Privacy-First Web Analytics Dashboard

Product Idea · Intermediate · Python, API Design

Problem Statement

Website owners need analytics but Google Analytics raises serious privacy concerns — tracking cookies, personal data collection, and GDPR consent banners. Existing alternatives like Plausible are paid SaaS, and Umami lacks a pluggable analytics pipeline.

Proposed Solution

Build a lightweight, self-hosted web analytics dashboard that tracks page views, referrers, devices, and geographic patterns without cookies, personal data, or external scripts. A single JavaScript snippet sends anonymized events to a backend API.

Key Features

• No cookies — Tracks without setting any cookies
• Lightweight script — Under 1KB JavaScript
• Real-time dashboard — Live visitor counts
• Referrer tracking — Traffic source analysis
• Device analytics — Browser, OS, screen size
• Geographic data — Country-level distribution
• Goal tracking — Conversion events
• Self-hosted — Deploy on your own infrastructure

Implementation Approach

Phase 1: MVP (6-8 weeks)

Python FastAPI backend with PostgreSQL. JavaScript tracking snippet. React dashboard with real-time charts.

Phase 2: Core Analytics (4-6 weeks)

Geographic data, goal tracking, API access, weekly email summaries.

Phase 3: Self-Hosting (4-6 weeks)

Docker Compose deployment, data retention policies, multi-site support.

Technology Stack

• Python 3.11+ / FastAPI — Analytics API backend
• PostgreSQL — Time-series data storage
• Redis — Real-time counter caching
• React — Dashboard UI
• Docker — Self-hosting deployment

FAQ

Who can build this?

A Python developer comfortable with APIs, databases, and basic frontend work.

What makes this different from Plausible or Umami?

Plausible is a paid SaaS. Umami is JavaScript-focused and lacks a pluggable analytics pipeline. This tool is MIT-licensed, Python-native, and designed with a hook system for custom analytics logic.