Marketplace

social-selling

Use when engaging prospects through LinkedIn, communities, and social channels to spark warm conversations and meetings.

$ 安裝

git clone https://github.com/gtmagents/gtm-agents /tmp/gtm-agents && cp -r /tmp/gtm-agents/plugins/sales-prospecting/skills/social-selling ~/.claude/skills/gtm-agents

// tip: Run this command in your terminal to install the skill


name: social-selling description: Use when engaging prospects through LinkedIn, communities, and social channels to spark warm conversations and meetings.

Social Selling Skill

When to Use

  • Prospect is active on LinkedIn, X, or niche communities.
  • Outreach needs warmer entry points than cold email.
  • SDRs must nurture accounts over weeks via digital touchpoints.
  • Need to convert marketing engagement (webinars, posts) into conversations.

Framework

  1. Core Principles – insight first, timely engagement, sequence public + private touches, lean on social proof, and lead with call-to-value offers.
  2. Engagement Ladder – monitor > micro-engage > value drops > DM > follow-through into email/call.
  3. Signal Tracking – monitor posts, job changes, events, and mutual connections for context.
  4. Cadence Planning – mix comments, shares, and DMs each week per target account.
  5. Measurement – watch connection acceptance, DM reply, meetings per 50 connections, and interactions per account.

Templates

  • DM Scripts: See references/engagement_playbook.md for scripts and signal tracking.
  • Checklist: See assets/social_checklist.md for daily/weekly routines.
  • Social listening checklist: (signals: hiring, promotions, launches, exec moves).
  • Weekly activity planner: (3 comments, 2 value shares, 1 DM per target account).

Tips

  • Engage within 30 minutes of prospect activity when possible for better visibility.
  • Alternate public cues (comments, reposts) with private DMs to avoid feeling pushy.
  • Tie every outreach to proof (mutual connections, customer stories) to earn trust.
  • Move hot threads to email/call quickly and log outcomes for attribution.