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Do your Cashiers scan every item?

Scan avoidance technology helping save supermarkets millions at checkoutStoplift 2.png

Stoplift 1.jpgIndependent grocers understand that inventory shrinkage ultimately reduces all-important profit margins— and too much shrink can mean the difference between being in the black and seeing red.

A growing trend by which to stem the flow of shrinkage at the checkout and turn the tide on leaking profits is to use smart computer artificial intelligence.  Innovative grocers and retailers around the world have been installing StopLift’s ScanItAll™ software at their checkouts utilizing their existing cameras.

StopLift’s ScanItAll™ visually determines what occurs during each POS transaction to immediately identify loss at the checkout.  The technology has already detected more than 2.3 million confirmed incidents at thousands of checkouts.

These incidents include “sweethearting”, when cashiers pretend to scan merchandise but deliberately bypass the scanner, thus not charging the customer for the merchandise.  The customer is often a friend, family member or fellow employee working in tandem with the cashier. 

StopLift’s patented Scan-It-All video analytics technology visually determines what occurs during each transaction to immediately distinguish between legitimate and fraudulent behavior at the checkout.  As soon as a scan avoidance incident occurs, StopLift, which constantly monitors 100% of the security video, flags the transaction as suspicious.  It quickly reports the incident, complete with video and identifying the cashier and/or customer.  This includes incidents which may be due to mistakes by the cashier or customer at manned and self-checkout as well as items left in the shopping cart.

To watch real scan avoidance incidents detected by StopLift, visit www.StopLift.com.

StopLift identifies dishonest associates are identified on the basis of video evidence the first time they conduct a fraudulent transaction, rather than months or even years down the road, significantly reducing inventory shrinkage, deterring future theft, and boosting profitability.  Dishonest customers are identified at the self-checkout.

Chris Ajlouny, who owns ten Piggly Wiggly supermarkets in the Birmingham, AL area, and Keith Holley, owner of Piggly Wiggly in Wetumpka, AL knew that cashiers were either stealing or failing to scan items, costing their supermarkets major losses.  Ajlouny estimated that his loss was $8,000- $10,000 per quarter for two stores.  Holley estimates that his one store was losing $6,000-$10,000 per month from checkout shrink, most of it in frozen food. 

Ajlouny did not tell any employees at his stores when he installed StopLift two years ago, so that he could see the extent of scan avoidance.  In the first week, he saw three cashiers steal $400-$500 at a time, sliding groceries past the scanner and later getting “kickbacks” from the customer.  One cashier admitted to getting kickbacks outside the store. 

From then on, Ajlouny showed StopLift videos to all new employees.

“My cashiers know they are being watched,” Ajlouny said.  “They see their performance on video.  Some of them need retraining.  All the managers see the reports of all the cashiers, and now they all work harder to give their respective stores the best record for preventing scan avoidance.

“There are barely any mistakes anymore,” Ajlouny said.  “It’s working great as a deterrent to stealing and careless scanning.”

“The system never sleeps.  It lets me sleep,” Holley said.  “It’s the best thing I’ve ever done.  It’s changed my life.  Every grocer should use it.”

Supermarkets have tried to track sweethearting or scan avoidance through data mining, but, as Kundu notes: “How do you data mine for theft that leaves no data trail?”

The U.S. National Retail Federation states that retail shrink was $44.5 billion in 2014 and more than $10 billion of that is due to sweethearting.  Supermarkets, with their lower profit margins, are particularly vulnerable to sweethearting, which has accounted for an almost 35% profit loss industrywide.

StopLift Checkout Vision Systems grew out of Kundu’s Harvard Business School research study “Project StopLift” on Retail Loss Prevention.  With technological research insights Kundu developed while at MIT, Project StopLift concluded that video recognition could be used to automate and, thus, make possible the comprehensive examination of surveillance video.  Prior to founding StopLift, Kundu developed facial recognition systems for identifying terrorists in airports.

For more information, contact:
Sherry Alpert

Sherry Alpert Corporate Communications

3 Riverview Road

Canton, MA  02021

(781) 828-9415, cell (617) 678-1613

sherry@alpert-publicrelations.com

"In a multi-store operation it is important to have control from a central point. STCR provides the systems and technical expertise to do just that."