Brick-and-mortar retail is in the midst of a transformation. Once considered at a disadvantage to e-commerce due to limited shopper data, physical retail environments are now becoming just as measurable, responsive, and insight-driven as digital channels. Advances in artificial intelligence, sensor-based technologies, and computer vision have enabled retailers to capture and act on real-time data that was previously inaccessible.

At the forefront of this shift is Sensormatic Solutions, the global retail solutions portfolio of Johnson Controls. By integrating AI-enabled sensors and cameras into retail environments, Sensormatic Solutions is helping retailers unlock critical business metrics tied to shopper behavior, store performance, and operational efficiency.

Its Store Guest Behaviors Analytics, powered by AI and built on Re-Identification (Re-ID) technology, gives retailers unprecedented visibility into how shoppers move, dwell, and engage inside physical stores. Delivered through Orbit AI overhead people counters, Video AI cameras, and ShopperTrak Analytics, the platform turns raw activity into actionable insights, enabling faster decision-making and measurable sales growth—all while maintaining shopper privacy.

This evolution represents a major moment for MarTech and retail analytics, where offline behavior is no longer a blind spot but a strategic growth lever.

Why In-Store Data Now Rivals E-Commerce Insights

Traditionally, e-commerce platforms have dominated when it comes to shopper analytics. Retailers could track clicks, conversion paths, dwell time, abandonment, and revenue attribution with precision. Physical stores, by contrast, relied on sales totals and foot traffic, offering limited context into shopper intent or engagement.

That gap is rapidly closing.

According to Sensormatic Solutions leadership, today’s brick-and-mortar retailers now have access to data that rivals, and in some cases complements, digital insights.

Key developments making this possible include:

• AI-powered computer vision that tracks movement without personal identification.

• Advanced sensors capable of distinguishing shoppers from staff and passersby.

• Real-time analytics platforms that transform foot traffic into business intelligence.

• Privacy-first design that excludes personally identifiable information.

The result is not just more data, but better data—information that directly influences store layout, staffing decisions, merchandising strategy, and revenue optimization.

Understanding Store Guest Behaviors Analytics

At the core of Sensormatic Solutions’ innovation is Store Guest Behaviors Analytics, a suite designed to convert in-store movement into measurable and actionable insights.

What Powers the Platform

Store Guest Behaviors Analytics is driven by a combination of hardware and software innovations:

• Orbit AI Overhead People Counters

  • AI-enabled sensors mounted overhead

  • Designed to accurately count shoppers

  • Exclude staff, children in strollers, and non-shopping traffic

• Video AI Cameras

  • Capture anonymized movement patterns

  • Enable behavioral attribution without facial recognition

• Re-Identification (Re-ID) Technology

  • Assigns anonymized IDs to track movement journeys

  • Identifies repeat behavior patterns during a visit

• ShopperTrak Analytics Platform

  • Centralized dashboard for data visualization

  • Translates raw inputs into actionable metrics

Together, these components create a complete view of shopper behavior across the store.

Privacy-First Design as a Core MarTech Principle

One of the biggest challenges in modern analytics is balancing personalization and insight with consumer privacy. Sensormatic Solutions has prioritized privacy by design.

Key privacy measures include:

• No collection of personally identifiable information (PII)

• No facial recognition or biometric capture

• Anonymized behavior tracking only within a single visit

• Exclusion of staff and irrelevant traffic from analytics

This approach allows retailers to benefit from high-quality behavioral insights while staying compliant with evolving global privacy regulations and maintaining shopper trust.

Driving Higher Conversion Through Shopper Journey Insights

One of the most valuable applications of Store Guest Behaviors Analytics is its ability to reveal the path to purchase inside physical stores.

