Case Study: Venue Demographics

The Challenge

Problem

Hospitality venues (restaurants, bars, hotels) lack real-time visibility into their customer demographics. Decisions about marketing, staffing, and operations are based on intuition rather than data.

No way to know who's actually visiting the venue
Marketing campaigns can't be targeted effectively
Staffing decisions are based on guesswork
No data to optimize promotions or menu offerings
Competitor analysis is impossible without footfall data

The Solution

Solution

Built a computer vision platform that analyzes camera feeds in real-time using DeepFace. The system detects faces, estimates demographics (age, gender), analyzes emotions, and generates actionable business intelligence — all while respecting privacy by not storing individual face data.

Processing Pipeline

Input

Camera Feed

→

Detection
DeepFace

→

Analysis
Age/Gender/Emotion/Ethnicity

→

Output

Insights API

Core Capabilities

Multi-Face Detection

Process 8+ faces simultaneously in a single frame. Handles crowded venues with high accuracy.

Demographic Analysis

Age estimation, gender detection, and ethnicity classification for comprehensive customer profiling.

Emotion Detection

Analyze customer mood — happy, neutral, surprised. Measure satisfaction in real-time.

Business Intelligence

AI-generated recommendations for marketing, staffing, and operations based on demographic trends.

Sample Analysis Output

Crowd Demographics (8 faces detected)

62%

Female

38%

Male

28

Avg Age

75%

Happy

          
          
          
          API Response
        

{
  "faces_detected": 8,
  "demographics": {
    "age_groups": {
      "18-24": 3,
      "25-34": 4,
      "35-44": 1
    },
    "gender": {
      "female": 5,
      "male": 3
    },
    "ethnicity": {
      "asian": 4,
      "white": 2,
      "latino_hispanic": 1,
      "middle_eastern": 1
    }
  },
  "emotions": {
    "happy": 6,
    "neutral": 2
  },
  "recommendations": [
    "Consider extending ladies night promotion",
    "Peak demographic: Young professionals (25-34)",
    "Diverse customer base - consider multilingual marketing",
    "High satisfaction detected - good time for upselling"
  ]
}
        

Technology Stack

DeepFace OpenCV Python Flask SQLAlchemy Gunicorn PostgreSQL Redis Docker

Results

8+

Faces processed simultaneously

<2s

Analysis time per frame

GDPR

Privacy compliant

The system processes camera feeds in real-time without storing individual face data, ensuring GDPR compliance while delivering actionable business intelligence to venue operators.

Venue Demographics