๐ฃ Score funding newsletter leads from Gmail with Bright Data and GPT-5.6
โก 1 views ยท ๐ฃ Lead Generation & Enrichment
Description
Quick overview
This workflow monitors a Gmail label for unread funding newsletters, extracts newly funded companies with OpenAI (GPT-5.6), enriches them via Bright Data search and website reads, scores fit against your buyer profile, stores results in an n8n Data Table, and emails you a single digest of the best prospects.
How it works
- Triggers every 15 minutes when an unread email arrives under the specified Gmail label.
- Extracts and cleans the newsletter body text, then uses OpenAI (GPT-5.6) to pull structured funding rounds and company details from the prose.
- Loads previously seen companies from the n8n Data Table and filters out repeats and small rounds, keeping only a capped list of new companies.
- For each new company, uses Bright Data to run a Google search, avoids publisher results, and selects the most likely official website.
- Uses Bright Data Web Unlocker to fetch the company homepage content and normalizes it for analysis.
- Sends the funding data, search snippets, and homepage text to OpenAI (GPT-5.6) to produce a 0โ100 fit score plus a call angle and โwhy now,โ then routes results by tier and upserts them into the Data Table.
- Builds a single HTML digest of the โhotโ companies (and a brief watch list) and sends it to your target address via Gmail.
Setup
- Connect your Gmail account, create a Gmail filter that applies a dedicated label to your funding newsletters, and update the label and recipient email in the Settings values.
- Add an OpenAI credential and ensure the model selection is available for the OpenAI nodes.
- Add a Bright Data HTTP Header Auth credential and set your Bright Data SERP and Web Unlocker zone names in the Settings values.
- Create an n8n Data Table named
funding_seenwith columnscompany_key,company,amount_musd,stage,tier,score,angle, andfirst_seen. - Edit the buyer description and scoring thresholds in Settings (minimum round size, max companies to score, and hot/watch score cutoffs).
๐ Nodes Used
HTTP Request, Gmail, Gmail Trigger, Basic LLM Chain, OpenAI Chat Model, Information Extractor
๐ฅ Import
Download workflow.json and import into n8n:
Workflow menu โ Import from File