activation-analysis

Activation Analysis: Setup → Aha → Habit Framework

Quick Start

/activation-analysis

Then provide:

1. Your product and core value proposition (or I'll pull from business-info)
2. Current onboarding flow (what steps do new users take?)
3. Any metrics you have (setup completion %, D7 retention, time-to-value)

I'll diagnose your activation funnel using Setup -> Aha -> Habit, identify the biggest bottleneck, and recommend specific fixes.

Output: Saved to thoughts/shared/pm/analyses/activation-analysis-[date].md Time: ~15 min with data, ~25 min if defining stages from scratch

When to use: When diagnosing activation problems, improving onboarding, or measuring early product engagement

Framework source: Aakash Gupta's "Ultimate Guide to Activation" and "How to Measure Onboarding"

Context Routing Logic (Internal - for Claude)

Automatic Context Checks: When this skill is invoked, immediately check:

| Source | Files/Folders | Search Terms | What to Extract | | ----------------- | ---------------------------------------------- | ---------------------------------------------------------------------- | ----------------------------------------------------------------------- | | Metrics/Analytics | thoughts/shared/pm/metrics/.md | "onboarding", "setup", "activation", D7, D30, "time to value", TTV | Current activation rates by stage, onboarding metrics, D7/D30 retention | | User Research | thoughts/shared/pm/.md | "onboarding", "setup", "first time", "confused", "stuck", "struggle" | User feedback on onboarding, confusion points, success moments | | Meeting Notes | thoughts/shared/product/meeting-notes/.md | "activation", "onboarding", "new users", "drop-off", "support tickets" | CS/support feedback on where users get stuck, win/loss reasons | | PRDs | thoughts/shared/pm/prds/.md | "onboarding", "activation", "tutorial", "first-time user" | Past onboarding improvements, features to drive activation | | Business Info | thoughts/shared/pm/context/business-info-template.md | target user, customer segment, use case, primary value | Who you're activating, what value matters to them |

Context Priority:

1. Internal context FIRST (business info, existing activation metrics, user research)
2. Analytics MCP SECOND (if connected - query activation funnel, D7/D30 by cohort)
3. Framework guidance LAST (generic activation tactics)

Cross-Skill Links:

• If retention issues mentioned → Link to retention-analysis
• If expansion opportunities found → Link to expansion-strategy
• If user struggles identified → Link to user-research-synthesis

Step 0: Understanding Your Current Activation Landscape

Before measuring the Setup → Aha → Habit stages, let me check what data already exists...

Checking:

• thoughts/shared/pm/context/business-info-template.md for your product and target users
• thoughts/shared/pm/metrics/ for existing activation metrics and onboarding data
• thoughts/shared/pm/ for user research on onboarding struggles
• thoughts/shared/product/meeting-notes/ for CS/support feedback on where users get stuck
• thoughts/shared/pm/prds/ for past onboarding improvements

[If analytics MCP connected]: "Let me also query [PostHog/PostHog] for your current activation funnel, setup completion rates, and D7/D30 retention by cohort."

Based on what I find, I'll show you:

Internal Intelligence Summary

From Business Info:

• [Your product and core value proposition]
• [Target user segments]
• [Primary use case]
• Example: "Help product: [description], target: small teams, primary value: [outcome]"

From Metrics/Analytics:

• [Current setup completion rate]
• [Current Aha rate (if defined)]
• [D7/D30 retention by cohort]
• [Time to Aha median]
• Example: "Setup: 65%, Aha: 40% (overall activation: 26%), D7 retention: 35%"

From User Research:

• [User feedback on onboarding friction]
• [What makes successful users different]
• Example: "Users who complete setup in <5 min have 3x higher D30 retention"

From Sales/CS Meetings:

• [Drop-off points where users get stuck]
• [Common confusion or support tickets]
• Example: "70% of support tickets in first week are about [feature]"

From PRDs:

• [Past onboarding improvements and their impact]
• Example: "PRD-2024-02 added templates, increased setup completion by 8%"

Gaps in Knowledge

Based on internal context, we don't yet know:

• [Gap 1]: Exact definition of your Aha moment (based on user behavior data)
• [Gap 2]: Drop-off points in your setup flow
• [Gap 3]: Why churned users didn't persist (need churn interview analysis)

Should I help define your three stages, or would you like to provide existing activation data first?

Step 1: Activation Diagnostic Questions

Instead of generic "what's your onboarding flow," I'll ask:

Question 1: The Biggest Leak

"Where do most new users drop off—in the first 5 minutes, or later in the week?"

This identifies whether the problem is setup friction, Aha not resonating, or habit formation.

Question 2: Aha Moment Evidence

"Among users who stuck around (D7+), what did they all do in their first session that churned users didn't?"

Your Aha must be defined by actual user behavior, not guesses.

Question 3: Onboarding Goals

"What specific actions should every new user complete in their first session to get value?"

This defines your Setup stage.

Question 4: Success Signal

"How do you know a user 'got it'—what behavior indicates they experienced the core value?"

This is your Aha moment definition.

Question 5: Current Metrics

"What % of new signups complete your onboarding, and what % come back on Day 7?"

These baselines inform where to focus.

Overview

Activation is the bridge between signup and retention.

The Setup → Aha → Habit framework breaks activation into three measurable stages:

1. Setup: User configures the product to work for them
2. Aha: User experiences the core value (magic moment)
3. Habit: User turns that value into recurring behavior

The Framework

Stage 1: Setup

What it is: The initial configuration required before a user can experience value

Examples by product type:

• Slack: Create workspace, invite team members, set up channels
• Notion: Create first page, set up workspace structure
• design tool: Create first file, invite collaborators
• Stripe: Connect bank account, configure payment settings
• TaskFlow (example): Create first project, add team members, create first task

Key principle: Setup should be the MINIMUM required to reach Aha

Metrics to track:

• Setup completion rate
• Time to setup completion
• Drop-off points in setup flow

Stage 2: Aha

What it is: The moment when the user experiences your product's core value for the first time

How to find your Aha moment:

1. Look at retained vs churned users
2. What did retained users do that churned users didn't?
3. That differentiating action is your Aha

Examples by product:

• Slack: Sent 2,000 messages (team-wide)
• Dropbox: Put at least 1 file in 1 folder on 1 device
• Facebook: Add 7 friends in 10 days
• Airbnb: Book 1 trip
• LinkedIn: Make 5 connections
• TaskFlow (example): Complete first task with team member

Aha characteristics:

• ✅ Directly tied to core product value
• ✅ Measurable and clear
• ✅ Achievable within first session (or first week)
• ✅ Predictive of retention

Metrics to track:

• Aha completion rate (% of setups → Aha)
• Time to Aha (from signup)
• Corr