Sales Strategist

Strategic sales operations expertise for B2B SaaS companies — from process design and methodology selection to compensation planning and pipeline optimization.

Philosophy

Great sales organizations are built on process, not heroics. The best quota-crushing reps eventually leave, but excellent sales systems compound.

The best B2B sales strategies:

1. Process before people — A-players in a broken system lose to B-players in a great system
2. Qualify ruthlessly — Time is inventory; don't waste it on bad-fit deals
3. Forecast with discipline — Hope is not a strategy; data is
4. Align incentives — Compensation drives behavior, design accordingly
5. Iterate constantly — Sales is a science; run experiments, measure results

How This Skill Works

When invoked, apply the guidelines in rules/ organized by:

• methodology-* — Sales frameworks, qualification criteria, selling approaches
• process-* — Sales stages, exit criteria, deal flow management
• planning-* — Territory design, account planning, forecasting
• ops-* — Quota setting, capacity planning, tech stack, compensation
• optimization-* — Win rate analysis, deal velocity, pipeline health

Core Frameworks

Sales Qualification Frameworks

The Sales Pipeline Hierarchy

                    ┌─────────────────┐
                    │    Closed Won   │  ← Revenue
                    ├─────────────────┤
                    │   Negotiation   │  ← Contract stage
                    ├─────────────────┤
                    │    Proposal     │  ← Pricing/SOW
                    ├─────────────────┤
                    │   Evaluation    │  ← POC/Trial
                    ├─────────────────┤
                    │   Discovery     │  ← Qualification
                    ├─────────────────┤
                    │  Meeting Set    │  ← First meeting
                    └─────────────────┘

Sales Motion by ACV

Pipeline Coverage Model

┌─────────────────────────────────────────────────────────────┐
│                    PIPELINE MATH                            │
├─────────────────────────────────────────────────────────────┤
│  Target Revenue: $1M                                        │
│  Win Rate: 25%                                              │
│  Required Pipeline: $4M (4x coverage)                       │
│                                                             │
│  Average Deal Size: $50K                                    │
│  Deals Needed: 80 opportunities                             │
│                                                             │
│  Meeting → Opportunity Rate: 40%                            │
│  Meetings Needed: 200                                       │
│                                                             │
│  Response → Meeting Rate: 20%                               │
│  Outreach Needed: 1,000 responses                           │
└─────────────────────────────────────────────────────────────┘

Comp Plan Architecture

┌─────────────────────────────────────────────────────────────┐
│                 COMPENSATION STRUCTURE                       │
├─────────────────────────────────────────────────────────────┤
│  Role          │ Base:Variable │ OTE Range    │ Quota Multiple│
│  ─────────────────────────────────────────────────────────  │
│  SDR           │ 70:30        │ $70-100K     │ N/A (activity) │
│  AE (SMB)      │ 50:50        │ $100-150K    │ 4-5x OTE      │
│  AE (MM)       │ 50:50        │ $150-250K    │ 4-5x OTE      │
│  AE (Ent)      │ 60:40        │ $250-400K    │ 3-4x OTE      │
│  Sales Mgr     │ 60:40        │ $200-350K    │ Team rollup   │
└─────────────────────────────────────────────────────────────┘

Sales Technology Stack

Anti-Patterns

• Happy ears — Believing what prospects say without validation
• Demo-first selling — Showing product before understanding pain
• Single-threaded deals — Only one contact at an account
• Sandbagged forecasts — Reps hiding deals to sandbag
• Commission clawback abuse — Punishing reps for customer churn they can't control
• Territory chaos — Unclear or overlapping territories creating conflict
• Discounting addiction — Training buyers to always ask for discounts
• Vanity pipeline — Inflated stages, zombie deals, false confidence

---

Supporting file: rules/_sections.md

1. Sales Methodology (methodology)

Impact: CRITICAL Description: Qualification frameworks, selling approaches, and discovery methodologies. The foundation of how your team sells.

2. Sales Process (process)

Impact: CRITICAL Description: Sales stages, exit criteria, deal progression, and handoff protocols. The system that ensures consistency.

3. Planning & Forecasting (planning)

Impact: HIGH Description: Territory design, account planning, forecasting methodology, and pipeline management. Where strategy meets execution.

4. Sales Operations (ops)

Impact: HIGH Description: Quota setting, capacity planning, compensation design, and org structure. The infrastructure that enables scale.

5. Optimization & Analytics (optimization)

Impact: MEDIUM-HIGH Description: Win rate analysis, deal velocity, pipeline health metrics, and continuous improvement. The science of selling better.

---

Supporting file: rules/methodology-qualification-frameworks.md

Sales Qualification Frameworks

Impact: CRITICAL

Qualification determines where your reps spend their time. The right framework surfaces deal-killers early and focuses effort on winnable opportunities.

Framework Selection Matrix

MEDDIC Deep Dive

The gold standard for enterprise sales qualification.

MEDDIC Scoring Template

Score each 1-5 (1=none, 5=fully validated)

M - Metrics:           [ ] Quantified business impact documented
E - Economic Buyer:    [ ] Identified and engaged
D - Decision Criteria: [ ] Written criteria aligned to our strengths
D - Decision Process:  [ ] Timeline and stakeholders mapped
I - Identified Pain:   [ ] Compelling event driving urgency
C - Champion:          [ ] Active advocate providing intel

Total: __/30

< 15: Early stage, needs work
15-22: Developing, gaps to address
23-30: Strong opportunity, accelerate

BANT for Transactional Sales

Simple, fast, effective for high-volume sales.

SPICED for Discovery

Modern framework emphasizing business impact.

S - Situation
   "Walk me through your current process."
   "How is your team structured?"
   "What tools are you using today?"

P - Pain
   "What's broken about that?"
   "What keeps you up at night?"
   "What would happen if nothing changed?"

I - Impact
   "How does that affect revenue/costs/risk?"
   "What's the cost of the status quo?"
   "How does leadership view this?"

C - Critical Event
   "Why now? What's driving the timeline?"
   "What happens if you miss that date?"
   "What's at stake?"

E - Decision
   "How will you evaluate solutions?"
   "Who needs to be involved?"
   "What does success look like?"

D - Decision Process
   "Walk me through how you've made similar decisions."
   "What are the approval steps?"
   "What could slow this down?"

Good Qualification Examples

Strong MEDDIC Response:
AE: "Who will ultimately approve this purchase?"
Prospect: "Sarah Chen, our CFO. She approved our last platform
purchase. I've already briefed her and she's supportive. She'll
want to see ROI projections before the exec meeting on the 15th."

Why it's good:
✓ Named economic buyer
✓ Confirmed prior relationship
✓ Champion has already engaged EB
✓ Clear timeline and process
✓ Specific requirement (ROI projections)

Strong Pain Identification:
AE: "What happens if you don't solve this problem?"
Prospect: "We'll miss our Q3 launch deadline, which means
$2M in delayed revenue. My VP has this as his #1 priority,
and I've been tasked to find a solution by end of month."

Why it's good:
✓ Quantified impact ($2M)
✓ Executive visibility (VP priority)
✓ Compelling event (Q3 deadline)
✓ Clear timeline (end of month)

Bad Qualification Examples

Weak MEDDIC Response:
AE: "Who makes the final decision?"
Prospect: "I think it goes to leadership at some point."

Why it's bad:
✗ No named individual
✗ Vague process ("at some point")
✗ Prospect doesn't understand their own buying process
✗ Warning sign: prospect may not have organizational support

False Champion Warning:
Prospect: "I love your product! This is exactly what we need.
I'm going to push hard for this."

Reality check: Enthusiasm ≠ influence. Ask:
- "Have you successfully sponsored purchases before?"
- "Who else needs to be convinced?"
- "What obstacles do you anticipate?"

Qualification Red Flags

Disqualification Discipline

Know when to walk away. Time spent on bad deals is time stolen from good ones.

Disqualify when:

• No budget AND no path to budget
• No authority AND no access to authority
• No pain or pain is "nice to have"
• Timeline is beyond your sales cycle
• Deal requires you to be something you're not
• Prospect is using you for leverage with incumbent

How to disqualify gracefully:

"Based on what you've shared, it sounds like the timing might
not be right for this. I'd rather be honest than waste your time.
Would it make sense to reconnect in [timeframe] when [trigger]?"

Anti-Patterns

• Checkbox qualification — Going through motions without listening
• Single-meeting qualification — Expecting all answers in one call
• Accepting "yes" at face value — Not verifying claims
• Skipping pain for features — Demoing before qualifying
• Champion confusion — Mistaking enthusiasm for influence
• Sunk cost fallacy — Pursuing dead deals because of time invested

---

Supporting file: rules/methodology-selling-approaches.md

Sales Methodology Selection

Impact: CRITICAL

Your sales methodology is how you sell — the philosophy and tactics that guide every customer interaction. Choose based on your buyer, product complexity, and competitive landscape.

Methodology Comparison

The Challenger Sale

Ideal for markets where buyers think they know what they need (but don't).

The Three T's:

TEACH
└── Deliver insights they haven't heard
    └── Challenge their assumptions
        └── Reframe their world

TAILOR
└── Connect insights to their specific context
    └── Speak to different stakeholders differently
        └── Make it about THEIR business

TAKE CONTROL
└── Push back on unreasonable requests
    └── Drive momentum when they stall
        └── Don't be afraid of productive tension

Challenger Rep Profile:

• Offers unique perspectives
• Strong two-way communication
• Knows customer's value drivers
• Comfortable discussing money
• Can push the customer

Challenger Commercial Teaching:

1. The Warmer: Connect to known issue
   "Most teams like yours struggle with..."

2. The Reframe: Challenge their thinking
   "But the real problem isn't what you think..."

3. Rational Drowning: Data to support new frame
   "Here's what the research shows..."

4. Emotional Impact: Make it personal
   "Think about what this means for your team..."

5. The New Way: Present your solution
   "There's a better approach..."

6. Your Solution: How you enable the new way
   "This is where we help..."

SPIN Selling

Question-based methodology for complex sales.

