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    Expert Column: Loyalty Lore and Truisms

    Exploring best practices to provide customer satisfaction

    By Jerry W. Thomas , Decision Analyst Inc.

    By Jerry W. Thomas, president and chief executive of Decision Analyst Inc.

    The many “truisms’’ of customer loyalty lore are mostly a set of mythologies to deceive the gullible and exploit the innocent. Let us explore these mythologies and then talk about best practices for customer satisfaction and customer loyalty research.

    The Mythologies:

    Rising customer satisfaction scores are positively correlated with increases in sales. Sometimes this is true, but just as often rising satisfaction scores are inversely correlated to actual sales. For example, as sales go down, stores are less crowded and store employees have more time to spend with customers, and often retail prices fall. All of these factors can result in rising satisfaction scores -- while sales are falling. Retailers, in particular, can “happily’’ go out of business amid a rising tide of customer satisfaction scores.

    It costs less to keep your current customers than to attract new customers. This is usually true, but not universally true. Keeping existing customers can become very expensive at times. Some customers are too costly to keep. The key is to focus on attracting and keeping the strategically profitable customers.

    Companies should always strive to maximize customer satisfaction ratings.  Companies can achieve the highest possible customer satisfaction scores by raising product quality, offering unlimited service and lowering prices. But these actions will lead to bankruptcy. No, the goal should not be to maximize customer satisfaction. The goal should be to optimize customer satisfaction so that the company’s long-term profits are maximized.

    One magical question is the ultimate measure of customer satisfaction and the ultimate predictor of future success (the so-called Net Promoter Score).  The Net Promoter Score is derived from a “would you recommend this product/service’’ question. Levels of recommendation, unfortunately, vary greatly by type of business and product category. You may recommend a car dealership or a restaurant (high-interest categories) but not mention a drugstore, gas station, bank or funeral home (low-interest categories). A better strategy is to tailor the customer satisfaction questions to your industry, your product/service, and to your business goals. Use multiple questions that measure satisfaction from different perspectives. Don’t buy into the illusion of universal truth. Don’t fall for simple answers to complex questions.

    Customer satisfaction scores are all-important, the ultimate determinant of a store’s or a dealer’s evaluation by senior management. Many senior executives are not aware that satisfaction scores vary by different regions within the U.S.; vary by the demographic makeup of a retailer's customers; and vary by age of the store. These variances make it very difficult to compare the satisfaction scores from one store to the next, or across different parts of the country. Few companies use sophisticated modeling to adjust for all of these natural variances to level the playing field.

    It’s all about the “customer experience,’’ as though customer experience is a magical, ethereal, transcendental idea. What is so revolutionary about the notion of understanding customers? Haven’t good companies been providing good customer experience since (and before) the coming of the Industrial Revolution? Isn’t marketing research about understanding how customers think, feel, behave and react -- at all touch points? Might customer experience just be a new name for something good companies have been doing all along?

    Key Questions 

    Okay, so it's easy to poke holes in the rhetoric surrounding customer satisfaction and loyalty measurement, but here are some of the questions to think about as you contemplate a customer satisfaction monitoring program:

    • What are the objectives and goals of a customer satisfaction or customer loyalty program? Is such a program likely to achieve its goals?
    • What are the relevant questions, the metrics that make sense for your industry and your company?
    • How much measurement is enough? Are surveys once or twice a year sufficient to accomplish your goals? Not every company needs to continuously measure customer satisfaction.
    • How do you interpret the results? Can the results be organized, weighted, normalized, analyzed, etc., so that the ratings are fair and useful?
    • Is a customer satisfaction program really worth the money it will cost?

    Best Practices

    Let’s assume you have done your homework and answered the above questions honestly, and feel that a customer satisfaction and loyalty program makes marketing sense and economic sense for your company. You have clearly defined the objectives for the program. What are the best practices to help ensure that your company gets the most out of its customer satisfaction and loyalty program?

