01
See what's happening
Configurable dashboards and KPIs by store, area and period, with the full customer journey from heatmaps to time spent in each zone.
Store decisions made on data, not on instinct.
TRISON Analytics applies artificial vision to physical spaces, turning everyday store activity into decision-ready data on footfall, conversion, queues and dwell time. It runs on the cameras you already have and is built around data protection regulation.
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Areas of insight
0
Images stored
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Platform, from pilot store to rollout
The challenge
Layout, staffing and service still run on gut feeling.
Layout, staffing and the in-store experience are decided every week across a retail network, usually on experience and gut feeling. Footfall reports arrive late, conversion is estimated, and what happens between the door and the till is invisible.
The information already exists. Security cameras record every visit, every queue and every route through the store, and it goes unused.
Cameras and sensors are already capturing store activity. TRISON Analytics turns it into data a store team can act on.
What it does
From what the cameras see to what the team does.
02
Act on it
Rule-based alerts and operational triggers turn detected patterns, such as long queues or overcrowding, into immediate action.
03
Stays compliant
On-premise anonymisation, no facial recognition, no image storage and staff excluded from statistics, built around data protection regulation.
04
Fits your setup
Works with existing CCTV or new IP cameras, on edge hardware with cloud management. Nothing already installed needs replacing.
05
Scales across locations
Every store, brand and account managed from one place, from a pilot store to a multi-country rollout.
06
Implementable in TRISON Spaces
Alerts reach TRISON Spaces through an API, so what the cameras detect can change what screens show and what the store sounds like.
Insights
What the platform tells you.
Thirteen areas of insight, grouped by the decision they support. Each one can be configured by store, zone and period.
In action
From insight to action, in one interface.
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Dashboard
Live view of traffic, waiting time, conversion and zone performance, by store, area and period.
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Alerts
Rule-based alerts turn detected patterns into an immediate response, with the reason behind each alert explained.
TRISON Spaces
Implementable in TRISON Spaces.
TRISON Analytics works alongside TRISON Spaces, TRISON's own content management platform. Alerts are sent through an API, so a pattern detected in store can trigger a change of content on screen.
Signage content and playlists are managed in TRISON Spaces, and their effect on dwell time and audience is measured back in TRISON Analytics. Screens with a measurable audience become media space that can be offered to brand partners.
VISIT TRISON SPACESWhat changes
What a store team gets.
Staff hours follow real demand, slot by slot, store by store.
Queues and drops in footfall are spotted while they happen, not in next month's report.
Every store is compared on the same metrics, from one screen.
Privacy is built in: no faces, no stored images, no staff in the figures.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCHPlatform / Insights
Thirteen areas of insight, grouped by the decision they support.
The platform does not stop at counting. It reads the data and says what it means, in plain language, so a store manager knows what to change today.
01
Traffic & timing
Footfall by store, day and time slot, the first and last hours of opening, and alerts the moment something looks wrong.
- Foot traffic
Visitors by store, day and time slot. - Opening hours
Real demand in the first and last hours of the day. - Real-time alerts
Unusual drops or peaks, flagged as they happen.
Conversion
Conversion by store and by hour, the moments when people leave without buying, and groups counted as the buying units they are.
- Conversion
Visitors who enter versus those who reach the checkout. - Exits without purchase
When and where visitors leave without buying. - Visit groups
Couples and families counted as one buying unit.
In-store behaviour
How long visits last, where people go and where they stop, how long they wait, and what happens in the fitting rooms.
- Dwell time
How long visits last, by store and by zone. - Paths and zones
Hot and cold areas, and how people move. - Queues
Waiting time and walk-aways at the tills. - Fitting rooms
How they are used and whether visits end at the checkout.
Operations & content
Staffing matched to real demand, stores compared on the same metrics, and the audience of every screen in the store.
- Staffing vs. footfall
Team size matched to real demand, anonymously. - Store comparisons
What better-converting stores do differently. - Screen and audio content
Audience per screen and the effect of each change.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCH01.1
Foot traffic
- What it measures
- Entries by store, day and time slot, with enough history to compare weeks and spot a trend before it settles in.
- Example insight
Weekday mornings are losing visitors while weekends hold steady, and the drop is concentrated on two days.
- What you can act on
- Rebalance staff hours and move promotions towards the slots that are growing.
