Using computer vision to measure customer experience in stores

Boris Fievet


use case iziday data data engineer big data machine learning deep learning ai ia

Luxury and Cosmetics

Context and Challenge:

As a luxury cosmetics brand, customer experience is a key aspect of brand image. Company want to ensure that every customer who visits their store or interacts with products has a positive and memorable experience. However, measuring customer experience can be challenging, especially in the cosmetics sector where products are often tested and tried on in store before purchase.


To improve customer experience measurement, we implement a computer vision system for stores analysis.

This system uses cameras and artificial intelligence to track customer behaviors and interactions with products. For example, it can track how long a customer spends trying on different products, or how often they engage with a particular display. This data is then analyzed and used to provide insights on customer preferences and behaviors.


By using computer vision to measure customer experience, we are able to gain a more accurate and detailed understanding of how customers interact with products and store environment. This allows to make data-driven decisions on how to improve the customer experience, such as by re-arranging store layouts or developing new products that are more in line with customer preferences.

Ultimately, this helps us to increase customer satisfaction and loyalty, leading to higher sales and revenue for brand.

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