CX Teknoloji
TR·EN·AR
PRK-02 · Retail Analytics

Demographic Analysis

Measure the age and gender mix of your visitors, anonymously.

95.4%
Demographic measurement accuracy
6
Age band breakdown
Anonymous
No identity records kept

Who a store speaks to is often an assumption. Collections, window displays and music are built around that assumption.

Demographic analysis measures the age band and gender mix of visitors anonymously; no identity record is kept and no facial image is stored. The result shows the gap between the intended and the actual audience — and that is usually where the most efficient correction to a marketing budget begins.

How it works

01 / DETECT

Visitor located

A person entering the frame is detected and given a temporary anonymous ID.

02 / CLASSIFY

Age and gender

Statistical classification is applied; no personal record is created.

03 / AGGREGATE

Distribution produced

Hourly and daily distributions are reported, not individual data.

The gap between intended and actual audience

The difference between the audience a brand targets and the one that walks in is often the reason for unexplained variance in campaign performance. Examined hourly, the distribution shows that two entirely different customer profiles use the same store during the day.

Age band distribution · last 30 days
18–2414%
25–3431%
35–4435%
45–5412%
55+8%

The 35–44 band is above expectation; revisiting tone of voice and product placement for this profile lifts conversion.

Female visitor share by hour · morning 71% / evening 48%
1071%
1268%
1462%
1657%
1852%
2048%

Because morning and evening profiles differ, the window display and staff approach should differ too.

Use cases

Retail

Collection planning

Product mix based on the real audience.

Mall

Tenant analysis

Visitor profile per floor.

Advertising

Screen content

Content that changes by hour.

Chain

Regional differences

Profile comparison across stores.

Technical requirements

CameraNear face-level angle; at the entrance or the head of an aisle
DataNo facial images stored, no identity matching
ComplianceGDPR/KVKK-compliant configuration with privacy notice support
OutputAge band and gender distribution, hourly breakdown
IntegrationBI tools, CRM segmentation, REST API

Frequently asked questions

How does Demographic Analysis work?

Who a store speaks to is often an assumption. Collections, window displays and music are built around that assumption.

Are our existing cameras suitable for this solution?

Required camera placement: Near face-level angle; at the entrance or the head of an aisle. Before installation we assess your camera inventory free of charge and report which points are suitable and, if needed, which camera should be added.

How accurate is it in the field?

Measured accuracy: 95.4%. The 35–44 band is above expectation; revisiting tone of voice and product placement for this profile lifts conversion. Thresholds are calibrated on your own site during the pilot.

Which systems does it integrate with?

BI tools, CRM segmentation, REST API. Events are published over REST API and MQTT, so it connects to your existing MES, ERP, VMS and alarm infrastructure.

Is it compliant with KVKK, Türkiye's data-protection law?

Footage is processed on an edge server inside your facility; raw video is not sent to the cloud. Facial recognition is not used; analytics outputs are anonymous and event clips are deleted automatically when the defined retention period ends.

See this solution on your own site
Let's test it with your existing camera in a 15-minute demo call.
Book a 15-min demo

Other solutions in Retail Analytics

PRK-01 · 96.2%
People Counting & Visitor Analytics
Count visitors with high accuracy and calculate conversion from real data.
PRK-03 · Heatmap
Heatmap & Route Analysis
See where customers linger — and where they never go.
PRK-04 · Queue
Queue & Checkout Management
Route staff the moment the queue threshold is passed.

Technical articles on this topic (in Turkish)

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