Data Overview
When you connect Coupler.io as a source, you gain access to the data that's already been imported by one of your existing data flows. The data structure depends entirely on the original source your flow connected to—whether that's Google Ads, HubSpot, Stripe, or any other integration Coupler.io supports.
What data is available?
Coupler.io doesn't have predefined entities or metrics of its own. Instead, it acts as a data passthrough. The columns, metrics, and dimensions you'll see match exactly what your original data flow imported.
For example:
If your source data flow pulls from Google Ads, you'll see campaigns, ad groups, keywords, performance metrics, and impressions
If it pulls from HubSpot, you'll see contacts, deals, companies, and engagement data
If it pulls from Stripe, you'll see transactions, customers, invoices, and revenue data
The data refreshes whenever your original source data flow runs. If you run the original flow, the Coupler.io source will pull the updated data on its next run.
Common use cases
Multi-source dashboards
Import data from three separate ad platforms (Google Ads, Facebook Ads, LinkedIn Ads) into individual data flows, then use Coupler.io to pull all three flows and combine them with Append to create a unified dashboard.
Chained transformations
Build a series of dependent flows: the first imports raw data, the second cleans and joins it, the third aggregates it, and the fourth pulls the aggregated data into your final destination.
Reduced API calls
If you have multiple destinations that need the same source data, create one data flow that imports from your source, then use Coupler.io sources in separate flows that pull from it. This keeps you within API rate limits and reduces redundant imports.
Derived metrics
Create a base data flow that imports your raw data, then use Coupler.io sources with Aggregate transformations to calculate conversion rates, average order value, cohort metrics, and other derived KPIs.
Use cases by role
Use Coupler.io to consolidate performance data from multiple ad platforms (Google, Meta, LinkedIn, TikTok) into a single marketing dashboard. Import each platform into its own data flow, then pull all flows using Coupler.io and Append them to create a unified view of spend, impressions, clicks, and conversions.
You can also build attribution workflows: one flow for ad clicks, another for website analytics, and a third using Coupler.io to join them and calculate which ad led to each conversion.
Chain data flows to automate reconciliation and reporting. For example, import raw transactions from your accounting system in one flow, use a second flow with joins to match them against invoices, then pull both with Coupler.io into a third flow that aggregates monthly revenue and costs by department.
This approach also helps when syncing budget vs. actual reports: one flow imports budget data, another imports actual spend, and Coupler.io combines them for variance analysis.
Build multi-step pipelines to track deal progression. Import your CRM data in one flow, use a second flow to join it with email engagement data, then pull both with Coupler.io to calculate win rates, average deal size, and sales cycle metrics by stage.
You can also use Coupler.io to combine pipeline data from multiple CRM instances or append historical data for trend analysis.
Use Coupler.io to build modular, reusable data pipelines. Create base flows for each data source, intermediate flows for transformations (joins, aggregations), and final flows that pull from intermediates to populate your data warehouse or BI tool.
This separation of concerns makes pipelines easier to debug, audit, and modify without affecting downstream consumers.
Platform-specific notes
Data freshness: Coupler.io pulls data from the most recent run of your source data flow. If the source flow hasn't run recently, you'll see stale data. Always ensure your source flows are on a regular schedule.
Dependent flows: If you have Flow B (Coupler.io source) pulling from Flow A, running Flow B alone won't trigger Flow A. You must run Flow A first, then run Flow B to get fresh data.
Deleted flows: If you delete the source data flow, the dependent Coupler.io source will break. Archive important flows instead of deleting them.
Nested chains: You can chain Coupler.io sources (Flow B pulls from Flow A, Flow C pulls from Flow B), but keep chains to 2–3 levels. Longer chains increase complexity and make troubleshooting harder.
Permissions: You can only select data flows that you created. Flows created by other team members won't appear in the dropdown.
Last updated
Was this helpful?