Getting new customers is one thing. Keeping them is another. It’s in retailers’ best interest to prioritize customer loyalty and retention. Why? There are a few key reasons.
Marketing toward customer acquisition tends to cost more than retention does, especially if you’re running paid advertising campaigns to attract new buyers. There’s also the fact that retailers have a higher probability of selling to an existing customer than a new prospect; and that repeat customers tend to spend more than new ones.
Long story short: How well your company can retain customers and drive repeat sales will have a huge impact on your bottom line. And your approach to retail analytics will determine how much insight employees are able to glean from data — then use those findings to shape decision-making in a way that drives loyalty and sales.
Here’s more on the relationship between retail analytics and customer loyalty as it pertains to profitability.
Helping Retailers Understand Customers & Boost Loyalty
One traditional challenge retailer has faced throughout the year was getting timely insights about customer preferences and behavior to those who need them most. It’s less helpful to know what customers wanted and how they acted six months ago than it is to understand their behavior and spending patterns for the current time period, for instance.
The latest wave of self-service retail analytics gives merchandisers, brand managers, store managers, marketers, executives and others immediate access to stored data. These employees can ask questions on the spot and get answers in a digestible format using search-driven or conversational analytics tools, like this one https://www.allego.com/platform/conversation-intelligence/. Artificial intelligence-driven analytics can also help uncover customer insights that nobody had yet thought to seek out, too.
Here’s a real-world example: One Fortune 100 Retailer uses ThoughtSpot data analytics to perform 40,000 weekly searches on product performance, including pulling data pertaining to customer behaviors for any date range. This has helped this major organization optimize its product offerings and promotions based in part on these customer behavioral insights.
The end result is that customers see what they want in stores and receive personalized promotions, giving them good reason to keep making purchases over time.
Key Metrics to Measure Customer Loyalty
Metrics are an integral part of goal-setting and performance analysis, and none are more important to access than key performance indicators (KPIs). These are the metrics a retail organization has deemed most important because they speak to the underlying stability and growth of the company.
Here are a few very important metrics to keep top of mind in conjunction with your retail analytics strategy:
- Customer Churn: Customer churn is the rate at which your retail business loses customers. High churn indicates you’re falling short in providing optimal retail experiences, or that customers are finding better luck with a competitor.
- Repeat Purchase Rate: Repeat purchase rate will tell you the percentage of customers who returned to buy again from your company. You can look at this metric by demographic to understand who your ideal buyer is.
- Customer Lifetime Value: Customer lifetime value will tell you the net profit you can expect over the entire course of a relationship. You can also compare this figure to how much you’re spending to acquire customers to make sure you’re remaining profitable.
Only retailers capable of truly understanding their customer bases — wants, needs, behaviors, short- and long-term spending habits — will be able to make decisions that drive loyalty. Retail analytics gives employees across an organization instant insight into customer behavior so they can adjust operations as necessary. This is how retail and customer loyalty analytics drive your bottom line as a modern retail organization.