Do Founder Led Sales

• You haven't closed your first 5 customers yet — you need to learn the market, not optimize the process
• You can't articulate your sales process — "We just close people" means it's not repeatable yet
• Pricing feels uncertain — you don't know if you should charge $100/month or $10K/month
• Objections feel unpredictable — if different customers raise different concerns, you haven't mapped the objection landscape
• Your network has warm prospects — your first 10 customers should come from warm intros, not cold outreach
• You're weighing a sales hire — before hiring, close 15 customers personally so you know what you're hiring for
• Early-stage revenue is lumpy — some months you close 2 deals, others zero; pattern isn't clear yet

Instructions

1. Build a prospect list from your network first

   • Start with people who know you (or know people who know you)
   • Avoid cold outreach in Year 1; warm intros convert 5-10x better than cold
   • List potential customers who have the pain you're solving (even if they haven't asked for a solution yet)
   • Prioritize based on: (a) relationship strength, (b) pain relevance, (c) ability to afford your product
   • You need 15-20 qualified leads to close your first 5-10 customers (typical conversion is 30-50% from warm intros)

2. Prepare your discovery framework

   • Your job is to listen 70% and talk 30%
   • Open with: "I want to understand the problem you're facing" — not "Let me show you my product"
   • Ask about current state: "How do you solve this problem today? What's broken about that approach?"
   • Quantify the pain: "How much time does this waste? How much does it cost?"
   • Understand their process: "Who else is involved in this decision? How would they evaluate a solution?"
   • Never pitch before you've asked at least 8 discovery questions
   • Document what you learn in your CRM so you see patterns across calls

3. Run the conversation like a discovery meeting, not a demo

   • Start by saying: "I want to understand your world before we go into our product"
   • Ask about their goals, constraints, and decision process
   • Take notes visibly (they should know you're listening)
   • If they ask about features, answer briefly, then go back to questions
   • At the end, only show the product if it's clearly relevant; otherwise just schedule a follow-up
   • Your goal is clarity on fit, not amazement at features

4. Price higher than you think and be willing to adjust

   • Your first customer will tell you if your price is way off
   • Start with a number that feels uncomfortable; you can always lower it
   • Don't offer multiple tiers if you have no data; pick one price and learn
   • If 3 people ask "Can you do it for less?" you might be priced high
   • If nobody asks about price, you're priced too low
   • Pricing leverage comes from: exclusivity (limited spots), speed of implementation, or unique value
   • As you close more customers at the same price, your confidence in that price increases

5. Handle objections as data collection, not rejection

   • Every objection you hear is a pattern (usually)
   • "Your product doesn't integrate with our Salesforce" heard from 3 prospects? That's a top-10 objection
   • "It's too expensive" from a company doing $100M revenue is different from "It's too expensive" from a $5M startup
   • Create an objection log: objection, who raised it, your response, what you learned
   • Share your objection log with your team; this becomes the sales training playbook
   • Don't argue with objections; instead, ask: "What would need to be true for this to be a fit?"

6. Position the product as founder-backed, not as finished

   • Customers buying from a founder expect flexibility
   • Say: "You're one of our first 10 customers, which means we're going to build some custom stuff for you"
   • Use this as a closing tool: "Since you're an early customer, we can commit to X feature you need"
   • Document custom requests; they become product priorities or clear nos for the roadmap
   • Your founder advantage is making commitments to roadmap items; use it

7. Close the deal by understanding the real objection

   • If they hesitate, ask: "What would need to change for this to be a yes?"
   • Often the objection isn't price or features; it's "I don't want to be your beta customer" or "I need board approval"
   • Address the real blocker, not the stated one
   • For early customers, offer: shorter contract (3 months instead of 12), success guarantee (if you don't hit these metrics, you don't pay), or risk reversal
   • Don't discount; instead, offer different terms or scope

8. Document every conversation and build your playbook

   • After each call, spend 15 minutes documenting: prospect profile, objections raised, their pain quantified, how you responded, what worked/didn't
   • After 10 calls, you'll see patterns (common questions, objections, pain points)
   • After 20 calls, you can articulate your repeatable motion: "Here's how we typically approach discovery with [customer type]"
   • This document becomes the training guide for your first sales hire
   • Share it with your team so everyone learns from each conversation

