Hop Designer
Shubham Kaushal
Category
Marketing, Revenue
This Hop maps customer spend based on their first purchased product and observes the value of their consecutive purchases within the specified timeframe. This is especially useful to identify the products that drive customer retention and spend. To better understand the report, here’s what each metric means:
First Time Customers: Number of first-time customers that purchased the product.
First Order Total Sales: The total sales value of the first order from first-time customers who purchased the product.
All Consecutive Total Sales: This is the consecutive total sales value (ie excluding the first order total sales) from first-time customers who had the product in their first order.
Total Orders: Total number of orders from customers who purchased the product in their first order.
Average Customer Value: This is calculated by dividing the sum of the First Order Total Sales and All Consecutive Total Sales by the number of First Time Customers.
Rank: This is a ranking of Average Customer Value for all products in the report.
For better decision-making, run this report to cover long periods (at least 6 months). It is also important to note that this report is sorted by product category.
Integration(s)
How to use this Hop.
Simply create an Airboxr account and connect your Shopify store to automatically run this export/analysis for your store. If you already have an account, click on the Add to my Collection button above.
Identify Key Products for Retention: By analyzing which initial products lead to higher consecutive spending, stores can focus on promoting these key products to attract new customers who are likely to become repeat buyers. This helps in strategic product placement and marketing efforts.
In This Report
Metrics
First Time Customers
First Order Total Sales
All Consecutive Total Sales
Total Orders
Average Customer Value
Rank
Grouped By
Product Category
Product
Connect your Shopify store and automate this report. You will never have to manually work with data again.