Customer Retention Metrics
Lexer is the customer data and experience solution for leading retail and ecommerce brands.
CUSTOMER RETENTION METRICS
WHAT ARE CUSTOMER RETENTION METRICS?
Sometimes, it can be hard for businesses to attract customers. What’s even more difficult, and yet even more important, is figuring out how to build loyalty and keep customers coming back.
This is called customer retention, and it’s one of the key aspects of running a successful and sustainably profitable business. Customers shopping at your store for the first time will more than likely be unfamiliar with your brand, your product offerings, your quality, and your pricing. As such, the first time they visit your store, either online or in person, they probably aren’t going to buy very much. Regular customers, on the other hand, will be familiar with your store and more enthusiastic about your products. They’ll tend to shop more frequently and feel comfortable spending more.
Having only one-time shoppers as your customer base means low sales and low visitation—both bad for business. Improving customer retention rates is a way of avoiding this by transforming a greater part of your customer base into regulars who buy often and in bulk.
Competition is becoming stiffer in all areas of retail. With the world of retail and ecommerce growing rapidly, people are no longer limited to shopping only at those retailers with nearby storefronts. Now anyone can shop virtually everywhere, which makes it hard for one company to stand out from the rest and build customer relationships. In response to these challenges, many companies have now turned to data science and customer analytics software to better understand what causes customer churn and how to use this information to drive customer retention.
In this article, we’ll go over the basics of this process. We’ll explain how loyalty is measured using the customer retention rate formula; we’ll talk about the omnichannel customer retention metrics that data software like Customer Data Platforms (CDPs) measure; we’ll go over how this info is analyzed and modeled; finally, we’ll show how the whole process helps brands and retailers make real-world decisions to keep customers happy and loyal.
CUSTOMER RETENTION MODELING
Data software has practically limitless applications in the world of retail. When dealing with the ways customers shop and interact with your store, one of the most simple things this software can do is show you how well your company is retaining customers—a key performance indicator in any line of business.
The customer retention KPI formula can be applied for any time period, big or small. It says that raw customer retention rate is equal to the number of customers your business has at the end of a period, minus any new customers brought in during this time, divided by the initial number of customers, then multiplied by 100 like this:
((End Customers-New Customers) / Initial Customers) X 100
For businesses with hundreds or thousands of customers and a variety of sales channels, figuring out how to measure customer retention rate accurately can be daunting. Customer data software, however, can make this quick and easy. Data programs measure the shopping patterns of anyone who visits your stores and keep track of whether they are new or returning customers, how often they shop, and how much they spend. This allows for customer retention modeling that is accurate and up to date. Knowing how loyal your customer base is at any given time, however, is just the first step and only a small fraction of what these data tools can do.
Customer lifetime value is another key metric to measure to understand the success of your customer retention efforts. By retaining customers with the highest lifetime value—and ultimately working on growing that lifetime value—you can drive the highest ROI for your business. Learn how to measure customer lifetime value here.
CUSTOMER RETENTION ANALYTICS
Customer retention analytics and data software can tell you much more about customer loyalty than just how many individuals continue to shop with you over a period of time.
In order to properly respond to issues of customer churn—where shoppers stop doing business with you and move to a competitor or other solution, you need to know more than just how many customers you’re managing to retain.
Analytics software, particularly with predictive analytics capabilities, can give you customer retention statistics that tell you what kinds of customers you are and aren’t keeping, how long customers are staying loyal, which customers are at the greatest risk of churn, and how these factors are changing. You can determine what loyal and transient customers are buying, how much they’re spending, and whether these habits are affected by things like seasons, price changes, and product lineups.
For example, you could use customer retention analytics to understand which customer segments are easier to retain and which have high churn rates. Brands like Wondercide and Mountain Khakis have used Lexer’s customer segmentation tools to improve their retention rates significantly. Read retail customer segmentation case studies for retention here.
One of the most important things to keep track of is how your rate of customer retention is affecting growth overall. There are many ways of doing this, but it usually comes down to gross retention vs. net retention. Gross retention focuses only on customer churn rates—what your revenue from customers looks like at the beginning vs. the end of a period. Net retention gives a more comprehensive picture, also taking into account any expansion or growth your business has seen in other areas. Together, these metrics give a good idea of the general health of your business from the point of view of customer engagement and loyalty.
CUSTOMER RETENTION DASHBOARD
These more advanced metrics and statistics give a much better picture of what’s happening in your business with regards to customer retention and loyalty. In order to be of use to you, however, they need to be compiled in an easy-to-understand customer retention dashboard.
