Note: This feature is currently in an early beta version and is only available to a limited number of merchants. We are gradually rolling it out over the coming weeks. You will be notified once Demography Insights becomes available in your Kustom Portal.

The Demography Insights page consolidates shopper-level data across all your orders, giving you a comprehensive view of your customer demographics and purchasing patterns over time. Data is updated approximately every 12 hours.

With Demography Insights, you can:

You can access the Demography Insights page from the main navigation menu in the Kustom Portal.

If you do not see the Insights option in the menu, you do not have the required access role.

Only users with the following roles can view the Insights page:

If you do not have one of these roles, the Insights option will not appear in your portal navigation.

This section shows the demographic breakdown of your shoppers by gender and age. Gender and age data are derived from shopper names, dates of birth provided during checkout and the authentication process.

The Gender distribution chart shows the share of orders placed by female, male, and unknown shoppers each month. This helps you understand whether your customer base skews toward a particular gender and how that mix evolves over time.

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

An Unknown category captures orders where age could not be determined. Tracking age distribution over time helps you understand whether your customer base is shifting and whether marketing or product changes are reaching new segments.

This scatter chart plots each age group (split by gender) against two dimensions: the number of orders on the X-axis and the average order value on the Y-axis. This makes it easy to identify which customer segments drive the most volume and which tend to spend more per order.

This heatmap shows the absolute number of orders broken down by both age group and gender. The colour intensity indicates order volume, darker cells represent higher volumes. Use this to quickly spot your largest and most active customer segments.

This section shows how shoppers access your store — which devices and browsers they use to place orders. Device and browser are inferred from the customer's user agent.

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

Monitoring device usage helps you understand where to prioritize your checkout and UX optimization efforts.

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 is particularly useful for identifying whether customers are shopping through social media apps or native browsers which can inform decisions about payment method integrations and checkout performance testing.

This section shows the geographic distribution of your shoppers — which cities they come from and how urban or rural your customer base is.

The Top cities table lists your highest-order cities, showing for each:

The table can be scrolled to explore beyond the top entries. Use this data to understand geographic concentration and identify cities with high shopper density or strong average spend.

The Degree of urbanization chart shows what share of your orders come from shoppers classified as:

This helps you understand whether your customer base is concentrated in cities or spread more broadly, which can be relevant for logistics, marketing targeting, and delivery partner decisions.

This section helps you understand shopper loyalty — how many of your customers are new versus returning, and how often customers purchase from you.

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

Tracking this distribution over time helps you understand how dependent your business is on acquiring new customers versus retaining existing ones.

This scatter chart plots age groups (split by gender) against two dimensions: the number of orders on the X-axis and the share of returning customers on the Y-axis. It helps you identify which customer segments have the highest loyalty rates and which are more heavily driven by first-time buyers.

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

This gives you a clear picture of how many customers are one-time buyers versus highly engaged repeat shoppers.

The Purchase frequency over time chart shows the same frequency bands as a monthly stacked bar chart, so you can track how your shopper mix shifts across months. For example, a growing share of 3+ purchase customers over time would indicate improving retention.

The Demography deep dive is a table that combines all customer segments — age group, gender, device, city, and returning status into a single view. For each segment it shows:

This makes it easy to compare performance across groups and identify which segments have high return rates or lower average spend that may warrant attention.

Please keep the following in mind when using this page: