linkedin-dm-signal-classifier

name	linkedin-dm-signal-classifier
title	LinkedIn DM signal classifier
description	Use this skill to scan a team member's LinkedIn DMs daily and turn conversations into routed signals. It classifies each chat into a bucket (customer support, commercial, pipeline, re-engagement, prospect, partner, VC, community, and more), updates account memory and the CRM, scores qualified signals and routes them to your MQL channel, and closes every scored signal with a suggested next move — a drafted reply for the thread owner or an approval-queued sequence for the rest of the buying committee. It never auto-sends outreach.
category	Signals

Template placeholders

Replace every {{...}} before enabling. See the setup checklist reference for the full setup list.

• {{TRIGGER_OWNER}} — Team member whose LinkedIn DMs are scanned (one skill instance per person)
• {{CRM}} — Your CRM (e.g. HubSpot, Attio)
• {{SIGNALS_CHANNEL}} — Slack channel for all DM signal posts + daily digest
• {{EXPANSION_CHANNEL}} — Slack channel for expansion/churn-risk cross-posts (optional)
• {{MQL_CHANNEL}} — Slack channel where your lead-scoring alerts post qualified accounts
• {{PARTNERSHIPS_OWNER}} — Person to flag partner/agency signals to
• {{FUNDRAISING_OWNER}} — Person to flag investor inquiries to (usually a founder)
• {{LEAD_SCORING_SKILL}} — Sub-skill reference: your lead scoring & qualification methodology
• {{OUTREACH_SKILL}} — Sub-skill reference: your outreach/sequence-building methodology
• {{HIGH_ACV_THRESHOLD}} — Company profile that suggests medium-to-high ACV (default: >30 employees, funded, or VP+/C-suite/Founder contact)
• {{SELF_SERVE_THRESHOLD}} — Company profile that should route to your self-serve / low-touch motion instead of being scored (default: <50 employees AND ≤$10M total funding)

⚠️ Optional EVAL mode (recommended for the first 1–2 weeks)

While you evaluate output quality, you can run with {{CRM}} writes disabled: skip every "create or update in {{CRM}}" step below and instead include the exact note text that WOULD have been written in the Slack post. Workspace account-memory writes stay ON either way. Once you trust the output, follow the steps as written — that is the live configuration.

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Overview

Daily workflow for processing LinkedIn DM conversations. Runs once per person per day via a personal scheduled trigger. The trigger owner's LinkedIn account is used automatically.

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Step 1 — Determine the Cursor

Check the trigger owner's user memory for a key like LI DM last run: [ISO timestamp].

• If found: this is a subsequent run. You will skip chats with no activity since that timestamp.
• If not found: this is the first run. Process chats up to the limit specified in the trigger instructions.

Do NOT write the cursor yet. The cursor is written at the END of the run after all chats have been processed successfully (Step 8). A mid-run failure must not advance the cursor — duplicate processing on retry is acceptable, silently skipped signals are not.

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Step 2 — Fetch Chats (paginated)

Fetch the trigger owner's chat list with your LinkedIn tools, up to 250 chats per page.

Important: LinkedIn calls must be made ONE AT A TIME. Never parallelize them.

Pagination logic:

• If the response indicates more pages AND the oldest chat returned has a last-message timestamp newer than the stored cursor (or this is the first run): fetch the next page using the returned pagination cursor.
• Continue paginating until either: no more pages remain, OR the oldest chat in the page has a last-message timestamp older than or equal to the stored cursor.
• On first run: respect the chat limit specified in the trigger instructions (default 50 if unspecified) — stop paginating once you've accumulated that many chats.

This guarantees no active chats are silently missed on a busy day.

After fetching all pages, filter the full list: keep only chats whose last message timestamp is newer than the stored cursor (on subsequent runs). On the first run, keep all fetched chats up to the trigger limit.

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Step 3 — Read Messages

For each remaining chat:

• Read the most recent messages in the chat (about 20 is enough context)

For each chat, note:

• Whether the last message is inbound (sent by the other person) — this feeds the awaiting-reply flag in Step 5
• The timestamp of the last inbound message, to compute days since last reply

Skip a chat if:

• All messages are outbound only (sent by the trigger owner, never replied to)
• The most recent inbound message is purely noise with no identifiable company context
• The contact is a known personal connection of the trigger owner — skip entirely, no Slack post, no writes. (Maintain a short personal-connections skip list in this skill or the trigger owner's user memory.)

