Lead scoring
This article explains how to set up a lead scoring system in FirstQuadrant using custom properties enriched by AI. It covers the difference between demographic and behavioral inputs, how to define and calculate a score, and how to use these scores for segmentation via Views.
A lead scoring system is a method used in sales and marketing to rank prospects based on their likelihood of converting into paying customers. In FirstQuadrant, you can build this scoring system using custom properties, enriched and maintained by the platform’s AI.
What is lead scoring?
Lead scoring assigns numerical values to contacts based on:
- Demographic and firmographic data: e.g. job title, company size, location, industry, revenue
- Behavioral signals: e.g. signed up on your site, requested a demo, visited key pages
These scores help you segment leads into categories like hot, warm, or cold — allowing you to prioritize outreach efforts effectively.
How to create a lead score property
- Navigate to any contact in FirstQuadrant.
- In the context panel, click “Add property” and then select “Create new property.”
- In the creation panel:
- Property type: Select
Number
- Property name: e.g. “Lead score”
- Property type: Select
- Toggle on “Enrich with AI”
- Choose “All contacts”
- For Source, select “Enrich from internal data”
Define your scoring system
In the Advanced > Description field, explain how the score should be calculated. For example:
The AI will then automatically analyze the available internal data to calculate a score accordingly.
Important: For this system to work, the behavioral data (like signups or demo requests) needs to be sent to FirstQuadrant via the API or Webhooks. For example, signing up on your site should trigger a note or event in FirstQuadrant that the AI can read and process. Additionally, any demographic or firmographic data used in scoring (such as company size, industry, or job title) may first need to be enriched via separate properties, as well.
Using lead score for segmentation
Once your lead score property is live and populated, you can use the Views feature to filter and segment contacts based on their score — for example:
Lead score > 60
→ Hot leadsLead score between 30 and 60
→ Warm leadsLead score < 30
→ Cold leads
This allows you to run targeted campaigns, exports, or nurturing flows.
See the dedicated helpdesk article on Views and segmentation for detailed instructions on setting up filters.