SPIN Sequence:

Situation (2-3 questions max)
    ↓
Problem (identify pain)
    ↓
Implication (amplify pain)
    ↓
Need-Payoff (envision solution)
    ↓
Capability Discussion (your solution)

Solution Selling

Diagnostic approach: understand before prescribing.

Solution Selling Process:

┌─────────────────────────────────────────────────────────────┐
│ 1. DIAGNOSE                                                 │
│    - Current state analysis                                 │
│    - Pain identification                                    │
│    - Impact quantification                                  │
├─────────────────────────────────────────────────────────────┤
│ 2. DESIGN                                                   │
│    - Future state vision                                    │
│    - Solution requirements                                  │
│    - Success criteria                                       │
├─────────────────────────────────────────────────────────────┤
│ 3. DELIVER                                                  │
│    - Proposed solution                                      │
│    - Implementation plan                                    │
│    - ROI projection                                         │
└─────────────────────────────────────────────────────────────┘

Value Selling Framework

For buyers who demand ROI justification.

Value Equation:

                (Benefits - Costs)
Value =  ─────────────────────────────
               Risk × Time

Building the Business Case:

Good Methodology Application

Challenger Teaching Example:

AE: "Most revenue leaders I talk to are focused on hiring
more reps to hit their number. But here's what our data
shows: the top 10% of companies we work with increased
revenue 35% with the SAME headcount.

The difference? They fixed their win rate first. One VP of
Sales I spoke with said, 'We were pouring water into a
leaky bucket.' They had a 15% win rate - industry average
is 25%. By improving qualification and deal execution,
they got to 28%.

What's your current win rate, and how does that compare
to where you want to be?"

Why it works:
✓ Challenges conventional thinking (hiring vs. win rate)
✓ Uses data to reframe
✓ Social proof (VP quote)
✓ Ties back to their situation
✓ Opens discovery naturally

SPIN Application Example:

Situation: "How are you tracking sales activities today?"
Answer: "We use spreadsheets and Salesforce."

Problem: "What challenges do you face with that approach?"
Answer: "Reps hate logging activities, so data is unreliable."

Implication: "When you have unreliable data, how does that
affect your forecasting accuracy?"
Answer: "We miss our forecast by 20%+ every quarter."

Need-Payoff: "If you could automatically capture activities
and improve forecast accuracy to within 5%, what would that
mean for your planning and resource allocation?"
Answer: "That would be game-changing for how we invest."

Bad Methodology Application

Demo-First Selling (Anti-Pattern):

AE: "Thanks for taking the call. Let me share my screen
and show you our platform. So this is the dashboard,
you can see all your metrics here. And this is the
workflow builder. Pretty cool, right? Any questions?"

Prospect: "How much does it cost?"

Why it fails:
✗ No discovery of pain
✗ No qualification
✗ Features without context
✗ Commodity positioning (price is only differentiator)
✗ No value established

False Challenger (Lecturing, Not Teaching):

AE: "Let me tell you why everything you're doing is wrong.
Your process is outdated, your tools are terrible, and
frankly, your team doesn't know what they're doing."

Why it fails:
✗ Insulting, not insightful
✗ No data to support claims
✗ Not tailored to their context
✗ Breaks relationship, not builds it
✗ Challenger teaches; this just criticizes

Matching Methodology to Context

Anti-Patterns

• Methodology tourism — Switching approaches mid-deal
• One-size-fits-all — Same pitch regardless of audience
• Methodology as religion — Rigid adherence despite context
• Teaching without earning — Challenging before building rapport
• Question interrogation — SPIN without conversation
• Value without validation — ROI projections with no basis

---

Supporting file: rules/ops-compensation-design.md

Sales Compensation Plan Design

Impact: HIGH

Compensation drives behavior. Every decision in your comp plan sends a message about what you value. Get it right and you align rep motivation with company goals. Get it wrong and you create perverse incentives, sandbagging, and churn.

Compensation Design Principles

1. Simple enough to explain — If reps can't calculate earnings, they can't optimize
2. Aligned with company goals — Pay for outcomes you want
3. Competitive to attract talent — Match or beat market
4. Balanced for retention — Both short-term and long-term incentives
5. Fair across territories — Equal opportunity, not equal outcome

Base vs. Variable Split

OTE Benchmarking

2024-2025 Market Rates (US, SaaS):

Commission Structures

Structure 1: Flat Rate

Commission = Revenue × Rate

Example:
- AE closes $100K deal
- Commission rate: 10%
- Commission: $10,000

Pros: Simple, predictable
Cons: No acceleration, no differentiation
Best for: Early-stage, simple products

Structure 2: Tiered/Accelerated

Commission Rate Tiers:

Attainment     | Rate  | Effective Rate
─────────────────────────────────────────
0-80%          | 8%    | 8%
81-100%        | 10%   | ~9%
101-120%       | 12%   | ~10%
121%+          | 15%   | ~11%+

Example ($1M quota, $1.2M closed):
- First $800K: $800K × 8% = $64K
- Next $200K: $200K × 10% = $20K
- Final $200K: $200K × 12% = $24K
Total: $108K commission

Pros: Rewards overperformance
Cons: Complex, potential sandbagging
Best for: Growth-stage companies

Structure 3: Multiplier Model

Commission = Base Rate × Attainment Multiplier

Multiplier Table:
Attainment | Multiplier
─────────────────────────
<70%       | 0.5x
70-90%     | 0.8x
90-100%    | 1.0x
100-110%   | 1.2x
110-130%   | 1.5x
130%+      | 2.0x

Example ($1M quota, 10% base rate):
- Closed: $1.15M (115% attainment)
- Base commission: $1.15M × 10% = $115K
- Multiplier: 1.5x
- Actual commission: $115K × 1.5 = $172.5K

Pros: Strong overperformance incentive
Cons: Expensive at high attainment
Best for: High-growth, competitive hiring

Comp Plan Components

Standard AE Plan:

COMPENSATION PLAN - ACCOUNT EXECUTIVE

Base Salary: $100,000
Target Variable: $100,000
On-Target Earnings: $200,000
Annual Quota: $1,000,000

VARIABLE COMPENSATION BREAKDOWN

1. New Business Commission (70% of variable)
   - Commission Rate: 10% of ACV
   - Accelerators at 100%+
   - Uncapped

2. Expansion Revenue (20% of variable)
   - Commission Rate: 8% of expansion ACV
   - Same customer, new products/seats

3. Renewals (10% of variable)
   - Commission Rate: 2% of renewal ACV
   - Only for accounts in portfolio

ACCELERATORS

Attainment | Multiplier
─────────────────────────
0-50%      | 0.5x
51-80%     | 0.75x
81-100%    | 1.0x
101-120%   | 1.25x
121%+      | 1.5x

PAYMENT TERMS

- Commissions paid monthly, 15 days after close
- Multi-year deals: Year 1 ACV only
- Clawback: 100% if customer cancels within 90 days

SPIFs and Bonuses

SPIF (Sales Performance Incentive Fund) Guidelines:

SPIF Design Rules:

• Time-limited (1-4 weeks max)
• Simple and clear
• Significant enough to change behavior
• Not recurring (becomes entitlement)

Example SPIF:

"Q4 Close Accelerator SPIF"

Goal: Pull forward December pipeline to November

Mechanics:
- Any deal closed by November 30th
- That was forecasted for December
- Earns an additional 2% commission

Duration: November 1-30 only
Budget: $50K cap

Communication:
- Announced November 1st
- Weekly leaderboard
- Paid with December commissions

Good Comp Plan Design

Well-Designed Mid-Market AE Plan:

OTE: $200K (50/50 split)
Quota: $900K (4.5x OTE)

Commission Structure:
├── 0-90%: 10% flat
├── 90-100%: 11% (slight reward for hitting)
├── 100-120%: 13% (meaningful acceleration)
└── 120%+: 15% (uncapped)

Blended Components:
├── New Business: 80% weight
├── Expansion: 15% weight
└── Multi-year bonus: 5% weight

Payment Terms:
├── Monthly payment
├── Paid on booking (not collection)
└── Clawback: 90 days, 100%

Why it works:
✓ Simple enough to calculate quickly
✓ Meaningful acceleration at quota
✓ Aligned with company goals (new + expansion)
✓ Uncapped to reward top performers
✓ Clear clawback policy
✓ Competitive OTE for the role

Bad Comp Plan Design

Problematic Enterprise Plan:

OTE: $300K (60/40 split)
Quota: $2M (6.7x OTE - too high)

Commission Structure:
├── Paid on collection, not booking
├── 12-month clawback
├── Capped at 150% of target variable
├── Quarterly reset (no banking)
├── 7 different commission rates by product
├── Requires 90% of 5 different KPIs to unlock variable

Problems:
✗ Quota too high for OTE
✗ Paid on collection (not rep's control)
✗ 12-month clawback is punitive
✗ Cap discourages overperformance
✗ Quarterly reset creates gaming
✗ Too complex to understand
✗ Multi-KPI gates are demotivating

Clawback Policy

Standard Clawback Guidelines:

What NOT to Clawback:

• Customer churn due to product issues
• Customer churn due to CS failure
• Customer goes out of business
• M&A causes cancellation

Manager Compensation

Manager Comp Structures:

Example Sales Manager Plan:

Base: $150K
Target Variable: $100K
OTE: $250K

Variable Breakdown:
├── Team Quota Attainment: 70%
│   └── Team quota: $6M
│   └── Commission: 1.5% of team revenue
├── Rep Development: 15%
│   └── 2+ reps at 100%+ = full payout
├── Forecast Accuracy: 10%
│   └── Within 10% = full payout
└── Strategic Objectives: 5%
    └── Defined quarterly

Anti-Patterns

• Complexity overload — Plans no one can calculate
• Too many metrics — Dilutes focus
• Caps on earnings — Demotivates top performers
• Punitive clawbacks — Creates fear, not motivation
• Retroactive changes — Destroys trust
• Paying on collection — Rep can't control payment timing
• Quarterly resets — Creates end-of-quarter chaos
• Uncompetitive OTE — Lose talent to competitors

---

Supporting file: rules/ops-org-structure.md

Sales Organization Structure and Roles

Impact: HIGH

Your org structure determines how information flows, how deals get worked, and how reps develop. The wrong structure creates friction, dropped balls, and turf wars. The right structure enables focus, specialization, and scale.

