5 Ways to Avoid Customer Drop-Off

“Big Data” is big business, but unless the data provides actionable results in a usable format and on a timely basis, bigger only means more complex.
Most industries have access to massive amounts of customer data—literally at their fingertips. The challenge today is to get value from that data. Who are your best customers? What do they look like? What is their revenue potential? And more.

The idea is to make sure your data is available, actionable and accurate.

  1. You may get high response rates—but too often that does not translate to completed applications or sales. Do you have the information in your database that will tell you where, in the online process, the prospect drops off? Is there a point of frustration that you can pinpoint—and fix?
  2. Can your data be used to make the application, claims, purchase and other processes more convenient for your prospects and customers? Can applications and other forms be pre-filled with data that has already been supplied by your customer in a previous transaction? This can go a long way toward minimizing drop-off in an online transaction.
  3. Does your database provide transactional history so you have a 360-degree view of your customers? That is, do you know what products and services they already have with your company and what might be the most logical next purchase? Demographic and behavioral information also provide important information that can suggest relevant offers.
  4. A comprehensive database provides other opportunities to keep a prospect or customer engaged. In a retail situation, these opportunities might include sales if there is a nearby brick-and-mortar location or a coupon on an item in an abandoned shopping cart.
  5. Apportion dollars by customer potential. Genting Casinos, one of the world’s largest casino operators, runs 45 casinos in countries throughout the world. But beyond the fact that most, if not all, of its customers enjoy a toss of the dice, Genting knew each casino had different appeal to different individuals. By tracking which casinos each customer went to and how much money they spent, Genting was able to appropriately apportion its marketing dollars; still reaching everyone but in a manner and with a “spend” that made sense, given the prospect’s potential.

Large quantities of data present both a challenge and an opportunity. The question really is, “Does the data you compile encourage actionable and profitable decision-making?”

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