InsightSquared Revenue Intelligence Platform's Machine Learning currently offers two key models, or answers two key questions: Confidence to Close: What is the confidence that a given opportunity will ‘Close Win’ based on how it is progressing? and Ideal Opportunity Profile: How closely does this deal ‘look like’ deals you typically win? With more to come!

Before a property can be analyzed, it must be categorized by type.

What are Machine Learning Types?

Before you establish a type, you need to understand under which type your data falls. There are seven Machine Learning types available:

・unique: Reserved for things like id’s, URLs, opportunity name. Something that will be mostly unique in the system

・temporal (date or time): Relating to dates like close date, create date, or renewal date

・boolean: if the value is true/false or 1/0 (i.e. opportunity is won)

・picklist: if the value is a single picklist entry (i.e. opportunity stage)

・multi-picklist: if the value can be multiple picklist values (a list)

・numeric: relating to a number value like number of seats or amount

・text: used for free form text like opportunity description or next steps

Establish Machine Learning Type

Establish what type of machine learning fits the data in your CRM.

Go to Settings > All Integrations > Select your CRM
Select Content Settings to open Content Policy List
Click your desired Content Policy from the list to open a Content Policy editor
Click Content Properties, then hover over a property in the list to produce the edit option, click edit
In the Property Mapping window, select the appropriate ML Data Type from the dropdown
Click done, then click finalize