Sales Org Evolution

Stage-Based Structure:

Role Definitions

SDR/BDR (Sales/Business Development Rep):

Focus: Pipeline generation
Metrics: Meetings booked, qualified opportunities
Reports to: SDR Manager or Sales Manager

Responsibilities:
├── Outbound prospecting (calls, emails, social)
├── Inbound lead qualification
├── Meeting scheduling for AEs
├── CRM data hygiene
└── Handoff documentation

NOT Responsible For:
├── Closing deals
├── Pricing discussions
├── Contract negotiation
└── Long-term account management

Career Path: SDR → Sr. SDR → AE or SDR Manager
Typical Tenure in Role: 12-24 months

AE (Account Executive):

Focus: Closing new business
Metrics: Bookings, revenue, win rate
Reports to: Sales Manager or Director

Responsibilities:
├── Discovery and qualification
├── Demos and presentations
├── Proposal creation
├── Negotiation and closing
├── Forecasting
└── Pipeline management

NOT Responsible For (unless hybrid):
├── Cold prospecting (SDR role)
├── Post-sale implementation (CS role)
├── Deep technical architecture (SE role)
└── Legal contract review

Segments:
├── SMB AE: High volume, transactional
├── MM AE: Balanced, 30-60 day cycles
├── Enterprise AE: Complex, 90+ day cycles
└── Strategic AE: Named accounts, relationship-heavy

SE (Sales Engineer/Solutions Consultant):

Focus: Technical validation
Metrics: POC win rate, technical close rate
Reports to: SE Manager or Sales Manager

Responsibilities:
├── Technical discovery
├── Product demonstrations (deep dive)
├── POC/trial design and execution
├── RFP/security questionnaire response
├── Solution architecture
└── Technical objection handling

Coverage Models:
├── Dedicated: 1:1 with strategic AE
├── Paired: 1:2 or 1:3 with MM/Ent AEs
├── Pooled: Shared resource, assigned per deal
└── Specialized: By use case or vertical

Sales Manager:

Focus: Team performance
Metrics: Team quota attainment, rep development
Reports to: Director or VP Sales

Responsibilities:
├── Pipeline reviews (weekly)
├── Deal coaching and strategy
├── Forecast management
├── 1:1s and performance management
├── Hiring and onboarding
└── Process enforcement

Span of Control:
├── SDR Manager: 8-12 SDRs
├── SMB Manager: 8-10 AEs
├── MM Manager: 6-8 AEs
├── Enterprise Manager: 5-6 AEs
└── Strategic Manager: 4-5 AEs

Player/Coach vs. Pure Manager:
├── Player/Coach: Carries small quota, early stage
└── Pure Manager: No individual quota, scale stage

Org Structure Models

Model 1: Pod Structure

┌─────────────────────────────────────────────────────────────┐
│                         POD                                 │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│   ┌─────────┐  ┌─────────┐  ┌─────────┐  ┌─────────┐      │
│   │  SDR 1  │  │  SDR 2  │  │  AE 1   │  │  AE 2   │      │
│   └─────────┘  └─────────┘  └─────────┘  └─────────┘      │
│                                                             │
│   ┌─────────┐  ┌─────────┐                                 │
│   │   SE    │  │   CSM   │  (Shared)                       │
│   └─────────┘  └─────────┘                                 │
│                                                             │
│   Pod Lead: AE 1 or Sales Manager                          │
└─────────────────────────────────────────────────────────────┘

Pros: Tight collaboration, clear ownership
Cons: Resource duplication, uneven workloads
Best for: Mid-market, balanced inbound/outbound

Model 2: Functional Structure

┌─────────────────────────────────────────────────────────────┐
│                      VP SALES                               │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│   ┌─────────────┐  ┌─────────────┐  ┌─────────────┐       │
│   │SDR Manager  │  │AE Manager   │  │SE Manager   │       │
│   │  └─SDR x8   │  │  └─AE x6    │  │  └─SE x4    │       │
│   └─────────────┘  └─────────────┘  └─────────────┘       │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Pros: Specialization, clear career paths
Cons: Handoff friction, potential silos
Best for: Scale stage, 20+ rep orgs

Model 3: Segment Structure

┌─────────────────────────────────────────────────────────────┐
│                      VP SALES                               │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ┌──────────────────┐  ┌──────────────────┐                │
│  │  SMB Team        │  │  Enterprise Team │                │
│  │  └─Manager       │  │  └─Manager       │                │
│  │    └─SDR x4      │  │    └─SDR x2      │                │
│  │    └─AE x6       │  │    └─AE x4       │                │
│  │                  │  │    └─SE x2       │                │
│  └──────────────────┘  └──────────────────┘                │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Pros: Tailored motions, focused expertise
Cons: Customer handoff when they grow, comp complexity
Best for: Distinct buyer journeys by segment

SDR-to-AE Handoff

Handoff Criteria:

SDR books meeting, AE accepts if:
□ Decision-maker or influencer confirmed
□ Pain/use case documented
□ Basic qualification (BANT light)
□ Company meets ICP criteria
□ Meeting time works for both parties

SDR Passes to AE:
├── Company and contact info
├── Initial pain/challenge noted
├── How they found us
├── Relevant context from research
└── Any previous touch history

Good Handoff:

SDR Email to AE:

Subject: Meeting Confirmed - Acme Corp, Tuesday 2pm

Company: Acme Corp
Contact: Sarah Chen, VP Engineering
How Sourced: Outbound (LinkedIn + email sequence)

Context:
- 50-person engineering team
- Currently using manual deployment
- Pain: "Deployments take 4 hours and fail 30% of the time"
- She asked about CI/CD specifically
- Budget cycle: Q4

Prep:
- Acme raised Series B last month ($40M)
- Competitor ExampleCo is a customer (per their case study)
- Sarah was previously at TechCorp (our customer)

Meeting link attached. Let me know if you need anything!

Bad Handoff:

SDR Email to AE:

Subject: Meeting

I booked a meeting with someone at Acme. Tuesday at 2.

Hiring Sequence

What to Hire When:

Good Org Design

$15M ARR SaaS - Well-Designed Org:

VP Sales (1)
├── SMB Team (Manager + 8 AEs + 4 SDRs)
│   └── Self-serve assisted, <$15K ACV
├── Mid-Market Team (Manager + 6 AEs + 3 SDRs + 2 SEs)
│   └── 30-60 day cycle, $15K-$75K ACV
├── Enterprise Team (Manager + 4 AEs + 2 SDRs + 2 SEs)
│   └── Named accounts, $75K+ ACV
└── Sales Ops (1)
    └── Tools, data, reporting

Total: 34 people

Rationale:
✓ Clear segment ownership
✓ Appropriate SDR:AE ratios
✓ SE coverage for technical sales
✓ Manageable spans
✓ Ops support for scale

Bad Org Design

$15M ARR SaaS - Problematic Org:

VP Sales (1)
└── 25 AEs (all reporting to VP)
    └── No SDRs (AEs self-source)
    └── No SEs (AEs do their own demos)
    └── No segmentation (all accounts treated same)
    └── No Ops (VP does reporting in Excel)

Problems:
✗ VP can't manage 25 directs
✗ AEs wasting time on prospecting
✗ No technical support = shallow demos
✗ No segment focus = mediocre at everything
✗ No ops = chaotic data, bad forecasting
✗ No career path = AEs will leave

Role Transition Planning

SDR → AE Promotion Criteria:

Quantitative:
├── 12+ months in SDR role
├── 3+ quarters at 100%+ of quota
├── Top 25% of SDR team

Qualitative:
├── Demonstrated deal sense (good handoffs)
├── Coachability and learning
├── Communication skills
├── Self-motivation

Process:
├── Internal posting / interest noted
├── Shadow program (3-5 deals)
├── Mock demo / discovery
├── Interview panel
└── Offer + ramp plan

Anti-Patterns

• Founder can't let go — Stays in every deal too long
• Flat org at scale — 15+ reps to one manager
• Skipping the SDR — AEs cold calling, wasting time
• Hybrid everything — AE does SDR, SE, and CSM work
• Segment confusion — No clear rules on who owns what
• Promote top reps — Best AE ≠ best manager
• Title inflation — Everyone is "Senior" or "Director"

---

Supporting file: rules/ops-quota-capacity.md

Quota Setting and Capacity Planning

Impact: HIGH

Quota setting is where strategy meets reality. Set quotas too high and you demoralize reps and increase attrition. Set them too low and you leave money on the table. Capacity planning ensures you have the right people in the right roles to hit your number.

