We’ve all heard by now that keeping an existing customer is significantly less expensive than acquiring a new one. That is to say, customer retention retail analytics has a direct effect on revenue and profitability.

Data is increasingly central to the goal of improving customer retention. Here are some of the primary ways companies can use analytics to keep customers coming back time and time again.

Get to the Root of Customer Churn

Of course, your enterprise is going to lose some customers over time — and one function of analytics is to help you understand not only your “churn rate,” but also to get to the bottom of why people are leaving.

It helps to understand where your company stands relative to industry benchmarks, too. According to Statista, the average customer retention rate within the retail sector stands at 63 percent — making it one of the industries most prone to churn. On one hand, this points to customer retention as an ongoing challenge; on the other, it reveals the opportunity at hand for brands able to take data-driven action to understand and address costly churn.

Advanced retail analytics today go far beyond showing employees static readouts of performance metrics, which would only serve to let decision-makers know how many people are churning without allowing them to keep drilling down into data to find out why.

Ad hoc, self-service analytics platforms can handle unlimited questions from managers, executives and associates — meaning that exploring churn rates just serves as jumping-off point for further explorations. Exploring the data from different angle may uncover one or more surprising potential reasons for higher-than-average churn: poor customer service, pricing issues, ineffective marketing, website difficulties … the list goes on and on.

At the end of the day, effective analytics tools allow users to keep analyzing churn from different angles so they can uncover its root contributors, then make targeted suggestions for addressing these core problems.

Personalize Product Recommendations

Earning a sale, whether online or in person, requires reaching the right customers at the right time with the right offers. Well-timed product offers, in addition to giving customers the sense that your brand understands their wants/needs, can also increase average order value. In fact, research has shown that product recommendations drive about one-fourth of ecommerce orders (24 percent) and revenue (26 percent).

Analytics is instrumental in understanding the impact of various approaches to product recommendations. For instance: Do people respond better to marketing messaging containing links to products they have browsed on your website in the past or links to overall customer favorites? Or both?

Digging into the data here allows brands to analyze the impact of their up-sell and cross-sell initiatives, their marketing and promotions communications and their online product recommendations.

Drive Your Loyalty Program with Data

A major contributor to overall customer retention is how your company rewards customers for their loyalty. According to marketing expert Neil Patel, here are some of the pillars of a strong loyalty program fueled by data analytics:

• Sending timely, relevant promotions to existing customers based on what data says about the behavior and preferences of various customer segments.
• Continue to target and specify product recommendations based on multiple factors like location, purchase history, customer spending profile and more. This way your brand can anticipate customers’ desires and needs early and impress them with your spot-on suggestions.
• Personalize rewards — and show customers appreciation for a variety of actions, from making a purchase to visiting your website to interacting with your marketing materials. Make sure customers clearly understand your rewards program, although occasional rewards “just because” can strengthen your relationship, too.

Retail analytics holds the key to boosting customer retention by providing insight into causes of customer churn, how to deliver effective product recommendations and how to foster long-term loyalty.