Deeper Relationships Require Intelligence

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If the relationship intelligence indicates that a customer is close to churning, for example, automating a message and offer (e.g., a free appetizer at a restaurant) might be able to help reverse that.

There is a lot that is hidden in the data that companies already have, but to make use of it, companies have to break down a number of barriers.

For one, “companies tend to have all of the data they need for effective relationship intelligence, but it’s typically siloed across the organization,” says Mark Smith, president of Kitewheel, a customer journey management solutions vendor.

Therefore, companies fail to leverage that data to improve customer interactions, and customer relationships suffer, he says. “When a customer service representative speaks to a customer, or even when a customer clicks on an email offer bringing them to your website, relationship intelligence can provide the real-time information needed to make that interaction more personal and impactful. In the customer service example, when a representative can see a caller’s history with the brand, it allows that representative to determine the next best action to take with that caller (or that action can even be recommended to them). In the email example, relationship intelligence would enable a decisioning engine to instantly personalize the website with relevant content, hyper-focused on the needs and interests of particular visitors.”


Artificial intelligence is another crucial element in relationship intelligence, Webb says. Some of the earliest uses were in the airline industry, where machine learning was first rolled out to determine how much to charge for seats and when to unlock higher and lower prices based on supply and demand.

AI enables marketers and sales professionals to have “conversations like we used to have, but at scale,” says Tara Kelly, president and CEO of Splice Software, a customer engagement solutions provider. Relationship intelligence fueled by AI enables users to deliver the right message to the right customers at the right time, but beyond that, it enables companies to take marketing to the next level by gaining a deeper understanding of the target’s behaviors and engagement.

“The best salespeople already do what the AI could do faster, but imagine if instead of a salesperson manually researching when emails get opened by a particular target to time a phone call, the CRM system would instead notify a sales representative to call ideal target John Smith at exactly 10:43 a.m. and talk about this one specific challenge because John has opened five nurture emails around that time and all of them had subject lines that spoke to that topic,” Kelly says.

AI-based relationship intelligence can make sales teams exponentially more effective by eliminating the time it takes them to research and deliver the most effective messaging, times to call, content offers, and channels to use, she adds, noting that “the possibilities truly are endless.”

These technologies can identify hidden buying patterns that would be impossible for humans to spot, Webb adds.

“An effective decisioning engine, powered by historical relationship information, is key to interpreting real-time insights, but the best relationship management requires human interpretation as well, ultimately driving better CX and more positive incomes,” Smith says.

Another challenge with relationship intelligence is that different information has varying degrees of relevance from one business to another. In the insurance industry, for example, companies derive the most value from knowing when someone is entering a new stage of life, such as having a child, getting married or divorced, or buying a home, according to Michelle Tilton, vice president of marketing at Infutor Data Solutions.

In rural areas, the type of truck a person drives and the type of engine it has might be important relationship data elements.

And for school supplies providers, knowing the ages of customers’ children can be useful; parents of preschoolers will obviously have different needs than those whose children are in high school or college.


Though artificial intelligence and machine learning can provide marketers with more insight and automated actions than ever before, companies still need to protect themselves from relying on false relationship intelligence triggers.

There are some signals that almost always run true to form. One such example is when someone turns 65 and qualifies for Medicare; insurance companies can count on that person’s needs changing, Tilton says.

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