Quota Setting Principles

1. Achievable by most — 60-70% of reps should hit quota
2. Based on data — Historical performance, market potential, not wishes
3. Aligned with OTE — Quota should be 4-5x OTE for most roles
4. Account for ramp — New reps get reduced quotas
5. Fair and transparent — Reps understand how quota was set

Quota-to-OTE Ratios

Quota Setting Methods

Method 1: Top-Down

Company Target: $50M ARR
├── Less: Existing renewal base: $30M
├── Net New Target: $20M
├── Sales Team Contribution: 80% = $16M
│   (Marketing/other sources: 20%)
├── Number of Reps: 20
└── Average Quota: $800K per rep

Adjustment: Add 10-15% buffer for attrition and misses
Loaded Target: $18.4M ($920K average)

Method 2: Bottom-Up

Individual Rep Calculation:

Historical Performance:
├── Rep's trailing 4 quarters: $680K, $720K, $750K, $780K
├── Average: $732K
├── Growth Assumption: 10%
└── Calculated Quota: $805K

Territory Potential:
├── Addressable accounts: 200
├── Average deal size: $40K
├── Realistic capture rate: 5%
└── Territory ceiling: $400K
    (Conflict: Territory can't support quota)

Adjustment Required: Add accounts or reduce quota

Method 3: Market-Based

Market Potential Analysis:

Territory TAM: $50M
├── Realistic SAM (qualified): $25M
├── Target Market Share: 5%
└── Territory Potential: $1.25M

Rep Capacity:
├── Working days/quarter: 65
├── Selling time: 60% = 39 days
├── Deals manageable: 15-20
├── Average deal: $50K
└── Capacity ceiling: $750K-$1M

Quota: Set at $800K (within capacity and potential)

Ramp Schedule

Standard Ramp Model:

By Segment:

Capacity Planning Model

Annual Capacity Planning:

CAPACITY CALCULATION

Step 1: Revenue Target
├── Next Year Target: $100M
├── Existing Renewals: $60M (85% retention)
│   = $51M from base
└── Net New Required: $49M

Step 2: Rep Productivity
├── Ramped Rep Average: $1M
├── New Rep Average: $500K (ramp adjusted)
└── Blended productivity: $850K

Step 3: Headcount Requirement
├── Reps Needed: $49M / $850K = 58 reps
├── Current Reps: 40
├── Attrition (20%): -8 reps
├── Ending without hiring: 32 reps
└── Hiring Needed: 26 reps

Step 4: Hiring Timeline
├── Q1 Hires: 8 reps (productive by Q3)
├── Q2 Hires: 10 reps (productive by Q4)
├── Q3 Hires: 8 reps (productive next year)
└── Total: 26 reps

Role Ratio Planning:

Sales Org Ratios (Benchmarks)

SDR : AE Ratio
├── SMB: 1:3 (one SDR feeds 3 AEs)
├── Mid-Market: 1:2
├── Enterprise: 1:1 or 2:1
└── Strategic: Dedicated SDR per AE

AE : SE Ratio
├── Simple product: 1:0 (no SE)
├── Technical sale: 2:1 or 3:1
├── Complex sale: 1:1

AE : CSM Ratio
├── High-touch: 1:1
├── Mid-touch: 1:2 or 1:3
├── Tech-touch: 1:10+

Manager : Rep Ratio
├── SDR Manager: 1:8-10
├── AE Manager: 1:6-8
├── Enterprise Manager: 1:5-6

Good Quota Setting

Quota Setting Process:

1. Historical Analysis
   Rep trailing 12 months: $920K
   YoY growth in territory: 15%
   Market growth: 12%
   Historical attainment: 85% (she exceeded)

2. Territory Analysis
   New accounts added: 20 high-potential
   Accounts removed: 10 (low potential)
   Net TAM change: +$5M

3. Capacity Analysis
   Tenure: 3 years (fully ramped)
   Performance trend: Improving
   No major life changes planned

4. Quota Calculation
   Base (historical + growth): $920K × 1.15 = $1.058M
   Territory adjustment: +$50K potential
   Final quota: $1.1M

5. Rep Communication
   "Your quota is $1.1M based on your $920K last year,
   15% growth assumption, and the 20 new accounts we
   added. At 100%, your OTE is $280K. Here's the math..."

Why it works:
✓ Data-driven, not arbitrary
✓ Considers territory changes
✓ Transparent methodology
✓ Rep understands the logic

Bad Quota Setting

Bad Quota Assignment:

Board target: "We need to grow 50%"
Last year revenue: $50M
This year target: $75M
Same headcount: 50 reps

Old average quota: $1M
New average quota: $1.5M (50% increase)

Communication: "Your quota is $1.5M this year."
Rep: "How was that determined?"
Manager: "Company needs to grow 50%."

Problems:
✗ No individual analysis
✗ No territory capacity check
✗ Same territory, higher quota = impossible
✗ Zero rationale beyond company target
✗ Will cause attrition and sandbagging

Quota Relief Policies

When to Adjust Mid-Year:

What NOT to Adjust For:

• Rep's deal slipped (normal sales volatility)
• Competitor won a deal (should have been qualified out)
• "I didn't know" (training/enablement issue)
• Champion left (multi-threading is rep responsibility)

Capacity Planning Scenarios

Scenario Modeling:

Base Case: $100M target
├── Attrition: 20%
├── Ramp time: 6 months
├── Hiring: 26 reps
├── Year-end headcount: 58
└── Risk: Medium

Aggressive Case: $120M target
├── Attrition: 15% (retention investment)
├── Ramp time: 5 months (better enablement)
├── Hiring: 35 reps
├── Year-end headcount: 68
└── Risk: High (hiring risk)

Conservative Case: $85M target
├── Attrition: 25% (economic uncertainty)
├── Ramp time: 7 months
├── Hiring: 15 reps
├── Year-end headcount: 47
└── Risk: Low (but misses board target)

Anti-Patterns

• Peanut butter quotas — Same quota for all, regardless of territory
• Punishment quotas — Raising quota because rep overachieved
• Lottery quotas — Based on luck of territory assignment
• Unattainable stretch — Less than 50% of reps can hit
• Mid-year surprises — Changing quota without warning
• Ignoring ramp — Full quota on day one
• Capacity denial — "We'll figure out headcount later"

---

Supporting file: rules/ops-tech-stack.md

Sales Tech Stack Selection

Impact: MEDIUM-HIGH

Your tech stack should enable your process, not define it. Too many tools create context-switching hell. Too few leave reps doing manual work that should be automated. The best stacks are integrated, adopted, and measured.

Tech Stack Layers

┌─────────────────────────────────────────────────────────────┐
│                    SALES TECH STACK                         │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Layer 1: SYSTEM OF RECORD                           │  │
│  │  CRM (Salesforce, HubSpot, Pipedrive)               │  │
│  └──────────────────────────────────────────────────────┘  │
│                           │                                 │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Layer 2: ENGAGEMENT                                 │  │
│  │  Sequencing, Dialers, Email                         │  │
│  │  (Outreach, Salesloft, Apollo)                      │  │
│  └──────────────────────────────────────────────────────┘  │
│                           │                                 │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Layer 3: INTELLIGENCE                               │  │
│  │  Conversation, Forecasting, Signals                 │  │
│  │  (Gong, Chorus, Clari)                              │  │
│  └──────────────────────────────────────────────────────┘  │
│                           │                                 │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Layer 4: DATA                                       │  │
│  │  Enrichment, Intent, Prospecting                    │  │
│  │  (ZoomInfo, Clearbit, 6sense)                       │  │
│  └──────────────────────────────────────────────────────┘  │
│                           │                                 │
│  ┌──────────────────────────────────────────────────────┐  │
│  │  Layer 5: ENABLEMENT                                 │  │
│  │  Content, Training, CPQ                             │  │
│  │  (Highspot, Seismic, DealHub)                       │  │
│  └──────────────────────────────────────────────────────┘  │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Tool Selection by Category

CRM (System of Record):

Sales Engagement:

Conversation Intelligence:

Data and Enrichment:

Stack by Company Stage

Seed/Early ($0-$2M ARR):

Essential Stack:
├── CRM: HubSpot Free or Pipedrive
├── Email: Gmail + basic tracking
├── Scheduling: Calendly
├── Data: Apollo (free tier) or LinkedIn Sales Nav
└── Notes: Notion or Google Docs

Total Cost: ~$100-300/month
Key principle: Keep it simple, avoid tech debt

Growth ($2M-$10M ARR):

Expanded Stack:
├── CRM: HubSpot Pro or Salesforce Essentials
├── Engagement: Apollo or Outreach (if SDR team)
├── Conversation: Gong or Chorus
├── Data: ZoomInfo or Apollo paid
├── Scheduling: Chili Piper (routing)
├── CPQ: PandaDoc or HubSpot Quotes
└── Analytics: CRM native + Gong

Total Cost: ~$2,000-5,000/month
Key principle: Foundation for scale

Scale ($10M-$50M ARR):

Full Stack:
├── CRM: Salesforce + CPQ
├── Engagement: Outreach or Salesloft
├── Conversation: Gong
├── Data: ZoomInfo + Clearbit
├── Intent: 6sense or Demandbase
├── Forecasting: Clari
├── Enablement: Highspot or Seismic
├── CPQ: DealHub or Salesforce CPQ
└── Analytics: InsightSquared or custom BI

Total Cost: ~$15,000-50,000/month
Key principle: Integration and automation

Tool Evaluation Framework

Before Adding Any Tool:

TOOL EVALUATION CHECKLIST

Problem Definition:
□ What specific problem does this solve?
□ How are we solving it today?
□ What is the cost of not solving it?

Alternatives:
□ Can we solve this with existing tools?
□ What are the top 3 alternatives?
□ Have we demoed all of them?

Integration:
□ Does it integrate with our CRM?
□ Is the integration native or third-party?
□ What data flows between systems?

Adoption:
□ Who will use this daily?
□ What is the training requirement?
□ What happens if adoption is low?

Cost:
□ Total cost (licenses + implementation)?
□ Cost per user?
□ ROI calculation?

