Digital Signage Audience Analytics
Understand Your Audience
Audience analytics transforms digital signage from blind broadcasting to measured communication. Understand who's watching, how long they engage, and what content resonates. Make data-driven decisions to optimize content, prove ROI, and deliver targeted experiences.
Analytics Overview
The Analytics Pyramid
┌─────────────────────────────────────────────────────────────────┐
│ ANALYTICS MATURITY MODEL │
│ │
│ ┌─────┐ │
│ / \ OPTIMIZATION │
│ / AI \ Self-optimizing content │
│ / Predictive\ Personalized experiences │
│ /─────────────\ │
│ / \ ATTRIBUTION │
│ / Attribution \ Connect exposure to │
│ / & Conversion \ business outcomes │
│ /─────────────────────\ │
│ / \ ENGAGEMENT │
│ / Attention & Dwell \ Measure how people │
│ / Interaction Tracking \ engage with content │
│ /─────────────────────────────\ │
│ / \ DEMOGRAPHICS │
│ / Demographic Detection \ Understand WHO │
│ / Audience Composition \ is watching │
│ /─────────────────────────────────────\ │
│ / \ TRAFFIC │
│ / People Counting \ Count viewers │
│ / Traffic Flow Analysis \ and traffic │
│ /─────────────────────────────────────────────\ │
│ / \ PROOF OF PLAY│
│ / Content Playback Logging \ What played │
│ / Basic CMS Reporting \ when │
│/─────────────────────────────────────────────────────\ │
│ │
│ ◄──────────────────────────────────────────────────────────► │
│ Basic Advanced │
│ │
└─────────────────────────────────────────────────────────────────┘
Key Metrics Framework
| Category | Metrics | Purpose |
|---|---|---|
| Exposure | Impressions, reach, frequency | Delivery measurement |
| Attention | Views, dwell time, gaze | Engagement measurement |
| Audience | Demographics, traffic patterns | Targeting validation |
| Engagement | Interactions, responses | Content effectiveness |
| Outcomes | Conversions, lift, ROI | Business impact |
People Counting and Traffic Analysis
Counting Technologies
| Technology | Accuracy | Cost | Privacy |
|---|---|---|---|
| Infrared beam | 90-95% | Low | High (anonymous) |
| Thermal imaging | 92-97% | Medium | High (no faces) |
| Video analytics | 95-99% | Medium | Configurable |
| WiFi/Bluetooth | 70-85% | Low | Medium |
| Stereo vision | 97-99% | Medium-High | Configurable |
| LiDAR | 98-99% | High | High (no images) |
Traffic Metrics
| Metric | Definition | Application |
|---|---|---|
| Total traffic | People passing through area | Baseline measurement |
| Direction flow | Movement patterns | Store layout optimization |
| Dwell zones | Where people linger | Engagement hotspots |
| Queue length | People waiting | Service optimization |
| Conversion rate | Entrants / passers-by | Store performance |
| Peak times | High traffic periods | Content scheduling |
Traffic Flow Visualization
┌─────────────────────────────────────────────────────────────────┐
│ RETAIL TRAFFIC HEAT MAP │
│ │
│ Store Entrance │
│ ════════════════════════════════════════════ │
│ ↓↓↓↓ │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │█████████│ │████ │ │██ │ │
│ │█████████│ ←──→ │███ │ ←──→ │█ │ │
│ │█████████│ │██ │ │ │ │
│ │ Display │ │ Aisle 1 │ │ Aisle 2 │ │
│ └─────────┘ └─────────┘ └─────────┘ │
│ │ │
│ └────────────────────┐ │
│ ↓ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │███████████████████ ←── High Dwell Zone │ │
│ │███████████████████ │ │
│ │ Checkout ───────────────────────────── │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ Legend: █████ High traffic ███ Medium █ Low │
