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    social-media-management

    B2B content writing with daily workflows

    By @shashwatgtm
    View on GitHub
    SKILL.md
    ---
    name: content-writing-thought-leadership
    description: B2B content writing with daily workflows and batching systems across Sales/HR/Fintech/Ops Tech
    metadata: {"clawdbot":{"emoji":"āœļø","homepage":"https://github.com/shashwatgtm","always":true}}
    ---
    ## **šŸŽÆ Multi-Dimensional Navigator**
    
    **Content writing varies dramatically by industry, stage, and role. Find your path:**
    
    ### **STEP 1: What's Your Industry Vertical?**
    
    Your industry determines:
    - Tone and voice (aggressive vs conservative)
    - Risk tolerance (what you can/cannot say)
    - Approval workflows (direct publish vs legal review)
    - Content topics and angles
    
    ```
    → Sales Tech - Aggressive, contrarian, data-driven
    → HR Tech - Professional, empathetic, research-backed
    → Fintech - Ultra-conservative, compliance-first
    → Operations Tech - Industry-specific, B2B2B2C nuanced
    ```
    
    ### **STEP 2: What's Your Company Stage?**
    
    Your stage determines:
    - Publishing frequency (founder bandwidth vs team)
    - Content depth (tactical vs strategic)
    - Approval requirements (founder autonomy vs committee)
    - Resources available (DIY vs professional design)
    
    ```
    → Series A - Founder voice, scrappy, tactical
    → Series B - Team effort, professional, strategic
    → Series C+ - Corporate voice, brand-controlled, category-defining
    ```
    
    ### **STEP 3: Are You Founder or Employee?**
    
    Your role determines:
    - Editorial freedom (can you be contrarian?)
    - Approval process (self-publish vs manager review)
    - Personal vs company brand
    - What topics are "safe" vs "risky"
    
    ```
    → Founder - Full autonomy, personal = company
    → VP/Director - Manager approval, aligned with brand
    → PMM/Content - Team collaboration, brand guidelines
    → Employee - Significant constraints, corporate voice
    ```
    
    ### **STEP 4: What's Your Primary Market?**
    
    Your geography determines:
    - Writing style (US direct vs India relationship-focused)
    - Examples and case studies (local companies)
    - Compliance considerations (GDPR mentions, etc.)
    
    ```
    → India - Relationship-driven, local examples, price-conscious
    → US - Direct, data-driven, premium positioning
    ```
    
    ---
    
    ## **Quick Navigation by Common Scenarios**
    
    1. **"I'm a Sales Tech founder, want to build thought leadership"**
       → Go to: **Section A1** (Sales Tech, Founder, Aggressive Voice Allowed)
    
    2. **"I'm VP Marketing at HR Tech, team writes content for me to review"**
       → Go to: **Section B2** (HR Tech, Series B, Professional Team Content)
    
    3. **"I'm at fintech, every post needs legal review"**
       → Go to: **Section C** (Fintech, Compliance-First Content)
    
    4. **"I'm PMM at ops tech, write about retail execution"**
       → Go to: **Section D** (Operations Tech, Industry-Specific Content)
    
    ---
    
    # šŸ“Š SECTION A: SALES TECH CONTENT WRITING
    
    **When To Use This Section:**
    - Your product: Sales engagement, conversation intelligence, sales enablement
    - Your audience: Sales leaders, CROs, RevOps, SDR managers
    - Your content angle: Tactical sales tips, data-driven insights, contrarian takes
    - Voice: Aggressive, confident, ROI-focused, can challenge incumbents
    
    ---
    
    ## **A1: Sales Tech @ Series A (Founder Voice, Aggressive Allowed)**
    
    ### **Your Reality Check:**
    
    ```
    COMPANY PROFILE:
    - Size: $1M-10M ARR, 10-100 employees
    - Stage: Series A
    - You: Founder or early marketing hire
    - Content goal: Build thought leadership + leads
    - Publishing: 3-5Ɨ per week (LinkedIn primary)
    - Approval: None (founder autonomy)
    - Time: 5-8 hours/week total
    ```
    
    ### **The Sales Tech Content Philosophy:**
    
    **Why Sales Leaders Engage with Content:**
    
    ```
    SALES LEADERS DON'T ENGAGE WITH:
    āŒ Generic motivational quotes
    āŒ Theory without data
    āŒ Long-winded essays (no time)
    āŒ Humble bragging ("We just closed...")
    
