Use this article to understand the Demography Insights page in the Kustom Portal, which shows who your customers are: their age, gender, location, devices and how often they buy from you.

Demography Insights brings together shopper-level data from all your orders, so you can follow your customer demographics and buying patterns over time. Data is updated approximately every 12 hours. With Demography Insights, you can:

These definitions apply to all metrics on the Demography Insights page:

Only users with one of these roles can view Insights in the Kustom Portal:

If you do not have one of these roles, Insights is not shown in your Kustom Portal menu. See User management.

This section shows your shoppers by gender and age. Gender and age come from shopper names, dates of birth entered at checkout and the identity verification process.

The Gender distribution chart shows the share of orders placed by female, male and unknown shoppers each month. Use it to see whether your customer base leans towards one gender and how that changes over time.

The Age distribution chart shows how orders are split across six age groups each month:

An Unknown group covers orders where the age could not be determined. Following age distribution over time shows whether your customer base is shifting and whether marketing or product changes reach new groups.

This scatter chart plots each age group, split by gender, by number of orders (X axis) and average order value (Y axis). Use it to see which customer groups place the most orders and which spend the most per order.

This heatmap shows the number of orders by age group and gender. Darker cells mean more orders. Use it to spot your largest customer groups at a glance.

This section shows which devices and browsers shoppers use to place orders. Device and browser are worked out from the customer's user agent (the information their browser sends about itself).

The Orders by device chart shows the monthly share of orders placed on:

Use this to decide where to focus your checkout and user experience improvements.

The Orders by browser chart shows the monthly share of orders placed through different browsers, including Chrome, Safari, Firefox, Edge, Samsung Internet and in-app browsers such as Instagram, Facebook and Snapchat.

This shows whether customers shop through social media apps or regular browsers, which can guide decisions about payment methods and checkout testing.

This section shows which regions and cities your shoppers come from, and how urban or rural your customer base is.

The Orders by region map shows where your orders come from. Regions with more orders are shaded more strongly.

Click a region on the map to filter the Top cities table and the Shopper location split chart to that region. Click the region again to return to the full view.

The Top cities table lists the cities with the most orders, showing for each city:

Scroll the table to see more cities.

The Shopper location split chart shows what share of your orders come from shoppers in:

This helps with decisions about logistics, marketing and delivery partners.

This section shows how loyal your customers are: how many are new or returning, and how often they buy from you.

How customer types are defined: A returning customer has made a purchase within the last 12 months. A reactivated customer has bought before, but their most recent purchase was more than 12 months ago. Kustom cannot see customer-level purchases before 1 October 2024.

The Returning shoppers chart shows the monthly share of orders from three customer types:

This shows how much your business depends on winning new customers compared to keeping existing ones.

This scatter chart plots age groups, split by gender, by number of orders (X axis) and share of returning customers (Y axis). Use it to see which customer groups are most loyal and which mostly buy once.

The Purchase frequency pie chart shows how your unique shoppers are spread across five frequency bands over the last 12 months:

The Purchase frequency over time chart shows the same frequency bands per month, so you can follow how your shopper mix changes. For example, a growing share of customers with 3 or more purchases indicates improving retention.

The Demography deep dive table combines all customer groups (age group, gender, device, city and returning status) in one view. For each group it shows:

Use it to compare customer groups and find groups with high return rates or low average spend.

Note: Return rates take time to settle. Orders from the current month will likely get more returns in the following month, so use fully closed months for the most accurate return rates.