As detailed in our latest retail fail (available here), the demand from consumers for highly personalized service has become firmly rooted in the expectations of daily commerce. In short, every transaction between business and customer MUST be personalized to the individual—meaning the new world of leveraging data has literally become one of feast or failure. But with all of the demands being made on business to be able to interact in such a highly unique way, the question remains: How does one actually get there?

By now, almost everyone is familiar with the concept of single-user-profile data—the holy grail of the new digital economy. However, as important as it is, the systems and measures that are required to enact such a revolutionary concept—a single, progressively built data file on every customer—is still something that most struggle with.

The blame in this case falls directly on disparate data systems, something that far too many businesses suffer from. For instance, old-school and now antiquated marketing and sales practices such as rewards programs, coupons, points cards, and so on, are a large part of the problem. Pair those data points with newer technology such as e‑commerce platforms and associated customer profiles, in-store POS-contained files, and more, and the proverbial water becomes muddier and muddier as each layer is added on.

The outcome? Think of it this way. sometime today you have probably logged into Facebook, LinkedIn, Twitter, and other social media sites, using a variety of usernames and passwords (at least I hope you have for cyber security sake but that’s a different conversation entirely). Now, imagine if all of those platforms were owned by the same company. It would literally mean that, for every one of your accounts, you would be “different people” from a data perspective. From user names to the ways that you log in, all represent you as a different individual. Welcome to the world of dirty data.

Now, take that same scenario and apply it to your retail establishment. A customer uses a specific username and password to log into your e-commerce platform, but uses a Gmail account for their rewards card, and an old Hotmail account when talking to the cashier that enters it into the POS for promotions—and there could be several more instances. The outcome? One customer is now officially multiple customers in your database. Furthermore, aside from the dirty data problem, the lost opportunity to connect the dots on all of those purchases means you just lost money . . . and lots of it.

You see, the path that needs to be followed in the new digital economy is connecting all data and its sources, meaning that the single user profile is exactly that . . . single. Therefore, the first step in achieving the goals is having a ubiquitous view of your data. And though that will inevitably mean cleaning potentially thousands of files, it’s the first step in mitigating risk against more dirty data accumulating in your systems.

The next is the technology that binds everything together. And like any new marketing and sales initiative, it means implementing a platform that connects all interaction points with each other. Now imagine the possibilities. A customer logs into your e-commerce platform and buys something. That data is recorded in their single user profile. Now, days later they visit the store with coupons, perhaps a rewards app, maybe even just an old-school points card to be scanned at the counter—again, in every instance it remains the same person due to everything being connected.

The real trick here—though not so much a trick as a process—is the interlinking of systems. The POS can capture specific data from the in-store staff when purchases are being made in person. Then, if that customer buys something online or in-app, the same name, email address, phone number, and so on, can be used to match their profile info—ultimately building data such as purchase history, likes, dislikes, and more.

Eventually, the platform could begin driving even more personalized offers based on that information, as well as leverage predictive data such as optimum conversion times (if a customer seems to always buy online at 2 a.m., the system can learn that and send them offers at 2 a.m.). And yes, I am quite aware of how creepy that may sound—and perhaps it is for some. But for the majority, the data shows that it’s what people actually want.

Gone are the days when people are accepting of generic “demographic” marketing and sales techniques. Now in our always-connected modern age, people are not only aware of their personal habit data, they fully expect it to be used. In fact, they are more than willing to give meaningful information at all contact points to garner the experience they want—one that is unique just for them.

Now the question becomes: Are you ready to give your customers what they want or give your customers to your competitor? Your call . . . and maybe that call should be to us. We can help.