    Always begin with some type of qualitative research (focus groups, depth interviews, online forums, ethnography) to better understand your customers, their perceptions, their experiences, their language, their fears, and their issues and concerns. If you don’t really understand your customers’ feelings, knowledge levels and perceptions, and don’t understand how customers interact with your company, it’s almost impossible to design a good customer satisfaction and loyalty monitoring program. The qualitative research will make it possible to design a very good survey questionnaire. In fact, the qualitative research should be repeated every two or three years as a safety check to ensure that your satisfaction program remains relevant and on track.


    Who do you survey? If you only talk to your current customers, you may be overlooking a sea of dissatisfied former customers. Generally, the best practice is to focus your surveys on your current customers, but include cells of infrequent customers and former customers. If you conduct your surveys as visits or transactions occur, your sample will tend to be biased toward heavy users. This can be a good thing, since heavy users account for a large share of your business, but it can overstate your customer satisfaction scores because you are conducting a high share of surveys among your most loyal customers. It’s like preaching to the choir.

    Questionnaire Design   

    The first rule is “do no harm.’’ That is, your attempts to measure customer satisfaction should not lower your customers’ satisfaction. This means that questionnaires should be simple, concise and relevant. Use very simple rating scales (2-point, 3-point, 4-point scales). Short word-defined scales (e.g., Excellent, Good, Fair, Poor) are easy for customers to answer, and the results are easy to explain to executives and employees. Moreover, short scales work well on personal computers, tablet computers and smartphones. Long, complicated scales should be avoided. The questionnaire should almost always begin with an open-ended question, to give the customer a chance to tell his/her story. An opening question might be: Please tell us about your recent experience of buying a new Lexus from our dealer in north Denver? 

    The questionnaire should always be pretested with 20 to 30 depth interviews. It’s also best practice to conduct 500 or 1,000 surveys, as another type of pre-test, and factor analyze the answers. Often this will allow you to shorten the final questionnaire by eliminating redundant questions or attributes.

    Survey Data Collection

    The method of data collection should be tailored to the customer base. Mail surveys work extremely well for automotive purchases, for instance. Telephone surveys are widely used because interviewers add a personal touch and can ensure that any problems are immediately addressed by the correct person or department. Online surveys are probably the most widely used survey method for customer satisfaction. It’s often the least expensive, if customers’ email addresses are systematically collected. Smartphones and tablet computers increasingly offer new ways to survey customers. Complaint-tracking or problem-tracking (types of customer satisfaction research) can be conducted via QR codes, IVR (interactive voice response), or survey invitations on invoices, sales receipts, paper coffee cups, etc.


    This is where most customer satisfaction measurement systems fail. If you are comparing different stores, or different geographical areas, you should normalize the survey results to make the comparisons fair and accurate. If you are looking at results for a particular store or division over time, you must be wary of seasonal variations. When the weather is very hot, or very cold, customers might tend to be more irritable. During the Christmas season, everyone tends to be emotionally stressed and satisfaction scores can go down. The use of advanced statistical methods is essential.

    The best practice is to build relevant and useful mathematical models to compensate for data biases and distortions, link together important measurements in sophisticated ways, and derive simple composite results that everyone, even senior executives, can understand and use.

    Benchmarking is important. You should collect customer satisfaction data for your major competitors, if possible, so that you have a relevant measuring stick to analyze your own satisfaction data.

    Economic Sense

    Meeting the needs of customers and providing great service doesn't guarantee business success, but it sure improves the chances of winning. There are no simple, universal truths about customer satisfaction measurement and management. Each company is unique and must think carefully about its business model and its objectives to design a customer satisfaction and loyalty program that really works and makes economic sense.

    By Jerry W. Thomas , Decision Analyst Inc.
    • About Jerry W. Thomas Jerry W. Thomas is president and chief executive of Dallas/Fort Worth-based Decision Analyst Inc., a leading international marketing research and marketing consulting firm. Further information is available at www.decisionanalyst.com. Thomas can be reached at 817-640-6166.

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