startup-positioning

Startup Positioning

Market positioning strategy that produces a complete positioning document, Moore + Neumeier positioning statements, competitive alternatives map, and market category analysis. Built on April Dunford's framework, enriched with JTBD discovery and stress-tested with Neumeier's Onliness Test.

How It Works

INTAKE → RESEARCH (2 parallel waves) → POSITIONING SYNTHESIS

The process: understand the product and its customers, research competitive alternatives and market context, then build positioning through Dunford's 5+1 components. Typical runtime: 10-15 minutes in Claude Code (parallel agents), 20-30 minutes in Claude.ai (sequential).

Language

Default output language is English. If the user writes in another language or explicitly requests one, use that language for all outputs instead.

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Phase 1: Intake

Short and focused — 1-2 rounds of questions. The goal is enough context to research alternatives and build positioning.

Check for Prior Work

Before asking questions, check if prior sessions have been completed. Look for these files in the working directory or subdirectories:

From startup-design:

• 00-intake/brief.md — product description and context
• 01-discovery/competitor-landscape.md — competitor profiles
• 01-discovery/target-audience.md — customer personas, pain points
• 02-strategy/positioning.md — initial positioning work

From startup-competitors:

• intake.md — product and market context
• competitors-report.md — strategic competitive analysis
• battle-cards/ — per-competitor profiles
• pricing-landscape.md — pricing analysis

If these files exist, read them and use the data as a head start:

• Extract the product description, known competitors, and customer pain points
• Use competitor profiles and battle cards to seed the competitive alternatives map
• Pull any existing positioning work as a starting hypothesis to test, not a conclusion to keep
• Use customer language and pain points to inform JTBD discovery

Tell the user: "I found data from a previous session. I'll use it as a starting point for positioning analysis."

Skip redundant intake questions. Go straight to research if prior data is sufficient.

What to Ask (if no prior data exists)

Round 1 — Core context:

• What's your product? (one sentence is fine)
• What problem does it solve and for whom?
• What do your customers do today instead of using you? (alternatives, workarounds, doing nothing)
• Who are your best existing customers? (if any — describe them, not demographics)

Round 2 — Sharpening (only if needed):

• How is your product different from the alternatives you mentioned?
• Have you tried positioning before? What didn't work?
• Are there competitors you're often compared to?

Don't over-interview. If the user gives a clear description upfront, move to research. The positioning process itself will surface what matters.

Output

Save to {project-name}/intake.md — a brief summary of the product, problem, alternatives, and customers. If built on prior session data, note the source files used. Project name: kebab-case (e.g., ai-email-assistant).

Create {project-name}/PROGRESS.md with: project name, skill name (startup-positioning), start date, language, research mode (Live / Knowledge-Based), and a phase checklist. Update it after each phase completes. If PROGRESS.md already exists from a previous session, resume from the last incomplete phase.

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Phase 1.5: Research Depth Assessment

After intake, assess market complexity and present the Research Depth recommendation to the user.

Reference: Read references/research-scaling.md for the complexity scoring matrix, tier definitions, wave configurations, and the user communication template.

Process

1. Score three factors from the intake: market breadth (1-3), known competitors (1-3), geographic scope (1-3)
2. Sum the scores (range 3-9) and map to a tier: Light (3-4), Standard (5-7), Deep (8-9)
3. Present the Research Depth table to the user (see research-scaling.md for the exact template)
4. Wait for user response: light, deep, or ok to accept the recommendation
5. Record the selected tier in PROGRESS.md

The selected tier determines the number of agents per wave and search rounds per agent in Phase 2. See research-scaling.md for exact wave configurations per tier.

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Phase 2: Research

Two parallel research waves exploring competitive alternatives and market context. Together they provide the raw material for Dunford's 5+1 positioning components.

Environment Detection

Check if the Agent tool is available:

• Agent tool available (Claude Code): Spawn all agents within each wave in parallel. This is faster.
• Agent tool NOT available (Claude.ai, web): Execute research sequentially, following the same templates. Same depth, just slower.

Web Search

This skill requires WebSearch for real data. If WebSearch is unavailable or denied, fall back to Knowledge-Based Mode: use training data, mark all findings with [Knowledge-Based — verify independently], and reduce confidence ratings by one level. Note the mode in PROGRESS.md.

Reference: Read references/research-principles.md before starting any wave. It defines source quality tiers, cross-referencing rules, and how to handle data gaps.

Wave 1: Competitive Alternatives & Customer Context

Reference: Read references/research-wave-1-alternatives.md for agent templates.

