Flame Analytics

Data intelligence for supermarkets

Flame turns the cameras you already have in your supermarket into actionable data: footfall by zone, checkout queues, conversion and basket. Supermarket analytics with artificial intelligence, no biometrics and fully GDPR-compliant, to optimise assortment, cashier staffing and layout with real data.

  • 99% accuracy
  • No biometrics · 100% GDPR
  • Real-time data
  • AI on your existing CCTV
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Brands already working with Flame

IKEADecathlonCushman & WakefieldTelefónicaCBRESantanderAlain AfflelouWestfieldHavaianasMerlin PropertiesIKEADecathlonCushman & WakefieldTelefónicaCBRESantanderAlain AfflelouWestfieldHavaianasMerlin Properties

The day-to-day of your supermarket.

These are the problems that recur in any grocery store and that you still manage today without real data.

Queues cut your sales

When the wait grows, the customer abandons the purchase or shrinks their basket. Without footfall data by time slot and alerts, you react late and without knowing when to add checkouts.

Cashiers poorly sized at peak times

Too many staff in off-peak hours and too few during the peaks. Planning shifts without knowing the real traffic of each slot creates unnecessary costs and lost sales.

Aisles and sections that underperform

There are cold zones almost nobody walks through and promotions almost nobody sees. Without heatmaps you don't know whether the problem is the product or its placement.

You don't know your real conversion

Counting tickets isn't enough: without cross-referencing real visits with sales, you don't know what share buys. And counting carts, children or staff distorts the figure.

What you can do

Everything Flame measures and activates in your supermarket

Eight capabilities that work on the CCTV cameras you already have, tailored to a supermarket's operations.

Section optimisation and cashier planning

Cross-reference each section's flow with sales to improve assortment and space, and adapt the cashier roster to each time slot. Put staff where and when the store needs them, without overspending or queues.

Footfall and flow by zone

Measure entries and exits and analyse how the customer moves through the supermarket. Compare days, slots and campaigns to know real traffic and spot the busiest zones.

Visit-to-purchase conversion

Cross-reference real traffic with your POS or ERP to calculate real conversion and average basket. Discover how many customers enter the supermarket and leave without buying.

Heatmaps and behaviour

Visualise paths, hot spots and dwell time in each aisle. Discover which sections attract, which are ignored and how to improve layout and gondola ends.

Real-time occupancy

Track how many people are present at any moment and by zone, with alerts when a section or the checkout line saturates. Act before crowding turns into a bad experience.

Queue and restroom management

Measure wait time and abandonment at the checkout line to open positions right when needed. Also track restroom usage to plan cleaning by real use, not a fixed schedule.

Capture and loyalty via WiFi

The WiFi captive portal turns visits into contacts and feeds them into your CRM (such as Mailchimp, Salesforce or HubSpot). Build a database to launch promotions and increase repeat visits with the customer's consent.

Data for daily operations

Plan cleaning, restocking and shifts based on the real flow of each time slot. Turn data into concrete decisions on staff, stock and maintenance.

And all of it, on top of what you already have, with full privacy:
Existing CCTVUse your cameras
HypersensorAdvanced AI video analysis
No biometrics100% anonymous data
100% GDPRPrivacy guaranteed

Fewer queues, better assortment, more conversion.
Personalised demo in 20 minutes.

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Case studies

Brands that already decide with data, not intuition

Large networks and chains that measure real traffic, queues and conversion with Flame.

The best brands talk about us

Irene Cuadrado

Somos clientes desde hace años y pretendemos seguir siéndolo. Flame te cuenta lo que no puedes ver sentado en una oficina o dando un paseo por el hall del centro comercial. Te acerca al cliente desde el momento en que pasa por delante.

Irene CuadradoMarketing & Specialty Leasing manager · ABC Serrano (Savills)
Vicente Alemany Climent

Gracias Flame analytics por acompañarnos en el apasionante reto de ofrecer a nuestros visitantes una experiencia omnicanal total.

Vicente Alemany ClimentCoordinador de Innovación · Cushman & Wakefield
Lucas Madiedo

Los datos de Flame nos ayudan a adaptarnos a nuestros clientes, cada vez más exigentes, y a las marcas, que nos demandan cada vez más información.

Lucas MadiedoDirector de Transformación Digital · Merlin Properties
Irene Cuadrado

Somos clientes desde hace años y pretendemos seguir siéndolo. Flame te cuenta lo que no puedes ver sentado en una oficina o dando un paseo por el hall del centro comercial. Te acerca al cliente desde el momento en que pasa por delante.

Irene CuadradoMarketing & Specialty Leasing manager · ABC Serrano (Savills)
Vicente Alemany Climent

Gracias Flame analytics por acompañarnos en el apasionante reto de ofrecer a nuestros visitantes una experiencia omnicanal total.

Vicente Alemany ClimentCoordinador de Innovación · Cushman & Wakefield
Lucas Madiedo

Los datos de Flame nos ayudan a adaptarnos a nuestros clientes, cada vez más exigentes, y a las marcas, que nos demandan cada vez más información.

