Customer databases hold a wealth of information— from individual customer preferences to sales information to demographic data. Yet, most small and medium-sized businesses don’t delve into these statistics to leverage these important insights for their marketing plans. With a minimal amount of effort, you can create meaning from your customer databases. One way to effectively use business data to improve a customer’s lifetime value is to distinguish between one-time and loyal customers.
Understands the Patterns of Loyal Customers
Sifting through your customer insights may seem overwhelming. To help you, we recommend analyzing your customer data – ideally with the use of business intelligence software – to identify when you consider somebody to be a loyal/returning customer. Figure out the threshold of how you’re defining “loyal customer”— maybe it’s their purchasing frequency over a period of time (i.e. a customer that’s purchased at least 3 times over the last 12 months), or maybe it’s their total dollar amount purchased over a particular time frame.
Once identified, review your loyal customers, and look back through their purchase history to find what their initial entry point was. Are there any particular patterns, for example, the types of products that they purchased, the price points, special promotions, etc.?
Typically, there are patterns. You can use this data to look at new customers who have just made their first purchase. Are any of them following the path that your loyal customers took when they were a first-time buyer? If so, add these to a special category or insert some other identifying mark so you can focus on these customers to determine if they follow the loyal-customer pattern.
Identify One-Time Customers Who Never Came Back
While you definitely want to repeat the patterns that led to loyal customers, you also want to understand why someone was only a single-purchase customer. Unless you are in the business of selling a one-time purchase item, you must focus your efforts on returning customers and new customers that show patterns similar to loyal ones.
As such, look at individuals that have only performed a single purchase. What patterns do you find, i.e. is it during a certain season or based on a particular product?
Create a Demographic Profile for Both Sets
Your demographic analysis may vary based on your preferences. Our advice? Focus on customers’ mailing and email addresses. This can help to significantly optimize advertising and messaging. For example, your loyal customers might highly index as females living in the suburbs versus one-time customers that are predominantly young millennial males.
Now, it’s time to develop a strategy. Let’s go back to the first-time customers that look similar to your loyal customers. It is important to build a strategy to approach them with offers and specific messages in order to increase the likelihood of them turning into loyal customers.
Align Your Digital Advertising with the Findings
Once you have everything in place, it is time to execute your advertising in accordance with your findings. Focus on the identified demographics and patterns. For instance, when doing paid search with more general keywords, narrow down your audience by infusing demographics targeting— all based on focusing on the winners versus the ones that never turn into anything. While you shouldn’t completely ignore a low-value, one-time customer, you shouldn’t also waste an exorbitant amount of money on them. One way to re-engage this market is to ask for feedback as to what would cause them to shop more with you, or drop them into an email newsletter and then cycle them out after so many months. These are usually less expensive ways to still engage them by keeping most of the marketing dollars focused on higher-value customers.
A wealth of absolutely worthwhile data exists in your customer database. Spend the time to strategize with business intelligence to identify optimal customer cohorts and behaviors, and then drive towards creating more of these.