01.2
Opening hours
- What it measures
- Footfall in the first and last hours of opening, including people waiting outside before the doors open.
- Example insight
People are already waiting outside before Saturday opening, while the last half hour on weekdays barely sees a visitor.
- What you can act on
- Adjust opening times and staffing at both ends of the day to the demand that is actually there.
01.3
Real-time alerts
- What it measures
- Live entries against the expected level for each slot, and conversion against its normal range, with rule-based thresholds.
- Example insight
Footfall at one store has been well below its usual level since mid-morning.
- What you can act on
- Check the entrance (door, lighting, access) the same day, not when the monthly report arrives.
Example insights are illustrative. Each client's insights are generated from its own data.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCH02.1
Conversion
- What it measures
- People who come in versus people who reach the checkout, by store and by hour, measured with a checkout line in the store itself.
- Example insight
The busiest slot of the week converts worst: more people come in and fewer of them reach the till.
- What you can act on
- Look at staffing and queues in that slot before drawing conclusions about footfall.
02.2
Exits without purchase
- What it measures
- When visitors leave without buying and what they did just before, such as joining the queue or using the fitting room.
- Example insight
Most non-buyers leave shortly after joining the checkout queue. Queue length, not interest, is driving these exits.
- What you can act on
- Treat the queue as the problem to fix, because the interest is already there.
02.3
Visit groups
- What it measures
- Couples, families and groups detected as one buying unit instead of several individuals, so conversion is read on real decisions.
- Example insight
Weekend traffic is mostly groups. Counted as buying units, the weekend converts better than it looks.
- What you can act on
- Read conversion on real buying units before changing anything in the store.
Example insights are illustrative. Each client's insights are generated from its own data.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCH03.1
Dwell time
- What it measures
- Visit length by store and by zone, split between visitors who buy and those who do not.
- Example insight
Visitors who stay past a certain point are far more likely to buy, while most non-buyers leave within the first minutes.
- What you can act on
- Give people reasons to stay, including the content and music managed in TRISON Spaces, and measure the effect here.
03.2
Paths and zones
- What it measures
- Hot and cold zones shown as heatmaps, how people move through the store, and where they stop.
- What you can act on
- Place key categories and screens where people actually go, and give cold areas a reason to be visited.
03.3
Queues
- What it measures
- Queue length, waiting time and walk-aways at tills and fitting rooms, by time slot, with thresholds that trigger alerts.
- Example insight
Waiting time stays short all week except on one evening, when it peaks.
- What you can act on
- Open an extra till or reassign staff only in the slots that need it.
03.4
Fitting rooms
- What it measures
- Fitting room use and whether those visits end at the checkout.
- Example insight
Two stores with the same product mix turn fitting room visits into purchases at very different rates, and the better one has staff assigned to the area at weekends.
- What you can act on
- Copy what works in one store to the rest of the network.
Example insights are illustrative. Each client's insights are generated from its own data.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCH04.1
Staffing vs. footfall
- What it measures
- Visitors per person on the floor, hour by hour, using anonymous in-store headcount. No personal staff data is processed.
- Example insight
Quiet weekday mornings carry more people on the floor than they need, while weekend afternoons run short.
- What you can act on
- Move hours to where the demand is, without adding cost.
04.2
Store comparisons
- What it measures
- The same KPIs side by side for comparable stores: footfall, conversion, dwell time and queues.
- Example insight
Two stores of similar size and footfall convert differently, and the better one has shorter fitting room waits.
- What you can act on
- Find out what the better store does differently and roll it out.
04.3
Screen and audio content
- What it measures
- Audience per screen and occupancy around each display, shared with TRISON Spaces through an API.
- Example insight
A static image on the entrance screen reaches more visitors than the video loop on the same screen.
- What you can act on
- Adjust the content from TRISON Spaces, and offer screens with a measurable audience to brand partners as retail media.
Example insights are illustrative. Each client's insights are generated from its own data.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCHPlatform / How it works
Built on the cameras you already have.
Video is processed in the store, only anonymous data leaves it, and everything is configured and managed from the cloud.
01
Capture
Existing CCTV or new IP cameras, including 360° and fisheye models. Cameras already installed are discovered and added from the platform.
02
Process on site
An edge server in each store processes video locally and generates anonymised KPIs, metrics and events. No images leave the store.