By understanding how shoppers move through a space, retailers can identify:

• Entry points with the highest engagement

• High-traffic versus low-traffic aisles

• Bottlenecks that prevent smooth navigation

• Drop-off zones where shoppers disengage

How Path-to-Purchase Analytics Improves Conversion

Retailers can use journey data to:

• Optimize store layouts based on real movement patterns

• Reposition high-margin or promotional products

• Improve signage and wayfinding

• Reduce friction in high-traffic zones

Rather than relying on assumptions or outdated floor plans, retailers gain data-backed clarity on how store design directly impacts sales conversion.

Boosting Merchandising Impact With Dwell and Zone Analytics

Beyond movement, understanding where shoppers spend their time is critical to merchandising success.

Store Guest Behaviors Analytics provides insights into:

• Zone preference

• Dwell time by display or category

• Engagement levels across store sections

Turning Dwell Time Into Revenue

With these insights, retailers can:

• Identify top-performing displays that capture attention

• Compare engagement across multiple product categories

• Test and validate new merchandising strategies

• Quickly adjust underperforming displays

This level of real-time feedback allows merchandising teams to move from static setups to dynamic, data-driven optimization.

Improving Operational Efficiency Through Smarter Staffing

Labor optimization remains one of the most complex challenges in retail. Overstaffing increases costs, while understaffing hurts customer experience and sales.

AI-powered traffic analytics offer a more precise approach.

How Real-Time Traffic Data Supports Staffing Decisions

Retailers can use traffic and behavioral data to:

• Identify peak shopping hours with higher accuracy

• Align staff scheduling with real demand

• Adjust floor coverage dynamically throughout the day

• Reduce wait times during high-traffic periods

By matching labor allocation to actual in-store activity, retailers improve both efficiency and shopper satisfaction without increasing labor spend.

Real-World Validation: LIDS Expands Its Insights With Orbit AI

Sensormatic Solutions’ innovations are already delivering measurable value for retail brands.

LIDS, a long-time partner of Sensormatic Solutions, has deepened its collaboration with the introduction of Orbit AI technology.

How LIDS Is Using AI-Powered Insights

According to LIDS leadership, the new technology provides:

• Clearer visibility into shopper flow

• Better understanding of in-store engagement

• Stronger decision-making around layout and merchandising

• Improved overall shopper experience

These insights demonstrate how AI-powered analytics can transition from experimentation to everyday operational value.

MarTech Meets Retail: A Broader Strategic Shift

Store Guest Behaviors Analytics represents a broader trend in MarTech: the blending of physical and digital intelligence.

Key implications for MarTech leaders include:

• Offline data is becoming first-class marketing intelligence

• Attribution is expanding beyond clicks to physical experiences

• Customer journey mapping is now omnichannel by default

• Real-time decision-making is extending into physical environments

Retailers that embrace this convergence gain a competitive advantage by aligning digital strategy with in-store realities.

NRF 2026: Bringing AI-Powered Retail Analytics to Life

Sensormatic Solutions will showcase Store Guest Behaviors Analytics at the 2026 NRF Big Show, taking place January 11–13 at the Jacob K. Javits Convention Center in New York City.

Attendees can expect:

• Live demonstrations of AI-powered analytics

• Hands-on walkthroughs of Orbit AI sensors

• Insights into upcoming retail technology innovations

• Direct discussions with Sensormatic Solutions experts

This event provides a tangible look at how AI-backed MarTech is reshaping physical retail.

Conclusion: Turning In-Store Behavior Into Strategic Advantage

The future of retail is no longer a debate between online and offline. It is about how effectively brands can connect data, insights, and action across every customer touchpoint.

Sensormatic Solutions’ Store Guest Behaviors Analytics shows what’s possible when AI, sensors, and MarTech principles converge. By transforming in-store activity into real-time, privacy-safe intelligence, retailers can:

• Increase conversion rates

• Strengthen merchandising performance

• Optimize staffing and operations

• Deliver better shopper experiences

As physical retail becomes more measurable and responsive, solutions like these will define the next era of data-driven growth. For retailers looking to compete smarter, faster, and more efficiently, AI-powered in-store analytics are no longer optional—they are foundational.

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