Overview
The Intent Scoring endpoints use semantic ranking to help you prioritize which companies and contacts to reach out to first. By analyzing signal data, the API scores each entity based on how closely their recent activity aligns with your ideal buying signals.
Credit cost: 5 credits per intent scoring request. This is higher than standard endpoints because intent scoring performs deep semantic analysis across multiple signals for each entity.
Score Company Intent
Endpoint: POST https://signals.autobound.ai/v1/intent/companies
Ranks companies by intent based on their recent signals. Pass a list of company domains and a description of the buying behavior you are looking for.
Score Contact Intent
Endpoint: POST https://signals.autobound.ai/v1/intent/contacts
Ranks individual contacts by intent using the same semantic scoring approach.
How Intent Scoring Works
The scoring process evaluates signals associated with each entity against your intent criteria. Each entity receives a relevance score from 0 to 1, with higher scores indicating stronger alignment with the buying behavior you specified.
Use Cases
Pipeline prioritization: Score your existing pipeline to identify which accounts are showing the strongest buying signals right now
Account-based marketing: Rank target accounts by intent to focus ad spend and outreach on the most active buyers
Lead scoring: Combine intent scores with your existing lead scoring models for a more complete picture
Territory planning: Identify which accounts in a territory are currently most active
Tips
Be specific with your intent description for more accurate scoring
Combine intent scoring with signal type filters to focus on the signals most relevant to your sales motion
Re-score periodically as new signals are detected to keep your prioritization current