October 17, 2002
Leveraging Your Customer Life Cycle
Attracting high value customers and keeping them coming back is what customer loyalty is all about. But true customer loyalty does not happen overnight. Instead, it’s built and earned one customer experience at a time. In most industries, customers typically evolve through at least seven identifiable life-cycle stages. For most off line customers, these stages are:
1. Suspect: anyone who might possibly buy your product or service
2. Prospect: someone who has both the need and the ability to buy your product or service
3. First time customer: someone who has bought from you one time
4. Repeat customer: someone who has bought from you two or more times
5. Client: someone who buys everything you have to sell that she can possibly use
6. Advocate: someone who buys everything you have to sell that he can possibly use and encourages others to buy from you.
7. Regained customer. This is customer who has bought from you in the past, then defected to a competitor, now returned and is buying from you once again..
On-line customers often evolve through eight stages in their customer life cycle: (1) surfer, (2) first-time site visitor, (3) repeat visitor, (4) first-time buyer, (5) repeat buyer, (6) client and (7) advocate (8) regained customer. In some cases, stage 3 (repeat visitor) may be skipped completely. And although it’s rare, an online customer may move from surfer to first-time site visitor to first-time buyer in one site visit.
Whether customers are buying from you on-line or off, at any point in their life-cycle, you are at risk of losing them. And the further into the life cycle they are when they defect, the more lost profit they represent. So what are some of the latest tools for maximizing your customer lifecycle and in doing so leveraging as much value and profitability from the relationship as possible? And what tools exist for ‘saving’ at- risk customers and ‘winning back’ those high value customers that stray? Consider these ideas:
Turning suspects/prospects into first time customers: Every industry has a limited number of high profit, or ultra customers. In retailing, ultra customers outspend other customers by a ratio of six to one, in the airline industry its twelve to one, and in the restaurant business its thirteen to one. Customer profiling and computer data modeling are helping firms identify these ultra prospects and pinpoint the marketing messages to which they will likely respond. Jan Hofmeyr and Butch Rice of Research Surveys located in Cape Town, South Africa, have created a computer model that enables a client’s marketplace to be viewed in terms of users and non-users. Users are divided into those who are truly committed and loyal and those who are convertible meaning they are declining in loyalty and ripe for being pulled away by a competitor. Nonusers (prospects and former customers) are divided into two groups: potentially convertible and non-available (since they are committed to their current supplier). For example, Hofmeyr and Rice have found that banks in the U.S. have a committed customer score of 62% while the commitment score for banks in the United Kingdom is only 36%. This means that many UK bank customers are at high risk of defection and a easy target for new competitors. The model has help companies plan the amount of advertising and promotional activity required for prospects according to their commitment level and potential value. - Turning repeat customers into clients--- Careful monitoring of profits has taught ScrubaDub Car Wash, a chain of successful family-owned car washes in metro Boston and Warwick, Rhode Island that only 13% of its customers account for virtually all of its profitability. Termed the More Valuables, these profitable customers tend to wash their cars at a much higher frequency than ScrubaDub’s other customer group, the Great Infrequents, who wash their cars only a few times a year. Such profit realities have spurred ScrubaDub to develop a sophisticated segmentation process by which customers are sub-divided into six value segments taking into consideration acquisition, development and retention costs, gross and net annual contribution and annual duration. Estimating a customer’s net relationship value enables ScrubaDub to determine how much the company can afford to invest in a customer at key points in the lifecycle. For example, Customers are encouraged to pay a one-time fee of $5.95 (good for the life of the car) to join the ScrubaDub’s frequent buyer program known as Car Care Club. When a customer signs up, ScrubaDub places a bar code on the member’s vehicle and then scans that code at the beginning of each visit. This scan provides information for the company’s data base and gives the attendant important computer screen prompts on how to add customized value for that customer at this visit. From the ability to call the customer by name to reminding the customer its time for his bi-monthly vinyl top cleaning, the data base is key to providing ‘smart’ service that helps turn returning customers into loyal clients. Winning back lost customers--- a national hotel chain, with 400 plus hotels was suspicious that customer defections were robbing the chain of much needed revenue. The chain went into its reward program data base and analyzed frequent business travelers by time periods, number of stays, frequency of stays, room rates and so forth.
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