We are planning to create an SEO SaaS platform - an improved version of the SEOGets.com service with extended functionality and a modular architecture, which:
- Collects data from Google through official APIs (Google Search Console, GA4)
- Authenticates users via Google OAuth
- Stores data in its own database
- Displays beautiful dashboards with graphs, tables, and metrics
Current stage: Pre-MVP, expertise is required for the correct selection of the technology stack and the development of a roadmap.
Main advantage: Google Search Console shows only 16 months of history and a maximum of 1000 rows of data. We collect ALL data through the API, store it for years, and provide users with quick access to the entire array of information.
Basic logic:
- The user logs in through Google, we gain access to their Search Console
- We synchronize data (clicks, impressions, queries, pages) → store it in our database
- We show all of the user's sites on one screen
- We build graphs, create filters, groupings, exports
Future development: After launching the basic version, we plan to add AI modules, automation, optimization recommendations, and other tools for SEO specialists
What needs to be done now?
We are at the Pre-MVP stage and are looking for an expert to help:
1. Analyze the reference
What we do:
- Study the functionality of SEOGets.com (7-day free access)
- Analyze the architecture: how they store data, how they build graphs, how filters work
- Document ALL features with Claude )))) (the list is attached below)
- Identify technical solutions that can be improved
Why: To understand what works well and what can be done better/faster/more conveniently.
2. Choose the technology stack
Selection criteria:
- Development speed - need to quickly launch the MVP
- Scalability - planning to grow to 10,000+ paid users
- Working with big data — billions of rows from Search Console and GA4
- Modularity — in the future, we will add automation AI tools, parsers, automation
What needs to be determined:
- Frontend: which framework? (React/Vue/Next.js?) + which chart library is best suited for our tasks?
- Backend: Node.js / Python / Go? + API framework
- Database: PostgreSQL / MongoDB / Clickhouse? (large volumes of data)
- Infrastructure: where to host? how to scale? CI/CD?
- Integrations: Google APIs, OAuth, possibly Stripe for payments
3. Create a development roadmap
Break the project into stages:
Stage 1: MVP (Core functionality)
- Authorization via Google
- Data synchronization from Search Console API
- Basic dashboard (graphs of clicks/impressions/positions)
- User's site list
- Date filters
- Export to CSV
Stage 2: Extended functionality (what we add after MVP)
- All features from the SEOGets list (see below)
- Grouping of sites (tags)
- Content Groups and Topic Clusters
- Cannibalization Reports
- Extended Storage (storage for 5+ years)
Stage 3: AI and automation (our improvements)
- Module "Task for the copywriter"
- On-Page recommendations
- Automatic content analysis
- And other tools
For each stage:
- Prioritization of features (must-have / nice-to-have)
- Estimation of development time
- Estimation of budget
4. Prepare a technical specification for hiring a team (2-3 hours)
After the roadmap, developers will need to be hired for the MVP. The expert should help:
- Determine who is needed: frontend/backend/fullstack/DevOps?
- Compile competency requirements
- Write a template for the technical specification for posting on exchanges
Full list of features for MVP (reference: SEOGets)
Core functionality (mandatory in MVP):
1. Authorization and connection
- Google OAuth authorization
- Connecting Google Search Console via API + GA4
- Multi-account support (multiple Google accounts)
- Unlimited websites
2. Master Dashboard
- Summary dashboard with all of the user's sites
- Key metrics: Clicks, Impressions, CTR, Average Position
- Graphs for each site
- Date filters (last 7/28/90 days, custom range)
- Weekly and Monthly views (not just daily, as in GSC)
3. Graphs and visualization
- Multi-line graphs (clicks + positions simultaneously)
- Cumulative metrics
- Period comparison (vs previous period)
- Area charts with fill
- Responsive design
4. Organization and tags
- Creating custom tags for sites
- Grouping sites by tags
- Hiding sites (hide function)
- Filtering by tags in the dashboard
5. Detailed site analytics
- Table with queries
- Table with pages
- Sorting by Clicks / Impressions / CTR / Position
- Search by queries and pages
- Pagination (up to 50,000 rows via API instead of 1000 in GSC)
6. Content Groups
- Creating page groups (for example, all blog posts)
- Filtering by URL patterns
- Tracking metrics by groups
- Comparing groups with each other
7. Topic Clusters
- Tracking groups of keywords
- Metrics: how many queries, pages, clicks in the cluster
- Tracking growth/decline of topic clusters
8. Growing & Decaying content
- Automatic identification of growing pages/queries
- Automatic identification of declining pages/queries
- Percentage change over the period
- Sorting by growth/decline rate
9. Filters and search
- Multi-Query Filtering (multiple queries simultaneously)
- Multi-Page Filtering (multiple pages simultaneously)
- Conditional Filtering (AND/OR logic)
- Branded vs Non-Branded filters
- PAA (People Also Ask) filter
- Long-tail keywords filter
10. CTR Analysis
- Comparison of CTR with industry benchmarks
- CTR by positions (1-10)
- Identifying underperforming pages
11. Cannibalization Report
- Finding pages competing for the same queries
- Visualizing conflicts
- Recommendations for consolidation
12. Striking Distance Report
- Queries in positions 11-20 (close to TOP-10)
- Potential for rapid growth
- Prioritizing optimization
13. Query Counting
- Counting the total number of queries over a period
- Tracking growth of keyword visibility
- Graphs of changes in the number of queries
14. Data export
- Export to CSV
- Export filtered data
- Bulk export for all sites
15. Privacy Blur
- Hiding URLs in screenshots
- Mode for demonstrations and cases
16. Annotations
- Adding notes to the timeline
- Google Core Updates labels (automatically)
- Custom events (content launch, redesign, etc.)
