Predictive Analytics Can Pinpoint Profitable Customers
When handling leads, it helps to distinguish between the good ones and the bad -- those who request a product demonstration compared to those who stop by your trade-show booth just to snag an attractive freebie. It's often easy to see who's worth the chase. Just like leads, there are good customers to pursue and bad customers to pursue. A recent Forrester report, "Optimizing Customer Retention Programs," explicates the benefits of "uplift modeling," which focuses on using predictive analytics to pinpoint profitable customers. From there, marketers can identify the prospects for whom campaigns will be most effective.
The report identifies four categories of consumers:
- "Savables": Receiving an offer won't induce these customers to leave, but not receiving one might. This is the group that marketers must focus on.
- "Sleeping dogs": An unwelcome marketing campaign can provoke this group to end the relationship altogether.
- "Sure things": Customers who don't need to receive offers to stay.
- "Lost causes": Customers who will leave regardless of the offer.
Of the four, Savables require the bulk of a marketer's investment; spending on all other categories should be deemed "wasteful," and must be reduced. In a contracting market, new customer acquisitions are hard to come by, making retention programs exponentially more important, the report states.
According to the report, companies face a three-prong challenge when it comes to formulating a concrete retention program:
- disagreement on the definition of "customer churn";
- failure to target appropriate offers to "churners"; and
- an attempt to retain all customers equally.
"When we typically think about churn analysis or retention analysis," says Suresh Vittal, principal analyst at Forrester Research and author of this report, "we [don't] think about how likely [it is that] the consumer [is] going to change their behavior because of what we did...[or] how your marketing is likely to impact that behavior." Most marketing programs, the report states, typically approach existing consumers with a blanket offer, motivated by the mentality that "all customers are equally important and all can be saved," rather than honing the offer to target the most profitable ones. Moreover, the report emphasizes that, even within the Savables segment, not every customer has the same value. Each customer should be treated differently, based on that particular customer's value to the organization.
Vittal argues that current retention techniques fail to provide marketers with the ability to take action when a marketing program is already in place. For example, he says, there are scoring techniques that can identify whether a particular consumer is more likely to respond to a cross-selling campaign or to a churn campaign. But what's missing is the ability to identify what happens when consumers actually receive the campaign, which is critical in determining whether an offer should have been sent in the first place. In other words, instead of simply looking at "likelihood to respond," uplift modeling focuses on predicting the change -- positive, negative, or nonexistent -- a particular offer can have on a particular consumer's behavior.
Retention activities, though less expensive than acquisition initiatives, still come with a price tag attached. Therefore, marketers must intelligently build campaigns that target customers who contribute directly to the company's overall profitability. Uplift modeling can also help marketers avoid triggering customer defection, an aspect of retention that often goes overlooked, Vittal says .
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