│ │
│ Insights: │
│ • 78% of entrants pass the entrance display │
│ • Average dwell at entrance: 4.2 seconds │
│ • Peak traffic: 12-2 PM weekdays, 11 AM-3 PM weekends │
│ │
└─────────────────────────────────────────────────────────────────┘
Demographic Detection
Detectable Attributes
| Attribute | Detection Method | Typical Accuracy |
|---|---|---|
| Presence | Face detection | 99%+ |
| Age group | Facial analysis | 80-90% |
| Gender | Facial features | 90-95% |
| Attention | Gaze direction | 85-95% |
| Emotion | Expression analysis | 70-85% |
| Glasses/sunglasses | Object detection | 95%+ |
| Group composition | Multi-face analysis | 90%+ |
Age Group Classification
| Age Group | Range | Visual Indicators |
|---|---|---|
| Child | 0-12 | Facial proportions |
| Teen | 13-17 | Skin texture, proportions |
| Young Adult | 18-34 | Skin elasticity |
| Adult | 35-54 | Facial lines, features |
| Senior | 55+ | Wrinkles, hair color |
Audience Composition Report
┌─────────────────────────────────────────────────────────────────┐
│ AUDIENCE COMPOSITION - WEEK OF FEB 1 │
│ │
│ TOTAL VIEWERS: 24,567 │
│ │
│ AGE DISTRIBUTION GENDER DISTRIBUTION │
│ ┌───────────────────────┐ ┌───────────────────────┐ │
│ │ Child ████ 8% │ │ Male ████████ 52% │ │
│ │ Teen ██████ 12% │ │ Female ███████ 48% │ │
│ │ 18-34 ██████████ 35%│ └───────────────────────┘ │
│ │ 35-54 ████████ 28% │ │
│ │ 55+ ██████ 17% │ ATTENTION RATE │
│ └───────────────────────┘ ┌───────────────────────┐ │
│ │ Viewers who │ │
│ DAY OF WEEK │ looked at display: 62% │ │
│ ┌───────────────────────┐ │ │ │
│ │ Mon ████████████ 3,421│ │ Avg dwell: 4.8 sec │ │
│ │ Tue ███████████ 3,156 │ │ │ │
│ │ Wed ████████████ 3,578│ │ Engaged (>3s): 41% │ │
│ │ Thu ███████████ 3,234 │ └───────────────────────┘ │
│ │ Fri █████████████ 4,012│ │
│ │ Sat █████████████ 4,234│ TOP HOURS │
│ │ Sun ██████████ 2,932 │ 12-1 PM ████████████ │
│ └───────────────────────┘ 5-6 PM ██████████ │
│ 11-12 AM █████████ │
│ │
└─────────────────────────────────────────────────────────────────┘
Attention and Engagement Measurement
Attention Metrics
| Metric | Definition | Calculation |
|---|---|---|
| Opportunity to See (OTS) | People in viewing area | Proximity detection |
| Viewers | People who looked | Gaze detection |
| Attention Rate | % who looked | Viewers / OTS |
| Dwell Time | Duration looking | Time tracking |
| Glance | Brief look (under 1 sec) | Short attention |
| View | Extended look (1-3 sec) | Moderate attention |
| Engagement | Sustained look (>3 sec) | High attention |
Gaze Tracking
┌─────────────────────────────────────────────────────────────────┐
│ GAZE TRACKING ANALYSIS │
│ │
│ Display Layout Attention Heat Map │
│ ┌─────────────────────────┐ ┌─────────────────────────┐ │
│ │ │ │██████████ │ │
│ │ HEADLINE │ │█████████████ │ │
│ │ │ │████████████████ │ │
│ │ ┌─────────────────┐ │ │ │ │
│ │ │ │ │ │ ██████████████████ │ │
│ │ │ MAIN IMAGE │ │ │ ████████████████████ │ │
│ │ │ │ │ │ ██████████████████ │ │
│ │ └─────────────────┘ │ │ │ │
│ │ │ │ ████████ │ │
│ │ CTA BUTTON │ │ ███████████ │ │
│ │ │ │ ████████ │ │
│ └─────────────────────────┘ └─────────────────────────┘ │
│ │
│ INSIGHTS: │
│ • Headline captures 89% of initial glances │
│ • Main image holds attention longest (avg 2.3 sec) │
│ • CTA button seen by only 34% of viewers │
│ • Recommendation: Move CTA higher, increase size │
│ │
└─────────────────────────────────────────────────────────────────┘
Engagement Scoring