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Step 4 — Identify the Company

For each conversation with a meaningful inbound message:

1. Look at the other party's profile name and headline in the chat metadata
2. Identify their company from their LinkedIn headline (e.g., "VP Sales @ Acme Corp")
3. Search your workspace for the company
4. If not found, enrich via research tools to confirm domain and firmographics

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Step 5 — Classify the Signal

Classify each conversation into exactly one bucket. Use the priority order below — first matching bucket wins.

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VENDOR_SPAM Vendors pitching products, recruiters, generic congratulations with no substantive follow-up, connection acceptances with no message, spam. → Skip entirely. No Slack post, no writes.

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CUSTOMER_SUPPORT The contact's company is a current customer (closed-won) AND the message indicates: a product issue, bug, outage, credit or billing problem, a complaint, or any frustrated / at-risk tone. (Canonical example: an angry DM about billing or credits from a paying customer.) → Treat as urgent. See Step 6.

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CUSTOMER_COMMERCIAL The contact's company is a current customer AND the message is about: expansion interest, renewal, plan upgrade/downgrade, pricing questions, or churn risk without a support/complaint dimension. → See Step 6.

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ACTIVE_PIPELINE The contact's company has an open deal in your pipeline (any active sales stage between qualification and procurement). → See Step 6.

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RE_ENGAGEMENT The contact's company is at a closed-lost, nurture, or self-serve stage — AND they are initiating contact after a prior sales interaction (demo completed, trial agreed, or previous outreach replied to). Self-serve accounts only qualify if there is evidence of prior sales contact in account memory or CRM history; a pure self-serve trial with no sales touch does not qualify. → See Step 6.

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PROSPECT_HIGH_ACV A prospect (known or new) where the company profile meets {{HIGH_ACV_THRESHOLD}}. Includes known prospects in early funnel stages as well as previously unknown companies that clear the threshold. → See Step 6.

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PROSPECT_LOW_ACV A prospect with low ACV potential: solo operators, fractional executives, independent consultants, tiny companies with no funding.

Also use this bucket when the contact has no identifiable company (no company name or domain in their headline or profile). Post with whatever profile info exists. Add the note: No company — enrichment skipped. Do NOT create a workspace company record or run scoring for these contacts. → See Step 6.

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IMPLEMENTATION_PARTNER Agency, consultancy, done-for-you services firm in your space — whether already tracked as a partner or new. Note in the post whether this is ACTIVE (already tagged as a partner) or POTENTIAL (not yet tracked). → See Step 6.

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COMMUNITY_SPEAKING Community demo requests, podcast invitations, event speaking invitations, newsletter or content distribution opportunities, co-marketing proposals with no service/revenue pitch. → See Step 6.

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VC_INQUIRY An investor (VC, angel, family office) reaching out — about your company as an investment, a portfolio-company intro, or general relationship building. → See Step 6.

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COLLABORATION Peer builders, friendly-competitor exchanges, or mutual-interest conversations with no clear revenue or partnership path. → See Step 6.

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UNKNOWN Business-relevant message that does not fit any bucket above. Do not force a classification — post it and let the human decide. → See Step 6.

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Awaiting-reply flag (applies to all buckets except VENDOR_SPAM): After classifying, check: is the last message in the chat inbound (the other person messaged last, and the trigger owner has not replied)?

• If yes: compute N = days since that message. Add this line to the Slack post: ⏰ Awaiting reply (N days)
• If no (the trigger owner sent the last message): do NOT include this line. The ⏰ flag is exclusively for threads where the other person spoke last. Outbound-last threads must never carry this line.

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Step 5b — Deduplication Check

Before posting any signal in Step 6, check whether a signal for this same contact has already been posted within the last 7 days. Re-posting an unchanged thread creates noise and masks real new signals.

If the contact's company exists in the workspace (account memory available):

• Scan the account memory for a DM signal entry matching this contact's name, dated within the last 7 days.
• If one exists:
  • Post again only if there is a new inbound message since the last entry that adds materially new information: a new ask, a changed timeline, a new objection, or a clear intent shift.
  • Do not re-post because the trigger owner replied or there was only outbound activity since the last entry.
  • When posting an update: use a short update format, not a full new signal post. Open with: 🔄 DM Update — [contact name] @ [company] (follow-up to [earlier signal date]) and include only what is genuinely new.
  • If nothing new: skip the Slack post entirely. Still update account memory if there is meaningful new content to log.

If the contact has no company record (no account memory to check):

• Read the trigger owner's user memory for a Recently Posted DM Signals section (format: - [contact name] — [ISO date]).
• Apply the same 7-day rule.
• After any new or update post for such a contact, add or update their entry in the trigger owner's user memory. If the section doesn't exist yet, create it before writing the first entry.

