LEAD GENERATION

Speaker Roster Research Desk in Airtable with Daily Watch

Watches a conference speaker page on a daily schedule, detects newly added presenters, researches each one.

CategoryLead Generation
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires
  • ActionScrape current speaker pageFirecrawl
  • LogicKeep only speakers not already in AirtableAirtableAirtable
  • ActionResearch each new speaker's role and company newsExa
  • ActionSummarize talking points and assign ownerOpenAI
  • OutputAppend researched speakers as rows in Airtable trackerAirtableAirtable

What it does

Keeps a living Airtable base of conference speakers as an ABM research desk. Each day it re-crawls the speaker page, finds presenters that weren't there yesterday, builds a research dossier for each, and appends a deduplicated row so the team works a clean, growing list.

When to use it

Use it for conferences that announce speakers in waves over weeks. Instead of checking the site manually, you get new presenters delivered into a structured tracker the moment they're listed, already researched.

How it works

  1. 1A daily schedule triggers the run.
  2. 2Firecrawl scrapes the current speaker page and returns the full presenter list.
  3. 3A dedupe step compares against speakers already stored in Airtable and keeps only the new arrivals.
  4. 4Exa researches each new speaker's recent posts, role changes, and company news.
  5. 5An OpenAI step summarizes the research into a talking-points field and a suggested outreach owner.
  6. 6Each new, researched speaker is appended as a row in the Airtable ABM tracker with status set to New.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FirecrawlCrawl, scrape, structured extract.
  2. 2
    Connect ExaNeural search across the web.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect AirtableBases, tables, views, automations.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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