How to set up HubSpot to Tableau Integration

Tableau is a powerful tool that helps organizations analyze and visualize their data.

In this article, we will talk about analyzing your HubSpot data with Tableau and the 2 different methods that can be used for HubSpot Tableau Integration.

The Sales, Marketing, and Customer data are invaluable in terms of analysis. Organizations can depend on the insights obtained from it to make conscious data-driven decisions.

What is HubSpot?

• HubSpot provides Sales, Marketing, Content Management, and Customer Support Services for software technologies.
• It houses some amazing tools that can help optimize your content using SEO to rank better in Google search results.

What is Tableau?

• Tableau is a Business Intelligence platform that helps you analyze your data and visualize it in the form of various charts and graphs.
• These visualizations help you understand your data better, derive insights, and make business decisions.

Prerequisites

• A HubSpot developer account.
• A Tableau account.

Manual Method to Connect HubSpot Tableau Integration

• Step 1: Install the Client Library
• Step 2: Get the Authentication Key
• Step 3: Identify the Required API
• Step 4: Implement the API Call
• Step 5: Prepare the HubSpot Data
• Step 6: Move the Data into Tableau

Step 1: Install the Client Library

Given below are the different client libraries supported by HubSpot. Install the library from the links given below that you want to use to make API call:

Language	Package Link
Node.js	https://www.npmjs.com/package/@HubSpot/apiclient
PHP	https://packagist.org/packages/HubSpot/apiclient
Ruby	https://rubygems.org/gems/HubSpotapiclient
Python	https://pypi.org/project/HubSpotapiclient/

Step 2: Get the Authentication Key

• Log in to your HubSpot developer account. Click the settings icon in the main navigation bar. Now move your mouse to Integrations and click on the API key.
• If a key hasn’t been generated click Generate an API key option. If there is an active key, click on Show and a window will pop up with the API key. 

Step 3: Identify the Required API

• Once you install a client library, you need to identify the API call from the HubSpot resource. For fetching different data HubSpot provides different APIs.
• You can use GET, POST, PUT and DELETE methods for the same.
• For example, to fetch all lead-specific data using the contacts API, we need to use GET /contacts/v1/lists/all/contacts/all method. Refer official page to view implementation using different clients.

Step 4: Implement the API Call

• In this article, an API call has been made using a Python client. All the HubSpot API calls return data in JSON format.

Sample Python code:

import requests
import json
import urllib

max_results = 500 
hapikey = 'demo' 
count = 5 
contact_list = []
property_list = []
get_all_contacts_url = "https://api.hubapi.com/contacts/v1/lists/all/contacts/all?"
parameter_dict = {'hapikey': hapikey, 'count': count}
#type your Authentication key in place of hapikey
headers = {}

# Paginate your request using offset
has_more = True
while has_more:
	parameters = urllib.urlencode(parameter_dict)
	get_url = get_all_contacts_url + parameters
	r = requests.get(url= get_url, headers = headers)
	response_dict = json.loads(r.text)
	has_more = response_dict['hasmore']
	contact_list.extend(response_dict['contacts'])
	parameter_dict['vidOffset']= response_dict['vidoffset']
	if len(contact_list) >= max_results: # Exit pagination, based on whatever value you've set your max results variable to. 
		print('maximum number of results exceeded')
		break
print('loop finished')

list_length = len(contact_list) 

print("You've succesfully parsed through {} contact records and added them to a list".format(list_length))

Step 5: Prepare the HubSpot Data

Sample Response Data: Here data is extracted in JSON format.

Example response:
{
  "contacts": [
    {
      "addedAt": 1390574181854,
      "vid": 204727,
      "canonicalvid": 204727,
      "mergedvids": [
        
      ],
      "portalid": 62515,
      "iscontact": true,
      "properties": {
        "firstname": {
          "value": "Bob"
        },
        "lastmodifieddate": {
          "value": "1483461406481"
        },
        "company": {
          "value": ""
        },
        "lastname": {
          "value": "Record"
        }
      },
      "formsubmissions": [
        
      ],
      "identityprofiles": [
        {
          "vid": 204727,
          "savedattimestamp": 1476768116149,
          "deletedchangedtimestamp": 0,
          "identities": [
            {
              "type": "LEAD_GUID",
              "value": "f9d728f1dff149b09caa247dbdf5b8b7",
              "timestamp": 1390574181878
            },
            {
              "type": "EMAIL",
              "value": "mgnewemail@HubSpot.com",
              "timestamp": 1476768116137
            }
          ]
        }
      ],
      "mergeaudits": [
        
      ]
    },
    {
      "addedAt": 1392643921079,
      "vid": 207303,
      "canonicalvid": 207303,
      "mergedvids": [
        
      ],
      "portalid": 62515,
      "iscontact": true,
      "properties": {
        "firstname": {
          "value": "Ff_FirstName_0"
        },
        "lastmodifieddate": {
          "value": "1479148429488"
        },
        "lastname": {
          "value": "Ff_LastName_0"
        }
      },
      "formsubmissions": [
        
      ],
      "identityprofiles": [
        {
          "vid": 207303,
          "savedattimestamp": 1392643921090,
          "deletedchangedtimestamp": 0,
          "identities": [
            {
              "type": "EMAIL",
              "value": "email_0be34aebe5@abctest.com",
              "timestamp": 1392643921079
            },
            {
              "type": "LEAD_GUID",
              "value": "058378c6951343e1a13a43a98d47aa22",
              "timestamp": 1392643921082
            }
          ]
        }
      ],
      "mergeaudits": [
        
      ]
    }
  ],
  "hasmore": true,
  "vidoffset": 207303
}

Since the data fetched by the API is in JSON format the data needs to be formatted before moving it into Tableau. For this, you need to identify the schema of the Database or Data Warehouse and specify the data formats according to the data fetched.

Step 6: Move the Data into Tableau

• Your data is now ready for analysis. Create a new workbook in Tableau and load data into it using load data from a data source option.
• Using Tableau, you can analyze this fetched data, and create visualizations and Dashboards.

Conclusion

This article offered valuable insights into HubSpot, Tableau, and the different approaches you can use to set up a HubSpot-Tableau integration. Although it is possible to build the integration manually, the process can be lengthy, intricate, and error-prone. Opting for a streamlined solution can save time, reduce complexity, and minimize the risk of mistakes, enabling you to focus more on leveraging your data effectively.

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