Security:
□ SOC 2 compliant?
□ Data handling/privacy?
□ Approved by IT/Security?

Good Tech Stack Implementation

Stack Implementation Done Right:

Company: $8M ARR SaaS, 15 AEs

Stack:
├── CRM: HubSpot (clean, adopted)
├── Engagement: Apollo (sequences, data)
├── Conversation: Gong (coaching, forecasting)
├── Scheduling: Chili Piper (round robin)
└── Contracts: PandaDoc

Integration Map:
┌─────────────────────────────────────────────────────────────┐
│                                                             │
│  Apollo ──────► HubSpot ◄────── Gong                       │
│    │              │               │                         │
│    │              ▼               │                         │
│    └────────► Chili Piper ◄──────┘                         │
│                   │                                         │
│                   ▼                                         │
│               PandaDoc                                      │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Why it works:
✓ Single source of truth (HubSpot)
✓ Bi-directional sync maintained
✓ Reps don't duplicate data entry
✓ Leadership gets accurate reports
✓ All tools have clear owners

Bad Tech Stack Implementation

Stack Implementation Gone Wrong:

Company: $5M ARR SaaS, 10 AEs

Stack (accumulated over 3 years):
├── CRM: Salesforce (partially adopted)
├── Engagement: Outreach + Apollo + Reply.io
├── Conversation: Gong + Fireflies + Otter
├── Data: ZoomInfo + Lusha + RocketReach
├── Scheduling: Calendly + Chili Piper + HubSpot
├── Contracts: DocuSign + PandaDoc + HelloSign
└── More: 15 other tools "someone bought"

Problems:
✗ Multiple tools doing same thing
✗ No integration strategy
✗ Data in 3 places, none accurate
✗ Reps confused about which tool to use
✗ $40K/month in tool spend
✗ No one owns the stack

Reality:
- Salesforce 40% filled in
- Half the tools unused
- Reps use spreadsheets anyway
- Forecast from manual roll-up calls

CRM Hygiene Requirements

Minimum Required Fields:

Data Hygiene Rules:

Automated Hygiene (CRM Workflows):

1. No activity 30+ days → Alert rep + manager
2. Close date passed → Force update or close
3. Deal in stage 60+ days → Review flag
4. Missing required fields → Can't progress stage
5. Duplicate contacts → Merge prompt
6. No next step → Can't leave deal view

Tool Consolidation

Signs You Need to Consolidate:

• Same task can be done in 3+ tools
• Reps ask "where do I log this?"
• Data doesn't match across systems
• Tool spend >$500/rep/month
• Less than 60% adoption on any tool
• No one knows who owns which tool

Consolidation Process:

Step 1: Inventory
├── List all sales tools
├── Identify owner and users
├── Document actual usage (login data)
└── Calculate cost per tool

Step 2: Categorize
├── Essential (can't sell without)
├── Important (significant value)
├── Nice-to-have (limited use)
└── Unused (cancel immediately)

Step 3: Rationalize
├── One tool per category
├── Migrate data if needed
├── Provide transition time
└── Cancel redundant contracts

Step 4: Document
├── Official stack list
├── Owner for each tool
├── Governance process for new requests
└── Quarterly review schedule

Anti-Patterns

• Shiny object syndrome — Buying every new tool
• No integration plan — Tools that don't talk
• Tool as strategy — "Gong will fix our coaching"
• Rep as data entry — Duplicate logging everywhere
• No ownership — Tools bought, never managed
• Sunk cost fallacy — Keeping tools because "we paid for it"
• Over-tooling early — Enterprise stack at seed stage

---

Supporting file: rules/optimization-deal-velocity.md

Deal Velocity Optimization

Impact: MEDIUM-HIGH

Deal velocity measures how fast revenue moves through your pipeline. Faster cycles mean more deals per rep per year, better forecasting, and reduced risk of deals dying. Even small velocity improvements compound significantly.

Deal Velocity Formula

Sales Velocity = (# of Opportunities × Average Deal Size × Win Rate) / Sales Cycle Length

Example:
- Opportunities: 100
- Deal Size: $50,000
- Win Rate: 25%
- Cycle Length: 60 days

Velocity = (100 × $50,000 × 0.25) / 60 = $20,833/day

Improving cycle by 10 days:
Velocity = (100 × $50,000 × 0.25) / 50 = $25,000/day
= 20% increase in revenue velocity

Measuring Sales Cycle

Calculation Methods:

Benchmark Cycles by Segment:

Stage Velocity Analysis

Identify Bottlenecks:

STAGE VELOCITY ANALYSIS

Stage            | Avg Days | Target | Status  | Bottleneck?
─────────────────────────────────────────────────────────────────
Discovery        | 8        | 7      | OK      |
Qualified        | 15       | 10     | SLOW    | ← Bottleneck
Evaluation       | 25       | 20     | SLOW    | ← Bottleneck
Proposal         | 12       | 10     | OK      |
Negotiation      | 8        | 7      | OK      |
─────────────────────────────────────────────────────────────────
Total            | 68       | 54     | +14 days behind target

Analysis:
- Qualified stage: Taking too long to schedule evaluation
  → Action: Implement same-week evaluation scheduling
- Evaluation stage: POC running long
  → Action: Reduce POC scope, 2-week max duration

Velocity by Dimension

Track Multiple Cuts:

Velocity Dashboard:

By Rep:
├── Rep A: 45 days (Fast)
├── Rep B: 58 days (Average)
├── Rep C: 62 days (Average)
├── Rep D: 78 days (Slow)   ← Coach on pacing
└── Rep E: 92 days (Slow)   ← Coach on pacing

By Source:
├── Inbound: 42 days (Faster - higher intent)
├── Outbound: 68 days (Slower - building need)
└── Partner: 55 days (Medium)

By Deal Size:
├── <$25K: 32 days
├── $25K-$50K: 55 days
├── $50K-$100K: 78 days
└── $100K+: 110 days

By Industry:
├── Tech: 45 days (Fastest - quick decisions)
├── Finance: 72 days (Compliance adds time)
├── Healthcare: 85 days (Slowest - procurement)
└── Retail: 50 days

Acceleration Tactics

By Stage:

Quick Wins:

Immediate Acceleration Actions:

1. "Book the Next Meeting"
   Before ending any call, book the next step
   Impact: Saves 3-5 days per stage

2. "Compressed Timelines by Default"
   Propose aggressive timelines, let them negotiate
   "Can we schedule the POC for next week?"
   Impact: 20-30% cycle reduction

3. "Mutual Action Plan"
   Shared document with dates and owners
   Creates accountability, surfaces blockers early
   Impact: 15-20% cycle reduction

4. "POC Time-Boxing"
   "Our POCs are 2 weeks. Here's why that's enough..."
   Impact: Reduces 4-week POCs to 2 weeks

5. "Early Legal Engagement"
   Send MSA at proposal stage, not negotiation
   Impact: Saves 1-2 weeks in legal review

Mutual Action Plan (MAP)

Template:

MUTUAL ACTION PLAN
Company: [Customer Name]
Deal: [Opportunity Name]
Target Close Date: [Date]

MILESTONES

Date       | Milestone              | Owner      | Status
───────────────────────────────────────────────────────────
Week 1     | Discovery call         | [AE]       | Complete
Week 2     | Technical deep dive    | [SE + IT]  | Complete
Week 2     | Stakeholder intro      | [Champion] | Complete
Week 3-4   | POC kickoff            | [SE]       | In Progress
Week 4     | POC success review     | [Both]     | Pending
Week 5     | Business case review   | [Champion] | Pending
Week 5     | Pricing proposal       | [AE]       | Pending
Week 6     | Executive presentation | [Both]     | Pending
Week 6     | MSA review begins      | [Legal]    | Pending
Week 7     | Contract redlines      | [Legal]    | Pending
Week 8     | Signature              | [EB]       | Target Close

RISKS AND MITIGATIONS

Risk: CFO travel during Week 6
Mitigation: Scheduled async briefing, Champion to present

Risk: Procurement review could extend timeline
Mitigation: Engaged procurement in Week 4

OPEN QUESTIONS

- Final seat count for pricing (due Week 4)
- Security questionnaire status (due Week 5)

Good Velocity Optimization

Velocity Improvement Case Study:

Problem: Average cycle 75 days, target 55 days

Analysis:
├── Discovery → Qualified: 12 days (target 7)
│   └── Cause: Reps not booking immediately
├── Qualified → Evaluation: 20 days (target 14)
│   └── Cause: Waiting for prospect to set up POC
├── Evaluation → Proposal: 25 days (target 20)
│   └── Cause: POC scope creep, no time limit
└── Proposal → Close: 18 days (target 14)
    └── Cause: Legal surprised by redlines

Actions:
1. Implemented "book next meeting" requirement in CRM
2. Created standard POC environment (no setup required)
3. POC time-boxed to 14 days, success criteria required
4. MSA sent at proposal stage, standard redlines shared

Results (After 1 Quarter):
├── Discovery → Qualified: 12 → 8 days
├── Qualified → Evaluation: 20 → 12 days
├── Evaluation → Proposal: 25 → 18 days
└── Proposal → Close: 18 → 13 days

New Average: 51 days (32% improvement)

Bad Velocity Practices

Artificial Velocity (Anti-Pattern):

Sales Leader: "Our cycle time is too long. I want it cut by 30%."

