Every marketing VP wants to know if their team’s marketing efforts attract both customers and repeat customers. Why? Because a boost in repeat customers leads to an increase in revenue. But don’t take our word for it. Here are a few reasons, backed by research from Bain & Co., Adobe, and other organizations, why repeat customers are important:
We have a metric to help marketing VPs from ecommerce companies discover which campaigns drove people to buy products and become repeat customers at different times of the year.
The Repeat Customers by 1st Month Cohort metric shows the number of customers that became first-time buyers in a specific month who turned into repeat customers. It’s good to know people are ordering your product(s) more than once. But how does this knowledge help you? It’s not enough to know that people are coming back.
If the metric above were created with data from your company, there are several insights you could discover by reviewing it. You would see that Q2 of 2017 was an amazing quarter for repeat orders with May’s numbers exceeding previous months. In general, the orders for each month in Q2 of 2017 almost doubled the orders of previous quarters on the chart.
Reviewing the chart also reveals that Q4 of 2016 started with mediocre repeat order numbers but in each of the following months the numbers dropped.
Once you’ve seen these results, you can start asking questions to figure out what caused the amazing performance of Q2 in 2017 and the poor performance of Q4 in 2016. What marketing campaigns were running at the time? Was any marketing channel performing especially well? Did you try a new marketing channel that led to a boost in orders or did you reduce efforts in a specific channel which led to a drop in orders? There are several other questions you could ask to understand the difference in performance.
When you have answers to your questions, you can optimize future marketing efforts to continue effective efforts and discontinue ineffective efforts. This allows you to increase repeat orders and ultimately increase revenue.
Using stacked columns to visualize this data makes it easy to see a side by side comparison of those who placed two or more orders. Each column represents a cohort or a group of people who made their first purchase in a specific month.