring the same product, service or company over time. Netflix offers a great example. In February 2011, the company’s NPS was very high at 73 percent. Then, in the fall of 2011, the company decided to split off its home delivery of DVDs and its streaming service into two companies, which angered customers. My company surveyed Netflix customers a month after the change and found the NPS had plummeted to a negative 7 percent.
Perhaps Netflix did perform the testing and anticipated losing customers. The much larger loss is likely due to other factors and perhaps to untested customer correspondence and the geometric effect of negative word of mouth. But using the NPS as a predictive analytic tool can help prevent disasters and identify winners early.
Be aware of bad profits. How does it feel to pay the check at the restaurant where you had terrible service and bad food? Or how about paying $150 to change your airline ticket reservation? Obviously, nobody likes to pay for a subpar or overpriced product or for bad service, and yet, in these examples, companies financially benefit from a customer’s negative experiences. However, it’s a short-term benefit. Those are bad profits, and they’re a ticking time bomb. They lead to customer resentment and a decrease in customer loyalty, and they eventually impact profits negatively.
By combining NPS data with customer-by-customer revenue data, a company can estimate the amount of revenue derived from bad profits. Even without access to financial data for one’s company or a competitor, the percentage of bad profit revenue can usually be estimated. For example, when my company measured customers of consumer software products a couple years ago, we found that about 17 percent of Adobe Photoshop users were detractors. Assuming everyone pays around the same price for a Photoshop license, some 17 percent of Adobe’s revenue from Photoshop comes from detractors.
While it’s bad to generate revenue from dissatisfied customers, it’s worse if a large proportion of a company’s revenue comes from detractors. Too much detractor revenue for a product or entire company makes that company more susceptible to new competition, alternatives or abandonment.
Two actions a company may take if more than 10 percent of company or product revenue comes from detractors are to stop selling to those customers or attempt to fix the problems that are making the detractors unhappy. Making the adjustments to price, quality and features to meet those customers’ expectations can be a huge challenge, but that’s usually what separates the best-in-class companies from the rest.
Find out what customers like most about your product/service. One of the most effective ways to understand what drives customer loyalty is to conduct a key driver analysis. Key drivers include quality (Are the products reliable? Do they work as described?), value (Does the product give buyers the best bang for their buck?), utility (Does the product offer essential features?), and ease of use (Can customers use the features without frustration?).
A key-driver analysis tells a company which features or aspects of its product or service have the largest statistical impact on customer loyalty. It can be conducted for all customers but also for each different customer segment. It will enable a company to identify the most popular or unpopular features or aspects of its product or service, and have customers rate that experience as well.
Pinpoint your haters. While companies should strive for more promoters, it’s often the customers who are least satisfied with their experience who have a much larger impact on referrals and the brand. Research supports that customers who are dissatisfied with a product or service experience are actually more likely to be vocal and tell more friends and colleagues about their bad experience than generally satisfied customers.
The negative effects of detractors can outweigh the positive effects of promoters. So, once a company has identified its detractors, its leaders will have to find out what will make its detractors happy and loyal, and then decide whether it is worth it to spend the resources to make those changes or whether it’s more cost-efficient simply to go after new customers who will be happy with the way the company currently operates.
Make sure you’re getting your money’s worth from promoters. Generally speaking, promoters are a positive asset to a company. But before going all-out to attract as many as possible, it’s a good idea to take the time to understand how valuable a promoter is, both in terms of revenue and in how many new customers a promoter brings to a company. The best way to understand how much revenue a promoter generates is to tie actual sales to survey responses to see how many promoters actually recommended someone, and how many of those people who heard the recommendation actually became customers.
With some estimate of the number of promoters needed to gain a new customer, a company can then weigh the cost of new programs, features, pricing and promotions to determine if the benefit from new customers outweighs the cost. If, for example, a company would have to reduce the price of its product to turn customers into promoters, gaining those promoters might not be financially sustainable. Similarly, if it would cost close to a quarter of a million dollars to add a new feature to a product while that new feature would generate only 10 new promoters, it’s not worth it. And for websites, a new “customer” might just be a new visitor or subscriber, so the cost of gaining new promoters can be important.
Another important point: Companies that use a particular price, deal or feature to gain promoters should think twice before changing it after those people have begun singing their praises, as the removal of a favored feature can frustrate the users and turn a promoter into a detractor.
Customer loyalty isn’t black and white. A company that uses analytics to dig into why customers buy from it, how often they do or don’t recommend it to others, and so on, can make better product decisions, provide better service, and make changes to ensure it can create many more loyal customers.
Jeff Sauro, author of Customer Analytics for Dummies, is a Six Sigma-trained statistical analyst and pioneer in quantifying the customer experience and the founding principal of Measuring Usability, L.L.C., a customer experience and quantitative research firm based in Denver with clients that include Walmart and Google. He specializes in making statistical concepts understandable and actionable, and his new book focuses on providing a working knowledge of how to measure each stage of the customer journey, and use the right analytics to understand customer behavior and make key business decisions.
Currently completing his Ph.D. in research methods & statistics at the University of Denver, Sauro has published more than 20 peer-reviewed research articles on statistics and the user experience. His other books include Quantifying the User Experience: Practical Statistics for User Research and A Practical Guide to the System Usability Scale.