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Learn how to use the Geckoboard app in Make.com to create scenarios.

Updated over a week ago

Make is a great option to bring your data into Geckoboard easily. It's flexible, affordable, and they also offer a generous free plan that doesn't require billing information on sign up, so you can try it out risk-free.

Geckoboard has an app on Make's platform that integrates with Geckoboard's Datasets API so you can send custom data to your dashboard with no coding required.

How it works

The basic concept is that you can create workflows within Make, called scenarios, that can fetch, send, and manipulate data to and from various services. The individual steps in a scenario are called modules. The image below shows a scenario consisting of three modules.

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A module can retrieve the data you want from a service (using its API). The output of the module is one or more bundles (JSON objects). The "magic" part of Make is using that output as an input value in a subsequent modele. For example, in the above we fetch some conversation data from Help Scout and then choose some of the values to send as values in a Dataset record. This is what lets you "integrate" the apps on their platform.

Existing scenarios

At Geckoboard, we have created scenarios with Airtable, Help Scout, Quickbooks online, OpenWeatherMap, Snowflake and Shopify (and working on a few more), if you are interested in the blueprint for any of these or would like to display data on your dashboard from another service supported by Make, please get in touch.

Building your own scenarios

At its simplest, building a scenario consists of finding the relevant modules - fetch data from service X, do this to it, then send it module Y - connecting them together, and mapping the outputs of one module to the inputs of another.

When developing a scenario, it's useful to see what a module's output bundles look like. To do this, either hit the "Run once" button in the lower left to run the entire scenario, or right click the module you're interested in and select "Run this module only" from the menu:

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All being well, the module will run successfully and you'll see this little thought bubble above it.

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This is where you can see what the module received as input, and what bundles it produced as output.

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The values in these bundles can be used as the input to subsequent modules. When clicking on an input field in a module, you'll be shown everything that's available to be mapped into it:

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To use one of these variables, just select it from the popover menu. The popover menu also has tabs to access built-in functions for doing things like manipulating dates, arrays, text, calculations, etc.

The Geckoboard app in Make

The Geckoboard app in Make integrates with Geckoboard's Datasets API. Before you can send data to Geckoboard, you first need to create a Dataset to store your scenario's output.

You can either create the Dataset via the command line (if you're familiar with our API already) or using the Create a Dataset module in Make. We recommend the latter for simplicity.

A Dataset needs a name and a schema, which is what describes the structure of the dataset. The Create a Dataset module gives you a nice UI for doing this, as well as setting the various schema options like whether that field can be empty, and whether it should be part of the Dataset's unique key.

Once you've filled out the Create a Dataset module, right click the module and select "Run this module only" to create the Dataset. You'll need to do this before setting up the Add Record to Dataset module, as that module only lets you select from Datasets that already exist.

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The Add Record to Dataset module is much simpler - select your desired Dataset and you'll see an input for each field. You can then map values from previous steps into these fields.

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Tip: If you're going to be modifying the schema a lot, add the Delete a Dataset module just before the Create a Dataset module. You can't change a schema once you've made a Dataset, hence needing to delete it first. But remember to remove the Delete module once you're done or you'll keep losing historic data.

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