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CRM Evolution Day 1: Personalization Requires Technology and the Human Element
'Customers want to be loyal to you…but we don't necessarily roll out the red carpet and make it easy for them to remain loyal to us,' says an expert on brand advocacy.
Posted Apr 25, 2017
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WASHINGTON — Delivering a customized experience to customers is all important, but creating such experiences and keeping customers coming back requires technology complemented by the human element, speakers contended on day one of the CRM Evolution 2017 conference.

“Software does not replace strategy,” Michael Fauscette, chief research officer at G2 Crowd, told the audience during his session “View From the Crowd: Digital Marketing.” He outlined the advantages of pairing analytics with a psychological understanding of customers’ individual preferences. “You can take analytics and psychometrics and combine them to get a behavioral model that lets you start to target in a much more micro-targeted way, because you can figure out what the person is looking for, when they’re looking for it, how they want it delivered, where they want their messages delivered…and how often,” he said. The combination of the two can determine a customer’s “tolerance for your delivery of content” as well as “the optimal way to deliver that content.”

Predictive analytics, too, should be put at the service of giving customers personalized experiences. “The promise of predictive analytics is about personalization—it’s not just having a segment, but the ability to send exactly the right message to exactly the right person at exactly the right time, with ‘exactly’ being the payoff that they’re actually going to buy,” said Steven Ramirez, CEO at Beyond the Arc, in his session “The Marketer’s Cookbook: Recipes for Using Predictive Analytics.” “Even though we have segments, we’re not thinking about [customers] as a segment; we have the promise of an individualized approach.”

Ramirez identified three steps to building a predictive analytics model: data collection and preparation; the creation and evaluation of a model; and the deployment of customer information into the model. “The fuel for predictive analytics is…[what] we can consider as data. It’s not that the data is different, [it’s that] there are some things that we never actually thought of as data that we could use as part of predictive analysis,” he added.

But it’s important not to view customers as abstractions, said Randi Busse, president at Workforce Development Group, during her session “Turning Customers into Brand Advocates.” “We look at customers as numbers—we look at them as interruptions, instead of as the reason we’re here in the first place,” she told the audience. “We act like the people we are serving are the enemy.”

“Customers want to be loyal to you; they don’t want to have to go look for a new bank, for a new insurance company, they don’t want to have to go look for a new doctor,” she continued. “But we don’t necessarily roll out the red carpet and make it easy for them to remain loyal to us. If you want your customers to be brand advocates, you’ve got to act like it, and it starts with who you’re hiring, and who you have representing your business…and how easy you’re making it for your employees to go above and beyond to delight customers.”

She noted that companies need to realize they’re not alone in competing for customers’ business. “Your customers have choices, and the experience that you provide is often the only differentiator between you and your competition.” Busse outlined seven components in turning customers into brand advocates: (1) treat customers like they are family; (2) be where your customers are; (3) solicit feedback and act on it; (4) make it easy for customers; (5) put yourself in your customer’s shoes; (6) provide a consistent human-to-human experience; and (7) provide a customized experience.


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