To link loyalty with profits, companies need to understand attitudinal metrics, customers’ actual purchase behaviors and customer drivers. The author breaks down each factor.
Editor’s note: Michaela Mora is president of Relevant Insights LLC, a Euless, Texas, research firm.
Whenever there is a sample of customers being surveyed, clients often want to capture attitudinal metrics such as overall satisfaction and likelihood to recommend, use or buy their products again. High scores in these metrics are usually interpreted as indicators of loyalty and contributors to the company’s profits.
The problem is that, often, clients don’t have access to data about customers’ purchase behavior or if they have it, it is not analyzed in conjunction with these attitudinal metrics. However, without data on customers’ actions, conclusions on customer loyalty are made on shaky grounds.
Intuitively, one would expect that a satisfied customer would keep buying from a company, but reasons for buying a product and for being satisfied with it are not always aligned.
Often, first-time buyers find themselves making a purchase because of factors such as these:
- the product is the only alternative in the market to solve a present problem;
- a lower price given by a discount or deal;
- recommendation from a reputable source (e.g., friends, media, celebrity, product review);
- convenience (e.g. location, easy purchase process); or
- impulse triggered by external cues (e.g., packaging, brand recognition) or latent needs.
First-time purchases are filled with expectations and the product’s ability to meet them will have an impact on satisfaction but not always on repeat purchases.
Dissatisfied customer may still continue buying the product or service because of:
- contractual obligations (e.g., TV subscription);
- no other alternatives are available or there is uncertainty about competing options (because of issues with product benefits or cost);
- inertia driven by the amount of effort needed to research and change to a competitor; or
- lowest price on the market or deals.
Satisfied customers may still change to a competing alternative or stop buying altogether if:
- a similar alternative is offered at a lower price;
- a new and improved alternative comes to the arket that better meets their needs;
- the product is out of stock; or
- price increases or no deals are offered.
Satisfied customers driven by expectations of deals and discounts are very fickle customers and should not be mistaken for loyal customers even if they make repeat purchases. This calls for caution when using satisfaction to gauge the potential for profits. You may have many “loyal” but unprofitable customers. They stayed while the prices are low, lowering profits, and leave as soon as the prices go up or no deals are offered.
Likelihood to recommend
Many companies now use likelihood to recommend as the key metric to measure loyalty (Net Promoter Score or NPS). After all, it makes senses that you would recommend a product if you buy it for yourself. However, in many studies I have done over the years, I have seen many respondents giving high recommendation scores at the same time they give low satisfaction scores, and vice versa. So, why would they recommend a product if they were not entirely satisfied with it or not recommend a product they were satisfied with?
Online product reviews, which are now so easily available, can shed light on this paradox. Nuanced product reviews often include pros and cons which in essence are trade-off analyses. The reviewer may find a lot of benefits in a product but would not recommend it for its high price, thus recommending a less satisfactory competing alternative that is more affordable and does the basic job. The same can happened in the other direction. Satisfaction and recommendations are sometimes driven by different factors.
Given the trade-off analyses that can hide behind recommendations, this metric is also subject to volatility and not always a good predictor of customer behavior. A new product can change the trade-off against or in favor of a recommendation and actual purchase behavior.
Loyalty and profits
To identify loyal customers, companies need to triangulate the result from these attitudinal metrics, its drivers and their actual purchase behavior. To make loyalty an actionable concept and link it to profits, companies should take into account the value contributed by customers (sales they generate minus cost of serving them) who score high on attitudinal metrics and also make repeat purchases. Repeat customers driven by deals and discounts are unlikely to be profitable and are far from being loyal.