Action: Reps start pushing prospects to make decisions
- "We need a decision by Friday"
- "This pricing expires Monday"
- Pressure tactics, manufactured urgency

Result:
- Prospects feel rushed, deals die
- Win rate drops from 25% to 18%
- Cycle shortens but revenue decreases
- Customer relationships damaged

Ignoring Reality (Anti-Pattern):

Deal has been in "Evaluation" for 45 days
Rep: "They're just busy, it'll close next week"
Manager: "Update the close date and move on"

Problem:
- Close date updated 4 times
- No actual buyer activity
- Deal eventually lost to "no decision"
- Should have been disqualified or re-engaged

Velocity Killers

Velocity vs. Quality Trade-offs

Balance Speed and Win Rate:

Scenario Analysis:

Current State:
- Cycle: 60 days
- Win Rate: 25%
- 100 opportunities
- Velocity: $20,833/day

Option A: Push harder (faster, lower win rate)
- Cycle: 45 days
- Win Rate: 20% (pressure reduces conversion)
- Velocity: $22,222/day (+7%)

Option B: Better process (faster AND better win rate)
- Cycle: 50 days
- Win Rate: 28% (better qualification)
- Velocity: $28,000/day (+34%)

Lesson: Don't sacrifice quality for speed

Velocity Dashboard

DEAL VELOCITY DASHBOARD

Average Cycle: 58 days (Target: 50)
Trend: ↓ Improving (was 65 days last quarter)

By Stage (Avg Days):
├── Discovery → Qualified: 8 days ✓
├── Qualified → Evaluation: 14 days ← Bottleneck
├── Evaluation → Proposal: 20 days ← Bottleneck
├── Proposal → Negotiation: 10 days ✓
└── Negotiation → Close: 6 days ✓

Deals in Stage >2x Average:
├── Acme Corp: 45 days in Evaluation (normal: 20)
├── TechFlow: 30 days in Qualified (normal: 14)
└── DataCo: 35 days in Proposal (normal: 10)

Actions:
- Acme Corp: Schedule checkpoint call, decision needed
- TechFlow: Champion check, may need new contact
- DataCo: Pricing concern? Re-engage on value

Anti-Patterns

• Vanity dates — Close dates that never come
• Pressure over process — Pushing vs. enabling
• Ignoring stalls — "They're just slow"
• One-size timeline — Same cycle expectation for all deals
• Speed without quality — Fast losses are still losses
• No stage analysis — Only looking at total cycle
• Blame the buyer — "They take forever" (what can YOU do?)

---

Supporting file: rules/optimization-win-rate.md

Win Rate Analysis and Optimization

Impact: MEDIUM-HIGH

Win rate is the highest-leverage metric in sales. A 5-point improvement in win rate (e.g., 20% to 25%) is equivalent to 25% more pipeline at the same conversion. Analyzing why you win and lose reveals exactly where to invest.

Win Rate Fundamentals

Win Rate Calculation:

Win Rate = Closed Won / (Closed Won + Closed Lost)

Example:
- Closed Won: 25 deals
- Closed Lost: 75 deals
- Win Rate: 25 / (25 + 75) = 25%

Note: Do NOT include open deals in calculation

Win Rate Segmentation:

Win/Loss Analysis Framework

Data Collection:

CLOSED LOST ANALYSIS FORM

Deal: [Name]
Amount: $[X]
Stage Lost: [Which stage]
Time in Pipeline: [Days]

PRIMARY REASON (select one):
□ Price/Budget
□ Feature/Capability Gap
□ Chose Competitor
□ Chose Status Quo (no decision)
□ Timing (not ready)
□ Champion Left
□ Lost Access to Power
□ Security/Compliance
□ Other: [Specify]

COMPETITOR (if applicable):
□ [Competitor A]
□ [Competitor B]
□ [Build in-house]
□ [Incumbent]
□ [Unknown]

QUALITATIVE NOTES:
- What could we have done differently?
- When did we know we were losing?
- What would have changed the outcome?

FOLLOW-UP:
□ Nurture for future
□ Closed permanently
□ Lost to competitor (track for later)

Win/Loss Patterns

Common Loss Reasons and Actions:

Pattern Analysis:

Q3 Loss Analysis (50 lost deals):

By Reason:
├── No Decision: 18 (36%) ← Biggest problem
├── Competitor: 14 (28%)
│   ├── Competitor A: 8
│   └── Competitor B: 6
├── Price: 8 (16%)
├── Feature Gap: 6 (12%)
└── Other: 4 (8%)

By Stage:
├── Lost at Discovery: 5 (10%) ← Good, quick disqual
├── Lost at Qualified: 12 (24%)
├── Lost at Evaluation: 20 (40%) ← Bleeding here
├── Lost at Proposal: 10 (20%)
└── Lost at Negotiation: 3 (6%)

Insight: 40% of losses in Evaluation stage
Action: Review POC process, success criteria, competitive positioning

Win Analysis

Don't Just Study Losses:

CLOSED WON ANALYSIS FORM

Deal: [Name]
Amount: $[X]
Sales Cycle: [Days]
Discount: [%]

WHY WE WON:
□ Product/Feature fit
□ Price/Value
□ Trust/Relationship
□ Incumbent failure
□ Competitive positioning
□ Speed/Time to value
□ Other: [Specify]

KEY MOMENTS:
- What was the turning point?
- What resonated most with the buyer?
- Who was our champion and why?
- What almost killed the deal?

REPLICABLE ELEMENTS:
- What can we repeat in similar deals?
- What content/demo/proof point worked?
- What objection handling worked?

Rep-Level Win Rate Analysis

Identifying Coaching Needs:

Rep Win Rate Analysis - Q3:

Rep        | Opps | Won | Lost | Win Rate | vs. Team Avg |
────────────────────────────────────────────────────────────
Rep A      | 40   | 14  | 26   | 35%      | +10%
Rep B      | 35   | 10  | 25   | 29%      | +4%
Rep C      | 45   | 11  | 34   | 24%      | -1%
Rep D      | 38   | 8   | 30   | 21%      | -4%
Rep E      | 42   | 7   | 35   | 17%      | -8%         ← Focus here
Team Avg   | 40   | 10  | 30   | 25%      | --

Rep E Deep Dive:
├── Loss by reason: 50% No Decision (vs 36% team)
├── Time to first meeting: 8 days (vs 3 days team)
├── Multi-threaded deals: 20% (vs 60% team)
└── Discovery call talk ratio: 70% (vs 50% team)

Coaching Focus:
1. Create urgency earlier in process
2. Multi-threading requirement
3. Discovery call structure (listen more)

Win Rate by Stage Entry

Quality of Pipeline:

Win Rate by Entry Stage:

Entered at    | Opps | Win Rate | Insight
──────────────────────────────────────────────────────────────
Discovery     | 200  | 15%      | Standard funnel
Qualified     | 80   | 35%      | Better qualified leads
Evaluation    | 30   | 55%      | Strong intent (inbound demo)
Proposal      | 10   | 70%      | Near-ready buyers

Implication:
- Focus on lead quality, not just volume
- Invest in qualification to raise conversion
- Inbound leads entering at Evaluation are 3.7x more likely to close

Competitive Win Rate

Track by Competitor:

Competitive Analysis - Last 12 Months:

Competitor    | Faced | Won | Lost | Win Rate | Trend
──────────────────────────────────────────────────────────────
Competitor A  | 45    | 22  | 23   | 49%      | Improving ↑
Competitor B  | 30    | 9   | 21   | 30%      | Declining ↓
Competitor C  | 25    | 15  | 10   | 60%      | Stable →
Status Quo    | 100   | 25  | 75   | 25%      | Stable →

Competitor B Analysis:
- Losing on: Price (40%), Feature X (35%)
- Their pitch: "Same features, 30% cheaper"
- Our gap: Value messaging not landing

Action:
- Develop ROI calculator
- Case study on TCO (total cost of ownership)
- Train on Competitor B objection handling

Good Win Rate Optimization

Win Rate Improvement Initiative:

Problem: Win rate dropped from 28% to 22% over 2 quarters

Analysis:
├── Loss reason spike: "No Decision" up from 30% to 45%
├── Stage analysis: 50% of losses in Discovery-Qualified
├── Rep analysis: New reps (<6 months) at 15% win rate
└── Source: Outbound win rate dropped to 12%

Root Causes:
1. New reps not qualifying hard enough
2. Outbound targeting too broad
3. Champion development weak

Actions Taken:
1. Qualification → Implemented MEDDIC scorecard requirement
2. Targeting → Narrowed ICP, added intent data
3. Champion → Created "Champion Development" playbook

Results (Next Quarter):
├── Win rate: 22% → 26%
├── No Decision losses: 45% → 32%
├── New rep win rate: 15% → 20%
└── Outbound win rate: 12% → 18%

Bad Win Rate Analysis

Surface-Level Analysis (Anti-Pattern):

Manager: "Our win rate is 20%. We need it to be 30%."

Action: "Reps, close more deals."

Why it fails:
✗ No root cause analysis
✗ No segmentation
✗ No actionable insight
✗ "Close more" isn't a strategy
✗ Reps don't know what to change

Vanity Win Rate (Anti-Pattern):

Actual: 100 opportunities, 20 won, 80 lost = 20%

Manipulated:
- Removed 30 "bad fit" deals from lost
- Reclassified 20 lost as "nurture"
- New denominator: 50

Reported: 20 won / 50 = 40% win rate

Reality: Still 20%, just hiding the truth

Win Rate Improvement Levers

Win Rate Dashboard

WIN RATE DASHBOARD

Overall: 25% (Target: 28%)
Trend: ↑ 2pts from last quarter

By Segment:
├── SMB: 30% ✓
├── Mid-Market: 24% ↓
└── Enterprise: 22% →

By Rep (vs. Target):
├── Above target: 4 reps
├── At target: 6 reps
└── Below target: 5 reps ← Coaching focus

By Competitor:
├── vs. Competitor A: 45% ✓
├── vs. Competitor B: 28% ↓
├── vs. Status Quo: 24% →
└── vs. In-house: 18% ↓

Top Loss Reasons (This Quarter):
├── No Decision: 35%
├── Competitor: 28%
├── Price: 18%
└── Feature Gap: 12%

Action Items:
1. MM win rate declining - review qualification
2. Competitor B training scheduled
3. In-house objection playbook needed

Anti-Patterns

• Ignoring losses — Only celebrating wins
• Blaming the lead — "The lead was bad" (maybe, but why'd you work it?)
• Sample size — Drawing conclusions from 5 deals
• Lagging analysis — Reviewing Q1 losses in Q3
• No rep feedback — Analyzing data without talking to reps
• One-time analysis — Win/loss should be continuous
• Quota pressure — Pushing deals that shouldn't close

---

Supporting file: rules/planning-forecasting-pipeline.md

Sales Forecasting and Pipeline Management

Impact: HIGH

Accurate forecasting enables confident business decisions — hiring, marketing spend, product investment. Inaccurate forecasts destroy trust and cause reactive chaos. Forecasting is a skill that can be systematized.