03
Use the data
Dashboards, alerts and workflows in the platform, plus output APIs, event messaging and exports to BI tools or a corporate data lake.
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Privacy and governance
Privacy by design, from the first camera.
- Anonymisation configured and applied on site, before any data leaves the store.
- No facial or biometric recognition.
- No image storage.
- Staff excluded from statistics.
- AI model auditing and traceability.
- Role-based data visibility by organisation, brand, space and device.
Configuration
The team sets the rules, not the vendor.
01
Spaces
Doors, zones and floors defined for each store, with traffic lines, queue areas and areas without visual coverage configured visually.
02
KPIs
KPIs selected by store, area and period, with operational objectives and thresholds, comparisons between stores and views by role.
03
Alerts
A rules and triggers editor, an operational alert centre and action workflows, with an explanation of why each AI-generated alert was raised.
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System health
Every camera and edge device, monitored.
Camera and edge device status and coverage are monitored zone by zone, so a disconnected camera is spotted before it leaves a gap in the data.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCHPlatform / Scale
Built to scale across every location.
One platform for every store, brand and country, managed from one place.
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Multi-site management
Every store, one view.
Each physical space is tracked individually, by brand, by city or by status, so a multi-store operation is managed from a single screen instead of one dashboard per location.
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Multi-brand ready
One structure for every brand you run.
Brands, formats and store concepts are organised under a single organisation, each with its own spaces, plans and permissions. No separate contract or dashboard per brand.
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Centralised account view
Every account, one list.
Every organisation, its plan and its current status live in one searchable list, without reconciling separate tools or spreadsheets.
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From pilot to rollout
Three tiers, one platform.
Plan tiers (PoC, Standard and Unlimited) set clear limits on spaces, devices and brands. The same platform takes a pilot store to a multi-country rollout without switching systems.
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Single source of truth
Everything about the account, always current.
Business details, contacts and the contracted plan for each organisation are kept in one record, with no side documents or outdated spreadsheets.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCHPlatform / Compare
Software on your cameras, not a box at every door.
How TRISON Analytics compares with the approach most stores still use: dedicated counting sensors at the door.
| Capability | Dedicated counting sensors | TRISON Analytics |
|---|---|---|
| Hardware | A device bought and installed at every entrance. | Runs on existing CCTV and IP cameras, with any video stream. No lock-in. |
| What is measured | Mostly entries and exits. | Entries plus dwell time, zones, queues, groups and conversion. |
| Staff | Counted with visitors unless they are tagged. | Excluded from statistics automatically. |
| Configuration | Usually set up and changed by the supplier. | Full self-configuration: zones, rules, KPIs and alerts. |
| From data to action | Reports to read after the fact. | Real-time alerts, workflows and operational actions. |
| Privacy | Depends on the device. | Anonymisation at source, no image storage, AI auditability. |
| Integration | Exports from a closed system. | Output APIs, BI and data lake integration, multi-tenant SaaS. |
| In-store content | Not connected. | Implementable in TRISON Spaces: alerts and audience shared through an API. |
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCHPlatform / FAQ
Frequently asked questions.
Do we need new cameras?
No. TRISON Analytics works with existing CCTV and with new IP cameras, including 360° and fisheye models. Video is processed by an edge server in each store, managed from the cloud.
Does it use facial recognition?
No. There is no facial or biometric recognition and no image is stored. Video is anonymised on site, and only anonymous KPIs, metrics and events leave the store.
Are staff counted as visitors?
No. Staff are excluded from the statistics, so footfall and conversion reflect customers only.
How is conversion measured?
With a checkout line configured in the store: the platform compares the people who come in with the people who reach the checkout. No till system integration is needed.
Can the data reach our other systems?
Yes. Data leaves the platform through output APIs, event messaging and exports to BI tools or a corporate data lake. Alerts can also be sent to TRISON Spaces through its API.
Can we start with a single store?
Yes. The platform has three plan tiers (PoC, Standard and Unlimited), so a pilot store and a multi-country rollout run on the same system.
We run several brands. Does that need separate contracts?
No. Brands, formats and store concepts sit under one organisation, each with its own spaces, plans and permissions.
Who can see the data?
Access is role-based, by organisation, brand, space and device, so each person sees what their role needs.
Get started
Start with one store. Scale to the whole network.
A pilot runs on the cameras the store already has, and the same platform takes it to every location, brand and country.
GET IN TOUCH