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Step 6 — Route by Classification

Global rule — Verbatim message required in all Slack posts: Every Slack signal post (all buckets except VENDOR_SPAM) must include the verbatim text of the last inbound message from the contact, quoted in a blockquote. Do not paraphrase or summarize as a substitute. If the thread has multiple inbound messages since the last outbound, include the most recent one verbatim; you may briefly note context from earlier messages separately.

VENDOR_SPAM

Skip. No writes, no actions.

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CUSTOMER_SUPPORT

1. Update account memory:

   [CUSTOMER SUPPORT DM] [trigger owner name] ↔ [contact name, title] — [date]
   Issue type: [bug / billing / credits / complaint / at-risk]
   Summary: [1 sentence]
   

2. Create or update the contact in {{CRM}} and log a note:
   • Find or create the contact record (name, title, LinkedIn URL, email if available), associated with the company
   • Log a note on the contact: DM via LinkedIn — [date]. [contact name] ([title]). Support signal. Issue: [type]. Summary: [1 sentence].
3. Post to {{SIGNALS_CHANNEL}}:
   • 🚨 Customer Support DM
   • Company name + domain
   • Contact: name, title
   • Issue type: 🐛 bug / 💳 billing/credits / 😤 complaint / ⚠️ at-risk
   • What they said (verbatim blockquote)
   • ⏰ Awaiting reply line (if applicable)
   • Conversation owner: [trigger owner name]
   • Note: Urgent — route to your support process

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CUSTOMER_COMMERCIAL

1. Update account memory:

   [CUSTOMER COMMERCIAL DM] [trigger owner name] ↔ [contact name, title] — [date]
   Signal: [expansion / renewal / pricing / churn risk]
   Summary: [1 sentence]
   

2. Create or update the contact in {{CRM}} and log a note (same format as above, with the commercial sub-type).
3. Post to {{SIGNALS_CHANNEL}}:
   • 📩 Customer Commercial DM
   • Company name + domain; contact name, title
   • Signal type: 📈 expansion / 🔄 renewal / 💬 pricing question / ⚠️ churn risk
   • 1-sentence summary; what they said (verbatim blockquote); ⏰ line if applicable; conversation owner
4. If signal is expansion or churn risk: also cross-post to {{EXPANSION_CHANNEL}}.

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ACTIVE_PIPELINE

1. Update account memory:

   [PIPELINE DM] [trigger owner name] ↔ [contact name, title] — [date]
   Deal stage: [current stage]
   Signal: [objection / timeline / pricing / champion re-engagement / positive]
   Summary: [1-2 sentences]
   

2. Load and follow {{LEAD_SCORING_SKILL}}. A mid-deal DM is strong first-party intent — do not apply any tier cap that normally limits passive signals.
3. Create or update the contact in {{CRM}} and log a note:
   • Find or create the contact record (name, title, LinkedIn URL, email if available), associated with the company
   • Log a note on the contact: DM via LinkedIn — [date]. [contact name] ([title]). Deal stage: [stage]. Signal: [type]. Summary: [1-2 sentences].
4. Post to {{SIGNALS_CHANNEL}}:
   • 📩 Pipeline DM Signal
   • Company + current deal stage; contact name, title; signal summary; what they said (verbatim blockquote); tier scored; ⏰ line if applicable; conversation owner
5. Continue to Step 6.5.

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RE_ENGAGEMENT

1. Update account memory:

   [RE-ENGAGEMENT DM] [trigger owner name] ↔ [contact name, title] — [date]
   Prior stage: [closed-lost / nurture / self-serve]
   Summary: [1 sentence]
   

2. Treat as first-party intent. Load and follow {{LEAD_SCORING_SKILL}}.
3. Post to {{SIGNALS_CHANNEL}}:
   • 🔁 Re-engagement DM
   • Company + prior stage; contact name, title; what they said (verbatim blockquote); tier scored; ⏰ line if applicable; conversation owner
4. Continue to Step 6.5.

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PROSPECT_HIGH_ACV

1. If the company is not yet in the workspace: enrich via research tools and add it.

2. ⛔ SELF-SERVE GATE — Run this before anything else. No exceptions.

   Check employee count (take the lower of enrichment vs LinkedIn) and total funding raised.

   If the company profile meets {{SELF_SERVE_THRESHOLD}}:

   • Move the account to your self-serve / low-touch stage and tag it accordingly (sync the stage to {{CRM}} if you mirror stages there)
   • Post to {{SIGNALS_CHANNEL}} using the PROSPECT_HIGH_ACV format but note: ⛔ Self-serve gate triggered — under threshold. No scoring. Moved to self-serve.
   • ⛔ STOP. Do not proceed to memory update, scoring, or MQL routing.

