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Identify which organic growth path to pursue — new segments, geographies, channels, or products. Use when diagnosing where a growth constraint lives and which McKinsey growth level to act on next.

Use this Skill: https://skilld.dev/gh/deanpeters/product-manager-skills/organic-growth-advisor

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Organic Growth Advisor Examples

These examples show how the Organic Growth Advisor helps a Product Manager diagnose which organic growth path to pursue next.

The four paths are:

  • L2: New Customer Segments — same value, nearby customer
  • L3: New Geographies — same product, new market context
  • L4: New Distribution Channels — same value, new access path
  • L5: New Products or Services — adjacent job, meaningful product change

Example 1: Good Organic Growth Diagnosis

Context

User shares:

"We have strong product-market fit with engineering teams, but growth has stalled. We tried paid ads and a PLG free tier. Neither worked very well. Most paid upgrades now come through existing customer referrals. We think product and design teams inside the same companies may have the same coordination problem."

Agent extracts context

  • Product: B2B SaaS project management tool
  • Current Core Customer: Engineering teams at software companies
  • Growth Challenge: Signups are flat; paid upgrades mostly come from referrals
  • What Has Been Tried: Paid ads and PLG free tier
  • Important Signal: Existing customers are already creating warm paths into adjacent teams

Diagnostic Question 1: Customer / Market Context

Agent asks:

Think about the next customer or market you want to reach. How familiar is that context?

User response:

Well known. Product and design teams are inside the same companies. They work with engineering already and have a similar coordination problem.

Agent interprets:

  • Customer / Market Context: Well Known
  • Reason: Same companies, adjacent teams, familiar problem space

Diagnostic Question 2: Degree of Product Change

Agent asks:

To reach that customer and grow, how much does the product need to change?

User response:

Low change. We may need different templates or onboarding language, but the core product already works.

Agent interprets:

  • Degree of Product Change: Low
  • Reason: Product value mostly transfers; messaging and onboarding likely need adjustment

Agent recommends

## Your Growth Path: L2 — New Customer Segments

**Where you sit on the matrix:**
- Customer/market context: Known
- Degree of product change: Low

**Why this path fits your situation:**
Your product already solves a coordination problem for engineering teams. Product and design teams inside the same companies likely have a nearby version of that problem. The referral pattern suggests growth is already trying to cross team boundaries, but you have not turned that signal into a deliberate expansion motion.

**The diagnostic question to keep asking:**
Who else has the problem we already solve?

**What innovation looks like here:**
Innovation is not rebuilding the product. It is finding adjacent buyers whose work is close enough that the current product mostly transfers, then adapting messaging, onboarding, and proof points so the value lands in their language.

**A first experiment to run this week:**
Pick ten strong engineering-team customers. Identify whether product or design teams exist inside those same accounts. Run five discovery conversations with those adjacent teams and ask how they coordinate work today, where handoffs break, and whether the engineering team's usage influenced their interest.

**Watch out for:**
Treating adjacent buyers as identical to the core customer. They may share the problem but describe it differently, buy differently, and need different proof that the product is worth adopting.

Why this works

  • Starts from a real growth constraint, not a pet idea
  • Uses evidence from current customer behavior
  • Separates “new segment” from “new product”
  • Recommends a testable L2 experiment
  • Avoids jumping to L5 because building new feels more exciting

Example 2: Good L3 Diagnosis

Context

User shares:

"We sell HR onboarding software to US mid-market companies. Domestic growth is slowing, but we keep seeing inbound from the UK and Australia. We have not localized anything yet. The product seems relevant, but we are not sure if international expansion is real."

Agent extracts context

  • Product: HR onboarding software
  • Current Core Customer: US mid-market HR teams
  • Growth Challenge: Domestic growth slowing
  • What Has Been Tried: No active international motion yet
  • Important Signal: Organic inbound from UK and Australia

Diagnostic answers

  • Customer / Market Context: Less Known
  • Degree of Product Change: Low

Agent recommends

## Your Growth Path: L3 — New Geographies

**Where you sit on the matrix:**
- Customer/market context: Less Known
- Degree of product change: Low

**Why this path fits your situation:**
Organic inbound from the UK and Australia is a useful signal because demand is showing up before you have invested in those markets. The product may travel, but the market context will not travel with it. Your next risk is probably local trust, compliance, buying norms, language, and onboarding friction.

**The diagnostic question to keep asking:**
Where is demand showing up that we do not yet serve well?

**What innovation looks like here:**
Innovation is learning how value travels in a new market before scaling the motion. That may mean local proof points, regional partners, compliance adjustments, onboarding changes, or trust signals that make the product feel credible in context.

**A first experiment to run this week:**
Pull recent inbound leads, signups, and usage from the UK and Australia. Interview five of those users. Ask why they found you, what they expected, what felt US-centric, and what would make the product easier to trust or adopt locally.

**Watch out for:**
Assuming localization means "translate the website and run ads." That is how teams turn a promising signal into a small international bonfire of paid acquisition spend.

