Archives: FAQs

Trends for the future

From BOPIS and hyperlocal delivery to personalization and contactless checkout, we unpack top strategic imperatives to prepare for the store of the future

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The acceleration of digital transformation

Learn how the latest digital technologies are helping drive positive shopper experiences, at scale

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Rewriting operational models

Experts discuss how brand and retailers can modernize their operating models to enable more efficiency and stay pandemic-proof

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Omni-channel as the new normal

Explore how to keep pace with the latest innovations in ecommerce, social, direct to consumer, and more to offer seamless experiences to always-on shoppers

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Is the consumer’s privacy protected?

Trax has successfully passed security due diligence for leading global retailers and is GDPR compliant. Our camera system includes sensor alerts in the event of an occlusion (an obstruction in front of the camera) that contains a human presence. The system analyzes every picture to determine whether a human is present before uploading to Trax’s cloud. If a picture contains a person, it’s immediately discarded. The process is repeated until the camera captures a picture without an occlusion. The occluded images are deleted from the gateway server and the IoT camera device. At the end of the process, no photos of people are saved at the store or the cloud.

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Who owns the data collected by the Trax?

Data ownership is a negotiable term in our contracts. Retailers and brands can own or resell the data we collect or adopt a shared ownership model with Trax.

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How hard is it to implement Trax’s image-recognition solutions?

A dedicated Project Manager and Analyst make setup, launch, and stabilization painless. To create your image database, we use your existing library or even build it from scratch.

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Can the Trax platform be integrated with other systems?

Open architecture is a core tenet of our approach. We have successfully integrated our technology with SFA tools, BI systems, and data lakes. To ensure our solutions work seamlessly with clients’ ecosystems, we work closely with their tech teams on integrations.

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Is human validation used?

The algorithm starts a new project with 90% accuracy and improves to 96% over the first few months, thanks to human validation. Humans continue to quality check to control for packaging updates.

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How does Trax measure image-recognition accuracy?

Every day, we take a sample of the images we collect and do a deep analysis of the recognition results. We aggregate the results and provide Accuracy reports every 3 weeks. You can learn more about the process in this video.

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