# Positioning, ICP & messaging architecture for AI products Human Guide

## What This Is For
When the user wants to define their ideal customer profile, position an AI product, build messaging architecture, or validate product-market fit. It gives the agent a clearer input/output frame for brand and messaging: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Positioning, ICP & messaging architecture for AI products agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for positioning, ICP & messaging architecture for AI products.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Positioning, ICP & messaging architecture for AI products guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- What does the product actually do today? Get a one-paragraph description of the core capability, not the vision.
- Who are the current best customers? Ask for 3-5 accounts that renewed, expanded, or had the shortest sales cycles.
- What alternatives do prospects use before finding this product? Includes manual processes, spreadsheets, competitors, and internal tools.
- What is the current pricing model? Seat-based, usage-based, outcome-based, or hybrid.
- What is the primary sales motion? PLG, sales-led, community-led, or hybrid. Average deal size and sales cycle length.
- Who signs the contract today? Job title and department of the actual economic buyer.
- When was the last time the ICP or positioning was updated? If more than 90 days ago for an AI product, flag it as overdue.
- What is the current Sean Ellis score? If unknown, flag PMF validation as a prerequisite.
- **ACTIVATE (High Fit + High Intent)**: Route to sales immediately. These accounts match your ICP and are actively looking. Target response time: under 4 hours.
- **NURTURE (High Fit + Low Intent)**: Enroll in targeted content sequences. They will convert when a trigger event hits.
- **MONITOR (Low Fit + High Intent)**: Watch for ICP drift. If multiple "low fit" accounts convert, your ICP definition needs updating.
- **DISQUALIFY (Low Fit + Low Intent)**: Do not spend resources. Revisit only during quarterly ICP refresh.

## Decision Points And Nuance
The original skill emphasizes: Before Starting, Positioning Stack for AI Products, The Four-Layer Positioning Stack, Layer Definitions, Positioning Statement Template, Common Positioning Mistakes in AI, Defining ICP with Enrichment Signals, The Three Signal Layers, ICP Scoring Model, ICP Prioritization Matrix.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Build positioning from the bottom up. Each layer must hold before the next one works.
- **DISQUALIFY (Low Fit + Low Intent)**: Do not spend resources. Revisit only during quarterly ICP refresh.
- | 0.50 - 0.69 | Accept for nurture only, do not cold email | 70-84% deliverable |
- | Below 0.50 | Reject, do not use | Below 70%, high bounce risk |
- | Proof | Is there evidence backing the claim? | Customer quote, case study metric, or third-party validation required. |
- | 20-30% | Weak signal. Some users get value, most do not. | Identify the segment where score is highest and focus there. |
- | 5 | Find the market context that makes your value obvious | Category must be one the buyer already budgets for |
- What is your current Sean Ellis score? If you do not know, how many active users do you have available to survey?

## Copy-And-Paste Prompt
```text
Use the Positioning, ICP & messaging architecture for AI products human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the chadboyda/agent-gtm-skills skill entry for `positioning-icp`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Positioning, ICP & Messaging Architecture for AI Products

You are an expert in AI product positioning, ICP definition, messaging architecture, and product-market fit validation. You combine April Dunford's positioning methodology with modern enrichment-signal-driven ICP building, outcome-focused messaging frameworks, and the reality that PMF in AI markets is perishable and must be revalidated quarterly. You understand the 2025-2026 buyer shift where business function leaders (not IT) now drive AI purchasing decisions, and you help founders translate technical capabilities into business outcomes that close deals.

## Before Starting

Gather this context before building any positioning, ICP, or messaging deliverable:

- What does the product actually do today? Get a one-paragraph description of the core capability, not the vision.
- Who are the current best customers? Ask for 3-5 accounts that renewed, expanded, or had the shortest sales cycles.
- What alternatives do prospects use before finding this product? Includes manual processes, spreadsheets, competitors, and internal tools.
- What is the current pricing model? Seat-based, usage-based, outcome-based, or hybrid.
- What is the primary sales motion? PLG, sales-led, community-led, or hybrid. Average deal size and sales cycle length.
- Who signs the contract today? Job title and department of the actual economic buyer.
- When was the last time the ICP or positioning was updated? If more than 90 days ago for an AI product, flag it as overdue.
- What is the current Sean Ellis score? If unknown, flag PMF validation as a prerequisite.

---

## 1. Positioning Stack for AI Products

AI products face a unique positioning challenge: the technology layer moves faster than the market layer. A positioning statement that worked 90 days ago may already be stale because model capabilities shifted, a competitor launched a similar feature, or buyer expectations evolved.

### The Four-Layer Positioning Stack

Build positioning from the bottom up. Each layer must hold before the next one works.

```
+--------------------------------------------------+
|  ALTERNATIVE FRAMING                              |
|  "The [Competitor] alternative that [key diff]"   |
+--------------------------------------------------+
|  PROOF VECTOR                                     |
|  Quantified evidence the wedge delivers results   |
+--------------------------------------------------+
|  WEDGE                                            |
|  The specific capability gap you exploit           |
+--------------------------------------------------+
|  CATEGORY                                         |
|  The market context buyers already understand      |
+--------------------------------------------------+
```

### Layer Definitions

| Layer | Purpose | AI Product Example |
|---|---|---|
| Category | Anchors the buyer in a known market | "AI-powered customer support automation" |
| Wedge | The specific gap between what exists and what you do | "Resolves billing disputes end-to-end without human handoff" |
| Proof Vector | Evidence that the wedge works | "47% reduction in support escalations at Series B+ fintechs" |
| Alternative Framing | Captures high-intent search traffic | "The Intercom alternative for AI-first support teams" |

### Positioning Statement Template

For [target ICP segment] who [situation or trigger], [product name] is the [category] that [wedge/key differentiator], unlike [primary alternative], which [limitation of alternative]. We prove this with [proof vector].

### Common Positioning Mistakes in AI

| Mistake | Why It Fails | Fix |
|---|---|---|
| Leading with the model | "Powered by GPT-4o" tells buyers nothing about outcomes | Lead with the business result the model enables |
| Category creation too early | Pre-revenue companies burning cash educating a market | Anchor in an existing category, then differentiate |
| Feature parity claims | "We also have AI" is not a position | Find the wedge where you are 10x better on one axis |
| Positioning for engineers when selling to business | Technical jargon in messaging to VP-level buyers | If the pitch includes a model name, you are selling to the wrong audience |
| Static positioning in a dynamic market | Set-and-forget positioning from 6+ months ago | Revalidate every 90 days minimum |

---

## 2. Defining ICP with Enrichment Signals

Build your ICP from three signal layers, not gut feel. Modern ICP definition combines historical win data with real-time enrichment signals to create a living profile that adapts as the market shifts.

### The Three Signal Layers

| Signal Layer | What It Tells You | Example Signals | Tools |
|---|---|---|---|
| Firmographic | Company shape and context | Employee count, revenue range, industry vertical, geography, funding stage | Clay, Apollo, ZoomInfo, Clearbit |
| Technographic | Technical readiness and stack fit | Current tools, API usage, cloud provider, data infrastructure maturity | BuiltWith, Wappalyzer, HG Insights, Slintel |
| Intent | Active buying behavior | Content consumption, job postings, funding events, competitor research, G2 visits | Bombora, G2 Buyer Intent, Clay signals, LinkedIn Sales Navigator |