Two agents (or two sequential blocks):

A1: Alternative Mapping (JTBD Lens) — Map ALL competitive alternatives, not just direct competitors. Include: direct competitors, adjacent tools competing for the same budget, manual processes, spreadsheets, hiring someone, doing nothing / status quo. For each: what job does the customer hire it for, where does it fall short, what triggers switching? The goal is the full set of things your product replaces.

A2: Customer Intelligence — Mine voice-of-customer data: reviews, forums, communities. Extract: pain points with current alternatives, exact language customers use, what "better" means to them, best-fit customer profile (who gets the most value fastest), switching triggers (what makes someone finally change). Build a language map — the words customers use to describe their problem and desired outcome.

Wave 2: Market Frame & Trends

Reference: Read references/research-wave-2-market-frame.md for agent templates.

Two agents (or two sequential blocks):

B1: Market Category Analysis — Identify 3-5 candidate market categories. For each: what do buyers expect from this category, who are the leaders, what's the competitive dynamic, how mature is it? Apply Dunford's category types: head-to-head (existing category), big fish/small pond (subcategory), or category creation. Assess which frame makes your unique strengths matter most.

B2: Trend & Timing Analysis — Identify relevant trends: technology shifts, behavioral changes, regulatory moves. For each: is it real or hype, how does it affect buyer expectations, does it make your positioning stronger or weaker? Assess timing — are you early, on-time, or late to the trend? Only include trends that genuinely change how buyers evaluate solutions.

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Post-Research Checkpoint

After both waves complete, before synthesis, briefly present what the research found to the user: the competitive alternative landscape (how many direct, adjacent, status quo), the strongest customer pains, and the most promising category candidates. Ask: "Does this align with your expectations? Anything to adjust before I synthesize the positioning?"

Keep it to one message — this is a quick alignment check, not a full report.

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Phase 3: Positioning Synthesis

Reference: Read references/research-synthesis.md for synthesis protocol and Dunford process details.

After the checkpoint, build positioning through Dunford's 5+1 components in order. The sequence matters — each step builds on the previous.

The 5+1 Components

1. Competitive Alternatives — From Wave 1. What would customers use if your product didn't exist? This is the anchor — positioning is always relative.

2. Unique Attributes — What do you have that the alternatives lack? Be specific and honest. Features, architecture, team expertise, business model, speed — anything defensible.

   ⏸ PAUSE — User Input Required. Present the research-derived attributes to the user. Ask them to confirm, add, or remove before proceeding to Value Themes. The founder knows capabilities that research can't surface.

3. Value Themes — Translate each unique attribute into a customer outcome. Attribute → "so what?" → value. Group related attributes into 2-3 value themes. Use customer language from Wave 1's language map.

4. Best-Fit Customers — From Wave 1 customer intelligence. Who cares most about your value themes? Define by characteristics that make them care, not demographics. These customers should be reachable, recognizable, and willing to pay.

5. Market Category — From Wave 2. Choose the category frame that makes your value obvious. Present 3-5 options with trade-offs. Recommend one. The right category triggers the right buyer expectations.

6. Trend Overlay (optional) — From Wave 2. Only include if a genuine trend makes your positioning stronger. Forced trend alignment is worse than none.

Validation

Two stress tests before finalizing:

Neumeier Onliness Test:

Basic form:

"Our [product] is the only [category] that [differentiator]."

Extended form (6 elements — WHAT/HOW/WHO/WHERE/WHY/WHEN):

"Our [product] is the only [category] that [differentiator] for [target] who [need] in [context]."

If you can't fill the basic form convincingly — if "only" feels like a stretch — the positioning is too weak. Iterate.

Ries/Trout Mental Ladder:

• Is it simple enough to remember?
• Does it claim one clear rung?
• Is that rung available (not owned by a competitor)?
• Can you explain it in one sentence?

If either test fails, revisit the 5+1 components. Don't ship weak positioning.

Output Files

Every deliverable file must start with a standardized header: # {Title}: {product} followed by *Skill: startup-positioning | Generated: {date}*. Every deliverable must end with Red Flags, Yellow Flags, and Sources sections (see templates in references/research-synthesis.md).

