I saw a thief on the subway last week. Chances are, she (or someone like her) is stealing from your company. I wonder if you’ll do anything about it.
No, it wasn’t a sly pickpocket in the crowded car, bumping into people and deftly removing wallets. It wasn’t a mugger threatening violence if someone didn’t hand over his cash and watch. It wasn’t even one of those guys who sell worn-out batteries for a dollar. The New York Police Department cleared Manhattan of the worst vermin (although the guys selling batteries are still around).
This thief identified herself in a conversation that went something like this:
Friend of the thief: I’m not sure I want to buy that dress. It’s sort of expensive.
Thief: Oh, just get it and wear it at the party. Then return it.
Friend: No! Get out!
Thief: Oh sure, I do it all the time.
So there she was. In plain sight, a woman was crowing to her friend about abusing stores’ return policies. She wasn’t a thief in the traditional sense, of course. Technically, she isn’t breaking the law. But in effect, she steals from companies.
Do you want this type of person as a customer? Assuming she isn’t generating much profit on other items when she buys, uses, then returns your products, I suspect you don’t.
An oft-overlooked area of customer retention programs is an upfront analysis of whom you do and don’t want as a customer. Although it’s generally good to keep all your customers happy, some may actually be costing you money and lowering profits.
For companies with the right data, it’s possible to identify the types of customers who sap profits and even the specific individuals doing the damage. Some of these people may blatantly abuse some aspect of your company’s policies, like that thief on the subway. Other customers may not be as easy to identify but nevertheless might be hurting your return on investment (ROI). Only a careful data analysis will yield their identities and characteristics. You may be surprised at what you find.
Your Best Weapon
The NYPD used the COMPSTAT system to wipe out crime in the city. You can develop and use a similar system to wipe out people stealing from your company.
Analysis of data supplied by a good working database is the best initial weapon against these “bad” customers. What are their characteristics? What items are they most likely to purchase? From which areas of your marketplace do they come? What stores do they hit?
Last week, a Wall Street Journal article discussed how Best Buy uses such analysis to identify its problem customers, or “devils” as its consultants term them. Once identified, Best Buy devised a strategy to thwart their efforts. Tactics include changing loss-leader promotions, which some customers abused (buying items at the loss-leader price, then reselling them on eBay). They excluded the devils from direct marketing promotions.
Best Buy has also identified habitual return abusers, like the subway thief. They’re labeled in the database. The database is integrated into the point-of-sale (POS) system and can identify would-be thieves when they attempt to make returns. The company also began strictly enforcing a 15 percent restocking fee policy.
A Knight in Shining Armor?
The Return Exchange offers another weapon to combat thieves. It compiles a database of potential return abusers from data supplied by multiple stores and companies.
The compiled data are analyzed, and return/exchange abusers identified. The Return Exchange notifies participating retailers in a process similar to credit-card authorization. The POS system identifies potential abusers. The retailer can then take whatever action it deems appropriate.
A Blind Eye to the Problem?
Despite the availability and use of these tools, some companies won’t solve the thievery problem. They have management goals tied to revenue and customer acquisition targets rather than profit goals and acquiring profitable customers. Such goals cause managers to turn a blind eye to the thieves stealing from the company.
The Subway’s Safe. What About Your Business?
Thanks to data analysis and an improved policing strategy, New York City’s crime rate in was drastically reduced. A similar approach at your company can help cut this type of thievery and improve profitability.
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
A new starter in Team SaleCycle recently asked me the following question… “Wouldn't they just come back anyway?”
American Apparel's chief digital officer discussed the future of retail, the importance of delivering value to the consumer, and strategies for an IoT and omnichannel world.
Every marketer has been sitting with his or her analytics team, reviewing an overwhelming spreadsheet of data points. It tends to hurt ... read more