Coupler.io data source

Note: the selected importer should meet the following criteria:

1. The importer should have at least 1 successful run
2. No errors in the importer 

Otherwise, the next error will be shown in the Transform data step and as a result importer run will fail.

Let's imagine our user is a Sales manager who is monitoring the performance of the employees (sales) and wants to see daily reports of the active deals. 

Here are the steps to get reports quickly and easily:

1. Create an importer based on (e.g. Hubspot) source with the raw data and name it (e.g. "Hubspot Deals data").
2. Run "Hubspot Deals data".
3. Create an importer based on the Coupler.io source (using "Hubspot Deals data" importer) and name it "Hubspot active deals_employee name".
4. Apply transformations such as:
   1. filtering by employee name, deals, etc.
   2. filtering by active deals
   3. sorting
   4. any other transformations
5. Copy the importer, fix transformations for another employee (filter by the correct employee, etc.). Repeat this action as many times as you need (for each employee).
6. Setup destinations
   1. for instance Google Sheets with the sheet associated with the employee. New importer (employee) - new sheet
7. Enable scheduler for importers.
8. Setup webhook to run dependent importers (per employee) after the main one.

Result:

1. We have 1 importer ("Hubspot Deals data") which fetches data. So there is no need to re-fetch data for each new employee's importer. It also speeds up the process.
2. We have separate importers per employee. Which can be easily updated or removed.
3. We have the destination file with the data on the sheets for each employee.
4. All importers are running smoothly depending on the main one.

Let's imagine our user is a Marketing manager who wants to unite data from different channels and join united data with the financial expenses

Here are the steps to get reports quickly and easily:

1. Create an importer based on several Ads sources: Facebook Ads, Google Ads, etc., and name it (e.g. "United Ads data").
2. Run the "United Ads data" importer.
3. Create an importer based on the Coupler.io source (using "United Ads data" importer) and one more source that stores expense data (e.g. Salesforce).
4. Apply Data Join between Coupler.io and Salesforce.
5. Apply other transformations if needed.
6. Setup destination
   1. for instance Looker Studio
7. Enable scheduler for importers.
8. Setup webhook to run the importer with JOIN after the "United Ads data" importer.

Result: 

We have 1 importer both with united data from all the channels and joined with the expense source.