9. Manage founder fatigue—founder-led sales is temporary

   • Founder-led sales is not scalable forever
   • You should be closing 2-3 deals per month
   • Once you hit 10-20 customers OR you're closing 5+ deals per month, it's time to hire
   • Don't optimize for speed yet; optimize for learning
   • If you're miserable on calls, hire faster; if you're learning rapidly, keep doing it

10. Know when to stop selling and hand off to a sales team

    • You've documented the repeatable process (playbook exists)
    • You can describe the ideal customer and their pain points clearly
    • You've closed 15+ customers and see consistent patterns
    • You're closing 5+ deals per month (scaling requires a team)
    • You should still be involved in enterprise deals, even after hiring a sales team
    • Your exit from daily sales should be gradual; mentor the sales hire by sitting in on their calls for their first 20 conversations

Output Format

FOUNDER-LED SALES MOTION TRACKER

Discovery Call Prep
═══════════════════
Prospect Name: [Name] | Company: [Company] | Role: [Title]
Introduction: [How do you know them? Who introduced you?]
Expected Pain: [What pain do you think they have based on warm intro?]

Discovery Framework (Prepare These Questions):
  1. How do you currently solve [problem]? (Context)
  2. What's broken about that approach? (Pain identification)
  3. How much time/money does this problem cost you? (Quantification)
  4. Who else cares about fixing this? (Buying committee)
  5. How would you evaluate a solution? (Process + decision criteria)
  6. What would need to be true for you to buy something? (Success criteria)
  7. Timing: When do you need to solve this? (Urgency)
  8. Budget: Do you have budget allocated for a solution? (Affordability)

Talk Track (What NOT to say):
  ✗ Don't pitch features
  ✗ Don't spend >5 minutes on your company history
  ✗ Don't talk more than 30% of the call
  ✓ Do ask "Tell me more" when they raise something relevant
  ✓ Do take visible notes
  ✓ Do ask "What else?" before you wrap up

Post-Call Documentation
═════════════════════════
Prospect: [Name] | Company: [Company]
Call Date: [Date] | Duration: [Minutes] | Temperature: [Warm/Hot/Cold]

Discovery Outcomes:
  Pain Identified: [What's actually broken for them?]
  Quantified Impact: [Hours/day wasted? Cost? Revenue at risk?]
  Buying Committee: [Who else is involved? Timing of their involvement?]
  Decision Process: [How do they buy things? Approvals needed?]
  Buying Signal: [0-10 scale, where 10 = "send me a contract"]

Objections Raised (CRITICAL):
  1. [Objection] — My response: [How you handled it] — What I learned: [Takeaway for playbook]
  2. [Objection] — My response: [How you handled it] — What I learned: [Takeaway for playbook]

Product Fit Assessment:
  ✓ Strong fit: [If yes, why? What pain does our product solve?]
  ☐ Possible fit: [If maybe, what would improve the fit?]
  ✗ No fit: [If no, why? Will we ever solve for them?]

Next Steps & Timeline:
  Immediate: [What happens this week?]
  By [Date]: [When is the next conversation/decision?]
  Their timeline to buy: [When do they need a solution? 1 month? 6 months?]

Prospect Value Assessment:
  Company size: [Revenue/employees/funding]
  Likely contract value: $[Amount] | Confidence: [High/Medium/Low]
  Reference potential: [If we close them, will they advocate for us?]
  Can they influence others in our market? [Yes/No/Maybe]

Pricing Reaction:
  Have you discussed price? [Yes/No]
  If yes: Our offer: $[Amount] | Their reaction: [Excited/Hesitant/Need to check]
  Price objection or fit objection? [If hesitant, was it price or something else?]

Sales Playbook Learnings
═════════════════════════
Objection Pattern: [Objection raised by N customers]
  └─ Prospect profiles affected: [Which types of companies/roles raise this?]
  └─ Root cause: [Why do they raise this objection?]
  └─ How to prevent: [What should we say in discovery to avoid this?]
  └─ How to overcome: [If they raise it anyway, how do we address it?]