| Score | Dwell Time | Behavior | Interpretation |
|---|---|---|---|
| 1 - Glance | Under 1 second | Quick look | Low interest |
| 2 - Notice | 1-2 seconds | Brief attention | Awareness |
| 3 - View | 2-4 seconds | Sustained look | Interest |
| 4 - Engage | 4-8 seconds | Active watching | High interest |
| 5 - Immerse | >8 seconds | Full attention | Very high interest |
Content Performance Analysis
| Content | Views | Avg Dwell | Engagement Score |
|---|---|---|---|
| Product Video A | 3,245 | 6.2s | 4.1 |
| Promotional Banner | 5,678 | 2.8s | 2.9 |
| Brand Story | 1,234 | 8.4s | 4.5 |
| Price Display | 4,567 | 3.1s | 3.2 |
| Social Wall | 2,345 | 5.7s | 3.8 |
Impression Measurement
Impression Calculation Models
| Model | Formula | Use Case |
|---|---|---|
| Play-based | Content plays counted | Basic reporting |
| Traffic-based | Plays × avg traffic | Standard DOOH |
| Attention-based | Plays × viewers | Verified impressions |
| Engagement-based | Plays × engaged viewers | Premium inventory |
Industry Standard: Geopath Model (US)
┌─────────────────────────────────────────────────────────────────┐
│ GEOPATH IMPRESSION CALCULATION │
│ │
│ Weekly Impressions = DEC × Circulation × VAC × Duration Factor │
│ │
│ Where: │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ DEC (Daily Effective Circulation) │ │
│ │ = Number of people with opportunity to see per day │ │
│ │ Based on: Traffic counts, travel patterns, visibility │ │
│ └─────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Circulation │ │
│ │ = Vehicles + pedestrians passing the display │ │
│ │ Source: Traffic studies, mobile data │ │
│ └─────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ VAC (Visibility Adjustment Coefficient) │ │
│ │ = Likelihood of noticing the display │ │
│ │ Factors: Size, angle, distance, illumination │ │
│ └─────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Duration Factor │ │
│ │ = Ad spot length / loop length │ │
│ │ Example: 10 sec spot in 60 sec loop = 16.7% │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ Example: Billboard on highway │
│ DEC: 50,000 | Circulation: 75,000 | VAC: 0.6 | Duration: 1/6 │
│ Weekly Impressions = 50,000 × 0.6 × (1/6) × 7 = 35,000 │
│ │
└─────────────────────────────────────────────────────────────────┘
Verified vs. Modeled Impressions
| Type | Method | Confidence |
|---|---|---|
| Modeled | Traffic data + assumptions | Medium |
| Measured | Camera-based detection | High |
| Verified | Third-party audited | Highest |
Analytics Platforms and Tools
Leading Analytics Solutions
| Solution | Strengths | Best For |
|---|---|---|
| Quividi | Computer vision pioneer | Retail, DOOH |
| AdMobilize | AI-powered, real-time | High-traffic venues |
| Advertima | Deep learning, privacy-first | Retail analytics |
| Linkett | Affordable, SaaS | SMB signage |
| Intel RealSense + Custom | Depth sensing, DIY | Custom deployments |
| RetailNext | Retail-focused, comprehensive | Retail chains |
Feature Comparison
| Feature | Quividi | AdMobilize | Advertima |
|---|---|---|---|
| People counting | ✓ | ✓ | ✓ |
| Demographics | ✓ | ✓ | ✓ |
| Attention tracking | ✓ | ✓ | ✓ |
| Emotion detection | ✓ | ✓ | Limited |
| Path analysis | ✓ | ✓ | ✓ |
| Real-time triggers | ✓ | ✓ | ✓ |
| Edge processing | ✓ | ✓ | ✓ |
| Privacy compliance | GDPR | GDPR | GDPR |
| Starting price | $$$ | $$ | $$$ |
Integration with CMS
| Integration Type | Description |
|---|---|
| API | Push/pull analytics data |
| Real-time triggers | Change content based on audience |