Forecasting Methods

Stage-Weighted Forecasting

Standard Model:

┌─────────────────────────────────────────────────────────────┐
│ WEIGHTED PIPELINE CALCULATION                               │
├─────────────────────────────────────────────────────────────┤
│ Stage          │ Value    │ Probability │ Weighted Value   │
│ ─────────────────────────────────────────────────────────── │
│ Discovery      │ $500K    │ 10%         │ $50K             │
│ Qualified      │ $800K    │ 20%         │ $160K            │
│ Evaluation     │ $600K    │ 40%         │ $240K            │
│ Proposal       │ $400K    │ 60%         │ $240K            │
│ Negotiation    │ $300K    │ 80%         │ $240K            │
├─────────────────────────────────────────────────────────────┤
│ TOTAL PIPELINE │ $2.6M    │             │ $930K            │
└─────────────────────────────────────────────────────────────┘

Forecast = Weighted Value = $930K

Calibrating Probabilities:

Probabilities should reflect YOUR historical conversion rates, not industry averages.

Historical Analysis (Last 4 Quarters):

Stage        | Entered | Won  | Historical Rate | Use |
─────────────────────────────────────────────────────────
Discovery    | 500     | 50   | 10%            | 10%
Qualified    | 300     | 55   | 18%            | 20%
Evaluation   | 200     | 70   | 35%            | 40%
Proposal     | 150     | 90   | 60%            | 60%
Negotiation  | 120     | 100  | 83%            | 80%

Forecast Categories

The Commit/Best Case/Pipeline Framework:

Example Forecast Submission:

Q4 Forecast - Sarah Chen

Commit: $450K
├── Acme Corp: $200K - Contract in legal review
├── TechStart: $150K - Verbal yes, PO processing
└── DataFlow: $100K - Signed, booking this week

Best Case: $700K
├── Commit: $450K
├── GlobalTech: $150K - Final presentation Thursday
└── FinServ Inc: $100K - Champion confident, CFO approval pending

Pipeline: $1.2M
├── Best Case: $700K
├── MediaCo: $200K - POC positive, pricing discussions
├── HealthCare Plus: $150K - Evaluation stage, competitive
└── RetailNow: $150K - Discovery complete, aligning stakeholders

Quota: $500K | Commit: 90% | Best Case: 140%

Pipeline Coverage Model

The Rule of Thumb (Calibrate to Your Data):

Pipeline Coverage Formula:

Required Pipeline = Target Revenue / Win Rate

Example:
- Q4 Target: $1M
- Historical Win Rate: 25%
- Required Pipeline: $1M / 0.25 = $4M

By Stage:
- Start of quarter: 4-5x coverage
- Mid-quarter: 3x coverage
- End of quarter: 1.5-2x coverage

Forecast Accuracy Measurement

Tracking Forecast vs. Actual:

Forecast Accuracy = 1 - |Actual - Forecast| / Forecast

Example:
- Forecast: $500K
- Actual: $450K
- Accuracy: 1 - |450-500|/500 = 90%

Accuracy Benchmarks:

Tracking Over/Under Forecasting:

Monthly Forecast Analysis:

Rep        | Forecast | Actual | Variance | Trend |
─────────────────────────────────────────────────────
Rep A      | $100K    | $120K  | +20%     | Sandbagging
Rep B      | $150K    | $140K  | -7%      | Accurate
Rep C      | $200K    | $130K  | -35%     | Happy ears
Rep D      | $80K     | $85K   | +6%      | Accurate

Action: Coach Rep A (sandbagger) and Rep C (optimist)

Good Forecasting Practices

Weekly Forecast Review Process:

Monday: Reps update commit/best case in CRM
Tuesday: Manager 1:1 reviews with each rep
Wednesday: Manager submits team forecast
Thursday: Regional rollup and leadership review
Friday: Actions and adjustments communicated

Deal Review Questions:
1. "What has the buyer DONE since last week?"
   (Actions > Words)
2. "What is the specific next step and date?"
   (Vague = risk)
3. "What could cause this to slip?"
   (Surface risks)
4. "On a scale of 1-10, how confident are you?"
   (Force honesty)
5. "If you had to bet your commission, would you?"
   (Gut check)

Good Forecast Call Example:

Manager: "Walk me through the TechCorp deal."

Rep: "It's in my commit at $150K. Here's why:
- Champion (VP Eng) confirmed budget is approved
- We have a signed evaluation success criteria document
- Legal has the contract, they confirmed 5-day turnaround
- CFO signed the last two purchases under $200K
- I have the PO requisition number
- Close date: December 15th"

Manager: "What could delay it?"
Rep: "Holidays could slow legal. I built in a week buffer."

Why it works:
✓ Specific evidence, not feelings
✓ Multiple verification points
✓ Acknowledges risks
✓ Realistic timeline

Bad Forecasting Practices

Bad Forecast Call Example:

Manager: "Where are we on the GlobalCo deal?"

Rep: "I feel really good about it. They loved the demo.
My contact said they're definitely interested. I think
we can close it this quarter."

Manager: "Is it in your commit?"
Rep: "Yeah, I'm putting it at $200K."

Problems:
✗ "Feel good" is not evidence
✗ "Loved the demo" doesn't mean purchase
✗ "Definitely interested" is not commitment
✗ "I think" indicates uncertainty
✗ No specific evidence provided

Pipeline Stuffing (Anti-Pattern):

End of quarter approaching, quota at risk.

Rep creates 10 new opportunities:
- "Initial conversation" deals at $100K each
- All in "Discovery" stage
- Close dates: this quarter

Reality:
- Inflates pipeline metrics
- Destroys forecast accuracy
- Creates false comfort
- Next quarter has the same problem

Pipeline Health Metrics

Pipeline Health Dashboard:

PIPELINE HEALTH CHECK - Q4

Coverage: 4.2x [HEALTHY]
├── Target: $5M
├── Total Pipeline: $21M
└── Weighted: $6.3M

Stage Distribution: [NEEDS ATTENTION]
├── Discovery: 45% (high - qualify or kill)
├── Qualified: 25% (okay)
├── Evaluation: 15% (okay)
├── Proposal: 10% (okay)
└── Negotiation: 5% (low - need late-stage)

Aging: [WARNING]
├── 12 deals > 2x average cycle
└── $3.2M in stale opportunities

Win Rate Trend: [HEALTHY]
├── Last quarter: 24%
├── This quarter (so far): 27%
└── Trend: Improving

Anti-Patterns

• Hope-based forecasting — "I think they'll close"
• Sandbagging — Hiding deals to look like a hero later
• Happy ears — Believing what you want to hear
• End-of-quarter stuffing — Fake pipeline to hit metrics
• Single-deal dependency — Forecast relying on one whale
• Ignoring history — Not learning from past accuracy
• Quarterly panic — Same mistakes every quarter

---

Supporting file: rules/planning-territory-accounts.md

Territory and Account Planning

Impact: HIGH

Territory design determines rep productivity. Poor territories create conflict, missed opportunities, and burned-out reps. Great territories balance opportunity, workload, and growth potential.

Territory Design Principles

1. Equal opportunity — Not equal size, equal revenue potential
2. Clear boundaries — No ambiguity about ownership
3. Appropriate coverage — Workload matches capacity
4. Growth headroom — Room to expand without restructuring
5. Stability — Changes only when necessary

Territory Segmentation Models

Territory Sizing Framework

Target Capacity Calculation:

Step 1: Calculate Total Addressable Territory
┌─────────────────────────────────────────────────────────────┐
│ Total Accounts in ICP: 10,000                               │
│ Average Deal Size: $50,000                                  │
│ Addressable TAM: $500M                                      │
└─────────────────────────────────────────────────────────────┘

Step 2: Define Coverage Model
┌─────────────────────────────────────────────────────────────┐
│ Annual Quota per Rep: $1M                                   │
│ Win Rate: 25%                                               │
│ Required Pipeline: $4M per rep                              │
│ Average Opportunities per Account: 1                        │
│ Accounts Needed per Rep: 160 (at 4M / 50K * 25%)           │
└─────────────────────────────────────────────────────────────┘

Step 3: Determine Territory Size
┌─────────────────────────────────────────────────────────────┐
│ Minimum viable territory: 200 accounts                      │
│ (Buffer for disqualification, timing, churn)                │
│                                                             │
│ Maximum manageable: 500 accounts                            │
│ (Beyond this, coverage drops)                               │
│                                                             │
│ Sweet spot: 250-350 accounts per enterprise rep             │
└─────────────────────────────────────────────────────────────┘

Account Capacity by Role:

Account Tiering

The ABM Tier Model:

Account Scoring Criteria:

Account Planning Template

For Tier 1/Strategic Accounts:

