The Orders by New vs returning customers metric compares the number of orders made by new customers to those made by returning customers. It helps track customer loyalty, acquisition efforts, and sales growth potential.
With Databox you can track all your metrics from various data sources in one place.
Used to show comparisons between values.
Databox is a business analytics software that allows you to track and visualize your most important metrics from any data source in one centralized platform.
To track Orders by New vs Returning Customers using Databox, follow these steps:
Shopify dashboard template which will give you insights and a complete control over your Shopify store.
Use this Shopify report to share important ecommerce performance metrics around orders, sales, products, customers, and more.
Shopify metrics in Databox are Event type metrics and Databox obtains the relevant data based on calculations of data for the specific event entity, such as an Order. Each entity received via the API will be stored in our database as a separate entry and each entry will have its own timestamp associated with it – the moment the event occurred. As a consequence, in cases when the Order that occurred in the past is edited, changed, or deleted in the Shopify User Interface after it has already been completed and synced to Databox, Databox cannot report on such historical data changes, which will result in discrepancies when data from Shopify is compared to values in Databox for the past Date Range.
Shopify can distinguish between returning and new customers differently in their User Interface than Databox can from their API, therefore the data discrepancy might be present for this metric in the following case.
Databox obtains data on the current state of a customer, so if the customer had never placed an order before and then placed two separate orders one after the other in the selected Date Range, Databox sees it as a ‘Returning’ customer with value 2 (Orders) present in the API. This would then indicate that both these orders were made from a ‘Returning’ customer, which is not technically correct since the first order made by the customer should be counted as made by a ‘New’ customer.
Hence, in Databox the value for the ‘Returning’ dimension will be higher and the value for the ‘New’ dimension lower than in the Shopify User Interface when the new customer is making multiple orders right after their first purchase.
Equates to product Selling Price x Ordered Quantity during the specified Date Range. Gross Sales does not include Discounts, Returns, Taxes, or Shipping.
Equates to product Selling Price x Ordered Quantity during the specified Date Range split up by New vs Returning Customers.
Equates to Gross Sales - Discounts - Returns + Taxes + Shipping Charges during the specified Date Range. Total Sales will be a positive number for a Sale on the date that an order was placed, and a negative number for a return on the date that an order was Refunded.
Equates to Gross Sales - Discounts - Returns + Taxes + Shipping Charges during specified Date Range split up by Tag.
Number of Taxes associated with a Sale or return during the specified Date Range.
The Returns by Billing City metric calculates the number of items returned to the store, grouped by the billing city of the customer who made the purchase. It helps in analyzing the areas with a high return rate and in improving customer satisfaction.
Total number of Customers gained.
Abandoned checkouts metric refers to the number of customers who added items to their cart but failed to complete the purchase, which can help merchants identify potential issues in the checkout process.