4 Ways To Identify Valuable Customers in E-Commerce
In order to deliver according to your customer’s expectations, you need to know where they are coming from as well as how they interact with your E-Commerce business. One of the most important tools in your arsenal is site analytics which gives you various data points on your customers. Here are some of the more important points you can use to identify valuable customers.
1. Customer Lifetime Number of Orders
This is a useful metric for determining a customers potential value to your brand. Through this metric, you can know the number of times a customer has placed an order through your store. This can be used to determine a customers loyalty to your company as it shows the willingness of a customer to keep coming back to your store.
2. Customer Lifetime Value
CLV or the Customer Lifetime Value is the metric which is used to identify the highest spending customers for a company. This data point gives us the amount of revenue a customer has generated for a company through making purchases. This is calculated by adding up the individual purchases
made by the customer.
For example, if a customer makes three separate purchases from your site over a period of time, the customer lifetime value is the sum of these separate purchases. By identifying customers with higher CLVs we can find the customers which bring higher value to our site.
3. Customer Average Order Value
Though finding a customers lifetime number of orders and their lifetime value, we can also obtain their Average Order Value (AOV). This metric defines the average amount spent every time a customer places an order on your sites.
A customers average order value can be calculated simply by dividing the total revenue from the customer by the total number of orders from the customer. For example, if a customer has made 3 purchases of different values, the average order value is obtained by summing the values of the purchases and dividing the total by three.
4. Age of Most Recent Order
This metric gives the age of the customers most recent order. It will calculate the amount of time which has passed between the last order placed by the customer and the present time. Taking an example of a customer who has a high CLV, but has not made a purchase at your store for a number of years, we can conclude that although they are a high spender, they are not a current customer and less focus can be placed on them.
In addition to the above data points which cover transactional commerce, there are a number of other metrics such as Key Performance Indicators (KPIs) which can give a broader view of your overall customer profile. A customer’s real-life interaction with your store can also be measured as we gain insight into their in-person buying habits, the frequency of their visits to a store, the categories of products they buy and the time of day they would most likely shop.