Pricing Signal: [Pattern emerging about pricing willingness]
  └─ Customers at [company size] are willing to pay: $[Amount]
  └─ Customers at [industry] are willing to pay: $[Amount]
  └─ Top objection related to price: [Price vs. perceived value]

Questions Asked 3+ Times:
  Q: [Question repeated 3+ times] → Answer to document: [What should we say?]
  Q: [Question repeated 3+ times] → Answer to document: [What should we say?]
  Q: [Question repeated 3+ times] → Answer to document: [What should we say?]
  └─ Next step: Build FAQ or product documentation to address these upfront

High-Value Discovery Insights:
  1. [Insight that changes how we pitch/position] — Impact: [Why this matters]
  2. [Insight about buying process] — Impact: [Why this matters]
  3. [Insight about ideal customer profile] — Impact: [Why this matters]

Founder-Led Sales Motion Summary
═════════════════════════════════
Customers Closed to Date: [#] | Total ARR: $[Amount]
Average Sales Cycle: [# of weeks] from discovery call to close
Average Contract Value: $[Amount] | Range: $[Low] - $[High]
Conversion Rate: [#] prospects → [#] closed ([%])
Repeatable? [Yes/No] — If yes: Documented? [Yes/No]

Top 3 Customer Types (by likelihood to close):
  1. [Profile: Industry + company size + pain point] — Conversion rate [%]
  2. [Profile: Industry + company size + pain point] — Conversion rate [%]
  3. [Profile: Industry + company size + pain point] — Conversion rate [%]

Most Common Objections (by frequency):
  1. [Objection] — Raised by [#] prospects ([%]) — Our best response: [What works]
  2. [Objection] — Raised by [#] prospects ([%]) — Our best response: [What works]
  3. [Objection] — Raised by [#] prospects ([%]) — Our best response: [What works]

Pricing Intelligence:
  Willing to pay: $[Amount]/month or [% of problem value]
  Price sensitivity: [Low/Medium/High] based on objection frequency
  Tier effectiveness: [If multiple tiers, which sells best?]

Ready to Hire Sales? [Yes/No]
  Customers closed: [#] (threshold: 15+)
  Process documented: [Yes/No] (threshold: Yes)
  Repeatable motion: [Yes/No] (threshold: Clear patterns established)
  Monthly close rate: [#] deals/month (threshold: 5+ deals means hire)
  ✓ Threshold met: Ready to hire | ✗ Keep selling: Need more data

Example

FOUNDER-LED SALES MOTION TRACKER

CALL 1: TechFlow Inc.
═══════════════════════
Prospect: Alex Chen | Title: VP Product | Company: TechFlow Inc.
Introduction: Warm intro from Sarah (former colleague); she knows Alex from a previous company
Expected Pain: TechFlow builds data pipelines; likely struggles with data quality and real-time sync

Discovery Framework (Prepared):
  1. How do you currently handle data quality checks? (Asked)
  2. What's broken about manual QA? (Asked)
  3. How many hours/week on data validation? (Asked - "About 12 hours")
  4. Who else owns data reliability? (Asked - "Me, plus 2 engineers")
  5. How would you evaluate a tool? (Asked)
  6. Budget allocated? (Not asked - need to circle back)

Post-Call Documentation
═════════════════════════
Call Date: March 15, 2026 | Duration: 38 minutes | Temperature: HOT
Prospect: Alex Chen | Company: TechFlow Inc. (45 employees, $2M ARR)

Discovery Outcomes:
  Pain Identified: Manual data validation is a bottleneck; they catch bugs after customers report them
  Quantified Impact: 12 hours/week of VP Product + 2 engineers = ~15-20 hours/week = $1.2K/week in wasted time + ~5-10 customer escalations/month from data bugs
  Buying Committee: Alex + 2 engineers who build the pipelines + CFO (need to approve spend)
  Decision Process: Engineering sign-off required (technical fit); CFO reviews any tool spending >$5K/month
  Buying Signal: 8/10 — Alex said "This is painful enough that we'd invest in a solution"

