Enrich new Airtable influencer prospects with Tubular insights
When a creator handle lands in your Airtable prospects base, auto-fill audience size, geo, engagement, top videos, and a fit score from Tubular Labs.
Integrations
Airtable
Tubular Labs
Type
Categories
- Marketing
Build an agent workflow that auto-enriches new influencer prospects in our Airtable base with Tubular Labs intelligence so my team can decide whether to reach out.
Trigger: poll Airtable for a new_record in our "Influencer Prospects" base/table. Use Airtable's first-class new_record poll trigger so the agent fires once per newly added row.
On each fire, the agent should:
1) Read the new Airtable row (Get Record, or List Records scoped to the triggering record id) and extract the creator handle and platform (YouTube / Instagram / TikTok / etc.) plus any other context columns the team filled in.
2) Call Tubular Labs via Execute GraphQL Query against api.tubular.io/graphql to look up that creator. Pull: audience size (followers / subscribers), primary country, age-gender breakdown, top recent videos (title + URL + views), average views per video over the last 30 and 90 days, engagement rate, and the top 3 content categories the creator posts in. If the schema or available fields aren't obvious, the agent should Introspect Schema first to discover what's queryable on this account.
3) Compare the creator against a configurable brand brief (target audience, content themes, must-avoids — surface these as workflow inputs so they're easy to edit) and write a short paragraph "fit assessment" plus a 1-5 fit score.
4) Use Airtable Update Record to write structured fields back onto the same row: audience size, primary geo, engagement rate, top category, fit score (1-5), fit summary (long text), and a status field (e.g. "enriched").
5) If the creator can't be found on Tubular (no result, or GraphQL errors with no usable data), the agent must still call Update Record and set the status field to "not found" with a one-line note explaining why. Never leave a row half-enriched and never fail silently.
Notes for the build: the brand brief, the Airtable base id, the table name/id, the handle column name, and the platform column name should all be workflow inputs the user fills in once at setup so they don't have to edit instructions to retarget a different campaign. Keep the agent stateless per row — one Airtable trigger fire enriches exactly one record.
What it does
- Watches your Influencer Prospects base in Airtable and runs the moment a teammate adds a new creator row.
- Pulls that creator's audience size, country and age-gender split, top recent videos, average views, engagement rate, and top categories from Tubular Labs.
- Writes a short fit assessment against the brand brief you configure (target audience, content themes, must-avoids) and a 1 to 5 fit score back onto the same Airtable row.
- Flags rows clearly when the creator can't be found in Tubular so nothing is left in a half-enriched state.
What you’ll need
- An Airtable base with a table of influencer prospects, including columns for the creator handle and the platform (YouTube, Instagram, TikTok, etc.).
- A Tubular Labs account with API access on the products you care about (Creator Intelligence / Video Intelligence).
- A short written brand brief: who you are targeting, what content themes fit, and what to avoid.
How to customize it
- Swap in your own brand brief, target audience, and must-avoids so the fit score reflects your campaign, not a generic template.
- Add or rename Airtable columns (for example, niche, brand-safety notes, or a status field) and the agent will fill them.
- Restrict the workflow to one specific Airtable view so it only enriches rows that pass an initial filter your team set up.
Use cases
- Lead Enrichment
- Research & Monitoring