Why this works

  • Treats geographic demand as a signal to investigate
  • Does not confuse product fit with market-context fit
  • Keeps the first experiment discovery-led and low-cost
  • Avoids global-launch theater

Example 3: Good L4 Diagnosis

Context

User shares:

"We make short-form video explainer software for marketing teams. Customers love the product and share finished videos everywhere. Growth has plateaued. Non-users see the outputs, but they do not understand where the videos came from or how to try the product."

Agent extracts context

  • Product: Short-form video explainer tool
  • Current Core Customer: Marketing teams
  • Growth Challenge: Growth faded after launch momentum
  • What Has Been Tried: Initial launch push and customer sharing
  • Important Signal: Product output is already being seen by non-users

Diagnostic answers

  • Customer / Market Context: Well Known
  • Degree of Product Change: High access/distribution change

Agent recommends

## Your Growth Path: L4 — New Distribution Channels

**Where you sit on the matrix:**
- Customer/market context: Known
- Degree of product change: High

**Why this path fits your situation:**
Your product output is already traveling farther than your signup motion. That makes distribution the constraint. The product creates visible artifacts, but the moment of curiosity does not yet become a path into the product.

**The diagnostic question to keep asking:**
Where else could customers discover or access our value?

**What innovation looks like here:**
Innovation is turning product usage into a distribution surface. The product does not need to become something else. The front door needs to move closer to the moment when non-users see value.

**A first experiment to run this week:**
Add a lightweight "Made with [Product]" link or interactive call-to-action to exported videos for a subset of customers. Track referral source, landing-page conversion, signup quality, and whether viewers understand what they can do next.

**Watch out for:**
Confusing campaigns with channels. A campaign gets attention once. A channel compounds because product usage keeps creating new discovery moments.

Why this works

  • Notices the product is already creating distribution surfaces
  • Does not recommend another campaign wearing a fake mustache
  • Focuses on the access path, not the core product value
  • Creates a measurable experiment

Example 4: Good L5 Diagnosis

Context

User shares:

"We sell analytics software to e-commerce teams. Retention is strong and customers trust us, but they keep asking for forecasting and inventory planning. Today they export data from us, manipulate it in spreadsheets, then use a separate planning tool. We are wondering if this is a feature request or a bigger product opportunity."

Agent extracts context

  • Product: E-commerce analytics platform
  • Current Core Customer: E-commerce operators and analysts
  • Growth Challenge: Strong retention, limited expansion
  • What Has Been Tried: Analytics product works; adjacent planning workflow not supported
  • Important Signal: Customers repeatedly pull the company toward an adjacent job

Diagnostic answers

  • Customer / Market Context: Somewhat Known / Less Known
  • Degree of Product Change: High

Agent recommends

## Your Growth Path: L5 — New Products or Services

**Where you sit on the matrix:**
- Customer/market context: Less Known
- Degree of product change: High

**Why this path fits your situation:**
Customers are not just asking for another report. They are trying to complete an adjacent job your product informs but does not currently solve. The repeated export-to-spreadsheet-to-planning-tool workflow is a strong L5 signal because customers are already showing you the seam between your current product and the next product opportunity.

**The diagnostic question to keep asking:**
What adjacent jobs are customers already trying to solve around us?

**What innovation looks like here:**
Innovation is absorbing more of the customer's workflow without wandering away from the core. The new product or service should extend the job customers already trust you to support, not drag the company into a random adjacent swamp with nicer TAM numbers.

**A first experiment to run this week:**
Interview eight customers who requested forecasting or inventory planning. Ask them to walk through the exact workflow before and after using your product: tools, handoffs, spreadsheets, decisions, timing, and failure points. Look for consistency before scoping anything.

**Watch out for:**
Calling every adjacent request a strategy. L5 has the most upside, but also the highest risk. If the pattern is not repeated, painful, and close to the core workflow, it is probably not a new product path yet.

Why this works

  • Distinguishes feature request from adjacent job
  • Uses repeated customer behavior as evidence
  • Keeps discovery ahead of roadmap commitment
  • Warns against shiny-object strategy theater

Example 5: Bad Diagnosis — Solution-First Growth Thinking

User shares

"We need to build an AI dashboard to grow revenue."

Why this fails

  • "Build an AI dashboard" is a solution, not a growth path
  • No customer segment is named
  • No growth constraint is diagnosed
  • No evidence suggests whether this is L2, L3, L4, or L5
  • The product team is already standing at the feature altar with flowers in hand

Agent should push back

An AI dashboard may or may not be the right solution. First we need to diagnose the growth path.

Quick context:

1. What product or offering are we trying to grow?
2. Who is the current core customer?
3. Where is growth stalling?
4. What evidence suggests an AI dashboard would unlock growth?

User clarifies

"Our analytics product has strong retention with e-commerce teams. Customers keep exporting reports into spreadsheets to do forecasting and inventory planning. They ask whether we can help with that."

Agent reframes

  • Possible Growth Path: L5 — New Products or Services
  • Reason: Customers are pulling the product toward an adjacent job
  • Better Diagnostic Question: What adjacent jobs are customers already trying to solve around us?

