How to Build a Multi-Domain SEO Share of Voice Analyzer

Simple Summary

This project creates a powerful data visualization tool to analyze and compare website ranking performance across multiple domains and competitors using STAT API data.

Product Requirements Document (PRD)

Goals:

• Create a data visualization tool to analyze share of voice for multiple domains and competitors
• Provide insights into keyword performance for top-ranking and underperforming keywords
• Enable easy comparison of SEO performance across different websites and competitors

Target Audience:

• SEO professionals
• Digital marketers
• Website owners managing multiple domains

Key Features:

1. Data retrieval from STAT API for multiple domains and competitors
2. Keyword categorization based on ranking performance (top 10 vs. others)
3. Share of voice calculation and visualization using line graphs
4. 30-day historical data analysis
5. Competitor comparison across all tracked websites
6. User-friendly interface for selecting domains and date ranges

User Requirements:

• Ability to select specific domains for analysis
• Option to choose custom date ranges within the 30-day period
• Easy-to-understand visualizations of share of voice data
• Capability to export data and graphs for reporting

User Flows

1. Data Retrieval and Processing:

   • User inputs STAT API credentials
   • System retrieves data for all domains and competitors
   • Data is processed and categorized based on keyword performance

2. Visualization Selection:

   • User selects domains to analyze
   • User chooses date range (up to 30 days)
   • System generates line graphs for share of voice

3. Analysis and Export:

   • User explores interactive visualizations
   • User can toggle between top-performing and underperforming keywords
   • User exports data or graphs for further analysis

Technical Specifications

Frontend:

• React.js for building the user interface
• Chart.js or D3.js for creating interactive line graphs

Backend:

• Python with Flask for API development and data processing
• PostgreSQL for storing retrieved and processed data

Data Retrieval:

• Python requests library for interacting with STAT API
• Celery for handling background tasks and scheduled data updates

Data Processing:

• Pandas for data manipulation and analysis
• NumPy for numerical computations

Authentication:

• JWT for secure API access

Hosting:

• AWS EC2 for application hosting
• AWS RDS for database hosting

API Endpoints

1. /api/domains - GET: Retrieve list of available domains
2. /api/competitors - GET: Retrieve list of competitors for a given domain
3. /api/share-of-voice - POST: Get share of voice data for selected domains and date range
4. /api/export - POST: Generate exportable data file

Database Schema

1. Domains

   • id (PK)
   • name
   • stat_site_id
   • stat_project_id

2. Keywords

   • id (PK)
   • domain_id (FK)
   • keyword_text
   • stat_keyword_id
   • market

3. Rankings

   • id (PK)
   • keyword_id (FK)
   • domain_id (FK)
   • competitor_id (FK)
   • date
   • position

4. Competitors

   • id (PK)
   • domain_id (FK)
   • name
   • stat_competitor_id

File Structure

Implementation Plan

1. Project Setup (1-2 days)

   • Set up development environment
   • Initialize Git repository
   • Create project structure

2. Backend Development (5-7 days)

   • Implement STAT API integration
   • Develop data retrieval and processing logic
   • Create database models and migrations
   • Build API endpoints

3. Frontend Development (5-7 days)

   • Design and implement user interface
   • Integrate Chart.js or D3.js for visualizations
   • Develop domain and date selection components

4. Data Processing and Visualization (3-4 days)

   • Implement share of voice calculations
   • Create line graph generation logic
   • Optimize data processing for performance

5. Testing and Refinement (3-4 days)

   • Conduct unit and integration tests
   • Perform end-to-end testing
   • Refine user interface and experience

6. Documentation and Deployment (2-3 days)

   • Write user and technical documentation
   • Prepare deployment scripts
   • Deploy to production environment

Deployment Strategy

1. Set up AWS EC2 instance for application hosting
2. Configure AWS RDS for PostgreSQL database
3. Use Docker for containerization of backend and frontend
4. Implement CI/CD pipeline using GitHub Actions
5. Use Nginx as a reverse proxy and for serving static files
6. Configure SSL certificates for secure communication
7. Implement automated backups for the database
8. Set up monitoring and logging using AWS CloudWatch

Design Rationale

The chosen tech stack (React, Python, PostgreSQL) offers a balance of performance, scalability, and ease of development. React provides a responsive frontend, while Python's data processing capabilities are ideal for handling STAT API data. PostgreSQL offers robust storage for time-series ranking data.

The decision to use line graphs aligns with the user's preference and is well-suited for visualizing share of voice trends over time. The 30-day analysis period provides a good balance between historical context and manageable data volume.

Separating top-performing and underperforming keywords allows for focused analysis, helping users identify areas of strength and opportunities for improvement in their SEO strategies.