Estimating Customer Share-of-Wallet
Market share is one of the fundamental metrics that companies monitor to see how they are faring against their competitors. But companies often want a more granular look at what share they command of their customers' spending in their category. A particularly attraction of this data is the potential to find customers that could consolidate their business with the company and generate significant incremental value. It is also seen as a good indicator of loyalty and customer engagement.
Before You Make the Leap...
While the the concept of being able to understand share at the customer level is a seductive one, companies should consider a few things before embarking on such an initiative. First, one needs to recognize that many markets are mature and stationary, which means that market share at the company level is stable. Absent some disruptive event (poor quality from one of the competitors, a new entrant into the market, etc.), market share is expensive to change solely through marketing. (By the way, we wrote an article about market share dynamics a while ago; you can find it here.
The "macro" share is a function of the "micro" actions of customers in the market. Merely knowing how customers are allocating their purchases does not imply that marketing alone can persuade low-share customers to switch their business. Again, it is likely to take some larger set of changes – new or differentiated products, pricing schemes, or some other significant factor – to change the dynamics in a meaningful way.
In fact, I believe that one of the best reasons to consider investing in understanding customer-level share is precisely when a company is planning such a major change, because for it to be successful, it must either change the dynamics of market share or represent an opportunity to become more profitable with the same market share.
One other compelling reason to contemplate understanding customer-level share is as a tool to monitor the health of the customer base. Often, overall market share erodes slowly, but it manifests itself first among certain customer segments. If we start to observe declining share in valuable segments, we need to address the problems before they lead to a real decline across the whole base.
Common (and One Uncommon) Methodologies
Unlike the market share of companies and brands, for which there commonly are reliable public and private sources of data available, estimating the share of wallet for customers is much more challenging. In certain categories, there are data compilers and resellers that track customer spending; some of this comes from survey-based data, some from transactional sources, and some of the information is modeled. For example, in the travel and leisure area, several vendors market overlay data that provides estimated category spending (air travel, hotels, etc.) for consumers.
Such data sources may be valuable in some cases. But in general we have observed that they often to not provide as much insight as hoped. For example, a hotel company may have several brands that service different segments – budget, business, luxury – yet the spending data may not provide sufficient detail on customers' spending within these subcategories. The data may also be heavily modeled, which is not necessarily a bad thing, but this is not always how it is presented. Finally, if such overlays are needed as a permanent data source, then another structural operating expense is introduced.
Another traditional way to develop this data is through quantitative research. We have used this approach many times in the past, and it brings with it all the challenges that research studies must overcome. Survey design and sampling are especially important, because customers often do not have good recall about their activity in a category. For example, if someone asked me to give the number of nights I have stayed in a hotel in the last six months, I could probably provide a reasonable estimate. But the share-of-wallet questions, which ask me to allocate stays to various brands, would be much more difficult for me to recall and subject to more bias. Nonetheless, a well-designed study can reveal competitive choices that customers are making, as well as the reasons behind these choices, and the resulting data can be used to build a model to estimate share for the entire base. Developing models to accurately score the customer database using research data presents some additional challenges, and in order to keep the models up-to-date, ongoing tracking research needs to be conducted.
A more direct approach, one that we have used successfully, is to use transactional data from your customers to develop a model. While the methodology is a bit involved, and beyond the scope of what we can cover here, the basic premise is first to build a model that estimates spending for your customers. We then apply this model to find customers where the estimates are wrong, on the assumption that these customers must be either giving us a lower or higher share than we expected. We can then build additional models that estimate share of wallet. This method has been surprisingly robust and validates well against data gathered from other sources.
The summary: make sure that market share estimates at the customer level will help drive business results. If they will, then choose the methodology that yields the best information at the lowest cost.
Posted at 03:43AM Aug 20, 2009
by David King in Analytics |
