How to send intent data in MadKudu from your data warehouse Snowflake, BigQuery or via S3?

  • Updated on Oct 28, 2024
  • Published on Oct 10, 2024
  • 2 minute(s) read

Previous article: How to integrate intent data to MadKudu?

If you have intent data sitting in your data warehouse that you'd like to leverage in MadKudu, please follow these steps. 

Format

To ingest Intent data, MadKudu needs the same format as other tracking tools like 

email  | event | event_timestamp | event_key 

which represent "someone did something on that date" that shows intent. 

If there is no date associated with the intent data it won't be usable since the intent is related to a point in time. 

With intent data, you usually don't get the email of the person, but just the domain associated with the IP. Therefore you'll need to transform the domain to "anonymous@domain.com" to send an email. 

Connector

Whether this data already sits in your data warehouse or in other tools, the way to send it to MadKudu is through our native integration with Snowflake, BigQuery, or Amazon S3. 

 

Step by step

We're here to help! Our support team will be happy to walk you through these steps, just contact the team here. 

Step 1: Format your data

  1. Stream your event data with the format email | event | event_timestamp | event_key. Learn more about the supported format. 

    Attribute

     

    Format

    Example

    Description

    event_key

    required

    String

    "abc123"

    A unique key identifying the event. If you do not have one, we suggest creating a combination of event_text + contact_key + event_timestamp

    event_text

    required

    String

    “signup”, “login”, “invited a friend”

    The action taken by the user.

    event_timestamp

    required

    Unix time

    “1436172703”

    The time at which the event happened

    email

    required

    String

     

    "anonymous@domain.com"

    The unique identifier of the visitor who showed intent.

    to create an email, you can append 'anonymous@' in front of each domain.

    event_*

    optional

    String or Numeric

     

    additional properties describing the event (e.g. event_url for the url of visited page, event_form_title for the title of form submitted...)

Step 2: Connect your source (Snowflake, BigQuery or S3) to MadKudu 

Please follow the instructions for

Step 3: Map these events in the Event Mapping 

Once MadKudu is pulled data from your source you'll be able to add these events to the Event mapping. 

Here's the article to learn how.

 

Step 4: Start leveraging your data!

In MadKudu Copilot

Once the event mapping is published, these intent events will automatically show in MadKudu Copilot in the

  • Account Intelligence: in the activity feed

  • Playbooks & Explore: available to use as filters to create playbooks or views

In MadKudu Scoring

If you have an Account Engagement model pushed to Salesforce, the signals field will also update automatically. To assign weight to these events, follow the usual steps to include new events to the Account Likelihood to buy model: 

  1. Duplicate your live Account Likelihood to Buy model 

  2. Load a fresh dataset 

  3. You should now see the new events in the Insights and Event Weights section. You can adjust the weight and decay.