{project-name}/positioning-doc.md — The main deliverable:

• Executive summary (positioning in 3 sentences)
• The 5+1 components with supporting evidence
• Strength assessment per component (Strong / Moderate / Needs Work)
• Strategic recommendations and next steps
• Data gaps & limitations

{project-name}/positioning-statement.md — Statements and messaging:

• Moore template: "For [target] who [need], [product] is a [category] that [benefit]. Unlike [alternative], we [differentiator]."
• Neumeier Onliness Statement (basic + extended)
• Elevator pitch (30-second version)
• Tagline candidates with stress-tested "Possible Misread" column
• One-liner variants for different channels (GitHub, marketplace, social, elevator)
• Freemium positioning (if applicable)

{project-name}/competitive-alternatives.md — Complete alternatives map:

• All alternatives (direct, adjacent, manual, status quo)
• Per alternative: job hired for, strengths, shortcomings, switching triggers
• Your unique attributes vs. each alternative

{project-name}/market-category-analysis.md — Category strategy:

• 3-5 candidate categories with buyer expectations
• Category type assessment (head-to-head / subcategory / creation)
• Recommendation with reasoning
• Implementation (category label, tagline direction, buyer expectation alignment)
• Red flags and yellow flags

{project-name}/messaging-implications.md — Bridge from positioning to copy:

• Messaging hierarchy (what to communicate first, second, third)
• Category label (exact phrase to use everywhere)
• Value anchor (what to compare value to, separate from category)
• Customer language vs. category language map (which words are customer verbs, which are category nouns)
• Words to use / avoid
• Social proof guidelines
• Freemium positioning (if applicable)

Raw Data

Each agent saves its raw output to {project-name}/raw/. The synthesis phase reads these raw files and produces the polished deliverables above. Agents must NOT write directly to deliverable paths — raw and synthesized output are separate.

Raw research files:

• alternative-mapping.md
• customer-intelligence.md
• market-categories.md
• trends-timing.md

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Phase 3.5: Research Verification

After all positioning deliverables are written, run a verification pass.

Reference: Read references/verification-agent.md for the full verification protocol, universal checks, and skill-specific checks.

Process

1. Spawn agent V1: Verification — it reads all deliverable files and checks for: unlabeled claims, internal contradictions, confidence rating consistency, missing data gaps, missing flags, stale data, and duplicate-source false corroboration
2. V1 also runs startup-positioning-specific checks: positioning statement vs. research data, JTBD vs. customer intelligence, cross-deliverable coherence, validation test integrity
3. V1 produces {project-name}/verification-report.md
4. If Critical issues found: Pause and present issues to the user. Ask: fix first, or proceed as-is?
5. If only Warnings/Info: Show one-line summary

In Claude.ai or when Agent tool is unavailable, run the verification checks yourself in the main conversation following the same protocol.

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Honesty Protocol

Reference: Read references/honesty-protocol.md for full protocol and anti-pattern details.

Positioning is only useful if it's honest. Core rules apply (label claims, quantify, declare gaps), plus positioning-specific additions:

1. No aspirational positioning. Position on what you ARE, not what you hope to become. Aspirational positioning crumbles at first customer contact.
2. Challenge "we're unique." The Onliness Test must be genuinely convincing. If it reads like marketing fluff, iterate.
3. Research wins over narrative. When customer data contradicts internal beliefs about positioning, the data wins.
4. Flag category creation risk. Most startups can't afford to educate a market. Default to existing categories unless the evidence is overwhelming.

Anti-Pattern	What It Looks Like	What to Say
"We're for everyone"	No target segment defined	"If you're for everyone, you're for no one. Who cares MOST?"
Feature-based positioning	Leading with features not outcomes	"Customers don't buy features. What outcome do they get?"
Aspirational positioning	"We'll be the AI-powered..."	"Position on what you deliver today, not the roadmap."
Category-of-one	Inventing a category to avoid comparison	"New categories cost millions. Is there an existing frame?"
Copycat positioning	Same message as the market leader	"Find genuinely different ground — you can't out-position the leader."

See references/honesty-protocol.md for the full anti-pattern table (7 entries) and detailed protocol.

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Reference Files

Read only what you need for the current phase.

File	When to Read	~Lines	Purpose
honesty-protocol.md	Start of session	~73	Full honesty protocol with anti-patterns
research-principles.md	Before starting Phase 2	~65	Source quality, cross-referencing, data gaps
research-wave-1-alternatives.md	When running Wave 1	~235	Agent templates for alternatives + customer intel
research-wave-2-market-frame.md	When running Wave 2	~210	Agent templates for categories + trends
research-synthesis.md	After both waves complete	~380	Synthesis protocol, Dunford process, validation tests, messaging implications
frameworks.md	During Phase 3	~133	Dunford/Moore/Neumeier/JTBD/Ries reference
research-scaling.md	After intake, before Phase 2	~75	Complexity scoring, tier definitions, wave configurations
verification-agent.md	After synthesis	~80	Verification protocol, universal + skill-specific checks