Customers reports

If your store is on the Shopify, Advanced Shopify, or Shopify Plus plan, then you have access to detailed reports about your customers. With the following reports, you can gain helpful insights about your customers, including their average order count, average order totals, and expected purchase value:

• Customers over time
• First-time vs returning customer sales
• Customers by location
• Returning customers
• One-time customers
• Customer cohort analysis
• Predicted spend tier

If your store is on the Advanced Shopify or Shopify Plus plan, then you also have access to the following reports:

• At-risk customers
• Loyal customers

Because of the way that the customer reports are generated, they might not display all the activity on your store from the past 12 hours. However, when you open theFirst-time vs returning customer sales reportreport, the data is up to date, give or take a few seconds. You can reopen or refresh the report to display newer data.

The Customers reports are limited to 250,000 customers. If you need to access customer data for more than 250,000 customers, then you can set up and use Google Analytics. To learn more, go toWorking with Google Analytics. However, you can export all your customers from theCustomerspage in your Shopify admin.

The data in customer reports is based on the entire order history of the new customers in the report, not only the orders that were placed during the selected timeframe. For example, if you access a report for November only, then a new customer from that month still displays as a repeat customer, even if they made their second purchase in December.

Access your customer reports

Steps:

1. ClickCategories.
2. ClickCustomersto filter the reports to show only customers reports.

Customers over time

TheCustomers over timereport displays how many customers placed orders with your store.

哟u can select a unit of time in theGroup bydrop-down menu to control how the data is grouped.

报告每次表显示两行nit when there are both types of customer: one for first-time customers, and one for returning customers. A first-time customer is a customer who placed their first order with your store. A returning customer is a customer who placed an order, and whose order history already includes at least one order.

For each time unit, you can find the following data:

• The number of new (first-time) customers who placed an order during that time. Such a group of customers is often called anew cohortof customers.
• The number of returning customers who placed an order during that time.

First-time vs returning customer sales

TheFirst-time vs returning customer salesreport displays the value of orders placed by first-time and returning customers.

哟u can clickGroup byto select the time unit that you want to display the total sales by in the graph: hour, day, week, month, quarter, year, hour of day, day of week, or month of year. The time unit specifies how the total sales are grouped.

The report table display two rows for each time unit when there are both types of customer: one for first-time customers, and one for returning customers. A first-time customer is a customer who placed their first order with your store. A returning customer is a customer who placed an order, and whose order history already includes at least one order.

For each time unit, you can find the following data:

• the number of orders placed by each group of customers
• the value of orders (total sales) placed by each group of customers

Customers by location

TheCustomers by locationreport displays data for new customers organized by geographical location. New customers are organized according to the geographical location in their default address in your Shopify admin.

For each geographical region, you can find:

• the number of new customers who placed their first order during the selected timeframe
• the total number of orders that those customers have placed since their first order
• the total amount that they have spent, including taxes, discounts, shipping, and any refunds

TheOrders to dateandTotal spent to datetotals are based on the entire order history of the new customers in the report, not only the orders that were placed during the selected timeframe.

Returning customers

TheReturning customersreport displays data about all your customers whose order history includes two or more orders.

哟u can find the following details for each customer:

• their name
• their email address
• whether they agreed to accept marketing when they placed their most recent order
• the date of their first order
• the date of their most recent order
• the number of orders that they have placed
• their average order value
• the total amount that they have spent, including taxes, discounts, shipping, and any refunds

One-time customers

TheOne-time customersreport displays data about all your customers whose order history includes only one order.

哟u can find the following details for each customer:

• their name
• their email address
• whether they agreed to accept marketing when they placed their most recent order
• 他们的第一个订单的日期。
• the number of orders that they have placed, which is1
• the value of their order, including taxes, discounts, shipping, and any refunds

Customer cohort analysis

TheCustomer cohort analysisreport displays data about your customer acquisition and retention. A cohort is defined as a group of customers that have similar characteristics. For theCustomer cohort analysisreport, customers are grouped into cohorts based on the date that they placed their first order.

哟u can use this report to find out which customers have made repeat purchases to identify your most valuable customers. You can use this information to help you make decisions about when to retarget customers, which customers to retarget, and which customers are lower value.

TheCustomer cohort analysiscontains the following reports:

• Cohort analysis table
• Retention rate chart
• Cohort analysis details

Cohort analysis table

The cohort analysis table displays data about repeat purchases by customers based on when they made their first purchase. Each row represents a cohort of your customers that made their first purchase in the same time period. TheCustomerscolumn displays the number of customers in the cohort, and the rest of the columns display how many of the customers in the cohort made another purchase during the new time period.

For example, your customer John made their first purchase in February 2022. John then made another purchase in June 2022 and in September 2022. In a monthly cohort analysis for 2022, John would be in the February cohort and would be counted as a repeat customer forMonth 4andMonth 7.

哟u can customize the report in the following ways:

• display the retention rate as a number or as a percent
• change the time period that cohorts are grouped by
• change the time period that the report displays

Retention rate chart

TheRetention ratechart displays the retention rate of all first-time customers during the time period that the report displays. You can also display the following comparisons:

• Comparison to previous period
• Comparison to previous year
• Comparison between cohorts

哟u can also display the retention rate for customers in all cohorts for the selected time period, or select a single cohort to display the retention rate for.

Cohort analysis details

哟u can access the cohort analysis details by clicking the time period in theCohortcolumn. You can find the following details for each cohort:

• total new customers that make up the cohort
• total amount spent by the cohort up to the current date
• average order value for the cohort
• the average total amount spent by each customer in the cohort
• thepredicted spend tieroverview for the cohort
• the top geographic locations of customers in this cohort

Using the cohort analysis report for customer segmentation

哟u can use the data from theCustomer cohort analysisreport to createcustomer segmentsout of high-value customer cohorts.

