Marketing’s crystal ball – predictive analytics – is one of the most exciting tools in data marketing today. The vast amount of real-time and historical data available about customer behavior gives marketers unprecedented ability to anticipate customer needs rather than merely respond to them.

Predictive analytics allows data marketers to easily identify the characteristics of their most likely customers, discover what they are like, what is likely to drive them to purchase, and begin what will be a hopefully long lasting relationship. Unfortunately, most of these modern-day fortune tellers are reading the left palm, but forgetting about the right.

Despite overwhelming proof that retaining customers is far more profitable than acquiring customers, many brand marketers use predictive analytics for customer acquisition but not retention. Strangely, this seems to indicate that marketers value non-customers more than current customers, and the reason may surprise you. Results of a 2016 Forbes Insights/Sailthru “Retentionomics” study show that the primary factor marketers have in making decisions about retaining and acquiring customers is inertia. In other words, “this is the way it has always been done.” In the study, 84 percent of respondents who focus primarily on customer acquisition reported that inertia drove their decision, compared to just 63 percent of those who focus on customer retention.

Hardly a pat on the back for the “Retention Gurus,” but nevertheless surprising considering widely known statistics that show increasing customer retention by 5 percent can lead to an increase in profits of 25 percent to 95 percent.

That same body of Bain & Co. research also finds that the likelihood of converting an existing customer into a repeat customer is 60 percent to 70 percent, while the probability of converting a new lead is 5 percent to 20 percent, at best.

The Forbes Insight/Sailthru research corroborates this truth, uncovering that more retention-based marketers significantly increased market share over the last year (14%) compared to acquisition-based marketers (5%). Retention marketers also scored better in terms of customer churn. Forty-five percent of those focused on retention strategies did not have increases in churn over the previous year, compared to just 33% of acquisition marketers. In addition, 88% of retention-based marketers say they are exceeding their customer acquisition goals.

So why are marketers so hell-bent on acquisition? For starters, measurement. It is easier to measure the cost of attaining a new customer, which feeds to the ROI demands of CFOs and CEOs. But with the proper tools, measuring the ROI of your marketing spend against current customers is not difficult.

Another reason marketers place more of their ad spend on acquiring new customers is clarity. The “Retentionomics” study reports that 96% of respondents said they have a clear picture of their most valuable acquisition channels and a solid understanding of customer lifetime value. Eighty-six percent said they have a good grasp on their churn rates. But the research shows that marketers generally have a murkier picture of existing customers and what makes them tick. Although more than half understand the causes and effects of repeat purchase rates (71%) and customers who purchase only once (64%), neither of these figures outweigh their stronger understanding of acquisition channels.

Given that marketers have far more data from their loyal customers by virtue of understanding their purchase history, they have a competitive advantage over companies attempting to poach these customers. Predictive analytics is the perfect tool to capitalize on this advantage and erase the lack of clarity of existing customers.

By leveraging customer data and predictive analytics, marketers can personalize their interactions with customers. They can anticipate when a loyal customer is likely to make a repeat purchase and make recommendations for additional products that a customer may be interested in based on past purchases. The data can also be used to make better use of loyalty programs. By focusing on recency, frequency and spend metrics, marketers can identify and reward their most genuinely loyal customers more generously.

Analytics can even be used to personalize these rewards. Instead of receiving generic offers, each customer is given their own unique experience with individualized incentives. On the other hand, the data can be used to entice customers to become more loyal or keep them from defecting to a competitor. Customers can be scored based on their likelihood to make a repeat purchase. Those that are less likely can be enticed with a special offer. Overall, predictive analytics allows for the incorporation of a deeper level of personalization into emails and social media, which is particularly necessary in an age of ad blocking.

Marks & Spencer Director of Loyalty, Customer Insights & Analytics Nathan Ansell says, “Our budget is all about retention, though we don’t necessarily use the word retention. Really it’s frequency—we focus on encouraging those who shop less often to shop more often and across categories.”

I’m not suggesting that you completely forgo customer acquisition. I’m simply suggesting that one of the best ways of doing this is by appealing to your current customers. It not only helps ensure long-term loyalty, it also means a large part of the job of attracting new customers will done for you through word of mouth. It will provide you with an audience that is more receptive to your social media campaigns and more likely to share posts, an audience less likely to complain and to be more tolerant of your mistakes, and – most importantly – an audience that is going to consistently spend money with you.