Dashboards are tools which collect all the customer data from your analytics software. Here, the most important metrics and KPIs are displayed in simple charts and graphs which are easy to understand and can be monitored constantly.
Dashboards are customizable. This allows you to pick and choose the kinds of data you want to look at and how you want to see them displayed. Dashboards can also be revised regularly to account for seasonal factors and other time-dependent metrics. As such, they are versatile enough to be of use to all kinds of businesses.
With all this information conveniently displayed in one place as a single customer view, you’re able to use customer retention charts and data to locate areas in need of improvement and formulate solutions to problems and challenges with customer retention. Dashboards are where those in charge can connect the numbers with real-world trends and work towards a better, more efficient, and more retentive business model.
CUSTOMER RETENTION ANALYSIS
Analytics programs and dashboards allow you to engage in customer retention analysis. They help you figure out why some customers stay, why others are leaving, and what to do about it.
Say, for example, that you are part of a company that sells men’s and women’s fashion and apparel. You run your customer retention analytics programs for a while and find that customer retention is significantly higher for female customers. The data shows that male customers usually remain loyal for around nine months of the year before their churn rate goes up sharply in the winter. You realize that the issue is with your men’s winter clothing lines, so the design team are then able to focus their full attention on this problem and come out with a new line more attuned to the wants and needs of your male customers and the feature sets offered by competitors.
Another company uses its analytics tools to determine that customers who have special memberships at their stores are more likely to remain loyal for longer. In response, the company trains its employees to ask customers if they’d like to sign up for a membership at checkout. Banners displaying the discounts and perks that come with membership are also hung around stores. As a result, more customers get memberships and end up buying more items more frequently, reducing overall churn rates and increasing profits.
As you can see, it’s only once the data is analyzed and the causes behind customer retention and churn are determined that real improvements and changes can be made.
HOW TO MEASURE CUSTOMER RETENTION
In order to get to analysis and brainstorming solutions, however, you’ve got to start out at the beginning and learn how to measure customer retention.
The data used to measure customer retention is usually gathered by software applications placed at your business touchpoints and then compiled into a single customer view using a tool like a customer data platform or CDP. When customers visit your store and interact with your POS system, when they browse and make purchases on your web store, and when they engage with ads, info is collected about their behaviors and shopping patterns. From here, your customer analytics programs can start determining who is loyal and who’s just passing through.
The average customer retention rate will look different depending on the line of business you’re in. In some industries, friendly customers will come in every week and make purchases. In others, even the most loyal shopper only has a real need to visit once every few months. In order to gather and analyze data in a way that will actually be beneficial, you have to first understand your sales cycles and what healthy retention metrics look like for your business. Every business is different, and the best way to see a difference through data is to build a system tailored to your unique business model and the kinds of customer personas you deal with.
Once you have a good idea of the drivers behind customer retention for your specific customer base, you can set up automated customer journeys across the customer lifecycle, including those geared toward retaining and upselling customers.
CUSTOMER RETENTION DATASET
At this point, it should be clear what kind of difference having an up-to-date and reliable customer retention dataset can make for your business. Having this data is only the beginning, however. In order to keep customers visiting your stores regularly and dedicated to your brand, you need the analytics and visualization software to help you understand the data and respond strategically to the insights you glean from it. This is what helps them make the changes and improvements that build better customer experiences in retail stores and online.
The customer retention rate ecommerce and retail businesses use to track customer loyalty will differ from company to company. This is why it’s important to find a software provider who understands the unique needs of your business and its customers to track and improve retention rates effectively.
For example, CDP vendors can make a massive impact on your customer retention rates, as well as other core business KPIs. There are 4 different types of CDPs, and choosing the right CDP vendor for you is a matter of carefully evaluating each. Once you’ve chosen, you need to build an effective CDP business case that resonates with stakeholders.
Lexer is one of the few companies offering solutions for all stages of the data analytics process from collection to analysis and activation. As the only CDP built specifically for retail, Lexer offers the tools and strategic guidance you need to understand your current customer retention rates and work to improve them. If you’re looking to take the next step into data-driven customer excellence, Lexer can help. Click here to learn the 15 reasons customers choose Lexer as their preferred CDP vendor, time and time again.
- Customer Data Platform (CDP)
- Retail Data Solutions
- Customer Intelligence Platform
- Retail Clienteling Software
- Retail Data Analytics Solutions
- Data-Driven Retail
- Big Data in Retail
- Retail Data Systems
- Customer Segmentation Tools
- Data Enrichment Tools
- Customer Experience in Retail
- Customer Insight Tools