Build a social intent monitoring system that turns public social conversations into qualified outbound triggers. Use when the user wants to monitor LinkedIn, X, Reddit, or other platforms for buying signals — competitor engagement, hiring intent posts, pain-point mentions, funding reactions, or public recommendation requests — and automatically route those signals into outreach workflows. Triggers on: "social listening", "social signals", "monitor LinkedIn for intent", "Trigify", "agentic social listening", "competitor mention monitoring", "social intent", "signal-led outbound", "signal infrastructure", "social buying signals", or any request to detect intent from public social content.
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name
social-intent-monitoring
description
Build a social intent monitoring system that turns public social conversations into qualified outbound triggers. Use when the user wants to monitor LinkedIn, X, Reddit, or other platforms for buying signals — competitor engagement, hiring intent posts, pain-point mentions, funding reactions, or public recommendation requests — and automatically route those signals into outreach workflows. Triggers on: "social listening", "social signals", "monitor LinkedIn for intent", "Trigify", "agentic social listening", "competitor mention monitoring", "social intent", "signal-led outbound", "signal infrastructure", "social buying signals", or any request to detect intent from public social content.
license
MIT
compatibility
Claude Code, Jesse, Codex, Hermes, Windsurf, OpenCode, Gemini CLI, Copilot, Zed, VS Code, Goose
metadata
{"version":"1.0.0","author":"LeadMagic","category":"prospecting","tags":["signals","social-listening","intent","outbound","trigify","agentic"],"related_skills":["signal-scoring","lead-enrichment","hiring-signal-play","multi-channel-outreach"],"frameworks":["Max Mitchum — Signal, Context, Action Framework (Trigify)","Trigify Workflow Patterns — Agentic Social Listening","ColdIQ Signal Taxonomy — Trigger-Based Selling"]}
Social Intent Monitoring
Overview
Most outbound programs are volume-gated rather than timing-gated. Reps build
lists and send sequences regardless of whether anything has actually happened.
Social intent monitoring replaces that model: an AI agent watches public
social conversations continuously, and an email or DM only fires when a
qualifying event occurs in real time.
The mistake this skill prevents: treating social platforms as broadcast
channels rather than signal feeds. Every competitor-mention comment, every
"does anyone have a recommendation for X" post, every founder publicly
describing a problem you solve — these are live intent signals that expire
within 24-72 hours. Catching them and acting fast beats the best cold copy
by a wide margin.
This skill builds the full monitoring architecture: what to watch, how to
qualify signals, how to route them to enrichment and outreach tools, and
how to measure signal quality over time.
When to Use
"Set up social intent monitoring for our target accounts"
"Monitor LinkedIn for people talking about problems we solve"
"Build a Trigify workflow that routes competitor mentions to outreach"
"Detect social buying signals before prospects fill out a form"
"Create a signal infrastructure for our outbound motion"
"How do I use social listening for lead generation?"
"Set up keyword monitoring on LinkedIn and X for intent"
"Automate outreach from social signals"
Authoritative Foundations
Max Mitchum — Signal, Context, Action Framework
Max Mitchum, Co-Founder & CEO of Trigify.io, published the Signal, Context,
Action model as the operating framework for signal-led outbound. The three
layers:
Signal — the public event that suggests an account is worth contacting
now. Examples from Mitchum's 2026 playbook: competitor engagement on LinkedIn
or X, hiring posts for GTM roles, founder or operator posts describing a
problem you solve, funding reactions, pain-point mentions in comments, product
launches in adjacent categories, public recommendation requests.
Context — the judgement layer. Who is this person? What company? Are they
in ICP? Why does this specific event matter? Is the timing strong? A signal
without context is noise; context without a signal is guessing.
Action — the downstream workflow. Enrich the person, find the email,
research the company, draft the message anchored to that specific signal,
push into the sequencer, alert the rep in Slack with the reasoning.
The core principle: the email is the commodity. AI can write decent emails.
The moat is knowing when the email has a reason to exist.
Trigify Workflow Patterns
Trigify's public documentation describes four canonical agentic workflow
patterns for sales and lead generation teams:
ICP-Filtered Post Trigger: New Post Trigger → Person Enrichment →
ICP filter (country, headcount) → Email Enrichment → deliverability check
→ CRM or email campaign push.
