AI Digital Marketing Lead Scorer

I’m looking to build a small-footprint, AI-driven tool that takes a list of company names from me and returns a ranked, fully-scored spreadsheet of prospects that clearly shows who is most in need of digital marketing help.

How I want it to work
1. I drop in a batch of company names (CSV, Google Sheet, or simple text input—whatever is fastest for you to wire up).
2. Your model or rules engine pulls public data from each company’s website, their social media profiles, and any major online directories.
3. It evaluates their overall digital footprint—site structure, SEO factors, social posting frequency/engagement, content freshness, and any other signals you think will sharpen the score.
4. The output comes back sorted by “need” score with a clear breakdown of gaps in three areas I care about most: SEO optimisation, social media management, and content creation.

Key acceptance criteria
• Automated data collection from company website, social media profiles, and online directories.
• Transparent scoring logic so I can tweak weightings later (Python, Node, or a low-code ML platform is fine—just keep it editable).
• Downloadable report (CSV or Google Sheet) listing the companies, their individual factor scores, and an overall “needs help” rank.
• A quick Loom or written walkthrough showing setup and how to retrain or adjust rules.

If you’ve already built lead-scoring or web-scraping automations, let’s talk—I’ll prioritise proven experience with Python scraping libraries, GPT or other LLM APIs, and lightweight front-ends (Streamlit, Flask, etc.).