Contacts

Determine likelihood to close with predictive lead scoring

Last updated: November 15, 2018

Applies to:

Marketing Hub
marketing-enterprise
Enterprise
Sales Hub
sales-enterprise
Enterprise

The Likelihood to close and Contact priority properties in your HubSpot Marketing Hub Enterprise or Sales Hub Enterprise account allow you to predict which of your contacts are most likely to become customers.

Likelihood to close and Contact priority properties

In your HubSpot account, click the settings icon settings in the main navigation bar. In the left sidebar menu, navigate to Properties. In the Contact Information property group, you'll find two properties related to predictive lead scoring: Likelihood to close and Contact priority.

  • Likelihood to close: a score that represents the percentage probability of a contact closing as a customer within the next 90 days, and is based on standard contact properties and behavior. For example, contacts with a close probability value of 22 have a 22% chance of closing as a customer in the next 90 days.
  • Contact priority: a category of contacts based on the Likehood to close score. The categories are Very High, High, Medium, Low and Closed won.
    • The categories Very High, High, Medium and Low each will contain 25% of your contacts based on the Likelihood to close score, with the Very High category having the top 25%.
    • The Closed won category is for contacts whose lifecycle stage is Customer.
    • Because the categories are relative groupings, it’s possible that the range of scores in each category shifts over time.
    • If you have a newer HubSpot account, you may see lower scores in the top tier. As more data accumulates on your contacts and customers over time, you may see higher scores in the top tier. These categories can be used as CRM filters to segment your best and/or worst leads.

Please note: you need at least 100 contacts in your HubSpot account to see values for the Contact priority property.

Scoring contacts

Using predictive machine learning algorithms, HubSpot analyzes your customers and industry customer sets to determine the probability that your open contacts will close as customers within 90 days. To do this, HubSpot looks at the following data:

  • Demographic information contained in standard contact properties (custom properties are not used in determining close probability)
  • Firmographic information provided by HubSpot Insights about the contact’s company 
  • Firmographic information about your business and HubSpot account
  • Interactions logged in the HubSpot CRM, such as tracked email clicks, meetings booked, calls made, etc.

If you have a HubSpot Marketing Hub account, HubSpot will also use relevant marketing data to determine close probability for your contacts:

  • Web analytics data
  • Marketing email interactions
  • Form submission events

How do specific properties influence my contacts' scores?

HubSpot uses the most current predictive machine learning algorithms to provide accurate predictions. These algorithms are known as black boxes. With a black box, data scientists understand the input and outputs of the model, but how the input is transformed into the output is unknown. The benefit of these models is that they’ve been proven to outperform white boxes, but it is not possible to break down how each individual input contributes to a contact’s score. Instead, the focus is on the overall predictive performance of the model.

Use predictive lead scoring information to prioritize contact outreach

To learn how to use lead scoring to prioritize your outreach efforts, check out the HubSpot Academy lesson on Understanding HubSpot Lead Scoring.

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