As an online retailer you may know a customer’s name and address, but what do you really know about them? According to an Oracle poll from earlier this year, 86% of respondents currently have access to foundational data, or basic information with simple segmentation and personalization.
This is a good starting point, but there are many other types of data that will give you a greater insight into your customers, which will help you market to them more efficiently and effectively. This post will take a look at the top three characteristics that will give you a well-rounded view of who your customers really are, and offer some tips for how to use this data in your email marketing.
1. Customer Lifetime Value
One of the biggest predictors of retail success is Customer Lifetime Value (CLV), which is defined as the total dollars flowing from a customer over their entire relationship with a business. Many retailers know their average CLV, but to truly create personalized marketing campaigns, you need to know much more than this.
For example, you can determine CLV for various segments and personas based on purchase history, which will provide you with a wealth of information for creating targeted email messages. There will likely be an overlap between your customers with a high CLV and your best customers who are the small group that are most valuable to you over time based on frequent purchases with a high order values. Since these are your most loyal customers, you should not treat them the same as your one-time buyers or churning customers.
To calculate CLV, multiply the number of purchases a customer has made per year by their Average Order Value, and then add together that number for each year that they have been a customer. For instance, if a customer makes two purchases a year averaging $50 each for a period of three years, then their CLV would be $300.
Email Tip: You can set up email campaigns with exclusive rewards just for customers with a high CLV. There are many ways to reward these customers, such as special discounts, VIP experiences, and exclusive events. You should also be strategic in offering discounts to save higher markdowns and related promotions for only your high value customers, which can yield great results.
2. Average Order Value
Average Order Value (AOV) describes the typical dollar amounts spent per order by each customer. For many retailers, AOV goes up on each customer’s subsequent purchase. This may be because repeat customers trust your brand more, spend more as they get comfortable with you, and discover more of your inventory that they are interested in. To calculate AOV, divide the total amount the customer has spent by the number of orders they’ve made.
Through this metric you can segment customers by high, medium, and low spenders, and then create optimized email marketing campaigns that deliver different content and promotions to each group.
Email Tip: If you see a specific day or time when AOV is significantly higher, you should act on it immediately. If it is a specific segment of your customers spending more during this period, you can craft targeted, exclusive messaging to this group. If it's something else, like a type of product that sells better at that time, you can segment everyone who has bought the product in the past, and test an email to them with cross/upsell messaging. Hopefully, you can replicate the trend.
3. Customer Latency
Latency is the average number of days between each purchase a customer makes. Once you figure out the phases of a customer's lifecycle, then you can determine what types of messaging to offer at various points in their relationship with your brand, in order to reach customers when they are most likely to buy again.
For example, if you have a post-purchase email series, you can match the cadence to different points in the customer’s lifecycle, with corresponding messaging that will appeal to customers at 30, 60, 90, or 120 days post purchase.
Email Tip: If the average customer takes 120 days to make a second purchase, then hitting them with sales messaging immediately after their purchase probably doesn't make sense. What makes more sense is to use the "honeymoon" period immediately following the purchase to reinforce your brand, and then as customers enter a point where statistically they are more likely to make a purchase, start stepping up direct offers.
These are just a few of the data points you can use to gain insights about your customers. By knowing what, when, why and how often they’re buying, you not only get to know who your customers are, but can also predict their future purchase behavior. This information allows you create personalized, data-driven email campaigns that will be able to drive customer engagement, revenue and retention.
As you get to know your customers, you can create consistent experiences both online and off-line by downloading the Modern Marketing Essentials Guide to Cross Channel Marketing.
Author's Bio: Andrew Pearson is Vice-President of Marketing at Windsor Circle, a predictive lifecycle and retention marketing platform that helps retailers grow customer lifetime value and increase customer retention. Andrew is a serial entrepreneur with over 15 years experience in technology start-ups, management and digital and email marketing.