Better next step

Before scoping an AI dashboard, interview customers who requested forecasting or inventory help.

Ask them to walk through:
- What they do before using your analytics product
- What they do after exporting data
- What decisions they are trying to make
- What tools or spreadsheets they use today
- Where the workflow breaks down

If the pattern is consistent, the opportunity may be L5.
If not, the dashboard is probably just another feature-shaped hallucination with a login screen.

Example 6: Bad Diagnosis — Confusing Campaigns with Channels

User shares

"We launched on Product Hunt and got 2,000 signups. We think Product Hunt is our new distribution channel."

Why this fails

  • A launch spike is not necessarily a channel
  • No evidence the motion compounds
  • No evidence that signups became activated customers
  • No repeatable access path has been identified

Agent should push back

Product Hunt may have created attention, but attention is not the same as a distribution channel.

A channel compounds. A campaign spikes.

Let's diagnose this:

1. Did signups continue after launch week?
2. Did the users activate and retain?
3. Can the mechanism repeat without another launch event?
4. What ongoing surface or behavior would keep exposing new customers to the product?

Better interpretation

  • Possible Growth Path: L4 — New Distribution Channels
  • But only if: The discovery/access mechanism can repeat without constant promotion

Better next step

Analyze Product Hunt signups separately from other cohorts.

Look at:
- Activation rate
- Retention after 30 days
- Paid conversion
- Referral behavior
- Whether users created outputs or invites that exposed the product to others

If the mechanism ends when the launch ends, it was a campaign.

Useful, maybe.

A channel, no.

Example 7: Bad Diagnosis — Jumping to L5 Too Early

User shares

"Growth is slowing, so we think we need a second product."

Why this fails

  • New product is the highest-risk organic growth path
  • No evidence that L2 or L4 has been exhausted
  • No adjacent job has been validated
  • Slowing growth does not automatically mean the product needs a sibling

Agent should push back

A second product may be right, but L5 is the riskiest path.

Before going there, let's check whether simpler growth paths are still available:

1. Are there adjacent customer segments that already have the problem we solve?
2. Are customers sharing or exposing our product value in ways we have not turned into channels?
3. Is demand showing up in new markets we do not yet serve well?
4. What adjacent job are customers repeatedly asking us to solve?

Better interpretation

The answer may still be L5, but only if customers are repeatedly pulling the product toward an adjacent job.

Better next step

Run an L2/L4/L5 comparison before committing.

For each path, capture:
- Evidence
- Assumption
- First experiment
- Cost of being wrong

If L5 wins after that, proceed.

If it only wins because "new product" sounds more strategic in a board deck, put the shovel down.

Example 8: Weak Input, Good Recovery

User shares

"We need growth. What should we do?"

Why this is incomplete

  • No product context
  • No current customer
  • No evidence
  • No known growth constraint
  • No prior attempts

Agent should recover with context questions

I can help, but I need the basic growth context first.

Answer briefly:

1. What does the product do?
2. Who is the current core customer?
3. Where is growth stalling: acquisition, activation, expansion, retention, or something else?
4. What have you already tried?
5. What evidence do you have that growth is still possible from the current product?

Why this works

  • Does not invent a strategy from fog
  • Gets the minimum viable context
  • Keeps the conversation moving
  • Prevents confident nonsense from putting on a strategy hat

Quick Interpretation Guide

Signal Likely Path
Nearby buyers have the same problem L2 — New Customer Segments
Demand appears in a new geography L3 — New Geographies
Product output is seen by non-users L4 — New Distribution Channels
Customers repeatedly ask for adjacent workflow support L5 — New Products or Services
Current customers are not retaining Fix L1 before using this skill
Stakeholders want a shiny new thing without evidence Diagnose before building

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub17d

    The organic-growth-advisor skill is a strategic diagnostic tool for identifying business growth paths. It operates through natural language interaction and contains no executable code or dangerous system capabilities. The skill is safe to use.

  • Socket17d

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    Risk: LOW · No issues

Signed by skilld at ba3fc8c. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last month.

Activeupdated 2 months ago
argument-hint
[product and growth context]
type
interactive
theme
strategy-positioning
Other metadata
intent
Guide product managers through a fast triage to identify which of four organic growth paths fits their current constraint: new customer segments (L2), new geographies (L3), new distribution channels (L4), or new products or services (L5). Uses a 2x2 diagnostic based on customer/market context familiarity and degree of product change required. Outputs a growth path recommendation with rationale and immediate next steps.
best_for
[
  "Choosing which organic growth motion to pursue when multiple seem viable",
  "Diagnosing whether the constraint is in reach, access, market context, or product value",
  "Setting up an AI-assisted growth experiment with the right starting hypothesis"
]
scenarios
[
  "We need to grow but aren't sure if we should go after new customer segments or new geographies",
  "Help me figure out which McKinsey growth level we should focus on",
  "We have strong product-market fit but growth is stalling. Where should we look?",
  "Which organic growth path fits our current situation?"
]
estimated_time
15-25 min

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