Stackby to Google Sheets Integration Explained

The instructions provided in this article are sufficient for creating an automated Stackby to Google Sheets integration. But please note that we are not responsible for the outcome if you use the instructions incorrectly, specify incorrect settings, or if there are changes in the app’s API. If you need help with the setup, we can offer this premium integration at an additional fee.

With Stackby’s numerous int§egrations it’s easy to import data from external apps into your boards. However, what about automating the exports outside of the platform? This is also easy to pull off and doesn’t necessarily require any coding. We’ve prepared a template that will help you move any data you want from Stackby to Google Sheets.

How to connect Stackby to Google Sheets?

Stackby’s Developer API is rather basic but it’s sufficient for pulling data from your stacks and boards. That’s what we’re going to show here.

Traditionally APIs require development skills. What’s more, even once you manage to pull the desired data, you need to format it to fit well into the destination app. 

Coupler.io simplifies both problems while giving you an easy interface to schedule data imports from the apps you love. Available integrations include Pipedrive to Google Sheets, Harvest to Google Sheets, as well as HubSpot, Jira, Airtable, Shopify, and others.

To pull data from Stackby to Google Sheets, you’ll need the template file with the ready-to-use configuration. Open it now and make a copy for yourself (File -> Make a copy).

Also, Install the Coupler.io add-on from the Google Workspace Marketplace. You’ll need it to automatically create Stackby importers.

Template to integrate Stackby to Google Sheets

Using the template, you’ll be able to pull a JSON file containing all of the available details of one of your Stackby boards. Fetching the data from other boards will be almost as simple as copy/pasting the existing configuration. 

Once the file is fetched on your behalf, Coupler.io will create a new tab in this spreadsheet and will import the board contents there. It will then repeat the process at the chosen interval and fetch any new changes this way.

To get started, you’ll need to populate the four green fields at the top of the sheet. These are:

• API key
• Stack ID
• Table name or ID
• Max # of rows

To get your API key, click on your avatar in the top-right corner of the page and choose Account. Scroll down the page and generate an API key or copy the existing one. Insert it into the first row of the template file.

Next, decide on the board you want to import first. Open it and look at the URL. The first string that appears after stack/ is the Stack ID. The second is Table ID. Copy and paste both into the respective fields in the template.

To make it simpler, you can use the table name instead of the table ID but only if the name doesn’t contain any spaces.

Last, choose the limit of rows for your import or leave the fourth field empty if you wish to fetch all available records. Check out Coupler.io pricing to learn the limits provided for each subscription plan.

You’re ready to go.

Stackby to Google Sheets – importing data

Now it’s time to launch the Coupler.io add-on. Click on the Extensions menu on top of your sheet and choose Coupler.io. Then, select Open Dashboard.

Note: At the time of writing, Google seems to be gradually releasing the new naming for this section. Due to this change, you may be able to look for Coupler.io in the Add-ons menu, rather than Extensions. It’s all the same thing, though.

When you click to open a dashboard, it will load to the right of the screen.

It will contain the details of your first importer – its name and the tab it will create that will receive the data. If you’d like to change anything here, edit the respective fields in the configuration file and press the refresh button above the importer.

If no importer appears on the list, double-check that the tab with the configuration is still named Datasource Index. Otherwise, no settings will be imported.

When everything is working, press the Run button. The importer will run for a short amount of time. If it’s successful, you’ll see a new tab populated with the desired data. Here’s a piece of our sample Stackby to Google Sheets import:

Suppose you want to pull data from more than one table. To do so, copy the configuration and paste it below the current one, leaving at least one row empty. 

Due to the CONCATENATE function, the IDs of your initial stack and board will also be imported even though we don’t need them here. Delete the URL of the second importer and insert one manually, following this format:

https://stackby.com/api/betav1/rowlist/STACK_ID/TABLE_ID

Then, press the refresh button in the Coupler.io dashboard so that both importers will be loaded. You can then run them individually or both at once.

You can add as many importers as you’d like this way but be sure to keep them all in the Datasource Index tab.

Stackby to Google Sheets – saving the importer

If you’re happy with either of the importers, you probably want it to run regularly and fetch any updates from your boards. To do so and set up a schedule, you need to save your importer.

Saving the importer will also allow you to import the data to another spreadsheet, even on another Google account. Better yet, you may also choose to import Stackby data to Excel or BigQuery if you would like.

To save either of the importers, click the three-dots next to it and then Edit.

The interface will load. Log in to the account where your data will be transferred. Then, choose the spreadsheet and sheet for the imports.

Lastly, decide on the schedule that your imports should follow and press the Save and Run button.

The importer will run as usual and quickly transfer the results to the chosen spreadsheet. The configuration will also disappear from the Datasource Index tab. This is done to avoid creating duplicates. If you’d like to change the file or setup, press the Back button and edit the configuration accordingly.

You’ll find all the saved importers in your Coupler.io dashboard

Stackby to Google Sheets integration – customization

When setting up an importer, you may be interested in pulling only some of the data from your board, not all of it. You can do this by setting up proper filtering criteria.

In the configuration file find the queryParams fields. To the right, we were thus far specifying the maximum number of rows to import. We can add some more filters now.

To start, run the importer with the current filters if you haven’t done so yet. It will be useful to see exactly which fields are fetched with the import. For example, the default Channels board contains different channels with the spendings for each.

Note: The ‘field.’ prefix is added by Coupler.io when it imports the data. When specifying the filter criteria, omit the prefix.

We want to pull just the channels where Total Spent is higher than $400. We’ll remove the current filter and reinsert it manually with the new addition:

maxrecord: 100

maxsize: 100

filter: greaterThan({Total Spent}, 400)

The available operators are: ​​toContains, doesNotContain, equal, notEqual, isEmpty, isNotEmpty, greaterThan, greaterThanEqual, lessThan, lessThanEqual, isExactly, isAnyOf, fileName, and fileType.

To combine multiple filtering criteria, use and/or operators. For example:

filter: greaterThan({Total Spent},400) and lessThan({Total Remaining},1500)

Another thing you can customize is the list of fields to be imported. If you only want some of them, insert the names, comma-separated into the fields field. For example:

Conclusion

With a Coupler.io JSON importer, you can pull data from virtually any Rest API. All you need to provide is the URL, authentication method, and optionally some filters you’d like to deploy. We’ll take care of everything else and run the imports as often as you choose.

Our list of integrations with Google Sheets continues to grow every day. We also add new apps based on requests from our community. If you would like to connect a service you use to Google Sheets, Excel, or BigQuery, let us know via this form. If there’s sufficient demand, we’ll definitely consider adding it to our roadmap.

Thanks for reading!