See llms.txt for all machine-readable content.

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Score Facebook Page leads from Apify by reachability and ad activity

Reads public business information from the Facebook Pages you list (category, followers, email, phone, address, website, creation date and whether the Page is running ads), dedupes against earlier runs and scores each Page as a lead: reachable by email or phone, big enough to matter, in your target category or area, and actively spending on ads. Built for agencies and sales teams that work from a list of Pages. Only business contact details that the Page itself publishes are collected; check local marketing and privacy rules before outreach.

How it works

  1. Daily schedule / manual run reads every setting from Config. A weekly schedule uses the same Config to send a report instead of running the actor.
  2. Starts the Apify actor asynchronously, then waits and polls the run; FAILED, ABORTED, TIMED-OUT or too many polls stop with an error.
  3. Downloads the dataset, validates rows and dedupes within the run and across runs (workflow static data, dedupeMemoryDays).
  4. A transparent rule score runs first, then an LLM chain with a structured output parser reads each record against your plain-English aiCriteria and returns a fit score, verdict, summary, outreach angle and red flags. Calls are batched with a delay for rate limits, retried, and fall back to the rule score if the model fails.
  5. Upserts every row to Google Sheets. Hot rows go to Slack as one approve / dismiss message (send-and-wait, 24 h limit) and the decision is written back to the sheet; warm rows go to an HTML email digest; cold rows stay in the sheet.
  6. Weekly report: reads the sheet, summarises the last 7 days (tiers, approvals, top 10) and emails it.
  7. A separate Error Trigger branch posts any failure to Slack.

Setup (about 15 minutes)

  1. Create an HTTP Header Auth credential: name Authorization, value Bearer <APIFY_API_TOKEN> (Apify Console > Settings > API & Integrations). Select it on the 3 Apify HTTP nodes.
  2. Create a Google Sheet with a tab named in sheetTab and a header row matching the sheet columns (see Upsert to Google Sheets, plus status and reviewedAt). Paste its ID into googleSheetId.
  3. Connect OpenAI (or swap the chat model sub-node for Anthropic, Gemini, Ollama...), Slack and Gmail; set slackChannelId and digestEmail in Config (also the channel on Slack: error alert).
  4. In Config set actorInput.pages (usernames, numeric IDs) or use startUrls, then minFollowers, targetCategories and targetPlaces. Feed it Pages you found elsewhere (for example from the local business or Maps workflows).
  5. Write your ideal-lead description in aiCriteria; set aiWeight (0 = rules only, 1 = AI only).
  6. Run once manually, check the sheet, then activate.

Customize

  • Edit weights in Score page leads (email 25, ads running 20, phone 15, followers 15, website 10, category 10, place 5).
  • Turn on includeLatestPost in actorInput to add the newest post, so the AI step can judge how active the Page is.
  • Swap Gmail/Slack for Teams, Discord, HubSpot, Airtable, etc. Each delivery node only reads $json.

Disclosure: I maintain these Apify actors (account transparent_meteorite). The actor is a paid pay-per-event Apify tool; check its Store page for current pricing before scheduling.