The Likelihood to close and Contact priority properties in your HubSpot Sales Professional account allow you to see which of your contacts are most likely to become customers. Here you can learn more about what these properties mean and how they're calculated.
What do each of the properties mean?
The Likelihood to close property is a score that represents the percentage probability of a contact closing as a customer within the next 90 days. For example, contacts with a close probability value of 22 have a 22% chance of becoming a customer in the next 90 days.
The Contact priority property represents four equally-sized tiers of your contacts. Tier 1 will always contain the top 25% of contacts based on close probability. Because the tiers are relative groupings, it’s possible that the range of scores in each tier will shift over time. If you have a newer HubSpot account, you may see lower scores in the top tier. Then, as more data accumulates on your contacts and customers over time, you may see higher scores in the top tier. Tiers are especially useful for saving CRM filters to segment your best and/or worst leads.
Please note: you must have at least 100 contacts in your HubSpot account to see values for the Contact priority property.
How does it work?
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 (please note that custom contact 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.
- Web analytics data (if available)
- Marketing email interactions (if available)
- Form submission events (if available)
If you have a HubSpot Marketing account, HubSpot will also use marketing data (web analytics, marketing emails history, and form submissions) to determine close probability for your contacts.
How do specific properties influence the scores of my contacts?
HubSpot uses the most modern and 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.