big data analytics and client experience

On my way to Dallas for client meetings, I decided to check my post office box for mail. I was there all of two minutes max, and when I started my car, all I heard was “click, click,” and the dashboard controls went black. After a jump, I headed to the auto repair shop to get a new battery. Not long after that, I was back on the road to Dallas.

Big Data Blunders

Here is where that national retailer made a significant data blunder. The very next day after replacing the battery, they send me a coupon for a battery replacement. Huge FAIL! What is worse than FOMO? Actually, missing out on saving money on a recent purchase. Surely their systems knew I replaced my battery. Why doesn’t the marketing team know it also? Could it be a classic case of departmental silos?

On a trip to Los Angeles last year, Uber’s vast data analytics recognized that my ride took longer than expected. That’s an impressive catch, but the email they sent was so disappointing that it made my experience worse. It was a tremendous missed opportunity to build their brand loyalty of which they are in desperate need.  “Your trip took longer than we estimated, and we know that’s not ok. We want you to have the best experience possible, and we hate that your latest trip fell short.” And???? That was it. Why not add “So we are giving you 10% off your next trip?” That would have improved an inferior experience.

Big Data Bulls-Eye

Are there companies using the hordes of data they collect to improve the customer’s experience?  Academy Sports and Outdoors did just that for me during the Christmas holidays. A gift I ordered online was delayed longer than they anticipated but with plenty of time to spare. I was satisfied with my shopping experience. To my surprise, I received an unsolicited card in the mail from Academy apologizing for the order delay. In the card was a coupon code for $20 off my next online purchase. Now that was an excellent implementation of big data analytics applied constructively. Kudos to Academy.

Data is fundamental, but what you do with that information is where you can differentiate and design magnetic client experiences.

What metrics are you collecting and not capitalizing on to enhance experiences? Helpdesk resolution time? Construction timelines and delays? Loyalty?

Are your analytics creating client magnetism or missteps?