Apify integration for GTM

Turn an Apify Actor into a complete GTM workflow.

Use Actor output to start a list, then enrich, score, validate, deduplicate, and route every row in a visual workspace your coding agents can build and operate.

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Actor datasetsCron + webhooksOwned enrichmentAgent configured

Apify finds the raw material. gtmcli turns it into a system.

Apify Actors can extract structured datasets from websites and other sources. Apify's own documentation supports programmatic control through its API, reactions through webhooks, and connections to AI agents and workflow platforms.

The gtmcli connector uses that output as a workflow source. Map the dataset into rows, attach owned people and company data, find and validate contacts, run custom scoring, and preserve the decision trail before anything leaves the workspace.

Scraping is context-dependent. Choose Actors and sources responsibly, review their terms, respect access controls and privacy requirements, and keep human approval around sensitive targeting or outreach decisions.

What you can build

One workspace from source to finished workflow.

Actor as a source

Run a suitable Actor with saved inputs and map its output dataset into an editable gtmcli table.

Schema normalization

Rename, transform, and standardize Actor fields before they reach enrichment or scoring steps.

People and company enrichment

Join extracted companies to owned data and find the right people for the documented use case.

Contact validation

Find and validate work emails or add supported mobile enrichment before a record can advance.

Scheduled runs

Put the complete play on a cron schedule and deduplicate every recurring batch.

Agent-built logic

Let Claude Code, Codex, Cursor, or OpenCode configure mappings, code columns, filters, and review rules.

How it works

Go from Actor run to approved audience.

01
Choose and test the Actor
Confirm the input, output schema, source permissions, reliability, and unit economics on a small run.
02
Map the dataset
Convert Actor output into stable company, person, URL, and evidence fields inside gtmcli.
03
Enrich and qualify
Add owned data, contact paths, validation, and a transparent ICP score.
04
Schedule with guardrails
Set the trigger, deduplication key, retry behavior, review queue, and approved destination.

Agent prompt

Run my saved Apify Actor every Tuesday.
Map company name, domain, source URL, and category.
Deduplicate by domain, enrich companies and VP contacts,
validate emails, and queue scores above 85 for review.

✓ Editable workflow ready for review

Compare approaches

Give each platform a clear job

Stage	Apify	gtmcli
Collection	Run Actors that produce source datasets	Trigger the Actor and receive its output
Normalization	Actor-specific output schema	Map fields into reusable GTM records
Enrichment	Depends on the chosen Actor	Owned data, providers, code columns, and validation
Workflow	Schedules, API, webhooks, and platform integrations	Cross-source logic, review states, deduplication, and destinations
Operator view	Actor runs and datasets	Editable GTM table and end-to-end workflow

Frequently asked questions

Straight answers before you build.

What does the gtmcli Apify integration do?

The integration lets an Apify Actor start or feed a gtmcli workflow. Actor output becomes rows that can be normalized, deduplicated, enriched, scored, validated, reviewed, and routed to another system.

Can any Apify Actor be used?

The connector is designed to work with Actor datasets that can be mapped into structured rows. The exact workflow depends on the Actor's input, output schema, permissions, reliability, and whether its use complies with the source site's rules and applicable law.

Can I schedule an Apify lead-generation workflow?

Yes. The workflow can run on a cron schedule, or it can respond to Actor completion and other webhook events. Add deduplication and review rules so recurring runs do not create duplicate or unsafe downstream actions.

Can Claude Code or Codex build the integration?

Yes. A coding agent can configure the Actor input, map returned fields, add enrichment and code columns, set acceptance rules, and prepare the recurring workflow through gtmcli's agent interfaces.

Does gtmcli replace Apify?

No. Apify runs Actors and produces datasets. gtmcli turns those datasets into governed GTM workflows with enrichment, scoring, validation, routing, and an editable visual workspace.

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