Help Scout to Google BigQuery

Automatically Export & Sync Help Scout Data to Google BigQuery

Help Scout
a black arrow pointing to the right
Google BigQuery
Conjuntos de datos completos
No se necesitan instrucciones
Sin código
Sin diagramas de flujo complicados
Sin desencadenantes
Se configura en menos de 3 minutos
Flat pricing starting at $19 /month

Conjuntos de datos

CompanyReport-Last X days
Date Rangable
Conversations-Last X days+Threads
Date Rangable
Filterable
Pre-blended combo set CONVERSATION-THREADS
Customers-Alltime
Customers-Last X days
Date Rangable

Información adicional

This service is designed to help anyone continuously export (i.e. "sync") bulk data from Help Scout.

If you only need to export your data one time, check the website of Help Scout to see if their service offers a one-time export feature natively. Sometimes a Data Source's native export feature may provide not as much data as its API does, in which case Flatly is the solution.

Additional Information

Flatly uses official API channels to provide an integration with Help Scout.
Help Scout is a provider of help desk software headquartered in Boston Massachusetts.
Scopes

Flatly's access to Plaid and Plaid's downstream connected financial institutions is read-only access to text. It is limited to account data (words, numbers, dates). It does not include any money-movement, transfer capabilities or account holder profiles/identities.

Plaid alone interfaces directly with financial institutions, caches data from those institutions on Plaid infrastructure, and then makes the appropriate scoped subset of that data available to partners like Flatly using secure connections called client libraries.

Looker reads tables from Google BigQuery.

Formatos de archivo

NDJSON

Integration Flow

Setup

Step 1

Select Help Scout from the Data Source dropdown and Google BigQuery from the Data Destination dropdown.

Step 2

Authorize Help Scout with your credentials using the flow.

Step 3

Authorize Google BigQuery with your credentials using the flow.

Step 4

Select your Data Set from the 4 Data Sets available using the dropdown.

Step 5

Click Flatten to sync your data.

Vídeo tutorial

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