For example, if the customer cohort for June of 2022 indicates high retention, then you can create a customer segment by using the First_order_date BETWEEN 2022-06-01 AND 2022-06-30 .

Learn more aboutcustomer segmentation.

Predicted spend tier

ThePredicted spend tierreport displays the predicted value of each customer in the selected cohort. This report can help you target customers that are part of the highest value cohorts. You can find the following details for each customer in the cohort:

• customer name
• the predicted spend tier
• email subscription status
• the date the customer placed their last order
• the total number of orders placed by that customer
• the total amount that customer has spent

Learn more abouthow the predicted spend tier is determined.

At-risk customers

哟u have access to theAt-risk customersreport only if your store is on the Advanced Shopify or Shopify Plus plan.

TheAt-risk customersreport displays data about all your returning customers who are at risk.

A customer is at risk if they're estimated to have a medium probability of returning to place another order with your store, but they haven't placed an order in a while.

Shopify uses a machine learning model to determine the likelihood that a customer will return to purchase an item in the next 90 days.

By knowing which of your customers are at risk, you can tailor or target your marketing. For example, you can offer your at-risk customers a discount to encourage them to buy from you again.

In the report, you can find the following details for each customer:

• their name
• their email address
• whether they agreed to accept marketing when they placed their most recent order
• the date of their first order
• the date of their most recent order.
• the number of orders that they have placed
• their average order value
• the total amount that they have spent, including taxes, discounts, shipping, and any refunds

Loyal customers

哟u have access to theLoyal customersreport only if your store is on the Advanced Shopify or Shopify Plus plan.

TheLoyal customersreport displays data about all your returning customers who are loyal.

A customer is loyal if they're estimated to have a high probability of returning to place another order with your store, and they've placed more orders than the average customer. This can be helpful in your marketing efforts. For example, marketing your high-margin products to your loyal customers might be an effective approach.

哟u can find the following details for each customer:

• their name
• their email address
• whether they agreed to accept marketing when they placed their most recent order
• the date of their first order
• the date of their most recent order.
• the number of orders that they have placed
• their average order value
• the total amount that they have spent, including taxes, discounts, shipping, and any refunds

Customize the Customers reports

If your store is on the Advanced Shopify or Shopify Plus plan, then you can use thefiltering and editing featuresto customize the reports about your customers.

The following is a sample of some of the filters and columns that are available, where applicable.

Filters for the Customers reports

Customer

• Customer email- The email address associated with a customer.
• Customer name- The first and last names of a customer.

Customer attributes

• Accepts marketing- Whether customers agreed to accept marketing when they placed their most recent order.
• Is one-time- Customers whose order history includes only 1 order.
• Is returning- Customers whose order history includes more than 1 order.

Customer segment

• Is at risk- Customers who are a repeat customer and estimated to have a medium probability of returning, but who have not placed an order in a while.
• Is dormant- Customers who have a low probability of returning to make another purchase.
• Is loyal- Repeat customers who are estimated to have a high probability of returning, and have placed more orders than the average customer.
• Is promising- Customers who are estimated to have a high probability of returning and becoming a loyal customer.

Location

• City/Country/Region- The city, country, and region of customers, based on their default address in your Shopify admin.

Columns for the Customers reports

Customer

• Customer email- The email address associated with a customer.
• Customer name- The first and last names of a customer.
• Customers- The total number of first-time and repeat customers who placed their an order during the selected timeframe.

Customer attributes

• Accepts marketing- Whether customers agreed to accept marketing when they placed their most recent order.
• Is one-time- Customers whose order history includes only 1 order.
• Is returning- Customers whose order history includes more than 1 order.

Customer segment

• Is at risk- Customers who are a repeat customer and estimated to have a medium probability of returning, but who have not placed an order in a while.
• Is dormant- Customers who have a low probability of returning to make another purchase.
• Is loyal- Repeat customers who are estimated to have a high probability of returning, and have placed more orders than the average customer.
• Is promising- Customers who are estimated to have a high probability of returning and becoming a loyal customer.

First order

• First order(day/month/week/year) - The date of a customer's first order.

Last order

• Last order(day/month/week/year) - The date of a customer's last order.

Location

• City/Country/Region- The city, country, and region of customers, based on their default address in your Shopify admin.

Order

• Average order value- The average value of customers' orders since their first order. It's calculated by dividing the total value of new customers' orders by the total number of new customers' orders. The total order value includes taxes and shipping, and is before refunds. The total number of orders does not include orders that consist only of gift cards.

Orders

• Total spent to date- The total amount that a customer has spent, including taxes, discounts, shipping, and any refunds. For example, let's suppose a customer ordered two $50 items from your store, paid no tax, received 10% on one of the items, spent $10 in shipping, and received a $7 refund for a shipping delay. In this example, theTotal spent to datewould calculate50 + 45 + 10 -7and display a total of$98.
• Orders to date- The total number of new customers' orders since their first order.

Time

• Day/Month/Week——天、月和周的订单。

Example customization: Target an email campaign towards returning customers

如果你想使用一个电子邮件活动encourage returning customers to make another purchase, then you could customize yourReturning customersreport so that it displays only the returning customers who agreed to accept marketing.

To create the report for this example:

1. ClickCategories.
2. ClickCustomersto filter the reports to show only customers reports.
3. ClickReturning customers.
4. From theReturning customersreport, clickManage filters.
5. ClickAdd filter.
6. SelectAccepts marketing, and then inSearch, selectYes.
7. ClickApply filters.

The report is now limited to returning customers who accept marketing.

哟u can then export the report to a CSV file, and you can use all the email addresses in the file for your email campaign.