Turn your existing cameras into a real-time engine for conversion, efficiency and growth.

About the Webinar

Physical stores remain critical to the US retail ecosystem, but growing profitability without continuously increasing headcount and operating costs is a real challenge. Join this session to see how leading retailers are turning their existing CCTV infrastructure into a real-time business intelligence platform using AI-based video analytics. We’ll cover customer behavior, footfall-to-revenue conversion, workforce and queue efficiency, multi-store scaling, ROI, and the roadmap from Smart Store to Autonomous Store.

What You Will Learn

• How to turn existing CCTV into a business intelligence platform without replacing your surveillance ecosystem
• How footfall, dwell time and customer movement can improve layout, merchandising and product placement
• How to improve visitor-to-buyer conversion
• How to align staffing and manage queues based on real-time traffic
• How to centralize KPIs and alerts across hundreds of stores
• Where measurable ROI comes from and how to choose the right use case before investing in AI
• The roadmap from Smart Store to Intelligent Store to Autonomous Store

Agenda

1. The New Reality of Brick-and-Mortar Retail

• Why physical stores remain critical to US retail despite e-commerce growth
• Increasing store profitability without continuously increasing headcount and operating costs
• Moving from monitoring stores to measuring and optimizing performance

2. From CCTV to Intelligent Store Intelligence

• How traditional CCTV is evolving into real-time business intelligence platforms
• Turning existing camera infrastructure into actionable insights without replacing the entire system
• Moving from “What happened?” to “Why did it happen?” and “What should we do next?”

3. Understanding Customers Inside the Store

• Tracking footfall, visitor patterns, dwell time and customer movement
• Understanding which areas attract the most attention
• Identifying engagement patterns and potential bottlenecks
• Using behavioral insights to improve layouts, merchandising and product placement

4. Converting Footfall into Revenue

• Measuring the relationship between store traffic and business performance
• Improving visitor-to-buyer conversion
• Optimizing staffing, promotions and merchandising using traffic and behavioral data
• Creating store-level benchmarks to identify high- and low-performing locations

5. Workforce & Operational Efficiency

• Understanding staffing requirements based on real-time store traffic
• Reducing unnecessary queues and improving checkout efficiency
• Monitoring service levels and employee productivity beyond manual observation
• Comparing operational performance across stores

6. Queue & Customer Experience Analytics

• Detecting queue build-up in real time
• Understanding peak periods and optimizing staffing
• Reducing wait times and improving the in-store experience
• Identifying recurring operational issues across locations

7. Scaling Intelligence Across Hundreds of Stores

• Challenges of managing analytics across multi-location retail networks
• Creating a centralized view of store performance
• Standardizing KPIs across locations, formats and markets
• Using dashboards and automated alerts to prioritize where action is needed

8. The ROI of an Intelligent Store

• Where measurable ROI comes from: increased conversion, improved workforce utilization, reduced wait times, better merchandising decisions, reduced operational losses, and improved security and compliance
• How to identify the right use cases before investing in AI

9. What the Future of Retail Intelligence Looks Like

• The convergence of AI, computer vision, POS data, customer analytics and store operations
• Moving toward predictive store management instead of retrospective reporting
• Making every store more measurable, responsive and profitable
• The roadmap from Smart Store → Intelligent Store → Autonomous Store Operations

Speaker

Suparv Jain
Director & Country Head – US, Transline Technologies Limited

Who Should Attend

• Retail CIOs, CTOs, VPs and Directors of IT
• Heads of Infrastructure and Retail Technology
• Digital Transformation leaders
• IT decision makers at multi-location US retail chains

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