Documentation
GitHubDiscordIdeas

HubSpot

The Hubspot Data Connector allows you to seamlessly integrate and synchronize data from your Hubspot account into Mantium. Hubspot is a popular inbound marketing, sales, and customer service platform that helps businesses grow better. With this data connector, you can access, analyze, and manipulate your Hubspot data.

Suggest Edits

Features

FeaturesSupportedNotes
Re-SyncingYes1 Hour
12 Hour
24 Hour
Weekly
Monthly
HistoryYesUnlimited
FieldsYescreated_at, updated_at, address, city, company, country, createdate, email, firstname, hs_lead_status, industry, jobtitle, lastmodifieddate, lastname, lifecyclestage, mobilephone, phone, salutation, state, zip
API ConfigurableYesContract Us

Setup Instructions

To set up the Hubspot Data Connector with Mantium, follow these steps:

  1. Log in to your Mantium account.
  2. Navigate to the Connectors section.
  3. Click on "Add Connector" and select "Hubspot" from the list.
  4. Click on "Connect to Hubspot" to start the OAuth process.
  5. You will be redirected to the Hubspot login page. Enter your Hubspot account credentials and grant the necessary permissions for Mantium to access your data.
  6. Once the authorization is successful, you will be redirected back to Mantium, and the Hubspot Data Connector will be added to your list of connected data sources.

Recommended Transformations & Enrichments

  • Element Count: Analyze the frequency of words in the address, city, company, country, email, firstname, industry, jobtitle, lastname, lifecyclestage, state, and zip columns.

  • Generate Text: Create a human-readable summary of each row using the firstname, lastname, jobtitle, company, and industry columns.

  • Summarization: Summarize long text fields like address or company description.

  • Create Column: Create new columns based on existing data, such as calculating the age of a contact or the number of days since the last interaction.

  • Rename Column: Rename columns for easier understanding or to comply with specific naming conventions.

  • Split Text: Split the email column into separate username and domain columns.

  • Clean Text: Remove unwanted characters or formatting from the address, city, company, country, email, firstname, industry, jobtitle, lastname, lifecyclestage, state, and zip columns.

  • Generate Embeddings: Create embeddings for text fields like jobtitle and industry to use for machine learning or clustering purposes.

  • Delete Columns: Remove unnecessary columns that are not needed for analysis.

  • Reformat CSV: Adjust the CSV format as required, including delimiters and encoding.

  • Columnize CSV: Convert a single column of CSV data into multiple columns for easier analysis.

Updated over 1 year ago

What’s Next