Data Intelligence for Retail

The five fundamental KPIs every retail chain should measure are: conversion rate (visitors to buyers), footfall (total visitors per period), average dwell time (visitor engagement), capture rate (passersby who enter), and staff performance (sales per employee vs. traffic ratio). Flame provides the first four automatically using existing cameras. Conversion rate is the most revealing: without footfall data, a 10% sales drop could mean 10% fewer visitors (marketing problem) or the same visitors buying less (in-store experience problem). Leading retailers use Flame to separate these factors and direct investments correctly. The same KPI framework applies across Flame's entire client base, from shopping malls measuring tenant conversion to physical spaces monitoring visitor engagement.

Flame transforms security cameras into business intelligence sensors without altering their surveillance function. Hypersensor technology connects to existing IP camera video streams via RTSP protocol and applies AI models that extract analytical data: People Counting, flow patterns, Zones analytics, and dwell time measurement. Cameras continue recording for security simultaneously and independently. Compatible with Axis, Hikvision, Dahua, Bosch, Hanwha, and most manufacturers with RTSP support. Minimum requirements: 720p resolution and top-down or angled mounting. The same camera-to-analytics approach powers Flame deployments across physical spaces of all types.

Flame clients see ROI in three areas within the first 90 days. Staffing optimization (aligning shifts with real traffic) reduces labor costs by 8-15%. Conversion rate improvement (using footfall data to identify in-store experience problems) increases sales by 5-12% without additional traffic. Marketing attribution (measuring footfall generated by campaigns) eliminates spending on ineffective promotions. For a retailer with 20 stores and EUR 50M in revenue, a 5% conversion improvement represents EUR 2.5M in additional revenue. Leading shopping mall operators, with 10 shopping malls using Flame, reported an average 12% increase in tenant conversion in the first year by sharing footfall data with store managers.

Flame serves both independent stores and enterprise chains. For small stores (1-5 locations), setup is simpler: 2-4 existing cameras provide People Counting and basic traffic analytics for EUR 150-400/month. The dashboard shows the same insights large chains receive: hourly traffic patterns, conversion rate (integrated with your POS), and day-of-week benchmarks. For enterprise chains (more than 50 stores), Flame adds portfolio analytics, store-vs-store comparisons, and AI-based staffing recommendations. The SaaS model is scalable: per-location pricing decreases with volume. What makes Flame accessible to small stores is leveraging existing cameras. Beyond retail, the same technology scales to shopping malls and other physical spaces.

Retail analytics closes the gap between marketing investment and physical-store results. Flame measures footfall before, during, and after campaigns, quantifying exactly how many additional visitors each promotion generated. Key metrics: footfall lift (percentage increase during the campaign), conversion quality (did the additional visitors buy or just browse?), time patterns (when did campaign visitors come?), and retention (did they return afterward?). Unlike digital media where attribution is standard, physical-retail marketing has historically operated without these metrics. Flame connects them: measuring traffic generated by out-of-home, radio, social media, and email campaigns, providing the real cost per visit for each channel. Shopping malls and other physical spaces use the same methodology to measure event-generated footfall.

Omnichannel analytics unifies customer behavior data across digital and physical channels. Flame makes it possible by connecting in-store traffic analytics with ecommerce data through API integration. Use case: a retailer discovers that 60% of Saturday shoppers browsed its website in the previous 48 hours, but in-store sales aren't attributed to ecommerce. Flame can cross-reference traffic patterns with web activity peaks to reveal these connections (without identifying individuals). For clients with loyalty programs, Flame's Connect links WiFi login data with loyalty IDs (with consent), creating a unified view of online-offline behavior. This omnichannel approach extends beyond retail to physical spaces like hotels, where operators correlate booking-channel data with common-area usage.

Flame offers SaaS pricing with monthly or annual subscriptions. Cost depends on number of locations, cameras per location, and analytics modules. Guideline breakdown: Single store (2-4 cameras): EUR 150-400/month including counting, basic traffic, and dashboard. Mid-size chain (10-50 stores): volume pricing negotiated individually, including API integration and account manager. Enterprise (more than 50 locations): custom enterprise license with dedicated SLA, custom integrations, and priority support. No upfront hardware costs when using existing cameras. Implementation (camera audit, calibration, training) is included. Typical contracts are annual. ROI exceeds investment in 3-6 months for most retailers. The same pricing model applies to Flame deployments in shopping malls and other physical spaces.

Flame is built from the ground up with privacy by design. Technical architecture: cameras send video streams to Flame software, which extracts analytical data (counts, flows, dwell times) and immediately discards the original imagery. No video or imagery is ever stored outside the existing security system. No facial recognition or biometrics are used at any time. The data produced is exclusively statistical: 147 people entered between 10:00 and 11:00, average dwell time in Zone A was 4.2 minutes. It is impossible to identify an individual from Flame data. Certifications: ISO 27001, verified GDPR compliance, EU data processing. The same privacy approach protects visitors across all Flame deployments, from retail stores and shopping malls to any other physical space.