Viral Engager Harvesting: Post with high engagement threshold detected
→ fetch all engagers → Person Enrichment → filter for VP/Director titles
→ CRM or agent memory.
Inbound Lead Routing by Seniority: Webhook trigger → Person Enrichment
using LinkedIn URL → seniority check → high-value: Slack alert to sales
team; others: nurture sequence.
ColdIQ's published trigger-selling taxonomy classifies intent signals into
four tiers: Hiring signals, Funding signals, Tech Stack changes, and
Behavioral intent (website visits, content engagement, review site activity).
Social listening adds a fifth tier — Public Conversation signals — not
captured by traditional data providers. Each tier requires different outreach
timing and angle.
Prerequisites
Target account list (CRM, CSV, or HubSpot/Salesforce export)
ICP criteria defined (firmographic + role criteria for signal filtering)
Social listening platform configured (Trigify recommended; alternatives:
Brandwatch, Mention, Keywordsio for simpler setups)
Enrichment provider for email and firmographic lookup (LeadMagic, Apollo,
Clay waterfall)
Outreach tool connected (Instantly, Smartlead, Salesloft, or HubSpot
sequences)
Slack or CRM for internal signal routing and rep alerts
Step-by-Step Process
Phase 1: Define Your Signal Taxonomy
Decide which social signals are worth acting on for your business. Not all
conversations are buying signals. The highest-value signals:
Signal Type
Description
Urgency
Outreach Angle
Competitor engagement
Prospect comments on, likes, or shares competitor content
High — 24-48hr window
Offer comparison, address common pain with that competitor
Problem statement post
Founder or operator publicly describes a problem you solve
High — act within 12 hrs
Reference their exact words; offer a specific solution
Recommendation request
"Does anyone have a recommendation for X?"
Very High — act within 2 hrs
Direct reply + personal DM
Hiring for GTM role
Post about hiring SDR, RevOps, VP Sales — roles your product supports
Medium — 3-5 day window
Tie outreach to the hiring intent; new hires evaluate tools
Funding reaction post
Company or founder posts about closing a round
Medium — 1 week window
Congratulate + connect to common post-funding challenges
Pain-point comment
Target prospect comments on someone else's post about a problem
High — act within 48 hrs
Reference the comment thread; show understanding
Content engagement pattern
Prospect consistently engages with content in your category
Low/Medium — warm long-play
Nurture track; add to account monitoring
Mitchum's rule: only act on signals where you can write a specific, non-generic
opening that references exactly what happened. If the signal can't anchor the
first line of the message, it's not a strong enough trigger.
Phase 2: Configure Social Listening
Using Trigify (full agentic workflow):
Create social listening searches for your target topics, competitors,
and keywords across LinkedIn, X, Reddit, and other configured sources.
Configure Signal types in the Signals tab — buying intent, hiring signals,
competitor mentions, product complaints, leadership changes.
Set score/severity thresholds to filter noise; only fire workflows above
your minimum signal confidence bar.
Set date windows — only act on signals from the past 24-72 hours; stale
signals lose their timing advantage.
Keyword search strategy:
Competitor names + pain phrases ("Competitor X is too expensive", "left
Competitor X")
Problem categories your product solves ("struggling with [problem]", "anyone
solved [problem]")
Recommendation requests ("looking for a tool that does X", "anyone use Y")
Avoid over-broad keywords that generate noise (company names alone,
generic industry terms). Signal quality matters more than signal volume.
Phase 3: Build the Enrichment and Qualification Layer
When a signal fires, the workflow must answer three questions before any
outreach is initiated:
Is this person in ICP? (job title, company size, industry, geography)
Is this company on our target account list? (or does it match ICP
firmographic criteria if not pre-listed?)
Is there a reachable email? (run through email enrichment with
deliverability verification before pushing to sequencer)
Typical workflow node sequence:
Signal Trigger → Person Enrichment (LinkedIn → firmographics + title)
→ ICP Filter (Boolean: title match AND company size match)
→ True: Email Enrichment → Deliverability Check
→ Verified: Push to Sequencer + Slack Alert with signal context
→ Unverified: Add to CRM without email trigger
→ False: Discard or add to low-priority nurture list
Use Trigify's built-in AI qualification agents to assess whether a post or
mention is genuinely relevant before enrichment credits are consumed.