17. Shareable Magic Links
- Generating public links to dashboards
- Access without registration
- Setting permissions (read-only)
Extended functionality (added after MVP):
18. Extended Historical Data
- Storing data for 5+ years (instead of 16 months GSC)
- Paid option - per site
- Backups and archiving
19. Index Reporting
- Monitoring page indexing
- Alerts when dropping out of the index
- One-click request indexing (via API)
- History of indexing changes
20. Content Decay Heatmap
- Heatmap of traffic decline by pages
- Visualization by months
- Quick identification of problems
21. Mobile App / PWA
- Adaptation for mobile devices
- Progressive Web App + Push notifications
22. Multi-user access
- Team accounts
- Role-based permissions
- Client management for agencies
Examples of future AI modules (our extensions):
23. Task for the copywriter
- Parsing TOP-10 SERP or collecting via ahrefs API
- Analyzing competitors' content
- Gap analysis (what's missing)
- Generating outlines
- Integrating keywords from GSC
- AI generation of tasks with entries
24. On-Page Optimizer
- Automatic page audit
- Improvement recommendations
- Comparison with TOP competitors
- Optimization checklist
25. Content Refresh Suggestions
- AI analysis of outdated content
- Recommendations for updates
- Prioritizing pages for refresh
Expert requirements
Mandatory competencies:
- Experience in developing SaaS platforms (preferably data-heavy projects)
- Expertise in choosing technology stacks
- Understanding of scalable application architecture
- Experience working with Google APIs and OAuth
- Knowledge of working with large volumes of data (ETL, storage, fast retrieval)
- Ability to create technical documentation
Additional competencies:
- Knowledge of SEO specifics and Google Search Console API
- Experience in developing dashboards and analytical interfaces
- Understanding of billing systems (Stripe/Paddle)
- Experience with web scraping and parsing
- Knowledge of AI/LLM integrations
Work format:
- Asynchronous work on documentation
- Final deliverable: technical specification + roadmap (15-30 pages)
- Possibility of consultations after the main stage
Expected results of the work
1. Technical document (20-30 pages):
Section 1: Reference analysis
- Detailed description of all SEOGets features
- Technical solutions they use (presumably)
- Strengths and weaknesses
- What can be improved in our version
Section 2: Recommended technology stack
- Frontend: framework, UI libraries, chart library
- Backend: language, framework, API architecture
- Database: type of DB, table structure (conceptually)
- Infrastructure: hosting, CDN, scaling
- Integrations: Google APIs, OAuth, Billing
- Justification for the choice of each component
Section 3: System architecture
- Diagrams: overall architecture, data flow
- Component interaction scheme
- API endpoints (main)
- Database structure (ER diagram)
- Data synchronization scheme from GSC
Section 4: Security and performance
- OAuth flow and token storage
- Rate limiting Google API
- Data caching
- Optimizing database queries
- Backup strategy
2. Development roadmap:
MVP stage (4-8 weeks of development):
- List of must-have features
- Implementation sequence
- Time estimation for each module
- MVP readiness criteria
Post-MVP stages (v1.0, v1.5, v2.0):
- Prioritization of features (should-have, nice-to-have)
- Step-by-step development plan
- When to add AI modules
- Time estimates
Budget estimates:
- Cost range for MVP
- Cost of each subsequent stage
- Monthly infrastructure expenses
3. Technical specification for hiring developers:
- Profiles of needed specialists (frontend/backend/fullstack/DevOps/PM)
- Required skills and technologies
- Template for technical assignment for posting on freelance exchanges
- Questions for technical interviews
4. Infrastructure recommendations:
- Choosing hosting (AWS/Google Cloud/DigitalOcean/Vercel, etc.)
- CI/CD processes (GitHub Actions/GitLab CI)
- Monitoring and logging
- Backup and disaster recovery
Budget
The final cost is determined by the expert in their proposal, based on:
- The scope of work
- Their expertise and experience
- Deadlines
How to respond?
In your proposal, indicate:
1. Your experience:
- Examples of SaaS projects (links, your role, stack)
- Experience with analytical platforms or data-heavy projects
Behance
