Coupler.io

Coupler.io is a data integration platform that lets you connect multiple data sources and build automated workflows. The Coupler.io source lets you reuse data that you've already imported through one data flow in a separate, new data flow — without having to reconnect to the original source.

Why connect Coupler.io as a source?

• Reuse existing data flows — Pull data from a data flow you've already set up instead of duplicating work

• Build complex workflows — Chain data flows together using Join, Append, and Aggregate transformations

• Simplify maintenance — Update your source data flow once, and changes cascade to all dependent flows

• Multi-step automation — Create advanced pipelines where one flow's output feeds into another

Prerequisites

• A Coupler.io account with at least one completed data flow

• The data flow you want to connect must have run at least once (a successful manual run is required)

Quick start

Before you start, make sure the data flow you want to use as a source has completed at least one successful manual run. Coupler.io sources must reference active, tested data flows.

1

In your new data flow, select Coupler.io as a source.

2

Select the data flow you want to pull data from. You'll see a dropdown listing only data flows you created. Choose the one containing the data you need.

3

Review the data preview and configure any transformations. If you need to combine this data with other sources, use Join or Append. If you're aggregating metrics, use the Aggregate transformation.

4

Choose your destination — Google Sheets, Excel, BigQuery, Looker Studio, or one of our AI destinations (Claude, ChatGPT, Cursor, Gemini, Perplexity, OpenClaw).

5

Run the data flow. Click the Run button to complete a successful manual run. Once this succeeds, you can schedule recurring refreshes.

How it works

When you use Coupler.io as a source, you're pulling the most recent data from an existing data flow. The workflow is straightforward:

1. Create or identify a data flow that imports data from your original source (e.g., Google Ads, Facebook Ads, Stripe)

2. In a new data flow, add Coupler.io as a source and select that existing data flow

3. The new flow will use the data from your original flow's last run

4. Chain multiple flows together if you need to combine data from different sources

This approach is especially useful when you want to build multi-step workflows—for example, importing data from three different advertising platforms into separate flows, then using Coupler.io to pull from all three and combine them in a final aggregated dashboard.

Coupler.io 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

Marketers

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.

Finance teams

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.

Sales ops

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.

Data analysts

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.

Coupler.io common issues

Connection issues

Why don't I see any data flows in the dropdown?

The Coupler.io source dropdown only shows data flows you created personally. If you're on a shared team account, you'll only see your own flows—not flows created by other team members.

If you need access to another user's flow, ask them to create a new data flow or request that they recreate it under your account so you can reference it.

I'm getting an "Invalid API key" error.

Verify that the API key you copied is correct and hasn't been revoked or rotated. Log into your Coupler.io account settings and copy a fresh API key. Make sure there are no extra spaces or truncated characters when pasting.

The source data flow I want to use isn't available in the dropdown.

Your source data flow must have completed at least one successful manual run before it can be selected. Check that the flow has run without errors. If it's never run or failed on its last attempt, complete a manual run first.

Missing data

Why is my Coupler.io source showing old data?

Coupler.io pulls from the most recent successful run of your source data flow. If the source flow hasn't been run recently, you're seeing stale data.

Always run your source data flow first, then run the dependent Coupler.io flow. Don't assume running the Coupler.io flow alone will refresh upstream data.

No data is appearing in my Coupler.io source, even though the source flow has data.

Check that your source data flow completed successfully on its last run. If it failed or was cancelled, no data will be available to pull. Review the source flow's run history and address any errors.

Also confirm that the source flow's destination contains data. If it was set to Google Sheets, verify the sheet isn't empty and the correct tab was used.

Permission errors

Why can't I see other team members' data flows?

Coupler.io sources only reference your own data flows. To use a flow created by a colleague, they must share the data with you through a different method (e.g., by adding it to a shared Google Sheet or exporting it) or recreate the flow under your account.

Data discrepancies

I'm seeing duplicate rows or missing data after appending multiple Coupler.io sources.

When appending data from multiple data flows, ensure each source ran on the same schedule or on compatible schedules. If one flow updated but another hasn't run yet, you may get incomplete or outdated data in your append.

Consider staggering your schedules so all source flows complete before your combining flow runs.

The data in my Coupler.io source doesn't match the original source system.

Coupler.io shows exactly what your source data flow imported—including any filters, transformations, or data type mismatches that exist in the original flow.

If you see unexpected data, trace back to the source flow and verify:

• Date range filters are correct

• No transformation errors occurred (check the flow's preview)

• The destination (Google Sheets, etc.) wasn't edited manually

• The source flow's last run completed without errors

Rate limits

Will using Coupler.io as a source count against my API limits?

No. Coupler.io sources don't make new API calls to your original data source. They only read data that was already imported by your source data flow. Your only API usage is from the initial import by the source flow, not from the Coupler.io source itself.

This is one of the key benefits of chaining flows—you reduce redundant API calls.

Coupler.io FAQ

Can I use a Coupler.io source that references another Coupler.io source?

Yes, but keep it simple. You can chain flows (Flow C pulls from Flow B, which pulls from Flow A), but avoid long chains—they become hard to troubleshoot. Two or three levels is usually the maximum before performance and maintainability suffer.

Do I need to run all my source flows every time, or just the main one?

You need to run all source flows in the chain. If you have a main aggregating flow that pulls from three separate Coupler.io sources (Google Ads, Facebook Ads, Stripe), you must run all three source flows, then run the aggregating flow. Running only the main flow won't trigger the upstream sources.

What transformations can I use with Coupler.io sources?

You can use Join, Append, and Aggregate just like any other source. For example:

• Append multiple Coupler.io sources to combine data from different platforms

• Join them on a common key (like customer ID) to correlate data

• Aggregate them to calculate metrics like total spend by channel or average order value by region

If I edit my source data flow, will the dependent Coupler.io source automatically update?

No. Changes to your source flow's structure (adding columns, removing fields) don't automatically cascade. However, data changes do—if you re-run the source flow with new data, the next run of the dependent Coupler.io source will reflect that new data.

If you add new columns to the source flow, the Coupler.io source will pick them up on the next run, but you'll need to update downstream steps or destinations to use them.

Can other team members use my data flows as Coupler.io sources?

No. Coupler.io sources only reference flows you created. Other team members can only see and use their own flows. If you want to share a data flow's output, export it to a shared destination (Google Sheets, BigQuery) instead.

For more on permissions and team access, see the best-practices section.

What happens if the source data flow fails to run?

If your source flow fails, any dependent Coupler.io sources will pull stale data from the last successful run. No error will be thrown—you'll just get outdated data. Always monitor your source flows to catch failures early.

Learn how to troubleshoot failed flows in common-issues.md.

Can I use Coupler.io sources with AI destinations like Claude or ChatGPT?

Yes. You can pull data via a Coupler.io source and send it to Claude, ChatGPT, Cursor, Gemini, Perplexity, or OpenClaw, just like any other source. This is useful for automating content creation, analysis, or drafting based on imported data.

Does using Coupler.io as a source count toward my API usage limits?

No. Coupler.io sources don't make new API calls. They only read data that was already imported by your source flow. Your API usage is only incurred by the original import, not by downstream Coupler.io sources.

For more on API limits and optimization, see the best-practices section.