Lucas MadiedoDirector de Transformación Digital · Merlin Properties

Frequently asked questions

How does analytics improve shopping mall management?
Footfall analytics transforms shopping mall management from intuition-based decisions to data-driven strategy. Flame provides shopping mall managers with real-time and historical metrics: total mall traffic, floor distribution, zone performance, and hourly patterns. This data drives key decisions: optimal event scheduling (when to generate traffic vs. when traffic is already high), tenant mix (which store types attract complementary footfall), marketing efficiency (which campaigns generate real visits), and operational planning (cleaning, security, HVAC based on real occupancy). A leading European operator manages its 10 shopping malls with Flame data, achieving quantified operational and strategic decisions. The same data-driven approach powers Flame's analytics across physical spaces of all types.
Can tenants access footfall data?
Yes. Flame offers multi-tier dashboards that allow shopping mall management to share relevant data with tenants while maintaining confidentiality of sensitive information. Each tenant sees: total mall traffic (context), their floor or zone traffic, and their own footfall if they have cameras connected. They don't see individual data from other tenants. This shared-data model benefits everyone: tenants understand the context of their performance (did my sales drop or the entire mall's?) and management demonstrates the mall's value with objective data. In lease negotiations, Flame data provides objective evidence of the traffic the mall generates for each zone. A similar multi-tier access model applies to Flame deployments in other physical spaces, where different stakeholders access the relevant metrics.
What is real-time occupancy management?
Real-time occupancy management continuously monitors how many people are inside the shopping mall, by floor and zone, comparing against defined capacity thresholds. Flame displays current occupancy on real-time dashboards and can trigger automatic alerts when predefined levels are reached (80%, 90%, 100% of capacity). Born as a post-COVID need, occupancy management has become permanent operational practice because it improves visitor experience (preventing crowding), optimizes resources (security, cleaning, HVAC based on real occupancy), and meets capacity regulations. Over 50 shopping malls in Flame's network use occupancy displays at entrances. The same occupancy management technology is deployed in retail stores and other physical spaces.
How does parking analytics work?
Parking analytics connects vehicle traffic data with foot traffic to provide a complete picture of the shopping mall visit. Flame can integrate data from existing parking sensors with its footfall analytics, revealing correlations: average time between parking arrival and mall entry, visit duration by access origin (car vs. public transit), and parking occupancy rates correlated with mall footfall. This enables optimizing parking signage, adjusting mall hours based on arrival patterns, and evaluating alternative transportation initiatives. Leading shopping mall operators use this combined data to optimize the arrival experience and reduce access friction.
How does it measure event effectiveness?
Flame measures shopping mall event impact in three dimensions: traffic lift (how many additional visitors the event generated), traffic distribution (did attendees visit stores or just attend the event?), and retention (did event visitors return in the following weeks?). The process: Flame establishes a baseline of traffic for the same day/time in previous weeks, measures traffic during the event, and calculates net lift. For a concert at a large shopping mall, Flame demonstrated that 67% of attendees visited at least two stores before or after the event, and 23% were new visitors, quantifying the event's real value beyond attendance. The same A/B measurement methodology applies to events in any physical space.
Can performance be compared across shopping malls?
Yes. Flame's portfolio dashboard allows comparing normalized metrics across shopping malls, controlling for size, location, mall type, and seasonality. Comparable KPIs include: footfall per square meter, parking capture rate, average visit time, traffic distribution by floor, and event conversion rate. A leading operator compares its 10 shopping malls with Flame to identify best practices, detect performance anomalies, and allocate marketing budgets based on objective data. Anonymous benchmarks from the database of more than 50 Flame shopping malls allow comparing your mall against the market. This level of competitive intelligence without personal data is exclusive to platforms with scale like Flame, which also benchmarks retail stores and other physical spaces in its network.
What reports do investors and owners receive?
Flame generates executive reports designed for investors and commercial real estate asset owners. Standard reports include: monthly and annual footfall trends (leading indicator of mall health), year-over-year comparisons (quantified growth or decline), zone performance (identifying areas needing repositioning), marketing campaign impact (ROI of promotional investments), and market benchmarks (relative performance against comparable malls). Reports are exported to PDF, Excel, or connected via API to real estate reporting platforms. Major real estate consultancies use Flame data in their asset valuation reports, where footfall trends are a key indicator of commercial asset value.
How does it help optimize the tenant mix?
Flame's analytics reveals how traffic flows between different store types and which tenant combinations generate the most cross-traffic. Key data for mix optimization: flow analysis by category (do fashion visitors then go to food service?), anchor effect (how much traffic each anchor tenant generates for surrounding stores), cold-zone analysis (low-traffic areas needing a destination tenant), and category synergy (which store types benefit from proximity). When a large shopping mall needed to reposition a floor with high tenant turnover, Flame data showed that food-service tenants on that floor generated 3x more cross-traffic than fashion stores, guiding the re-leasing strategy. Similar zone-flow analysis helps optimize space planning in other physical spaces.

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Discover the power of Flame in just 20 minutes and learn how it can improve the results of your organization.