This article supports Gainsight NXT, the next evolution of the Customer Success platform. If you are using Gainsight CS Salesforce Edition, you can find supporting documentation by visiting the home page, and selecting CS > Salesforce Edition.
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IMPORTANT NOTE: Gainsight is upgrading Connectors 2.0 with Horizon Experience. This article applies to tenants which have been upgraded to the Horizon Experience for Connectors 2.0. If you are using Connectors 2.0 with the previous version, you can find the documentation here.
This article explains to admins about how to create a connection from Gainsight to Pipedrive, create a data job, merge datasets, and configure job or Job chain schedules in Gainsight.
Note: This document provides general guidance on creating a Connection and setting up Jobs because the use case of each job is different and needs unique configuration. For detailed information on creating the required Job or Job Chain, refer to the Configuration of Connectors Path in the Additional Resources section at the end of this article.
Pipedrive is a Sales CRM product that enables businesses to plan their sales activities and monitor deals.
Gainsight integration with Pipedrive allows you to sync data from source objects like Deals, Accounts, Contacts, and custom objects from the Pipedrive system to Gainsight.
Benefits of Pipedrive integration:
Pipedrive integration extends the power of Gainsight NXT to customers who are also using Pipedrive CRM, without onboarding through an S3 or API based approach.
Admins can integrate Gainsight with Pipedrive and sync data from objects like Deals, Accounts, Contacts, etc., and benefit from business solutions offered by Gainsight, like Renewal Management, Customer Health Scoring, Customer 360 view, creating Reports, etc.
To create a connection with Pipedrive to sync data with Gainsight:
- Navigate to Administration > Connectors 2.0.
- Click Create Connection. Create Connection dialog appears.
- Select Pipedrive in the Connector dropdown list.
- Enter name of the connection.
- Click Authorize to validate the connection. The Pipedrive login page opens in a new tab.
- Enter your Pipedrive org credentials. You can also complete Authorization through Google, LinkedIn, and SSO that are integrated with Pipedrive.
- Click Login.
Pipedrive’s access grant page is displayed with a list of all the types of data that can be synced with Gainsight such as Deals, Accounts, Contacts, Users, and custom objects.
For more information, refer to the Connections List Page in the Additional Resources section at the end of this article.
Create a Job
Create jobs from the Jobs page to sync data from required source objects like Deals, Accounts, Contacts, Users, and any custom objects with Gainsight. Create a dataset from one source object, and similarly create multiple datasets to create a Job. For more information, refer to the Preparation of Connector Jobs in the Additional Resources section at the end of this article.
Note: (Optional) Create multiple data jobs, as required. If the data jobs in a connection are dependent on each other, create a Job chain and configure the schedule to the Job Chain. For more information, refer to the Job Chain Page in the Additional Resources section at the end of this article.
Merge two datasets together and create an output dataset. For example, merge Deals and Account objects to collect the business deals stored for each Account with their details and work on them to provide a better customer experience. For more information on Merge, refer to the Preparation of Connector Jobs in the Additional Resources section at the end of this article.
In the Preparation step of a connector job, admins can Transform data and Add Case Fields to get more meaningful insights from the customer data.
Example Business use case: The Transform function provides the capability to create or modify new case fields. The new case fields can be used to modify the external field as per the consumption requirement in Gainsight’s data model. Case fields can be defined to populate different values for different case conditions. For example, External picklist values such as New, Open, and Closed can be modified to Active and Inactive to match Gainsight’s picklist values.
For more information on Transform Data, refer to the Preparation of Connector Jobs in the Additional Resources section at the end of this article.
Once the final output dataset is prepared, add a destination to the output dataset to sync data from the source to the target Gainsight object. For more information on Add Destination, refer to the Preparation of Connector Jobs in the Additional Resources section at the end of this article.
In the Direct Mapping, map fields from the output dataset to the target object in the field mappings. Data sync happens from the source fields of the external system to the target fields of Gainsight, per field mappings. For more information on Direct Mapping, refer to the Preparation of Connector Jobs in the Additional Resources section at the end of this article.
This is optional and you must configure the derived mappings only if you want to populate values into the target fields of data type GSID. GSID values are populated from the same or another object through lookup. In this stage, create Lookup mapping in a data sync job. You can have a lookup to the same object or another standard object and match up to six columns. Once the required matching is performed, fetch Gainsight IDs (GSIDs) from the lookup object into GSID data type fields. For more information on the derived mappings, refer to the Preparation of Connector Jobs in the Additional Resource section at the end of this article.
Note: To use Derived Mappings, your target object must have at least one field of data type GSID.
Configure Job or Job Chain Schedule
Configure the schedule of a data job or Job chain as required. For more information, refer to the Configure Job or Job Chain Schedule in the Additional Resources section at the end of this article.
View the Execution and Update Activities of all the data jobs in the Activity page. Download the logs of the job execution from this page to help troubleshooting the configuration issues. For more information, refer to the Activity Page in the Additional Resources section at the end of this article.