    SALES LEADERS ENGAGE WITH:
    āœ… Data-driven insights ("Analyzed 10K calls, here's what top reps do")
    āœ… Tactical frameworks (copy-paste into your process)
    āœ… Contrarian takes ("Everyone is wrong about cold calling")
    āœ… Competitive intelligence ("What Gong doesn't tell you")
    āœ… ROI calculations ("This tactic = 23% more meetings")
    ```
    
    ### **Sales Tech Voice Guidelines:**
    
    **AGGRESSIVENESS SPECTRUM (Sales Tech):**
    
    ```
    TOO TIMID (Don't Do This):
    "We think conversation intelligence might be helpful for some teams..."
    
    APPROPRIATELY CONFIDENT (Do This):
    "Gong analyzed 1M calls. We analyzed 2M. Here's what they missed."
    
    TOO AGGRESSIVE (Even for Sales Tech):
    "Gong is garbage. Their data is fake. We're 100Ɨ better."
    
    SWEET SPOT:
    - Confident, data-backed assertions
    - Respectful but contrarian takes
    - Challenge category leaders on methodology
    - But: Never personal attacks, never unverified claims
    ```
    
    ### **Content Types for Sales Tech Founders:**
    
    **CONTENT MIX (Sales Tech Series A):**
    
    ```
    40% DATA-DRIVEN INSIGHTS
    - "We analyzed X sales calls, here's what we found"
    - "The data says [surprising insight]"
    - Source: Your product data, public research (Gong, Pavilion)
    - Length: 300-500 words
    - Frequency: 2Ɨ per week
    
    30% TACTICAL FRAMEWORKS
    - "The 3-question discovery framework"
    - "How to handle pricing objections [step-by-step]"
    - Source: Your experience, customer wins
    - Length: 400-600 words
    - Frequency: 1-2Ɨ per week
    
    20% CONTRARIAN TAKES
    - "Why everyone is wrong about [X]"
    - "Gong says [X], but the data shows [Y]"
    - Source: Your unique perspective, counter-research
    - Length: 200-400 words
    - Frequency: 1Ɨ per week
    
    10% PERSONAL/BEHIND-THE-SCENES
    - "How we lost a $50K deal (and what I learned)"
    - "The sales hire that changed our trajectory"
    - Source: Your journey
    - Length: 300-500 words
    - Frequency: 1Ɨ every 2 weeks
    ```
    
    ### **Series A Sales Tech: Daily Content Workflow**
    
    **MONDAY: Data-Driven Insight (1.5 hours)**
    
    ```
    09:00-09:30 | Find Data
    
    SALES TECH DATA SOURCES:
    ā–” Your product: Export anonymized metrics
      Example: "Average discovery call = 32 minutes in our data"
      
    ā–” Public research:
      - Gong Labs reports (free)
      - Pavilion benchmarks (if member)
      - Public earnings calls (check Salesforce, ZoomInfo)
      
    ā–” Customer interviews:
      - "What was your close rate before/after using us?"
      - Turn into: "Customer X increased close rate 23%"
    
    09:30-10:30 | Write Post
    
    STRUCTURE:
    
    **HOOK (First 2 lines):**
    "We analyzed 50,000 sales calls from SMB B2B SaaS companies.
    The average discovery call is 32 minutes. But top performers? 19 minutes."
    
    **BUILD (3-5 paragraphs):**
    Why this matters:
    - Shorter calls = more qualified prospects
    - Top reps ask fewer questions (but better ones)
    - They don't "interrogate," they diagnose
    
    What we found:
    1. Average rep asks 18 questions in discovery
    2. Top rep asks 9 questions (but they're open-ended)
    3. Top rep listens 67% of the time (vs 42% for average)
    
    **PAYOFF (1-2 paragraphs):**
    The 3 questions top reps always ask:
    1. "Walk me through your current process for [X]"
    2. "What happens if you don't solve this in the next 90 days?"
    3. "Who else is impacted by this problem?"
    