   If employee count is unavailable: treat as unknown and apply the gate by default. A strong funding signal alone (well above threshold) may override the gate.

3. Update account memory:

   [PROSPECT DM] [trigger owner name] ↔ [contact name, title] — [date]
   ACV tier: HIGH
   Summary: [1 sentence]
   

4. Load and follow {{LEAD_SCORING_SKILL}}. DM = first-party intent. Promotion rule: A substantive inbound DM (the contact initiated a real business conversation) is strong first-party intent. If the account's current tier is one below your alert tier, instruct the scoring skill that this direct DM interaction justifies promotion one tier up — unless there is contrary evidence in the account memory (explicit disqualification, stated "not now", churned for cause). Never lower an existing tier as a result of this DM run.

5. Create or update the contact in {{CRM}}:

   • Find or create the contact record with name, title, LinkedIn URL, and email if available
   • Associate with the company record

6. Post to {{SIGNALS_CHANNEL}}:

   • 📩 High-ACV Prospect DM
   • Company + enriched summary (employees, funding, description)
   • Contact: name, title, what they said (verbatim blockquote)
   • Tier scored; ⏰ line if applicable
   • Close with a note that accurately reflects what actually happened:
     • Both ran: Note: Enriched + scored.
     • Enrichment ran, scoring skipped: Note: Enriched. Scoring skipped.
     • Enrichment skipped: Note: Enrichment skipped. [Reason].

7. Continue to Step 6.5.

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PROSPECT_LOW_ACV

1. Do NOT create a workspace company record. Do NOT run scoring.
2. Post to {{SIGNALS_CHANNEL}}:
   • 📩 Low-ACV Prospect DM
   • Contact: name, title, company (if any); what they said (verbatim blockquote); ⏰ line if applicable; conversation owner
   • No company — enrichment skipped (only if no company was identified)
   • Note: Low ACV signal — no workspace record created.

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IMPLEMENTATION_PARTNER

1. Update account memory (if company record exists):

   [PARTNER DM] [trigger owner name] ↔ [contact name, title] — [date]
   Status: ACTIVE / POTENTIAL
   Summary: [1 sentence on what was discussed]
   

2. Post to {{SIGNALS_CHANNEL}}:
   • 🤝 Implementation Partner DM
   • Company name, domain, what they do; contact name, title
   • Status: ACTIVE or POTENTIAL
   • Summary of what was discussed; what they said (verbatim blockquote); ⏰ line if applicable; conversation owner
   • Note: Flagging for {{PARTNERSHIPS_OWNER}}'s awareness

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COMMUNITY_SPEAKING

1. Post to {{SIGNALS_CHANNEL}}:
   • 🎤 Community / Speaking Opportunity
   • Contact: name, title, company (if any)
   • Opportunity type: podcast / event / community demo / distribution / co-marketing
   • What they proposed (verbatim blockquote); ⏰ line if applicable; conversation owner
   • Note: Surface for review — no action taken.

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VC_INQUIRY

1. Post to {{SIGNALS_CHANNEL}}:
   • 💼 VC Inquiry
   • Contact: name, title, fund name; what they said (verbatim blockquote); ⏰ line if applicable; conversation owner
   • Note: Surface for {{FUNDRAISING_OWNER}}'s awareness.

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COLLABORATION

1. Post to {{SIGNALS_CHANNEL}}:
   • 🤜 Collaboration / Peer Exchange
   • Contact: name, title, company; brief summary (1 sentence); what they said (verbatim blockquote); ⏰ line if applicable; conversation owner

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UNKNOWN

1. Post to {{SIGNALS_CHANNEL}}:
   • ❓ Unclassified DM
   • Contact: name, title, company (if any); what they said (verbatim blockquote); ⏰ line if applicable; conversation owner
   • Note: Could not classify — needs human review.

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Step 6.5 — MQL Routing & Suggested Next Move

This step applies whenever {{LEAD_SCORING_SKILL}} was called in Step 6 — i.e., for ACTIVE_PIPELINE, RE_ENGAGEMENT, and PROSPECT_HIGH_ACV signals.

MQL channel routing

Let the scoring skill's standard alert routing run in full — do not suppress it.