Phase 4: Craft Signal-Anchored Outreach
The outreach message must reference the specific signal. Generic openers
destroy the value of the signal layer.
Fake personalisation (signal wasted):
"Hi Sarah, I noticed you're scaling your GTM team. Curious if you'd be
open to a quick call about how we help companies like yours..."
"Hi Sarah, Saw your comment on Chris's post about the SDR ramp problem —
specifically your point about the first 60 days. We helped three teams
at similar stages cut ramp from 90 to 45 days. Worth a conversation?"
Rules for signal-anchored messages:
The first line must be traceable to the exact signal event
Do not ask for a meeting in the first message; offer context or a question
Keep total message under 100 words
No product feature lists; one specific proof point tied to their signal
If the signal is a comment, quote or closely paraphrase what they said
Phase 5: Route and Alert
Qualified signals with verified emails enter the sequencer. Uncontacted
high-value signals (CEO, VP-level with no email found) get a Slack alert
to the rep with the signal context included — enough for a manual LinkedIn
outreach.
Signal routing tiers:
Account Tier
Signal Strength
Action
Named target account
Any qualifying signal
Immediate Slack alert + email enroll
ICP-match not on named list
High signal (recommendation request, problem post)
Email enroll + add to CRM
ICP-match not on named list
Medium signal (competitor engagement, hiring post)
CRM add + nurture track
Non-ICP
Any signal
Discard
Phase 6: Measure Signal Quality
Track signal performance separately from overall outreach metrics. The signal
layer needs its own feedback loop:
Reply rate by signal type — which signal types generate the highest
reply rates? Reallocate monitoring budget to the highest-performers.
Signal-to-meeting rate — of all signals that triggered outreach, what
percentage booked a meeting?
Signal freshness distribution — what percentage of signals fired within
24 hours vs. 24-72 hours vs. older? Older signals should be deprioritized.
False positive rate — signals that triggered enrichment and outreach
but were not actually relevant. Review and tighten keyword search or ICP
filter criteria.
Review signal performance weekly during ramp; monthly once stable.
Output Format
Social intent monitoring system documentation:
Signal taxonomy — table of signal types with urgency, outreach angle,
and platform sources configured for each
Listening configuration — keyword list, competitor list, topic
categories, and score thresholds per platform
Signal types defined with urgency windows (not just categories)
ICP filter criteria specified before enrichment step (prevent credit waste)
Email verification in workflow before sequencer push
All message templates reference signal in first line — no generic openers
Slack or CRM alert configured for high-value uncontacted signals
Keyword searches reviewed for noise — signal quality over volume
Signal freshness thresholds set (24-72 hr maximum for high-urgency signals)
Measurement plan covers reply rate by signal type, not just overall rate
Common Pitfalls
Acting on stale signals. A competitor mention from last week is not the
same as one from yesterday. Set hard freshness windows: recommendation
requests expire in 2 hours, most other signals in 24-72 hours. Signals
older than 72 hours should go to a low-priority nurture track, not hot
outreach.
Generic outreach from signal data. Running a signal-triggered sequence
with the same generic opener you'd send to a cold list defeats the entire
point. The signal must appear in the first sentence. If you can't reference
it specifically, don't send the email.
Enriching before filtering. Running every signal through enrichment
before checking ICP fit burns credits and slows workflows. Filter by job
title and company size using free platform data first; only enrich confirmed
ICP-matches.
Keyword search too broad. Monitoring your own company name or a one-word
competitor name without context generates hundreds of irrelevant signals.
Use phrase-level queries and negative keyword filters.
No feedback loop on signal quality. Running signal-led outbound without
tracking reply rate by signal type means you never know which signal types
are actually worth acting on. Some categories that seem strong (funding
signals) often underperform industry-specific problem posts. Measure weekly.
Confusing social listening with social selling. Social listening is about
monitoring what others say publicly (inbound signal collection). Social
selling (the social-selling skill) is about building your own presence
and engaging with your network. They work together but require separate
workflows and metrics.
Execution Artifacts
references/framework-notes.md — Named frameworks and reference tables
templates/output-template.md — Deliverable shell for agent output
