You've been building your LinkedIn network for years. Connecting after every conference, every job change, every interesting conversation. But here's what nobody tells you about professional relationships: they have a half-life.
The half-life model
In physics, half-life describes the rate at which a radioactive substance decays. The concept maps surprisingly well to professional relationships.
Operationally: a relationship loses approximately 50% of its warmth every 90 days without meaningful interaction.
The formula: Score = 100 × 0.5^(days_since_interaction / 90)
Run this against your connections and the picture gets uncomfortable:
Contact you met at a conference 6 months ago, had one follow-up call, never connected again: warmth score ≈ 25%. Red zone.
Colleague you worked with closely 2 years ago, occasional LinkedIn likes since: warmth score ≈ 6%. Functionally cold.
Someone you had a genuine conversation with 3 weeks ago: warmth score ≈ 79%. Green zone.
Most people's LinkedIn network, when scored this way, looks like: 10% green, 30% yellow, 60% red.
Why this matters for outreach
Cold outreach to red-zone contacts fails at a much higher rate than warm outreach to yellow-zone contacts — not because the relationship is dead, but because you're reaching out with nothing specific to say.
The half-life model solves the "who should I contact" problem. But you still need to solve "what should I say."
The reconnection intelligence problem
When you look at a contact you haven't spoken to in 14 months and try to write a reconnection message, you're essentially writing cold outreach to someone who vaguely remembers you. The default result is either:
a) Generic ("Hey, it's been a while! Would love to catch up")
b) Nothing — you stare at the blank message box and move on
What actually works: a message that references something specific and recent about them. Their company announcement. A post they made. An industry shift that affects their role. This requires research, and research takes time, which is why most people do nothing.
Building a system around this
The basic system I've implemented:
Calculate half-life scores for all connections (based on last interaction date)
Sort by score to identify red and yellow zone contacts
For each red-zone contact, pull recent context: current company news, any public digital footprint (blog, GitHub, LinkedIn activity)
Generate a personalized reconnection message that leads with the specific context
Calendar the follow-up
This turns "I should probably reach out to some people" into a weekly workflow with specific contacts, specific context, and specific copy.
The half-life model alone won't rebuild your network. But it will tell you exactly where to start.
I built this model into SocialCraft AI's LinkedIn Network Intelligence feature — if you want to see the half-life scoring in action against your actual connections, you can upload a LinkedIn CSV export at
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