Why E-commerce Companies Are Segmenting Their Audience by Shopping Data

As marketers who got into personalization to better connect with customers, we were curious about how people use our platform to connect with theirs.

To help other marketers better segment their audiences, we dove into data on thousands of Ninetailed experiences.

This allowed us to uncover how Ninetailed power users segment their audiences.

This article is a quick snapshot of our recent Segmentation Report, presenting our findings around segmentation based on shopping data. Here’s what we found.

The Top 5 Segmentation Variables in 2024

In the past couple of years, there’s been a drastic shift in marketing spend from paid ads to organic content. Consumers are seeking more personalized experiences from new and familiar companies alike. This demand puts more pressure on marketers across industries to tailor content to their customers’ needs. Before we reveal how each industry segments, here are the general top segmentation variables:

1. 22.6% of all companies in our data set segment by location

2. 18.2% of all companies in our data set segment by behavior

3. 18.0% of all companies in our data set segment by page visit

4. 14.3% of all companies in our data set segment by paid traffic

5. 5.5% of all companies in our data set segment by shopping data

Our Take:

These segmentation variables dominate website content personalization due to their direct impact on user experience, relevance, and higher ROI.

Shopping data segmentation, although less common at 5.5%, is critical for e-commerce. It provides insights into purchase history and preferences so that companies can create highly personalized shopping experiences.

Shopping Data and Segmentation Among E-commerce Companies

The e-commerce market has exploded over the past few years, with global sales growing from $4.9 trillion to $6.3 trillion between 2021 and 2024.

Between the crowded market, stricter data privacy regulations, and decline in paid ad performance, e-commerce companies are rethinking their marketing strategies. For most, this has led to a greater focus on personalization.

Here’s how they’re breaking up their audiences:

1. Location — 27%

2. Page Visit — 18.6%

3. Paid Traffic — 16.9%

4. Behavior — 16.9%

5. Shopping Data — 7.1%

Shopping data provides direct insight into customer purchasing habits. It includes characteristics like purchase frequency, average order value, product preferences, and payment method.

Our Take

By breaking up their audiences by shopping data, e-commerce companies can optimize their marketing spend by only targeting customers who are most likely to convert.