U.S. retailers lost $94.5 billion to shrink in 2021—much of it driven by theft. Most retail security strategies rely solely on internal data, leaving blind spots around high-risk locations, times, and products. Without external signals, theft can go undetected until it’s too late.
🧠 The smartest retailers are now combining internal sales and inventory data with real-time external insights—like theft trends, location-based risks, and even social chatter—to prevent losses before they happen.
Why External Data Is Critical to Preventing Theft
When retailers integrate third-party data into their risk systems, they can:
✅ Detect emerging theft threats earlier
✅ Identify high-risk items, locations, and time windows
✅ Improve response speed with anomaly alerts and real-time signals
✅ Optimize staffing and surveillance resources
✅ Reduce shrink and protect profit margins
How It Works
🔹 Predictive Analytics models forecast when and where theft is likely to happen
🔹 Anomaly Detection tools flag suspicious sales or inventory activity in real time
🔹 Time-Series & Association Analysis help pinpoint repeat behaviors and patterns
🔹 Random Forests & classification models detect theft-like behaviors before they escalate
Real-World Impact: Lowe’s Real-Time Security Efficiency
Lowe’s saved nearly $1 million by switching from paper-based safety audits to a real-time reporting tool—identifying threats faster and improving security procedures across stores.
📩 Want to reduce shrink with smarter, proactive strategies?
Let’s talk about how Blue Street Data can connect you with the right external signals to detect and prevent theft.
👉 Talk to a Data Expert