The customer buying journey has evolved from an end-to-end experience to a data-driven relationship. And a big part of that relationship is using customer data responsibly.
|“Machine learning really helps us see which customers we should be targeting … this shows you is just how granular we can go,” SAP’s Naomi Ko said (see the video below)|
“If you think that consumers are generally indifferent about their privacy or personal data, ask your colleague or boss for the passcode to unlock his or her phone, Google account, or Facebook page,” The Hill stated last week. “We’re told it’s normal for someone to have access to our personal information, but it’s not.”
Organizations can use customer data to seamlessly interact with people, regardless of where, when and how they decide to engage, but it must be mutually beneficial — and clearly so. Intelligent technologies, such as analytics and machine learning within SAP C/4 HANA and SAP Leonardo, help users deliver that personalized customer experience (CX) across channels, just remember …
“Don’t Be Creepy”
“Customers want their data to be protected; of course they want personalization, but not at the cost of their privacy,” Alex Atzberger, president of SAP Customer Experience, said during the opening keynote of SAPPHIRE NOW last month. “Customers are done with creepy — don’t be creepy … without consent, don’t personalize.”
This can be tricky across channels; a CX might begin on social media, and then lead to a retailer’s webstore and email campaign before achieving the sale in a brick-and-mortar store. For example, our hypothetical shopper, Lisa, begins her journey by looking for inspiration on Pinterest, where she sees the photo of a dress she likes.
“She clicks on it, and right away she’s led to the website,” SAP Solution Engineer Naomi Ko said during a demonstration at SAPPHIRE NOW (see the video below). Lisa decides to sleep on it; but before she leaves, the webstore asks her to sign up for exclusive offers and updates — and she gives her consent.
Lisa’s consent and data are as good as gold to the retailer.
Using Customer Data As Currency
In our example, Lisa uses her data like currency, consenting in exchange for personalization and special promotions. Meanwhile the retailer can combine Lisa’s data with that of other customers for greater insights from analytics.
“Machine learning really helps us see which customers we should be targeting,” Ko said, highlighting data visualization dashboards and predictive scores. “Throughout all of the interactions that the customers are having with the retailer or the brand — across all of their channels — we’re actually able to capture their interests.”
This means highly relevant outreach to consenting subscribers based on the specific products they’re looking for, how close they are to a brick-and-mortar store, the nearest store’s inventory and myriad other factors. A clienteling app can even alert in-store associates that Lisa is on her way into the store for a specific dress, briefing them on her omnichannel customer journey thus far.
How Data Delivers Exactly What Customers Want
“The recommendation engine is able to identify certain accessories that she most likely would want to buy, and that pairs best with the dress,” Ko said. “She’s really excited; she’s in awe of the dress … she’s in love with everything, and so she splurges.”
But that isn’t the story’s end, especially if Lisa posts about the dress or her CX on social media. Her friends and followers learn about the product or brand. And the retailer can refine its 360-degree profile of a happy customer — in hopes of better serving Lisa in the future.
“Of course, on a day-to-day basis, the marketing team will not go into Lisa James’ profile and see, ‘How should I target to Lisa James?’” Ko said. “But what this shows you is just how granular we can go to see how we can personalize the customer experience.”
Cultivating the End-To-Never-Ending Experience
“We have grown accustomed to the ease with which technology enables our lives … [but] we have to actually pay for all of the ‘free services,’” Forbes stated this month. “Data is the currency that makes free or near-free services possible.”
And, like any currency, customer data must be safeguarded. This is a tremendous responsibility, but benefits to the customer and organization can make it one worth bearing.
“Expect to be flexible and, dare I say, even agile when responding to the challenges we face,” Eastman VP and CIO Keith Sturgill said during the ASUG keynote at SAPPHIRE NOW. “Learn to adapt — and even anticipate the inevitable change.”
Part of this adaptation is knowing that the customer journey isn’t over at the point of sale. It continues indefinitely by responsibly cultivating data-driven relationships.