AI predictive lead score is an AI-generated percentage score for contacts that predicts the likelihood of a contact converting to a customer. This score can be used similarly to lead scoring, in your campaigns with segmentation and automated programs.
Unfortunately, this feature is not currently supported for European customers.
Create AI Predictive Lead Score Segments
Create segments based on contacts' AI predictive lead scores. This can be useful to group contacts based on their current level of interest and message those groups with emails tailored to their current likelihood of converting to a customer.
- Go to Contacts > All Contacts.
If you use marketing lists in Act-On, see Creating a Segment and then continue from step 3 below.
- If you want to include all of your contacts, on the left select All Segments and at the top right, click New segment.
If the contacts you want are already in an existing segment, such as contacts associated with a specific campaign, hover over that segment, click (More actions), and select Create subsegment( (more information here). - Name your new segment and select the Method 'Query'.
- Select the query method Score, choose AI predictive score, and select the criteria you want:
- Set any other criteria you want for the segment. For example, here criteria are set so the segment will contain contacts with AI predictive scores between 25 and 49:
- At the top left, click Save to create your segment and click OK to confirm.
- If you want, create more segments to divide your contacts into different AI predictive scores, for example:
Use AI Predictive Lead Score Segments in Automated Programs
Now, using these segments, you can create an Automated Program to send tailored emails based on the contacts' current likelihood of converting to a customer. For more on this strategy, see Marketing Automation Strategy.
- First, create the tailored emails. For example, one for each of the three positions in the funnel (top, middle, and bottom) and one for MQLs.
- Then create an Automated Program using branches to send the tailored emails based on the contacts' AI predictive lead scores, and an early exit condition for MQLs. For example:
When the Automated Program runs, your tailored emails are sent to contacts based on their AI predictive lead score.