Transform your Retail Store using AI-Powered Retail Video Analytics

40%+ increase in Conversion Ratio.
16%+ Improvement in Average Order Value
45% reduction in DEPS
65% increase in SOP Compliance Adherence

Trusted By Leading Brands

Make Your Store A Smart Store

Retail Video Analytics

Retail video analytics is a powerful tool that can help businesses gain insights into customer behavior and preferences.

Guesswork on customer preferences → Data-driven insights
Reactive decision making → Proactive decision making
Basic foot traffic counting → Advanced behavior analytics
Intuition-based decisions → Real-time intelligence
Manual monitoring → Automated AI surveillance

Case Study: Converting Footsteps into Sales for a Leading Footwear Retailer

A multinational footwear chain with 1800+ high-street stores wanted to transform raw CCTV footage into data-driven decisions. Traditional manual audits showed growing gaps between store traffic and actual shoe purchases, but managers lacked real-time insight. The retailer adopted Agrex.ai’s retail video analytics suite—deploying People Counting, Passerby Counts, Demographics, Staff Exclusion, Dwell Time tracking and Shoe-Trial detection—across its flagship outlets.

Solution implementation

People Counting & Passerby Counts pinpointed the true conversion funnel: how many pedestrians looked in, walked through the door and reached the fitting zone.
Demographic analytics revealed age- and gender-wise demand, letting merchandisers spotlight trending styles for each cohort.
Staff Exclusion algorithms separated employees from shoppers, delivering accurate, management-ready KPIs.
Dwell Time heatmaps exposed cold corners and bottlenecks, while Shoe-Trial sensors measured every try-on event—a direct proxy for buying intent.

All metrics streamed into a live Agrex.ai dashboard, accessible on tablets by store leads and on a central command screen at HQ.

Results in 180 days

+14 % average footfall after window displays were rebuilt for segments with the highest passer-by-to-entry ratio.
+18 % conversion rate driven by relocating top-selling SKUs to zones with longest dwell time and highest trial counts.
-26 % billing queue time once staffing was rescheduled to match hourly foot-traffic peaks identified by People Counting.
+11 % customer satisfaction (post-purchase survey NPS) thanks to faster service and more available sizes.
3-month ROI: the system paid for itself in eleven weeks through incremental revenue and labour savings.

Why it worked

Retail video analytics replaced guesswork with granular truths: every entrance, every trial, every lingering minute on the shop floor. By knowing precisely who entered, when they engaged and what they tried, the chain aligned staffing, merchandising and marketing in near real time. Executives now run weekly “data walk-throughs,” filtering the Agrex.ai dashboard by city, store size and demographic, then rolling best practices network-wide.

Key takeaways for footwear retail

Deploy people counting software first—clean traffic data underpins every KPI.
Layer dwell time and shoe-trial analytics to expose product-level friction.
Use demographic insights to personalise window creatives and digital campaigns.
Let staff exclusion protect data integrity and reveal true labour needs.

If your footwear, apparel or sportswear brand wants the same results, book a Retail Video Analytics demo today—schedule a call with Agrex.ai now.

Use Cases

Customer Intelligence and Footfall

Collect accurate footfall analytics ignoring staff
Collect demographics info like Age and Gender
Track Unique/Repeat Customers
Analyse Peak vs Off Peak Hours, track seasonal changes

Heatmap and Dwell Time

Locate High Engagement Areas
Analyse where people go and how long they stay
Get section-wise dwell times and heat maps
Optimise Product Placement and Visual Merchandising with real-time and accurate data

Improve NPS Scores

Reduce Queuing Times and Queue Lenghts
Allocate staff where-ever needed
Maintain Cleanliness by regular updates
Keep track of Uniform/Hygiene
Track queue length average time in queue

Loss Prevention

Keep track of Suspicious Behaviour
Detect intrusions / theft attempt
Detect tampering with the camera
Face Recognition for record keeping of offenders
Detect if Guard is sleeping or absent