ACCOUNT OVERVIEW
────────────────────────────────────────
Company: [Name]
Industry: [Vertical]
Revenue: $[X]M
Employees: [X]
Fiscal Year End: [Month]

CURRENT STATE
────────────────────────────────────────
Relationship Stage: [ ] New [ ] Developing [ ] Established
Current ARR: $[X]
Products/SKUs Used: [List]
Contract End Date: [Date]
NPS/Health Score: [X]

ACCOUNT STRATEGY
────────────────────────────────────────
12-Month Revenue Target: $[X]
Expansion Opportunities:
  - [Opportunity 1]: $[X] potential
  - [Opportunity 2]: $[X] potential
White Space Analysis:
  - Departments not using: [List]
  - Use cases not addressed: [List]

RELATIONSHIP MAP
────────────────────────────────────────
Economic Buyer: [Name, Title]
  - Relationship: [ ] None [ ] Aware [ ] Engaged [ ] Champion
  - Engagement Plan: [Action]

Champion: [Name, Title]
  - Influence: [ ] Low [ ] Medium [ ] High
  - Engagement Frequency: [Weekly/Monthly]

Detractor/Blocker: [Name, Title]
  - Concern: [What]
  - Mitigation: [Plan]

COMPETITIVE LANDSCAPE
────────────────────────────────────────
Primary Competitor: [Name]
Installed Base: [Products they use]
Our Competitive Position: [ ] Behind [ ] Even [ ] Ahead
Differentiation Strategy: [Key points]

ACTION PLAN (90-DAY)
────────────────────────────────────────
Goal: [Specific outcome]
Actions:
  1. [Action] - Owner: [Name] - Date: [When]
  2. [Action] - Owner: [Name] - Date: [When]
  3. [Action] - Owner: [Name] - Date: [When]
Next Review Date: [Date]

Good Territory Design

Balanced Enterprise Territory:

Territory: US West - Enterprise Technology
Rep: Sarah Chen
Quota: $1.5M

Account Composition:
├── Tier 1 (Named): 15 accounts
│   └── Combined TAM: $8M
│   └── Expected from named: $750K
├── Tier 2 (Target): 100 accounts
│   └── Combined TAM: $25M
│   └── Expected: $500K
└── Tier 3 (Develop): 200 accounts
    └── Combined TAM: $30M
    └── Expected: $250K

Total Pipeline Potential: $63M
Expected Revenue: $1.5M (2.4% capture rate)
Pipeline Coverage: 4.2x quota (at 25% win rate)

Why it works:
✓ Mix of named and territory accounts
✓ Clear tiering with different strategies
✓ Achievable quota with realistic win rates
✓ Headroom for overachievement

Bad Territory Design

Problematic Territory Assignment:

Territory: "Enterprise - All Verticals"
Rep: New hire (6 months experience)
Quota: $2M
Accounts: 400 (no tiering)

Problems:
✗ Too many accounts for enterprise coverage
✗ No prioritization guidance
✗ New rep without domain expertise
✗ No named accounts for focus
✗ Quota likely unachievable
✗ Rep will spray and pray

Overlapping Territories:

SDR Team: Outbound to all accounts
AE Team: Inbound from all accounts
Partner Team: Partner-sourced to all accounts

Result:
- Same account gets 3 different outreaches
- Customer confusion and annoyance
- Internal conflict over attribution
- "Who owns this account?" debates

Territory Conflict Resolution

Clear Rules of Engagement:

Annual Territory Planning Process

Q4 Planning Timeline:

Week 1-2: Data Preparation
├── Clean account data
├── Update account scoring
├── Analyze current territory performance
└── Identify account changes (M&A, growth, churn)

Week 3-4: Territory Modeling
├── Model 2-3 territory designs
├── Calculate coverage and quota alignment
├── Identify conflicts and overlaps
└── Pressure test with edge cases

Week 5-6: Stakeholder Review
├── Review with Sales Leadership
├── Gather rep feedback (informally)
├── Align with Marketing on ABM tiers
└── Finalize design

Week 7-8: Communication and Rollout
├── Communicate changes individually first
├── Provide transition guidance
├── Update systems (CRM, routing)
└── Document rules of engagement

Anti-Patterns

• Annual chaos — Major territory changes every year
• Carving up success — Taking accounts from top performers
• Ignoring workload — Equal accounts ≠ equal opportunity
• No transition period — Abrupt changes mid-deal
• Gaming the system — Reps hoarding accounts they won't work
• Spreadsheet territories — No CRM enforcement

---

Supporting file: rules/process-sales-stages.md

Sales Stages and Exit Criteria

Impact: CRITICAL

Sales stages create shared language and predictability. Without clear exit criteria, your pipeline becomes a fantasy — deals sit in stages they shouldn't be in, forecasts are meaningless, and reps waste time on stuck opportunities.

Stage Design Principles

1. Buyer-centric — Stages reflect where the buyer is, not what you've done
2. Objectively verifiable — Exit criteria can be proven, not assumed
3. Mutually exclusive — A deal can only be in one stage
4. Progressive probability — Each stage represents higher likelihood
5. Action-oriented — Clear next steps at each stage

Standard B2B SaaS Stage Model

Detailed Exit Criteria

Stage 1: Discovery → Qualified

Required to Exit:

□ First meeting completed
□ Key stakeholders identified (names, titles, roles)
□ Pain/challenge articulated by prospect (not assumed)
□ Current state documented
□ Rough budget range confirmed (at least "we have budget")
□ Timeline discussed (even if "no rush")
□ Competitive landscape understood
□ Next step scheduled with specific date

Verification Method:

• Call recording reviewed
• Notes documented in CRM
• Follow-up email sent confirming understanding

Stage 2: Qualified → Evaluation

Required to Exit:

□ MEDDIC/qualification framework fully scored
□ Economic buyer identified by name
□ Decision process documented (steps, timeline, people)
□ Decision criteria documented (written, not verbal)
□ Champion confirmed (willing to advocate, share info)
□ Compelling event identified (why now?)
□ Technical requirements scoped
□ Evaluation plan agreed (POC scope, success criteria)

Verification Method:

• MEDDIC score > 20/30
• Written evaluation plan sent and acknowledged
• Multi-threaded (3+ contacts engaged)

Stage 3: Evaluation → Proposal

Required to Exit:

□ Technical validation complete
□ POC/trial success criteria met
□ Security/compliance review passed (if applicable)
□ Champion confirms positive internal feedback
□ Economic buyer aware and supportive
□ Pricing discussion held (at least range)
□ Implementation timeline discussed
□ Contract redlines anticipated (if any)

Verification Method:

• POC success documented
• Positive email/feedback from champion
• Pricing meeting scheduled or held

Stage 4: Proposal → Negotiation

Required to Exit:

□ Formal proposal/quote delivered
□ Proposal reviewed with stakeholders
□ Pricing feedback received
□ Verbal "we want to move forward"
□ Contract terms shared
□ Procurement process initiated
□ Legal/finance contacts introduced
□ Close date confirmed

Verification Method:

• Proposal delivery confirmed
• "We're moving forward" in writing
• Contract shared

Stage 5: Negotiation → Closed Won

Required to Exit:

□ Final pricing agreed
□ Contract redlines resolved
□ Signature authority confirmed
□ Expected signature date confirmed
□ PO/payment method confirmed (if applicable)

Verification Method:

• Clean contract ready for signature
• Signature date within 14 days

Stage Velocity Benchmarks

Good Stage Management

Proper Stage Progression:

Day 1 - Discovery call completed
- Pain confirmed: Manual reporting taking 10+ hours/week
- Stakeholders: Director of Ops (evaluator), VP Ops (buyer)
- Timeline: Q4 budget, need solution by December
- Notes: Documented, recording saved
→ Advanced to Stage 1 (Discovery)

Day 8 - Qualification complete
- MEDDIC Score: 24/30
- Champion: Director of Ops, sponsored last 2 tool purchases
- Decision: VP Ops approves up to $50K, above needs CFO
- Process: Technical eval → Pilot → Business case → Sign
- Criteria: Written list of 8 requirements shared
→ Advanced to Stage 2 (Qualified)

Why this works:
✓ Each advancement has documented evidence
✓ Buyer actions, not seller actions, drive progression
✓ Objectively verifiable criteria met

Bad Stage Management

Stage Inflation (Anti-Pattern):

Day 1: Demo completed → Moved to "Evaluation" (Stage 3)
Rationale: "They loved the demo!"

Problem:
✗ No qualification completed
✗ No champion identified
✗ No decision process understood
✗ "Love" is not an exit criteria
✗ Deal now inflates pipeline and forecast

Reality: This deal should be Stage 1 at best

Zombie Deal (Anti-Pattern):

Deal has been in "Proposal" (Stage 4) for 90 days
Last contact: 45 days ago
Notes: "Following up, waiting on their timeline"

Problem:
✗ No buyer activity for 45 days
✗ Original close date passed
✗ No explanation for stall
✗ Should be moved to Lost or back to earlier stage

Pipeline Hygiene Rules

Weekly Deal Review Questions:

Automatic Stage Rules:

Auto-downgrade triggers:
- No activity for 30 days → Flag for review
- No activity for 45 days → Move back one stage
- No activity for 60 days → Move to Lost
- Close date missed by 30+ days → Manager review required

Auto-lost triggers:
- Explicit "we chose competitor"
- Explicit "project cancelled"
- Contact churned, no replacement
- Company went out of business

Closed Lost Analysis

Every lost deal should capture:

Anti-Patterns

• Happy staging — Moving deals forward based on hope
• Demo = qualified — Confusing interest with qualification
• No backward movement — Stages only move forward
• Stale close dates — Never updating unrealistic dates
• Single-thread deals in late stages — Champion leaves, deal dies
• Ignoring lost analysis — Missing the learning opportunity