Account Signals & Interaction Orbit
AutoReach tracks two layers of buying behavior beyond what leads explicitly post about: Interaction Orbit (individual engagement patterns) and Account-Level Signal Aggregation (company-wide purchase intent).
Interaction Orbit (Dark Funnel)
Interaction Orbit detects buying behavior revealed through who leads engage with on social media.
How It Works
AutoReach tracks who each lead replies to on social media. When a lead replies to posts from specific accounts, those accounts become "orbit targets." The system builds a map of engagement targets per platform, tracking interaction count and first/last seen dates.
Target Classification
Each orbit target is classified into categories like Competitor, Adjacent Vendor, Thought Leader, or Peer using your offer's competitor list and AI analysis.
Cluster Detection
Orbit targets are grouped into clusters - collections of related accounts a lead engages with together within a recent time window.
Example: A prospect replies to 3 data warehouse companies and 2 BI tool accounts in a short period, forming a "data stack evaluation" cluster.
When a new cluster forms, it generates an orbit signal that feeds into buyer scoring. Competitor clusters are the strongest signal, as they indicate active evaluation of solutions in your space.
Lead Profile Integration
When orbit data is available, the lead profile shows:
Orbit targets - accounts the lead engages with
Clusters detected - groups of related engagement targets
Cluster velocity - engagement frequency (interactions per week)
Privacy
Interaction Orbit only tracks public engagement - public replies, likes, and follows. Private DMs and conversations are never tracked. This is equivalent to what you would manually discover by viewing someone's social activity.
Account-Level Signal Aggregation
Account-Level Signal Aggregation combines buying signals from multiple leads at the same company into a single heat score - an indicator of company-wide purchase intent.
How Heat Score Works
The heat score reflects the overall buying intent at a company. It factors in:
Signal strength: Stronger signals (like asking for recommendations) contribute more than weaker ones (like a single post like)
Recency: Recent signals carry more weight than older ones
Team breadth: Signals from multiple people at the same company are a stronger indicator than signals from just one person
Company Identification
Companies are identified by LinkedIn company ID (preferred) or normalized company name. Generic values like self-employed, freelance, or consultant are filtered out.
Only companies with 2 or more leads are included in heat scoring.
Signal Types
The following signal types are aggregated across all leads at a company:
Competitor Engagement
Engaging with competitor accounts
Engagement Pattern
Category research patterns
Orbit Cluster
Dark funnel cluster detection
Hiring
Company hiring signals
Tool Mention
Mentions of tools or technologies
Switching
Signals of switching or evaluation
Alternative Search
Searching for alternatives
Asked Recommendation
Asked network for recommendations
Funding
Funding rounds
Pain Match
Matches a pain point your solution addresses
Product Launch
Product launches
Mergers and Acquisitions
M&A activity
Geographic Expansion
Geographic expansion
Cost Cutting
Budget pressure signals
IPO Filing
IPO filings
Complained
Complained about a problem you solve
Custom Intent
Custom intent signal from your ICP
Own Post Engagement
Engaged with your posts
Own Post Reply
Replied to your posts
Own Post Repeat Engagement
Engaged with your posts multiple times
Heat Categories
Hot
Strong, multi-threaded signals across the company
Urgent, coordinated outreach
Warm
Consistent signals from diverse team members
Priority outreach
Cool
Light or isolated signals
Standard cadence
Heat Trend
Rising
Score increasing day-over-day
Stable
Score flat
Cooling
Score decreasing
Next Steps
Buyer Intelligence: How individual lead scoring works
Analytics: Track overall pipeline performance
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