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Held this year in Santa Fe, New Mexico, the American Marketing Association's annual Advanced Research Techniques Forum brought together top academics and practitioners from around the world to present and discuss advanced statistical techniques and emerging market-research trends.
Satisfaction vs. Loyalty
Several presentations centered on moving beyond traditional customer satisfaction measurement towards a more meaningful evaluation of customer loyalty.
The argument goes like this: In today's extremely competitive marketplace, a customer reverts back to a prospect immediately following the purchase, and therefore must be converted again and again. That is, unless the customer is loyal.
While it is great to have satisfied customers, if they do not continue to purchase your product or service, they do not consistently add to the bottom line. Satisfaction is simply a measurement of a person's attitude towards your company. Loyalty, on the other hand, is a quantifiable measurement of their behavior. While satisfaction certainly has an impact on loyalty and should in no way be dismissed altogether, it is not nearly as powerful as loyalty for predicting customer behavior.
Moving beyond satisfaction measurement means evaluating a company's set of value propositions in relation to its competition. The fact is, most people migrate to companies that offer the best value. More than a simple trade-off of cost versus quality, however, value is a multidimensional construct that includes hard to define factors like brand equity.
Brand Equity
Another hot topic of the 1999 ART Forum, and one that naturally dovetailed with the customer loyalty discussions, was brand equity-What is a brand name worth?
Traditionally thought of as a price premium, or the extra price a person will pay to buy your product over and above competition, brand equity is itself a multidimensional construct, impacted by a host of factors that can be modeled via structural equation modeling. Not to go into the math, as it would put most to sleep, structural equation modeling looks at how factors interact with each other and how they impact brand equity.
For instance, research has shown that brand equity is driven by such factors as a customer's relationship with the brand, their evaluation of the brand's personality, their level of emotional attachment to the brand, as well as their evaluation of the product's functional attributes. Structural equation modeling mathematically derives the magnitude of these relationships, providing direction for companies on what they can influence that will have the greatest impact on their brand equity.
Consider including loyalty and brand equity measurements in your next customer survey and utilizing structural equation modeling to analyze the data. You will open up a rich source of new data that far surpasses traditional satisfaction testing.
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