    **CTA:**
    "What's your go-to discovery question?"
    
    10:30-11:00 | Edit & Publish
    
    SALES TECH EDITING CHECKLIST:
    ā–” Cut 20-30% of words (brevity = respect for time)
    ā–” Verify: Every claim has data/source
    ā–” Add: Numbers, percentages, specifics
    ā–” Remove: Fluff, qualifiers ("I think," "maybe")
    ā–” Check: Does this make sales leaders smarter?
    
    PUBLISH:
    - Time: 9 AM EST / 6 AM PST (catch US East + West)
    - If India: 9 AM IST (catch Indian B2B audience)
    - Platform: LinkedIn primary, Twitter thread secondary
    ```
    
    **TUESDAY: Tactical Framework (1.5 hours)**
    
    ```
    STRUCTURE:
    
    **HOOK:**
    "The pricing objection framework every SDR should memorize:
    (Learned this from watching 1,000+ pricing conversations)"
    
    **FRAMEWORK:**
    When they say: "That's too expensive"
    
    DON'T say:
    āŒ "We're actually quite affordable"
    āŒ "Let me talk to my manager about a discount"
    āŒ "What's your budget?"
    
    DO say (3-step framework):
    
    Step 1: REFRAME
    "Expensive compared to what? [competitor]?"
    → Forces them to make comparison explicit
    
    Step 2: QUANTIFY THEIR PROBLEM
    "Walk me through what this problem costs you today.
     How many hours per week? What's your team's loaded cost?"
    → Now you have their ROI baseline
    
    Step 3: CONTRAST VALUE
    "So you're spending $50K/year in time right now.
     Our solution is $15K/year and eliminates 90% of that.
     That's a $35K gain. Does that math work?"
    → Reframe from cost to investment
    
    **EXAMPLE:**
    [Insert short dialogue showing this in action]
    
    **CTA:**
    "Try this next time you hear 'too expensive.'
     Let me know how it goes."
    
    LENGTH: 400-600 words
    TIME: 1.5 hours (research + write + edit)
    ```
    
    **WEDNESDAY: Contrarian Take (1 hour)**
    
    ```
    STRUCTURE:
    
    **HOOK (Provocative):**
    "Unpopular opinion: Gong is making your sales team WORSE.
    (And I have data to prove it)"
    
    **SETUP:**
    Everyone thinks conversation intelligence = better sales.
    More data = better coaching = more wins.
    
    But here's what we're seeing:
    
    **THE CONTRARIAN INSIGHT:**
    When sales teams get Gong:
    - Month 1-3: 15% improvement (reps more aware)
    - Month 4-6: Flatline (back to baseline)
    - Month 7+: Often 5-10% decline
    
    Why?
    1. Analysis paralysis (too much data, not enough action)
    2. Reps game the metrics (talk more to hit "talk time" goals)
    3. Managers overwhelmed (100 dashboards, 0 time to coach)
    
    **THE ALTERNATIVE VIEW:**
    Conversation intelligence isn't the problem.
    How you USE it is.
    
    Best teams:
    - Track 3 metrics max (not 30)
    - Focus on ONE skill per quarter
    - Coach live (not post-call reviews)
    
    **NUANCE (Important for Aggressive Takes):**
    "Am I saying Gong is bad? No.
    Am I saying most teams use it wrong? Yes."
    
    **CTA:**
    "Using conversation intelligence? What's working for you?"
    
    RISK LEVEL: Medium-High
    APPROVAL: Founder only (don't do this as employee)
    WHEN: Only if you have data + alternative
    ```
    
    **THURSDAY: Quick Tip (30 minutes)**
    
    ```
    STRUCTURE:
    
    **HOOK:**
    "The 2-minute LinkedIn outreach hack that 3Ɨ my reply rate:"
    
    **THE HACK:**
    Before sending connection request:
    1. Comment on their post (genuine, add value)
    2. Wait 24 hours
    3. THEN send personalized connection request
    
    Why it works:
    - They remember you (positive association)
    - Not cold anymore (warm intro via comment)
    - Shows you did res
    
    ... (truncated)