Objections Raised (CRITICAL):
  1. "How long to implement?" — My response: "3-5 days to get running with your data; you'll see value in week 1" — What I learned: Implementation speed is a top concern for early-stage companies (they don't have dedicated IT)
  2. "Will this integrate with our Fivetran setup?" — My response: "Yes, we have a pre-built connector" — What I learned: Need to document integrations prominently (they're evaluating 3 competitors)
  3. "This feels like a lot of upfront cost for 45 employees" — My response: "What if we structured it as $X/month for the first 3 months, then we evaluate?" — What I learned: Price elasticity is high early-stage (they want flexibility)

Product Fit Assessment:
  ✓ Strong fit: Their data validation pain is exactly what we solve; they're a perfect early customer

Next Steps & Timeline:
  Immediate: Send Alex a one-pager on Fivetran integration + references from similar companies
  By March 22: Alex to talk to 2 engineers about fit; come back with technical questions
  Their timeline: Want to fix this by Q2 (April-June); decision needed by early April

Prospect Value Assessment:
  Company size: $2M ARR, 45 employees (early-stage, growing fast)
  Likely contract value: $1.5K-3K/month (based on their size) | Confidence: High
  Reference potential: Very high — VP Product is vocal, and they'll likely see 50%+ time savings (spreadable story)
  Influence: Yes — they evaluate a lot of tools; their recommendation carries weight in their network

Pricing Reaction:
  Have you discussed price? [Yes]
  Our offer: $2K/month | Their reaction: "That's not crazy, but let me check with CFO"
  Price objection or fit objection? Fit objection primarily (they want to make sure it's worth the upfront effort) — price is secondary

---

CALL 2: Luminous Data
═════════════════════
Prospect: Jordan Smith | Title: Data Lead | Company: Luminous Data
Introduction: Cold email (ouch, but necessary to reach 20 prospects); Jordan responded
Expected Pain: Same industry as TechFlow; likely has data quality problems

Discovery Framework (Prepared):
  1. How do you currently monitor data quality?
  2. What's frustrating about that process?
  3. How much time does it consume?
  4. Who else cares about this?
  5. How would you evaluate solutions?
  6. When would you want to solve this?

Post-Call Documentation
═════════════════════════
Call Date: March 17, 2026 | Duration: 22 minutes | Temperature: COLD
Prospect: Jordan Smith | Company: Luminous Data (12 employees, $800K ARR, pre-seed stage)

Discovery Outcomes:
  Pain Identified: They use custom Python scripts; when something breaks, they have no visibility until a customer complains
  Quantified Impact: Takes ~1 day to debug when it breaks; happens ~3x/month = 12 hours/month + lost customer trust
  Buying Committee: Just Jordan (he makes tech decisions); CEO signs off on spend
  Decision Process: Informal; CEO approves anything <$500/month without approval
  Buying Signal: 5/10 — "This is painful but not urgent; we're focused on product right now"

Objections Raised (CRITICAL):
  1. "We're bootstrapped; can't spend a lot on tools" — My response: "What if we did a 30-day free trial so you see the value before paying?" — What I learned: Price sensitivity among bootstrapped companies is EXTREME; trials or risk reversal are needed
  2. "How is this different from Great Expectations?" (open-source competitor) — My response: [I fumbled this — need to articulate differentiation better] — What I learned: CRITICAL — Need a battle card for open-source competitors; this will come up again
  3. "We'd rather build this ourselves" — My response: "That makes sense; we built it because we found ourselves rebuilding the same thing 3 times. But let's stay in touch as you grow" — What I learned: Early-stage founders have strong build-vs-buy bias; lean into "you could build this, and if you do we can integrate with your build"

Product Fit Assessment:
  ☐ Possible fit: They have the pain, but they're not ready to buy yet (too early-stage, open-source fits their constraints better)

Next Steps & Timeline:
  Immediate: Send Jordan a comparison doc: Our tool vs. building in-house + cost analysis
  Revisit: 6 months (once they've hit product-market fit and hiring growth)

Prospect Value Assessment:
  Company size: $800K ARR, 12 employees (too early)
  Likely contract value: Not viable yet; maybe $200-500/month if they bought (but they won't)
  Reference potential: Low (they're too early to be a credible reference)
  Influence: Medium (good relationships in data engineering community, but too small to move their network)

Pricing Reaction:
  Have you discussed price? [Yes]
  Our offer: $2K/month | Their reaction: "That's 2.5% of our revenue; we'd rather build it"
  Price objection or fit objection? Both — but it's really a timing objection (not ready to buy)

