The Customer Overview section in Audience Insights provides an essential snapshot of your customer base, giving you valuable data to guide strategic decisions. By understanding customer demographics, purchase behavior, and regional insights, businesses can tailor marketing efforts, improve customer retention, and maximize revenue.
Key Features
Customer Size: Breakdown of total, new, and returning customers.
Order Insights: Understand the proportion of orders from new vs returning customers.
Location Insights: Identify top-performing countries and cities.
Audience Segment selector: get insight for specific audience segment you have created.
💡 Learn more: How to create an Audience Segment
Customer Size & Order Insights
The Customer Overview section contains several critical metrics that provide insights into customer composition and behavior. Here’s a detailed explanation of each metric:
1. Customer Size
Definition: The total number of customers who have made at least one purchase within the selected date range.
Example: If your customer size is 35,294, this represents the total unique individuals who have engaged with your business.
💡 Use cases:
Compare the current customer size to previous months to track growth.
Identify trends in customer acquisition during key marketing campaigns or seasonal sales.
❗ Note:
If a customer purchases their 1st and 2nd order during the selected time, the customer will be counted both as a new customer and as a returning customer. This would cause the sum of new customers and returning customers greater than the customer size.
2. New Customer Size
Definition: The number of customers who made their first purchase within the selected period.
Example: If the New Customer Size is 25,211, these are entirely new individuals who joined your customer base.
💡 Use cases:
Identify campaigns that attract new customers effectively.
Use this data to measure the success of your acquisition strategies like Meta Ads, Google Ads, or email campaigns.
3. Returning Customer Size
Definition: The number of customers who made at least one purchase before or during the selected date range and returned to make additional purchases during the current period.
Example: A Returning Customer Size of 10,083 indicates strong customer loyalty.
💡 Use cases:
A high returning customer count signals strong retention strategies.
If returning customer size is low, consider enhancing email campaigns, loyalty programs, or personalized incentives.
4. Orders (Total, New, and Returning)
Definition:
Total Orders: Total transactions made in the selected date range.
New Customer Orders: Orders placed by new customers.
Returning Customer Orders: Orders from returning customers.
Example:
Total Orders: 157,483
New Customer Orders: 82,058 (52.11%)
Returning Customer Orders: 75,425 (47.89%)
💡 Use cases:
A balanced ratio between new and returning orders suggests healthy customer acquisition and retention.
If new customer orders are significantly higher than returning orders, consider enhancing retention strategies to maximize lifetime value (LTV).
Location Insights
Location data highlights where your customers are located, helping you understand your audience’s geographical distribution.
1. Top Countries
Definition: Displays the top-performing countries ranked by the number of customers.
Example:
United States: 80,766 (59.72%)
Canada: 5,228 (3.87%)
Unknown Countries : 33,294 (24.62%) (lack geo location information)
💡 Use cases:
Identify regions with strong customer bases to tailor localized promotions.
If unknown locations have a high percentage, improve tracking capabilities (e.g., UTM parameters or geolocation tools).
2. Top Cities
Definition: Lists the top-performing cities ranked by customer count.
Example:
Los Angeles: 572 (0.42%)
Chicago: 514 (0.38%)
Unknown Cities : 33,294 (24.63%) (lack of geo location information)
💡 Use cases:
Identify urban centers that generate high sales for targeted campaigns.
If smaller cities show potential, explore regional marketing strategies to expand outreach.
3. Top Cities with High LTV Customers
Definition: Highlights cities that have customers with the highest lifetime value.
Example:
Los Angeles: 219 (0.65%)
San Diego: 165 (0.49%)
💡 Use cases:
Prioritize high-LTV regions for premium offers or loyalty programs.
Identify patterns in these cities to refine targeting strategies.
4. Top Cities with Loyal Customers
Definition: Lists cities where customers have shown repeated engagement and consistent purchasing behavior.
Example:
London: 87 (0.26%)
Singapore: 83 (0.25%)
💡 Use cases:
Focus on retaining these loyal customers by offering VIP programs, early access deals, or exclusive offers.
Use this data to expand community-building efforts in identified cities.