If you're purchasing intent data from Clearbit Reveal, G2Crowd, ZoomInfo Intent, Bombora...etc, you have access to data like "someone from this domain showed interest in this solution or visited this content", but you don't have access to the email of this anonymous visitor. Since MadKudu scores accounts based on the activities of emails attached to the account (and not from anonymous people), you'll need to associate an anonymous email to this intent data for MadKudu to be able to take it into account in the scoring. 

Here's how. 

Before we start...

Why use intent data?

Intent Data represents the data collected from potential buyers' digital footprint when searching the web, visiting industry websites, downloading whitepapers, etc. Over time, as this digital footprint becomes larger, it signals a likelihood that they are progressing through their buyer’s journey and will likely be receptive to an approach from your marketing and sales team. 

What are the types of existing intent data?

Intent data is recorded and tracked with cookies, based on visitors' IP addresses, when they visit your website (first-party) or other websites (third-party). You may be using a tool like Clearbit Reveal to de-anonymize your anonymous web traffic or you may be purchasing 3rd party intent data directly from providers like G2Crowd who gather browsing activity on B2B reviews. Both types are relevant but provide different types of information: first-party intent data tells you who already has knowledge of your brand and what they're interested in knowing from you, while third-party intent data may tell you which other solutions they are looking at. 

When to use intent data?

If you are interested in scoring your accounts based on their activity to identify which ones are showing readiness to buy, you may be considering including intent data. However, you should consider where in the funnel and in which motions you'll want to use this segmentation: if you are trying to surface product-qualified accounts (PQA) to your Sales team for expansion, intent data would provide a much lower signal than product usage. On the other hand, if you are trying to surface accounts for your marketing team to get them to engage with your brand, then intent data may come in handy.  

How to include Intent data into MadKudu scoring?

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 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: Send your intent data to MadKudu through S3 

1. Create an Amazon S3 bucket 
2. 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...)

3. Grant MadKudu access to your S3 bucket 
4. Contact the support team who will finish the setup and follow up with you to validate the format.   

Step 2: Map these events in the Event Mapping 

Once our team has confirmed the data is pulled from S3 and available on the platform, you'll be able to add these events to the Event mapping from S3. 

Here's the article to learn how.

Step 3: Include new events in your Account Likelihood to Buy model 

After updating the event mapping, 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.