Should They Stay Or Should They Go?
Richard Branson Reveals His Customer Service Secrets [Source: http://www.youtube.com/watch?v=Fy4lYDN1gz4]
Many of us would agree that the customer is always right. But which customer?
Recent academic research suggests that in a tight economy, organizations often have a difficult decision to make: to spend money on keeping current customers happy or to use those funds to acquire new ones. Sometimes the decision becomes clear if you're in a particular industry. Airlines, for example, are known for keeping loyal customers happy. Mobile telephone companies, however, sometimes look past their customers in an effort to sign up new people to their calling plans.
Things sure seemed a lot more apparent a half-century ago. Automobile companies had several brands, each aimed at a different demographic. The idea was that a loyal customer would "trade up" to a more expensive brand as he got older and earned a bigger salary. With customers becoming more discerning and the marketplace more competitive, I suppose today's automaker might choose, instead, to focus their marketing budget on attracting buyers who have never owned or considered one of their brands.
In the end, each company is different. So each one has a different set of considerations on which to base its consumer retention strategy. Big Data is obviously becoming a valuable part of these constructs. When an enterprise learns more about how its customers think and act, its leaders can decide how much weight they want to give the retention of old customers and the attraction of new ones.
There's another angle in this decision-making process that's vital to achieving the right mix: the trusty "80-20" rule. I recently came across an item that said it's a given that a small number of customers tend to account for the biggest amount of an organization's profits. But depending on the market, that concentration of value can vary widely. For instance, in retailing, the best customers out-spend the rest by 16 to 1. In the airline industry, they out-spend the rest by 12 to 1. And in the hospitality industry, it's 5 to 1.
Therefore, if you're a retailer, you're most likely going to choose rewarding your current customers - especially the very best ones. If they're outspending the rest of your consumer base by 16 to 1, you definitely want to keep them shopping in your stores. But what about a discount motel? If the very best patrons outspend the rest by 5 to 1, then maybe it's more cost-effective for your motel chain to concentrate its marketing efforts on attracting a steady stream of new customers.
The Engaging Digital Consumers survey by Infosys revealed just how discerning modern consumers can be. A large portion of the 5,000 people polled said, for example, that they'd consider switching banks if they knew another institution was better at keeping their deposits safe from things like cybercrime. It's interesting to consider a bank's point of view as well. It stands to reason that some of those customers have enormous bank accounts and are constantly using all sorts of the bank's services, which translate into lucrative fees. Yet other customers undoubtedly have small accounts and never utilize the bank's add-on services. The bank will want to concentrate its efforts on rewarding the high-value customers. If it tries to attract new customers, it will want to utilize as much technology as possible to find and market to the high-value crowd.
No business wants to spend money on retaining customers who serve as a drain on the organization's resources. If someone is constantly buying clothing from a retailer and returning it a few days later, does that clothing chain truly want to reward that person with perks and special promotions? Probably not. What about mail-order catalogues that offer free delivery? If a customer tends to order lots of cheaper items more often, then he's less valuable to the company than the customer who orders lots of big-ticket items at a time.
However, a retailer doesn't want to cut a customer loose and risk bad publicity. A few years ago a cellular phone service did just that: It weeded out the customers who were costing the company money. The company failed to account for the bad buzz that its "rejection" letters created in the marketplace. Maybe if that company had better data analytics, it could have figured out how to better monetize services for otherwise low-value customers. Indeed, today's savviest enterprises are using the power of Big Data to maximize both the effectiveness and efficiency by which they interact with all their customers.