| Reporting | Combined playback + audience reports |
| Optimization | AI-driven content selection |
Privacy and Compliance
Privacy-Preserving Analytics
| Approach | Implementation | Trade-off |
|---|---|---|
| Edge processing | All analysis on-device | Higher hardware cost |
| Aggregation | Only store statistics | Less granular data |
| Anonymization | No facial recognition storage | Can't track individuals |
| Consent-based | Opt-in for detailed tracking | Lower sample size |
| Synthetic data | Modeled from samples | Privacy vs. accuracy |
Compliance Framework
┌─────────────────────────────────────────────────────────────────┐
│ PRIVACY COMPLIANCE CHECKLIST │
│ │
│ DATA COLLECTION │
│ ☐ No personally identifiable information (PII) collected │
│ ☐ No facial recognition templates stored │
│ ☐ Raw video frames deleted immediately after processing │
│ ☐ Edge processing - data stays on device │
│ ☐ Aggregated statistics only transmitted │
│ │
│ TRANSPARENCY │
│ ☐ Signage indicating analytics in use │
│ ☐ Privacy policy available │
│ ☐ Data controller identified │
│ ☐ Purpose of data collection explained │
│ │
│ DATA SECURITY │
│ ☐ Encrypted transmission (TLS 1.2+) │
│ ☐ Encrypted storage (AES-256) │
│ ☐ Access controls and audit logging │
│ ☐ Regular security audits │
│ │
│ DATA RETENTION │
│ ☐ Retention period defined (e.g., 90 days) │
│ ☐ Automatic deletion after retention period │
│ ☐ No sale of data to third parties │
│ │
│ REGIONAL COMPLIANCE │
│ ☐ GDPR (EU) - Legitimate interest or consent │
│ ☐ CCPA (California) - Opt-out mechanism │
│ ☐ BIPA (Illinois) - No biometric data storage │
│ ☐ Local regulations reviewed │
│ │
└─────────────────────────────────────────────────────────────────┘
Analytics ROI
Calculating Analytics Value
| Benefit | Measurement | Typical Value |
|---|---|---|
| Content optimization | Engagement lift | 15-30% improvement |
| Targeting accuracy | Relevance score | 20-40% improvement |
| Proof of performance | Client retention | Longer contracts |
| Operational efficiency | Scheduling optimization | 10-20% cost reduction |
| Sales attribution | Conversion tracking | Measurable ROI |
Investment Guidelines
| Deployment Size | Analytics Investment | Expected ROI |
|---|---|---|
| 1-10 screens | $200-500/mo | 2-3x in insights |
| 11-50 screens | $500-2,000/mo | 3-5x in optimization |
| 51-200 screens | $2,000-10,000/mo | 5-10x in efficiency |
| 200+ screens | Custom pricing | 10x+ at scale |
Implementation Best Practices
Camera Placement
| Factor | Recommendation |
|---|---|
| Height | 8-12 feet, angled down 15-30° |
| Distance | Cover viewing area (6-15 feet) |
| Field of view | 90-120° horizontal |
| Lighting | Avoid backlight, ensure face illumination |
| Resolution | 1080p minimum for face detection |
| Frame rate | 15+ FPS for tracking |
Deployment Checklist
- Define measurement objectives
- Select appropriate technology
- Ensure privacy compliance
- Install cameras with proper positioning
- Configure analytics platform
- Integrate with CMS
- Establish baseline metrics
- Set up reporting dashboards
- Train staff on data interpretation
- Schedule regular optimization reviews
Frequently Asked Questions
Next Steps
- AI in Digital Signage - Intelligent analytics
- Programmatic DOOH - Measured media buying
- Success Metrics - Business KPIs
- ROI Calculator - Prove value
Analytics specifications and accuracy figures reflect 2026 industry standards. Technology capabilities vary by vendor.