---

FOUNDER-LED SALES MOTION SUMMARY (After 5 Calls)
════════════════════════════════════════════════════
Customers Closed to Date: 1 | Total ARR: $30K (TechFlow, 12-month contract at $2.5K/month)
Average Sales Cycle: 6 weeks (from warm intro to contract)
Average Contract Value: $30K (one data point so far)
Conversion Rate: 1 closed, 4 in pipeline ([%] TBD — too early)
Repeatable? [In Progress] — Documented? [Yes, patterns emerging]

Top 3 Prospect Types (emerging):
  1. [Profile: $1M-5M ARR SaaS, data-intensive, 30-100 employees] — Conversion rate [100% so far: 1/1]
  2. [Profile: Bootstrapped <$1M, data-focused but not urgent] — Conversion rate [0% so far: 0/2]
  3. [Profile: Mid-market data engineering teams, 5-20 person teams] — Conversion rate [TBD: 2 calls pending]

Most Common Objections (by frequency):
  1. "Integration requirements" — Raised by [3 prospects (60%)] — Our response: "Pre-built connectors for Fivetran, Airflow, dbt; custom integrations available"
  2. "Build vs. buy" — Raised by [2 prospects (40%)] — Our response: "Fair; we've been there. You could build this in 8-12 weeks. Or you can focus on product."
  3. "Price for early-stage company" — Raised by [2 prospects (40%)] — Our response: "Free trial + ROI guarantee for first 30 days"

Pricing Intelligence:
  Willing to pay: $2K-3K/month (profitable SaaS companies) or $500-1K/month (bootstrapped/early-stage)
  Price sensitivity: HIGH for companies <$1M ARR; LOW for companies >$2M ARR
  Tier effectiveness: TBD — currently offering one tier; should we offer "Growth" tier at $500/month for early-stage?

Ready to Hire Sales? [Not Yet]
  Customers closed: 1 (threshold: 15+) ← Need more data
  Process documented: Emerging (need 5+ more data points)
  Repeatable motion: Patterns visible but not yet confirmed
  Monthly close rate: [TBD] (need at least 3 months of data)
  ✗ Keep selling: Need 10+ more customers to validate motion

Edge Cases

1. Prospect asks for custom feature as buying condition

   • How it breaks: "We'll buy if you add [custom feature]"; you commit in the moment; feature takes 6 months to build
   • Prevention: Ask "How critical is this to your decision?" before promising; offer workaround or integration instead
   • Recovery: Push the custom request to "let's validate value with the core product first; then we'll prioritize that feature"

2. You price wrong (too high or too low) and close 5 customers

   • How it breaks: You charge $1K/month but should've charged $5K; now you're locked in at wrong price
   • Prevention: Price higher than you think; adjust down later if needed, but adjusting up is painful
   • Recovery: If too low, grandfather existing customers at old price, but announce new pricing for future customers immediately

3. First customer wants concessions you can't deliver

   • How it breaks: "We'll buy if you add SSO, custom reporting, and a dedicated account manager"
   • Prevention: Qualify before discovery—if their demands seem outsized, have a filter conversation early
   • Recovery: Offer partial concessions (e.g., "We'll build SSO; the other two you can access through our standard tooling")

4. You're splitting your time and sales motion stalls

   • How it breaks: You're raising funding, building product, and doing sales; none of them move
   • Prevention: Protect 10 hours/week for founder-led sales even when busy; non-negotiable
   • Recovery: Stop other activities; sales motion is the fastest way to get traction (traction helps fundraising too)

5. Network runs out of warm prospects

   • How it breaks: You've talked to everyone in your network; now what?
   • Prevention: After 10 customers, you should have references who can make warm intros to similar companies
   • Recovery: Shift to "warm-ish" outreach (LinkedIn message from mutual connection, cold email with specific personalization)

6. Objections keep changing; no pattern emerges

   • How it breaks: Every customer raises different concerns; you can't build a playbook
   • Prevention: Document ruthlessly; objections are data. You need 20 conversations to see patterns
   • Recovery: Keep selling; once you hit 15-20 customers, objections will cluster into top 3-5 that dominate