Equates to Gross Sales - Discounts - Returns + Taxes + Shipping Charges during the specified Date Range split up by New vs Returning Customers.
With Databox you can track all your metrics from various data sources in one place.
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 Total sales 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 advanced report to share high-level and in-depth metrics of your ecommerce store performance. Present key metrics like Orders, Net Sales, New 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.
The amount Refunded across the transactions during the specified Date Range.
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.
The Orders by Billing Country metric shows the number of orders placed by customers based on their billing country. It helps track the geographic distribution of sales and is useful in making decisions related to marketing and advertising strategies.
Discounts metric shows the total amount of discounts offered by the store to customers over a given period of time. It helps in analyzing the effectiveness of promotional activities and their impact on the store's revenue.
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.
The New Customers metric measures the number of unique visitors who have made a purchase on a Shopify store for the first time during a given period.
The Quantity by Product Vendor metric indicates the total number of units sold for each product vendor in a given time period. It helps determine which vendors are most successful and which products are driving sales.