Fighting Back Organized Retail Crime with Geolocation Intelligence

In the bustling world of U.S. retail, one leading retailer chain is embroiled in a costly battle against organized retail crime (ORC). As theft incidents escalated and profits dwindled, the retailer turned to AKTEK for a novel solution using advanced geolocation intelligence. The mission was clear: track hidden patterns, identify hotspots, and shed light on the organized networks behind these thefts. Here’s how we did it—and what we found.

The Data Dive Begins

The retailer had data from over 5,000 theft incidents across over 250 store locations spanning 30 states for three years. However, incident data alone wouldn’t be enough to unearth organized crime patterns.

Looking for anonymous traces left by smartphones around these incidents — privacy-compliant geolocation signals within a one-mile radius of each store, recorded within a four-hour window around the time of the crime. Altogether, AKTEK amassed over 100 million data points from 50 million unique devices.

The purpose was to find patterns to transform how the retailer approached ORC, moving beyond reactive losses to proactive crime prevention. AKTEK zeroed in on devices that repeatedly showed up at multiple stores around the time of thefts.

After careful analysis, the results were striking: 17,031 devices (0.034% of all observed) had a recurring presence across three or more retail locations, their movements coinciding with reported thefts.

Zooming into the top suspicious, 446 appeared in 5 or more locations during theft (0.0009% of the total). These devices formed a roadmap, revealing hidden connections and movement patterns across the retail landscape.

Tracing the Hotspots: California's Clusters

With most incidents concentrated in California, AKTEK homed in on this state. We aimed to identify secondary locations where multiple recurring devices might gather, potentially revealing organized theft networks' meetup points.

Two locations quickly surfaced: "Garcia Market" on Broadway Place and “The Makeup Store”  on Whittier Blvd, both in Los Angeles. Each location revealed a surprising concentration of devices tied to theft incidents across different stores.

• Garcia Market: 7 devices had appeared three or more times near stores during theft incidents.
• The Makeup Store: 21 devices exhibited suspicious recurrence, with some visiting on as many as 15 separate days in 2023, overlapping with multiple recorded theft times.

Significantly, these findings were validated by historical raid reports at these locations, where law enforcement recovered stolen goods.

By correlating device patterns with these known hotspots, AKTEK highlighted these locations' critical role in facilitating ORC activities.

Cross-Referencing Clusters: The Network Expands

Going deeper, AKTEK observed a web of connections among the devices in Los Angeles. Sixteen devices that had repeatedly surfaced around “The Makeup Store” had also appeared near “Garcia Market” during overlapping timeframes. This link provided a crucial clue about potential shared players in the ORC network. Additionally, one of these devices led to another address— “Storage For Less” in Rosamond, CA, which showed signs of being used as a holding space, possibly for stolen merchandise.

This broader view of device movements gave the retailer actionable intelligence. AKTEK recommended monitoring these secondary locations closely, collaborating with law enforcement on high-theft areas, and adjusting in-store security based on device movement trends. 

Scaling Up: Towards a Stronger Security Strategy

By leveraging this intelligence, the retailer can transition from a reactive strategy to a dynamic, preventive stance. Proactive monitoring, weekly ORC threat intelligence reports, and daily proximity alerts will allow loss prevention teams to anticipate potential threats and respond swiftly. This shift empowers teams to allocate resources strategically, focusing security budgets where they’re most needed and reducing theft risks at vulnerable locations nationwide.

Protecting Privacy While Uncovering Patterns

Data-driven solutions, especially those using geolocation intelligence, must balance effectiveness with respect for privacy. In this analysis, AKTEK implemented strict protocols to protect individual privacy while broadly targeting suspicious behaviors.

Rather than investigating specific individual devices, the system looked for overarching patterns, flagging groups of devices only after they met clear criteria for unusual, recurrent movements across multiple retail locations in theft-specific timeframes.

The approach prioritized privacy by avoiding personalized tracking and focused on anonymized, aggregate data that could expose ORC operations without infringing privacy rights.

Looking Forward

AKTEK’s approach has begun to dismantle the invisible networks underlying organized retail crime, revealing connections, patterns, and critical locations that were previously hidden. As data-driven crime prevention expands, this retailer gains an invaluable advantage, arming itself with the tools to anticipate, deter, and address ORC.

The model is a game-changer in protecting stores, assets, and the retail experience. And as the insights deepen, the fight against organized retail crime will only grow more formidable.