> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/functionality/destination-setup.md).

# Destination Setup

Choose where Coupler.io sends your data and define how it should land there. Use it to connect tools like Google Sheets, BigQuery, Microsoft Excel, Power BI, and other supported destinations, then configure the required settings for a reliable export.

{% hint style="success" %}
You can check the list of available destinations on the [Destinations page](/destinations/readme.md).
{% endhint %}

#### Browse destination categories

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>AI destinations</strong></td><td>Send data to AI tools so you can analyze it with prompts and assistants.</td><td><a href="https://docs.coupler.io/destinations/categories/ai">https://docs.coupler.io/destinations/categories/ai</a></td></tr><tr><td><strong>Dashboards</strong></td><td>Send data to BI tools or start with ready-made dashboard templates for reporting.</td><td><a href="https://docs.coupler.io/destinations/categories/dashboards">https://docs.coupler.io/destinations/categories/dashboards</a></td></tr><tr><td><strong>Spreadsheets</strong></td><td>Send data to spreadsheet tools for simple sharing, review, and reporting.</td><td><a href="https://docs.coupler.io/destinations/categories/spreadsheets">https://docs.coupler.io/destinations/categories/spreadsheets</a></td></tr><tr><td><strong>Data warehouses</strong></td><td>Load large data sets into scalable storage for modeling, queries, and analytics.</td><td><a href="https://docs.coupler.io/destinations/categories/database">https://docs.coupler.io/destinations/categories/database</a></td></tr><tr><td><strong>API</strong></td><td>Export data as JSON for custom apps, developer workflows, and integrations.</td><td><a href="https://docs.coupler.io/destinations/categories/api">https://docs.coupler.io/destinations/categories/api</a></td></tr></tbody></table>

#### Set up a destination

{% stepper %}
{% step %}

### Select the destination

Open the **Destinations** step in your data flow. Add the app or file you want to send data to.
{% endstep %}

{% step %}

### Choose the data view

Pick the data view you want to export. If your flow has several prepared views, select the one that matches this destination.
{% endstep %}

{% step %}

### Connect the target account

Authorize the destination account. Choose the exact destination for the export. This can be a spreadsheet, worksheet, table, folder, or report, depending on the app.
{% endstep %}

{% step %}

### Set the import mode

Choose **Replace** if you need a fresh snapshot on each run. Choose **Append** if you want to preserve previous rows and build history over time.
{% endstep %}

{% step %}

### Save and run the flow

Review the settings, save the destination, and run the flow. Check the result in the target app to confirm the data landed as expected.
{% endstep %}
{% endstepper %}

#### Multiple destinations

If needed, you can set up multiple destinations per data flow, so the data is exported to different platforms/files simultaneously. The setup process is the same: simply choose and connect the needed ones on the Destinations step of your data flow:

<div align="left"><figure><img src="/files/rQVHjiyH7L3NdnlCD3et" alt="" width="563"><figcaption></figcaption></figure></div>

#### **Data set to share**

Your data flow can have different data views you worked with on the Data Sets step. You can choose one of the available data views while setting up the destination, and that data will be exported:

<div align="left"><figure><img src="/files/vaaNwDdmJ0gzufOq1CXB" alt="" width="563"><figcaption></figcaption></figure></div>

#### Import mode: Replace vs Append

Coupler.io has 2 import modes: Replace and Append.

**Replace** drops the existing table and recreates it with fresh data on every run. This is ideal when you always want a clean, current snapshot — for example, a live view of active campaigns or current CRM records.

**Append** adds new rows below the existing data without touching what's already there. Use this when you want to build a historical log — for example, tracking daily ad spend over time.

{% hint style="info" %}
If you're unsure, Replace is the safer starting point. You can always switch to Append once you know your schema is stable.
{% endhint %}

#### Update data in the destination

Coupler.io supports two approaches to scheduled data updating in the destination: either update the data each run, or update data only if the source data has changed.

**Update data each run**

To use this approach, enable the `Update data each run` setting during the destination setup:

<div align="left"><figure><img src="/files/93fw2J1pqQsrJAvNqn0r" alt="" width="375"><figcaption></figcaption></figure></div>

Once you define a schedule for the data flow with this setting, Coupler.io **will update your data in the destination sheet each time the data flow is executed**. If you set it up to run hourly, Coupler.io runs every hour, pulls your data, and saves it to the destination.

**Update data only if the source data has changed**

In Coupler.io terms, "*the source was changed*" means:

* new data added
* old data updated
* data order is changed
* other eligible actions

The logic behind this is that Coupler.io calculates the hash of your data and compares it during runs.&#x20;

{% hint style="warning" icon="keyboard" %}
Even adding space to some secondary field you don't care about is counted as a data change.
{% endhint %}

To use this approach, disable the `Update data each run`setting during the destination setup.

Once you define a schedule for the data flow with this setting, **Coupler.io will update your data in the destination sheet only if it has changed in the data source** since the last time our tool imported it.&#x20;

If you set up a data flow to run hourly, Coupler.io runs every hour, pulls your data, and checks whether something has changed or not.

{% hint style="info" icon="cloud-check" %}
If your data updates only once per day (in your data source), Coupler.io will update it in your destination only once per day as well (even if you set up data refresh frequency to 1 hour).
{% endhint %}

{% columns %}
{% column width="50%" %}
**Update data each run**

To use this approach, enable the `Update data each run` setting during the destination setup:\
![](/files/tRjLRzlg2HbyVevsvY80)<br>

Once you define a schedule for the data flow with this setting, Coupler.io **will update your data in the destination sheet each time the data flow is executed**. If you set it up to run hourly, Coupler.io runs every hour, pulls your data, and saves it to the destination.
{% endcolumn %}

{% column width="50%" %}
**Update data only if the source data has changed**

In Coupler.io terms, "*the source was changed*" means:

* new data added
* old data updated
* data order is changed
* other eligible actions

The logic behind this is that Coupler.io calculates the hash of your data and compares it during runs.&#x20;

> Even adding space to some secondary field you don't care about is counted as data change.

To use this approach, disable the `Update data each run` setting during the destination setup.

Once you define a schedule for the data flow with this setting, **Coupler.io will update your data in the destination sheet only if it has changed in the data source** since the last time our tool imported it.&#x20;

If you set up a data flow to run hourly, Coupler.io runs every hour, pulls your data, and checks whether something has changed or not.

{% hint style="info" icon="cloud-check" %}
If your data updates only once per day (in your data source), Coupler.io will update it in your destination only once per day as well (even if you set up data refresh frequency to 1 hour).
{% endhint %}
{% endcolumn %}
{% endcolumns %}


---

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