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Risk and Rewards: How Property Data Helps Retailers Prevent Loss

While one may have expected retail theft would decrease during the lockdown periods caused by COVID-19, burglary continued, with rates varying across the country depending on location and store as well as crime type. According to the National Retail Federation (NRF), organized retail crime perpetuated by professional groups of criminals is also continuing to grow, with 2020 experiencing a 2 percent increase from the same period a year earlier.

As retailers continue to reopen and shoppers increasingly return to brick-and-mortar locations, retail operations must continue to be vigilant in mitigating loss prevention and crime. According to the 2020 National Retail Security Survey, which covers 2019 data for retailers in all categories, inventory shrinkage hit an all-time high of 1.62 percent, up from 1.38 percent in 2018. That translated to $61.7 billion in losses to retailers, compared to $50.6 billion in 2018.

Below, I’ll discuss the different risk factors retailers face and how they can better leverage property data to get ahead of these risks.

Risk Factors to Consider

There are varying factors that can determine crime risk. For example, researchers Chang and Jacobson found that consistent foot traffic in an area thwarts crime and property theft. CoreLogic data shows that the crime rate where customers live is a partial predictor of theft and shrink at the stores in which they shop, as is the crime risk where the store is located. Even the time of year can impact theft, with 81 percent of season losses occurring during the winter holidays.

In an effort to optimize staffing and hours, some retailers are putting fewer employees on the salesfloor. However, this can create more opportunities for shoplifting. Similarly, retailers often make the mistake of placing their least-experienced managers in stores that are in less-desirable locations but also have the most shrinkage.

Related story: The Rise of Pandemic-Driven Retail Fraud: How Brands Are Leveraging Prescriptive Analytics to Fight Back

Organized Retail Crime Trends

Crime rings are forming with the intent to perpetrate schemes including return fraud, smash and grab, cargo theft, and forgery. Organized retail crime costs the industry approximately $30 billion each year. Without significant improvements, price tags could increase for customers, and communities can pay the price — literally — if sales tax isn’t collected for the correct city (i.e., where the merchandise was intended to be sold).

Retailers are responding to crime risk with changes to return policies, product placement, trespassing guidelines and video surveillance. Adequate staff levels are also key, along with regular training for theft deterrence. In some cases, employees are part of the crime ring, which puts pressure on more extensive background checks.

Mitigating Risk With Property Data Intelligence

Through property data, retailers can gain insight into past, current and future crime risk, including organized retail crime activity in the surrounding area. For example, retailers can see a location-specific picture of overall crime risk, with drill-down capabilities into crime categories that include robbery, assault, homicide, burglary, vandalism, general theft and motor vehicle theft, giving them an overall risk score of the area. The score can re-calculate every 30 feet to provide a precise view of risk that changes as you move to a new address, even within the same block.

In this way, property data can help retailers understand, at a granular level, which locations are at greatest risk of crime. This insight helps retailers make data-driven decisions about where to deploy additional security resources and staff to reduce vandalism and theft.

The Retail Road Ahead

As the retail space continues to both thrive and simultaneously shift with the times in a post-COVID-19 world, utilizing big data to determine when and where to optimize security spending and staffing and improve location planning will be instrumental in improving a retailer’s bottom line.

For instance, a location with high risk could consider a store layout and design that allows for aisle placement to facilitate easy visual monitoring by employees and reduces blind spots. By staffing a location with a greeter, a shoplifter may think twice before walking past an employee that noticed his entrance and exit. Increasing the frequency of inventory stock counts can also identify any discrepancies that may be caused by employee theft.

Crime is not constant or created equal. For retailers, analyzing crime trends through the lens of property data intelligence allows them to see the ebb and flow of crime risk in a region over time and take the necessary precautions to mitigate that risk. In this way, retailers ensure three invaluable outcomes: the safety of customers, staff, and the success of their business.


Sherrie Clevenger | Author’s page

Sherrie Clevenger is Principal, Product Management, New Markets at CoreLogic. As a leading provider of gold standard data, analytics and platforms, CoreLogic enables real estate professionals, financial institutions, insurance carriers, government agencies and other housing market participants to help people make their dream of homeownership a reality.

Sherrie leads the charge with new market strategies, bringing into focus markets that are adjacent to the company’s traditional competencies.

Prior to CoreLogic, Clevenger worked at NADAguides. She is a subject matter expert in manufactured housing and personal property valuation and spent 20 years in the industry before joining CoreLogic. She earned a bachelor’s degree in organizational leadership from Chapman University and an MBA from Brandman University, a Chapman University System.