How and why retailers use AI

Cappasity Blog
Published in
4 min readMay 22


AI technology emerged as a powerful tool to optimize almost every aspect of any retail business. According to a recent report, the global AI in retail market size is expected to reach $24.1 billion by 2028, rising at a market growth of 24.4% CAGR during the forecast period. Retailers use artificial intelligence in various ways to enhance customer experience, boost sales and improve operational efficiency. Let’s learn why some well-known brands use AI and see how Cappasity’s AI analytics can benefit retailers.

AI helps Zara enhance in-store customer experience and predict trends

Zara, one of the most successful global fast fashion retail brands, uses AI in a number of ways, including employing AI robots to speed up online pickup orders. The retailer needed to find a way to avoid long lines and reduce the waiting times of customers after adopting the BOPIS (Buy Online, Pick-Up in Store) concept. For this purpose, Zara introduced AI robots, which fetch the products from the back of the automated retail stores and fasten the in-store collecting process. Additionally, the fashion retailer partners with Jetlore, an AI-powered consumer behavior prediction platform which maps consumer behavior into structured predictive attributes, like size, color, fit, or style preferences.

H&M Group uses AI to make fast fashion sustainable

H&M Group is leveraging AI to achieve a climate positive value chain by 2040. In 2021, one of the H&M Group brands and external partners launched a Body Scan Jeans pilot project. Customers could have their body 3D scanned in-store, which then generated a digital avatar, enabling them to try different denim colors and styles virtually. Machine learning then converted the body scan into a paper pattern and measurement list. Then the customer could pick up the personalized item in-store. According to Linda Leopold, head of AI at H&M, this is an example of on-demand manufacturing, which “not only solves the problem of size and fit for the customer but also leads to fewer returns and decreased CO₂ emissions”. In addition, the brand is using AI to determine the environmental impact of its raw material.

How Cappasity’s AI analytics helps retailers

Cappasity is the first end-to-end solution for fast production, easy embedding, and powerful analysis of 3D/AR content. Our enterprise clients are provided with access to an AI-based analytical system that allows them to study consumer behavior on a website or a mobile app. Thanks to a wide variety of features, Cappasity AI helps retailers in many ways:

  1. Cappasity AI helps brands measure consumers’ engagement. Cappasity AI allows you to track all consumers’ interactions with your 3D Views like rotating items, zooming in, etc. Average Interaction Time is one of the helpful metrics that the analytical system provides. This allows you to measure the impact of 3D Views on Time on Page and, consequently, on sales. Besides the Average Interaction Time, our AI-based analytical system shows an Interactions Ratio — the percentage of users who interacted with the 3D View after viewing it. It’s useful when it comes to estimating consumers’ engagement and the efficiency of 3D View content.

2. Cappasity AI helps you conduct A/B testing to improve your product packaging. The solution generates a heatmap (Zoom map) for every product, which illustrates each customer’s interactions with product 3D Views, like rotating them, zooming in, etc. Using these heatmaps, you can compare and analyze the reactions of different focus groups to product packaging. You can also use heatmaps to see how a consumer reacts to different product packages. Creating perfect packaging design is highly expensive, so this mechanism of visual testing comes in very handy.

3. Using Cappasity’s AI-based analytics, retailers can extract specific data about consumers’ behavior and preferences. Each 3D View uploaded to a website is matched with corresponding tags, allowing you to extract specific data for different audience segments. For example, you can see how consumers of a certain age react to a specific product category. This is helpful when analyzing the behavior of different audiences and their reactions to certain products or product categories, and makes your data about customers’ behavior even more informative. The extracted data is also useful for launching effective marketing campaigns for different audiences.

Contact our team at to integrate immersive content into your catalog and use our advanced AI-powered analytics system.

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