Amazon customers, eBay sellers, and users of the Payback customer loyalty card (widespread in Germany, Poland, and India) know the routine: You are suddenly inundated by advertising e-mail and flyers for products that you don’t care about. That was yesterday. As companies now have access to more and more precise information on customers, they are learning to use it new ways. Moreover, many companies have realized that if they want to be successful in the long term, they must ask customers what they are allowed to do with their data first.
What do customers get out of it?
“There is an underlying fear that the data could be misused,” states Björn Bloching, co-author of a book on the subject, called “Data Unser”. “But there are still millions of Payback cards out there”. And millions of times each day, the intelligent IT systems at BigBazaar hypermarket outlets, Foodhall grocery stores, and anyone else integrated in the Payback system keep track of who buys which products and for how much. The cardholders regularly receive vouchers offering five, ten, or even twenty percent off various products. No Payback user would jump ship in light of such rewards. “Of course, the analyses of buying patterns are tremendously valuable to the companies,” says the Hamburg-based marketing expert at Roland Berger Bloching. What do people buy in the morning or after work? What are the preferred products in small towns or in large metropolitan areas? Shopping patterns also provide specific leads for additional business. If someone buys several Matchbox cars for their children in the toy department, they are sent an ad for a slot-car racing track. Bloching calls this “cross-selling potential”.
In another example, Groupe Casino and SAP are currently rolling out the “Apollo” project in French hypermarkets. Shoppers log on to a smartphone app to identify themselves and get suggestions for potentially suitable products as they walk from aisle to aisle. The app even awards spontaneous discount coupons. “Predictive analytics” is the name of this research field, now being implemented in practice. In this case, SAP says it has boosted sales by more than ten percent.
A helpful factor in utilizing these new methods is the lightning-fast analysis of huge datasets – often called “big data,” a term coined by McKinsey and IBM – with in-memory tools. The analysis of large datasets, such as giant customer files, has now become a crucial competitive factor. And a great deal of potential still lies dormant at companies. According to his experience, Bloching says, “Around ten percent of the companies currently do everything that is possible.”
Next page: Big data isn’t just for the big guns
Yet it is not only the large retail chains in the Payback system, with an estimated 15-20 million customer addresses, that are analyzing customer data. It is also companies who don’t need the highly innovative in-memory technologies, such as SAP HANA, because they simply don’t have that much data.
From BMW purchases to blood sugar readings
A customer journey requires just 30 or so criteria to determine how someone arrives at a purchase, claims the Bloching. When BMW presents its new 3 Series, it distributes prospects. A customer then finds more information in the Internet and prints it out, or reads test reports in car magazines. “He also configures his dream care in the configurator, saves it, and books a test drive,” explains Bloching. Then he follows the development and debates in blogs and forums. “With this,” Bloching is convinced, “we have captured 80 percent of the purchasing motivators.” Last but not least, some of the customers can be tracked in the Internet and customer data can be obtained from various channels. Entirely without in-memory systems.
The medical technology sector can also benefit from tracking customer or patient behavior. “Ideally, the customer benefits as well,” says Bloching. Take diabetics, for example: transmitting the patients’ blood sugar medicines electronically, recording movements and eating patterns, and combining them with doctors’ diagnoses on the course of the illness could help to avoid long-term damage through better therapy recommendations.
But not all customers are willing to submit this data. The fear that personal, private information could be mined further, or even sold to third parties, is too great. Customer data is a valuable resource – especially in an era in which Facebook CEO Mark Zuckerberg has announced the “end of privacy” for its more than a billion members, apps like Whatsapp pass on personal data without asking, and every eBay sale ends with a flood of spam mail in the seller’s mailbox.
Data misuse is a fatal mistake for companies
Ultimately, trustworthiness is the key word that will determine whether analyzing customer data – with or without in-memory tools – will benefit a company. Hamburg-based mail order giant Otto, for example, printed and distributed its catalogs to 15-20 million recipients for decades. In today’s digital age, the 15-20 million data records Otto has in its system provide the company with an attractive opportunity to share the address data and other insights with other companies. Smartphone users also leave valuable trails with their providers – O2, Deutsche Telekom, and Vodafone – providing location information when they are on the go. “This information could be very interesting for companies looking for a location for a new promotion,” says Bloching.
The temptation to make quick deals is certainly present. But it won’t help the company at all if their customers feel betrayed. In Bloching’s words, “A company that misuses its customers’ data will only survive another year at most.”