VideoMining offers visibility into the entire in-store shopping process from storewide to category and shelf-level applications.

Retailers require a definitive advantage to respond to rapid industry transformation.

VideoMining (VM) makes this possible by providing advanced solutions that leverage AI and Big data to decode in-store shopper behavior. This enables retailers to measure, track, test, and optimize their shopper-centric investments.

Solutions

Tracker

Provides retailers with standardized shopper behavior data and insights, benchmarked against the industry, broken down into storewide, category, and brand-level behavior insights and trends to drive and assess the impact of shopper-centric investments.

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Optimizer

Uses AI-powered optimization algorithms leveraging in-store behavioral data along with other retailer data to optimize critical retailer applications, including Category Reset and Display Location Planning.

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Innovator

Offers an always-available test lab facility, with a comprehensive methodology to deliver rapid test results. Enables measurement and tracking of in-store shopper responses - extracting actionable insights that can impact the innovation process and reduce rollout risk.

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39%Of the decisions on category resets were impacted by VM’s insights.

VM’s optimization platform generated the data and insights via an in-depth pre and post-category reset study conducted at a major grocery retailer.

Retailer Domains

Optimize store layout and space allocation across categories based on real-world shopper behavior. Study shopper behavior and measure behavioral responses in a real-world context, e.g., material at shelf or checkout.

Optimize store layout and space allocation across categories based on real-world shopper behavior. Study shopper behavior and measure behavioral responses in a real-world context, e.g., material at shelf or checkout.

Optimize store layout and space allocation across categories based on real-world shopper behavior. Study shopper behavior and measure behavioral responses in a real-world context, e.g., material at shelf or checkout.

Optimize store layout and space allocation across categories based on real-world shopper behavior. Study shopper behavior and measure behavioral responses in a real-world context, e.g., material at shelf or checkout.
Innovate and execute 10x faster — measure and track shopper responses with speed and confidence.

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