A workflow in Datamorf is a complete, automated GTM activation pipeline. It defines how data is extracted from a source, transformed and enriched, and then activated across your GTM tools — without writing a single line of code. Workflows are the core building block of Datamorf, and the mechanism through which your marketing, sales, and RevOps stack stays synchronized.

Every workflow follows the same structure: Extract → Transform → Activate.

1. Trigger — How the Workflow Starts

Every workflow begins with a trigger. The trigger determines when the workflow runs and what data it receives. There are four trigger types:

• Extractor (Reverse ETL): The Extractor pulls records from a CRM, database, or scraping source on a recurring schedule. This is the recommended trigger for most GTM activation workflows — it proactively keeps data clean and enriched over time.

• Built-in Integration Trigger: Starts the workflow based on an event in a connected app, for example, a new contact created in HubSpot or a deal moving to a new stage.

• Webhook — Secondary: A unique URL endpoint that receives data pushed from an external system in real time, for example, HubSpot sending contact data, or a form platform posting a submission.

• Schedule — Secondary: Runs the workflow automatically at a defined interval without requiring an Extractor or incoming event.

2. Data Sources — Pulling Additional Context

Once a workflow starts, it can fetch additional data from other systems to enrich the records being processed. For example, if the Extractor pulls contacts from your CRM, Datamorf can also query an enrichment provider, retrieve related deal records, or look up activity history — all within the same workflow run. Multiple sources can be connected, and conditions can control which ones execute for each record.

3. Transformations — Modifying and Enriching Data

Transformations are where raw records get shaped into activation-ready data. This step lets you:

• Standardize fields — names, phone formats, job titles, company domains

• Deduplicate or merge records based on matching criteria

• Run AI models to score leads, classify records, or generate personalized copy

• Apply math, string operations, or conditional logic

• Execute custom JavaScript for advanced business rules

Transformations chain together (the output of one feeds the next) allowing complex logic without complexity.

4. Activation — Sending Data to GTM Destinations

The processed data is delivered to one or more destinations:

• CRMs: HubSpot, Salesforce, Pipedrive

• Outreach and sequencing: Instantly, Lemlist, Apollo

• Ad platforms and audiences: LinkedIn, Google Ads

• Databases and data warehouses

• Communication tools: Slack, Gmail

• Another Datamorf workflow, for chained multi-stage pipelines

Why Workflows Matter for GTM Teams

• Reusable — One workflow can handle multiple data streams or be triggered from other workflows.

• Scalable — Built to handle millions of executions with automatic scaling.

• Transparent — Every run is logged, giving full visibility into every extraction, transformation, and activation step.

In short, a Datamorf workflow is your GTM data's operating layer — ensuring every tool in your stack always works from clean, enriched, up-to-date records.