Is the store attracting the audience the collection was designed for?
Compare visitor mix before and after product drops, campaigns and window changes — then read the pattern alongside footfall, dwell and sales data.
Customer demographics
Know who visits.Design what works.
Turn everyday retail video into aggregate age-band and gender-presentation insight — so merchandising, staffing and campaign teams can plan with evidence instead of instinct.
- Existing IP cameras
- Edge · On-prem · Cloud
- SDK & API
- Built in JapanComputer vision since 2007
- Camera-readyWorks with compatible CCTV
- Privacy-consciousAggregate, configurable reporting
- Enterprise integrationAPIs, exports and dashboards
From traffic to decisions
See the audience behind every visit.
Footfall tells you how many people arrived. Demographic analytics helps explain which audience segments came, when they came, and where engagement changed.
- 01
Plan the right assortment
Compare audience mix by store, zone, time of day and campaign period.
- 02
Schedule with confidence
Align service coverage with the customers who actually arrive.
- 03
Measure campaigns
See whether a window, a promotion or a media placement changed traffic quality.
Audience overviewSample data
- Example store
- Last 30 days
- All entrances
- Visitors analysed48,692Sample data
- Leading age band25–34Sample data
- Peak audience time17:00Sample data
Age-band distributionShare of estimates
Audience mixAggregate
- Group A 54%
- Group B 43%
- Uncertain 3%
Campaign windowAudience mix shiftedCompare periods, stores and zones
One operational view
Insight your retail teams can use.
Move from isolated detections to a shared view of customer mix across stores, entrances, zones and time periods.
- 01Age-band trends
Configurable ranges, so a change in audience shows up without presenting a false level of precision.
- 02Gender-presentation mix
Aggregate probabilistic estimates, held to a confidence threshold, with an uncertain category that stays visible.
- 03Time, zone and location comparison
Compare patterns by hour, day, store, entrance or campaign window.
- 04BI-ready data
Send aggregated events to dashboards, warehouses and reporting tools through APIs or exports.
Built around retail questions
Start with the decision you need to make.
Discuss fashion retail
Which audience segments engage with each counter and campaign?
Understand aggregate visitor mix across beauty zones and hours, and use it to refine promotions, service coverage and merchandising.
How does the audience change by entrance, floor and event?
Compare anonymised demographic patterns across zones and tenants to support leasing narratives, event planning and media sales.
Did the content reach the audience the media plan expected?
Measure aggregate audience composition and attention windows, with policy-controlled outputs and no identity required.
Camera to business intelligence
Fit the system to your stores — not the other way around.
Use compatible cameras and choose where processing and data live. Ayonix engineers review real footage, tune thresholds, and connect aggregated results to the systems your teams already open every morning.
Review your camera environmentResponsible by design
Useful insight.Appropriate boundaries.
A demographic output is an estimate, not a fact about a person. The deployment has to be designed around a documented purpose, the law that applies where it runs, and your own policy.
- 01
Aggregate by default
Report group-level patterns. Neither enrolment nor identity matching is required for this analysis.
- 02
Control retention
Configure image, event and metadata retention separately, around the minimum the operation actually needs.
- 03
Keep uncertainty visible
Use confidence thresholds, keep an uncertain category in the report, and validate on footage from the site itself.
- 04
Restrict the use
Do not use a demographic estimate on its own to decide eligibility, pricing, employment or anything else with a high impact on a person.
A practical evaluation path
Prove the value in your own stores.
No brochure can predict field performance. Start with representative video, a defined question and a controlled proof of concept.
- 01
Define the decision
Choose the business question, the zones, the audience labels and what a useful answer looks like.
- 02
Validate the video
Check camera position, lighting, face size, motion, crowding and coverage against the question.
- 03
Run a controlled PoC
Measure detection coverage, estimation quality, latency and whether the reporting answers the question.
- 04
Scale with governance
Connect the systems, document the policy, train the teams and keep monitoring performance site by site.
Does Ayonix identify individual shoppers?
Not for this analysis. Customer Demographics runs as aggregate analytics, and neither enrolling shoppers nor matching them against a database is required to report age-band and gender-presentation mix.
Can it use our existing CCTV cameras?
Often, yes. Whether a given camera is usable depends on its angle, the size of a face in frame, lighting, motion and compression. Ayonix reviews representative footage from your own site before a deployment is proposed.
How should we read the age and gender results?
As probabilistic estimates for aggregate analysis. Age is reported as a band rather than a number, gender as a gender-presentation estimate rather than a fact, and results below the confidence threshold stay in an uncertain category instead of being forced into a group.
Can the data reach our BI or retail systems?
Yes. Aggregated events can be delivered through APIs or scheduled exports into approved dashboards, warehouses and reporting workflows. Which systems, which fields and how often is settled during solution design.
Where can the processing run?
At the edge, on-premises, or in a cloud environment you have approved. The right choice depends on latency, camera count, network conditions, security review and where your data-governance policy allows the video to go.
Can we use this to set prices or decide who gets an offer?
No. A demographic estimate is not evidence about an individual, and Ayonix does not support using it on its own for eligibility, pricing, employment or any other decision with a high impact on a person. Use it for aggregate planning, and keep individual decisions with people and with data that was collected for that purpose.
Start with a real store
See what your cameras can reveal.
Share your camera layout, some sample footage and the question you need answered. We will help scope a measurable, privacy-conscious proof of concept.