As a company grows the customer base becomes significantly more diverse. Different customers have differing value. It also becomes more and more difficult to care about a single customer. Most metrics push towards aggregates, the focus is on the quantity and not the quality. This is the Abstract Customer. We replace the real customers with a potentially dangerous amalgamation.
As an individual he is of no importance to the department store. He is important as “a” customer; the store does not want to lose him, because this would indicate that there was something wrong and it might mean that the store would lose other customers for the same reason. As an abstract customer he is important; as a concrete customer he is utterly unimportant.
– Erich Fromm, Escape from Freedom (published in 1941!)
The abstract customer is a valuable strategic tool. It helps make sense of either too many or too few customers. An abstract customer can never be happy, sad, mad, or frustrated. They aren't real, and never will be. They will never refer a friend to you. Abstract customers are important but they are never as important as a single, real customer. This doesn't mean the abstraction doesn't have internal value, but it requires an awareness of the pointy ends of the tool.
The tighter we embrace the abstract customer the looser our relationship with real customers. Every customer is different. It can be challenging to understand why some are happy and others are not. A company is built not upon the abstract but the real, very human, customer. Losing this focus will inevitably lose customers. I believe the Abstract Customer can help maintain closer real relationships, but it must be done deliberately and cautiously, fully aware of the dangers.
This is a natural part of simply being human. The Similarity Heuristic is a powerful tool to help us make decisions quickly. It simply states that when faced with a set of items, we will naturally generate and form a representation of items in that set. Unfortunately this also means we are going to lose track of some very critical details.
Without focusing on the important details, the risk of a slow transformation of the Abstract Customer into the Ideal Customer rises. Instead of representing a group of customers, instead it is a hand-picked subset of the favorite users. These ideal users, a small minority, are now hoisted up as representatives of the mainline customers. They will use more of the service, happily pay more, and likely they will refer more users. Focusing on them, though, will alienate the bulk of the average users. Often times this ends up with a product become user-hostile, with so many features it requires a training course to operate.
Find the right balance between the ideal minority and the majority. While the ideal minority tends to be the customers to keep happy at all costs, focusing exclusively there can alienate the majority. The abstract customer is a defense against this. Create multiple abstract customers that represent each group of existing customers, as well as future potential customers. Make sure they cover the entire spectrum, and don't forget to also represent those wretched customers that will never be happy.
Example panel of an Abstract Customer, showing the range of divergence and the median.
The purpose of this exercise is to make informed decisions before hand, rather than trusting illusory or self-fulfilling results. It helps maintain thorough understanding of the real customers, bad and good. Give these abstract customers names, be able to show deviation in the group and how many real customers they represent. Abstract customers should be created from your real customers, backed by real data. If you don't have customers, fake the metrics that generate these customers, but do not make up abstract customers arbitrarily.
Photo courtesy Flickr user Rob DiCaterino