Impact CTRL theft prediction

In retail, trust is good – but control is better.


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Leverage Machine Learning technology to control the impact of theft on your business and revolutionize self-service theft prevention.

Impact CTRL identifies shopping patterns leading to theft at a store level and assigns an individual probability of theft to every self-service customer in the store. Theft probabilities are updated in real-time for every step of the customer journey!

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Theft in Retail

Shoplifting is the leading cause of shrinkage in retail. Research conducted by ECR on 140 million self-service (Scan & Go and Self-Checkout) transactions from different stores & suppliers shows that theft’s impact on retail losses has been underestimated for years.

  • 2.8% of all store transactions contained at least one error
  • 9 out of 10 times a self-service transaction with over 100 items contains errors
  • 18% average higher shrinkage rate in stores with Scan & Go or Self-Checkouts 
  • 60% of the time shoppers with over 50 items made at least one error

Take control of your store transactions by leveraging your own data against fraud. Impact CTRL pools information from available resources, identifies fraud patterns, and learns based on those patterns – uncovering, on average, over twice the number of transaction errors during random checks than traditional measures.

Fully GDPR compliant, Impact CTRL targets transactions, not individuals. The platform offers customizable parameters that can be automatically adjusted based on store crowd-level. It detects fraud-sensitive products as well as checkout devices, calculating a personalized risk percentage and advising whether a partial or a full rescan is recommended to minimize theft.

Want to learn more? Check out our Knowledge Session on this groundbreaking theft prediction solution, and learn how it can help safeguard your retail business.

Take control of your store transactions and prevent theft with Impact CTRL

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