Create your first data flow

Read how to set up your first data flow or use the interactive block below to check out the flow in action.

On the homescreen, you'll see a big banner with the Create Data Flow button in it.

Alternatively, you can navigate to the data flows section. Whichever option you choose, you'll see two options to create a data flow: Use prebuilt data set and Set up from scratch:

If you opt for Setup from scratch, you'll get to the Sources selection step right away.

Learn more about data set templates in Coupler.io

If you chose the template option, select the appropriate template. After that, you'll need to connect your source data.

1

Sources

Choose the sources you want to collect data from and configure them according to the required fields. You may need to choose/specify properties, reports, data entities, metrics, date range, etc. Here is an example of what it looks like for Google Analytics 4 as a data source.

You can add multiple data sources to your data flow as follows:

Option 1

Option 2

When creating a data flow from a data set template, the data source will be preselected. However, you still can add more data sources if needed.

2

Data sets

At this step, Coupler.io previews rows from your connected sources and allows you to organize the data using the built-in transformations.

In the case of creating a data flow from a data set template, you'll get your data organized and structured already. At the same time, you can apply additional transformations if needed.

Here are the available data transformation options:

Column management — hide columns you don't need, rename them, reorder, or change the column type. Supported types: string, number (integer, decimal, percent, currency — with precision control), date, and datetime.

Filtering — set criteria to include only the rows you need.

Sorting — order data by one or more columns.

Custom columns — add new columns with calculated values using formulas.

Data blending and aggregation

In addition to the basic column-level transformations, Coupler.io enables you to reshape your data via aggregation or combining multiple sources.

Append

stacks data from sources with a similar structure. Columns are matched by name

Join

merges data from sources with different structures. You select one or more shared columns to link the data sets

Aggregate (summarization)

calculates summary values across rows using sum, average, count, min, or max

Unlike Append and Join, Aggregate doesn't require multiple sources. You can aggregate a single data set to roll up detailed data into totals or averages.

3

Destinations

Select the destinations you want to load your data set to and configure them according to the in-app instructions.

Coupler.io supports multiple destinations within a data flow. For example, you can automate data load from Google Analytics to Google Sheets, your Data Studio dashboard, and Claude, within a single data flow.

Moreover, if you have different data sets within your data flow, you can load different data sets to different destinations. For example, the data set from Google Ads may go to Google Sheets, the data set for Facebook Ads - to Looker Studio, and the LinkedIn Ads data set can be connected to Claude.

4

Flow settings

This step allows you to automate data refresh on a schedule. Additionally, you can see the history of runs and set up webhooks for triggered automations.

5

AI Agent (Optional)

This step is not mandatory, but it allows you to use the Coupler.io AI agent for conversational analysis of your data sets.

Learn more about AI agent