⚠️ CRITICAL — Use your standard lead-scoring alert format for {{MQL_CHANNEL}} posts. Do NOT post a custom DM-signal format to that channel. DM context (verbatim last inbound message, conversation owner, days awaiting reply) must be embedded within the standard format — with the verbatim DM woven in as the primary signal (e.g., "Inbound DM from [name] ([title]) — [verbatim quote]") — not posted as a separate custom block. One channel, one format: readers of the MQL channel should never need to learn a second layout.

Decide the next move

After scoring completes, read the full DM thread, account memory, and current deal state, then decide the right next action. Apply these rules:

The person already in the thread — suggest a reply, never enroll in a sequence: The contact is in a live conversation with the trigger owner. Never enroll them in an automated sequence. Instead, draft a suggested reply in the voice of the conversation owner (the trigger owner). If the contact is addressing or asking for someone else on your team, name that person as the right sender in the draft. Include the draft directly in the Slack post so the owner can send it manually.

Other people at the account — outreach is allowed, with checks: Outreach to buying-committee members who are NOT already in the thread is permitted. Before building any sequence:

1. Run a duplicate-outreach check: search all existing sequences for each target contact in any status. If a sequence already exists for them — finished, running, or awaiting approval — do not build a new one; flag for human review instead.
2. Follow {{OUTREACH_SKILL}} for sender selection and sequence construction.
3. All DM-originated outreach must be queued for approval — never auto-send, regardless of tier.

Approval always required: A DM thread means a human relationship is in motion. The human decides what goes out. No exceptions.

Slack post closing line

End every ACTIVE_PIPELINE, RE_ENGAGEMENT, and PROSPECT_HIGH_ACV signal's Slack post with a Suggested next move: line — one concrete, actionable recommendation. Examples:

• Suggested next move: [owner] should reply today — draft above.
• Suggested next move: Enroll [VP Sales name] in a sequence — queued for approval.
• Suggested next move: No action — await their reply before following up.
• Suggested next move: [teammate] to take over — DM context in thread above.

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Step 7 — End of Run Summary

After processing all chats, always post a summary to {{SIGNALS_CHANNEL}}. This post is mandatory on every run — including runs where zero signals were found. Silence must mean a failure, never "nothing found."

If at least one non-noise signal was found:

📋 LinkedIn DM Scan — [trigger owner name] — [date]
Chats fetched: [total fetched] | Processed: [N after filter]
Signals found: [N] — support: X, commercial: X, pipeline: X, re-engagement: X,
high-ACV prospect: X, low-ACV prospect: X, partner: X, community/speaking: X,
VC: X, collab: X, unknown: X
Vendor spam / noise skipped: [N] ([breakdown: recruiters, vendors, outbound-only, etc.])
⚠️ Memory-full warnings: [N accounts] (list company names if any)

Omit the memory-full line if count is 0.

If zero non-noise signals were found:

📋 LinkedIn DM Scan — [trigger owner name] — [date]. Chats checked: [N]. No new signals.

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Step 8 — Write the Cursor

Only after all chats have been processed successfully, write the cursor to the trigger owner's user memory: LI DM last run: [ISO timestamp of when this run started]

Use the timestamp from when the run started (captured at Step 1), not the end time — this ensures the next run re-checks any chats that became active mid-run.

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Important Constraints

• LinkedIn calls are sequential — never parallel
• Never surface noise signals — filter aggressively
• Never auto-send outreach. The only outreach this workflow may produce is a drafted reply surfaced in Slack, or an approval-queued sequence built per Step 6.5 — a human sends everything.
• If a company is tagged as competitor or vendor: skip, log in memory only, no Slack post
• Memory-full handling: If an account memory write fails due to capacity, do NOT delete or trim existing entries to make room. Skip the memory write entirely. Add ⚠️ account memory full — signal not persisted to that signal's Slack post, and count it in the end-of-run digest.

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What good looks like

A great run puts every business-relevant DM in exactly one bucket with the right routing: urgent customer-support signals surface same-day with the verbatim complaint quoted in a blockquote, qualified signals get scored and land in {{MQL_CHANNEL}} in the standard alert format, every scored signal's post closes with one concrete Suggested next move: line (often a ready-to-send drafted reply), the 7-day dedup keeps the channel quiet (updates use the short 🔄 format), the end-of-run digest posts even on zero-signal days — silence must mean failure, never "nothing found" — and the cursor only advances after a fully successful run.

Mediocre looks like: vendor spam surfacing as signals, unchanged threads re-posted, a missing digest, awaiting-reply flags on threads where the owner spoke last, custom DM formats polluting the MQL channel, the contact in the thread getting enrolled in an automated sequence, or anything auto-sent without human approval.