That same onus is on the payments industry as a whole -- particularly those providers serving consumers. Customers have higher expectations than ever, and the transactions space must evolve to meet and exceed them. Here are a few data-driven lessons they can learn from the best of data-driven marketing.
To know me is to love me
Successful customer relationships depend on understanding the customer as an individual, not as part of their Zip+4 or demographic.
Retailers frequently allocate shelf space by brand, with products from the same vendor grouped together. That works in categories like soup, where shoppers often select a specific brand and then desired flavor. However, with milk, the average customer cannot name the brand last purchased, but will likely know whether it was skim or 2% and whether they prefer gallon or quart. Longitudinal analysis of customer baskets over time yields the insight to place all skim, gallon-sized cartons from various brands next to each other.
Putting customer data at the center of product placement enables a better understanding of the customer's decision tree for each product category, organizing the store to ensure that people are able to find their usual purchases easily, while also discovering desirable alternatives. How will payments providers make repeat purchases easy for every customer?
Customer data can also improve perception on assortment. Usually, revenue and margin are analyzed to remove the worst-performing products in the category. However, a customer-centric decision reviews loyal customers over time to determine which products they consider valid alternatives. This ensures that products without substitutes carry greater importance -- even if they are financially less desirable in isolation. While no retailer can carry every product, it's important to carry the ones that loyal customers expect. These are the kinds of expectations the payments industry must strategize to anticipate.
I'm a special snowflake
For decades, retailers have sent offers via direct mail and e-mail, often distributing the same coupons to entire customer segments and calling that “targeting.” Shopper data can be used to create highly personalized communications wherein no two customers get the same set of offers -- even at scale of over 10 million mailings. Redemption rates for these offers are significantly greater. The payment industry must be aware of the needs of customers on an individual level, customizing aggressively.
Don't steal my time
Finally, here is an example from the payments space. I recently caught a New York cab and saw that I could pay for my ride using a smartphone app. Curious, I downloaded Way2Ride, entered my credit card details and tip preference and “checked in” to the cab. At the end, the receipt printed immediately. Amazed, the driver asked how I had paid so quickly. Unaware that his own cab now has this pay-by-phone feature, he had automatically been paid while I received an alert on my phone with the transaction details.
These user experiences are crucial. They must be personal, convenient and, ultimately, emotional. With so much discussion in the payments industry about the impact of mobile, NFC, biometric scanners and other technologies, we must remember the larger goal: to deliver an experience so pleasing that the customer can't wait to tell her friends about it.
The payments industry is not the first to have to overcome this challenge. The shopkeepers of yesteryear excelled at personally connecting with every customer. This didn't scale with mass retail. Big Data and associated technologies are reversing this trend, enabling large retailers to build loyalty by returning to that more personal experience.
Customer-centric decisions throughout retail marketing help develop relationships based upon a simple concept: that the retailer is loyal to the customer, not only the other way around. The winners in the payments space will be the providers who nail this principle and infuse every transaction with customer centricity. Are they ready to rise to the occasion? Only time -- and data -- will tell.