Platform Selection:
| Lambda 1 | Scrape company website and relevant sources | scans relevant sources to compute a level 1 and 2 categorization for the business (marketing, target accounts, etc.) | Updated CSV with categorization |
| Lambda 2 | Leverage sensitivity analysis to identify top 5 recommendations | Considers both L1&2 GTM strategies combined with the constraining factors from sensitivity analysis to identify 5 best recommendations for improving revenue | Recommendations for each constraining factor |
| Front End | Client can view description of each constraining factor and detailed recommendations | A summarized view of each constraining factor identified in sensitivity analysis with recommendations for each | Elegant UI |
Tools and TechStack:
Cloud Repo & version control: GitLab
Cloud Provider: AWS (S3, Lambda)
Languages & Frameworks:
- Typescript (Node, Express, Next.js)
- Python (Flask, NumPy, Pandas, SciPy)
- Zenrows
Other Productivity Tools:
- Tar Heel Live Website Builder
- Notion
- GitLab Issues (task manager)
- Visual Studio Code
- Slack
Architecture Diagram
Client architecture for sensitivity analysis
Architecture for Recommendation Engine
