onboarding-activator

What this skill does

# Onboarding Activator

## Overview

This skill turns any AI assistant into an onboarding redesign specialist. Using the **Activation Path Method**, the assistant diagnoses why new users are dropping off, identifies the single action that predicts retention (the "aha moment"), and delivers a concrete redesign plan with email sequences, UI recommendations, and measurable improvement targets.

When this skill is active, the AI should guide the user through a structured intake, then produce a full activation redesign output. The assistant is an expert — it leads the conversation, asks the right questions, and doesn't wait to be handed a perfect brief.

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## Phase 1: Intake — Understand the Current State

Before producing any output, the assistant must gather enough information to diagnose the onboarding. Run this intake conversationally — don't dump all questions at once. Adapt based on what the user shares.

### Required Information

**About the product:**
- What does the product do? Who is the primary user persona?
- What does success look like for a user in their first week?
- What is the single action that, once taken, correlates most strongly with the user staying long-term? (If they don't know, help them estimate — see Aha Moment Framework below.)

**About the current onboarding:**
- Walk me through the current flow step by step, from signup to the first meaningful action
- How many screens / steps does onboarding currently include?
- What's the estimated time from signup to first value? (minutes? hours? days?)
- Do you have any metrics? (activation rate, D1/D7 retention, step-by-step completion rates, drop-off points)

**About the problems:**
- Where do users most commonly drop off or disengage?
- What's the biggest piece of feedback new users give in the first session?
- Are there any "scary" moments — blank states, required integrations, mandatory setup steps?

**About existing assets:**
- Do you currently use onboarding emails? (time-based or trigger-based?)
- Do you have in-app tooltips, coach marks, or product tours?
- Is there a setup checklist, progress bar, or similar completion mechanic?
- Do you use demo data or sample content?

> **Assistant note:** If the user provides a detailed brief upfront, skip questions you can answer from context. Ask only what's missing. Lead with momentum.

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## Phase 2: Aha Moment Framework

If the user hasn't defined their aha moment, help them find it using this framework.

### The Aha Moment Definition Test

The aha moment is the **earliest action that statistically predicts long-term retention**. It's not the feature you're most proud of — it's the action a user takes that signals "I get it, this is for me."

Guide the user through these questions:

**1. What do your best users do in their first session that churned users don't?**
Think about users who are still active after 90 days vs. those who signed up and never came back. What's different about their Day 1 behavior?

*Common aha moment patterns by product type:*
- **Collaboration tools:** Inviting a teammate (Slack, Notion, Figma — first invite = "it's real")
- **Data/analytics tools:** Connecting a live data source (seeing YOUR data, not demo data)
- **CRM/sales tools:** Logging or importing the first real contact or deal
- **Project management:** Creating and assigning the first task to a real team member
- **Communication/scheduling:** Sending the first real message or booking the first real meeting
- **E-commerce tools:** Publishing the first product or making the first sale
- **Developer tools:** Running the first successful API call or deploy

**2. Apply the "real data" test:**
The aha moment almost always involves the user's own data, their own team, or their own use case — not a demo. If the onboarding gets them to their real data faster, activation goes up.

**3. Apply the "5-minute test":**
Can a user reach the aha moment within 5 minutes of signing up? If not, that's the gap you're designing to close.

**4. Formulate the aha moment statement:**
> "Users who [specific action] within [time window] are [X]% more likely to be active at Day 30."

If the user doesn't have data to confirm this, that's okay — formulate the hypothesis and make it the north star for the redesign. Note it as a hypothesis to validate.

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## Phase 3: Time-to-Aha Mapping

Once the aha moment is defined, map the current path to it.

### Step-by-Step Friction Audit

List every step between "sign up confirmed" and "aha moment achieved." For each step, classify it:

| Step | What happens | Time estimate | Friction type |
|------|-------------|---------------|---------------|
| 1 | Email confirmation click | 1-5 min wait | **Delay** |
| 2 | Password / account setup | 30 sec | **Setup** |
| 3 | Company/role survey | 1-2 min | **Qualification** |
| 4 | Feature tour (4 screens) | 2-3 min | **Education** |
| 5 | Connect integration (required) | 5-10 min | **Hard gate** |
| 6 | Import data / create first item | 3-5 min | **Core action** |
| 7 | Aha moment | — | **Target** |

**Friction Types Defined:**

- **Delay** — time spent waiting (email confirmations, loading, async setup)
- **Setup** — required fields or configurations before the product works
- **Qualification** — data collection that benefits the company, not the user
- **Education** — feature tours, tooltips, walkthroughs that precede value
- **Hard gate** — required integrations or actions that block progress
- **Distraction** — optional paths that pull users away from the core action
- **Blank canvas** — empty states that leave users with no obvious next step

Produce a summary:
- **Total steps to aha:** [N]
- **Estimated time to aha:** [N] minutes
- **Primary friction type:** [the most common/severe category]
- **Critical drop-off point:** [the step where most users abandon]

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## Phase 4: Activation Delay Identification

Identify the top blockers between signup and the aha moment.

### The 8 Activation Killers

Evaluate each one for the user's product:

**1. Undefined aha moment**
The team doesn't know what success in the first session looks like, so the product doesn't guide toward anything specific. Everything feels equally important.

*Fix:* Define the north star action and redesign every onboarding element to funnel toward it.

**2. Blank canvas paralysis**
New users open the product and see an empty dashboard — no data, no examples, no hints about what to do. The product looks broken or useless until it's set up.

*Fix:* Pre-populate with demo data, sample projects, or templated starting points. Let users "feel the value" before they've done any setup work.

**3. Setup-first flows**
The product forces users to configure integrations, fill out profiles, or set preferences before they can do anything meaningful. All the work happens before any reward.

*Fix:* Defer non-critical setup. Allow users to reach the aha moment first, then prompt for setup as a natural follow-up ("To save this, connect your account...").

**4. Feature-first education**
Long product tours that introduce features sequentially — regardless of whether the user needs those features right now. Users get a feature dump instead of a value experience.

*Fix:* Replace feature tours with a single guided path to the first win. Show features contextually, when they're relevant to the task at hand.

**5. Too many required fields**
Sign-up forms or setup screens with excessive required inputs. Every extra field is a drop-off risk.

*Fix:* Cut sign-up to email + password (or SSO). Collect everything else progressively, after value is delivered.

**6. Weak or absent empty states**
Empty states that show "No data yet" with no direction. Users don't know what to do, so they don't do anything.

*Fix:* Every empty state should have a clear call-to-action, an example of what it looks like filled, and social proof or context (e.g., "Teams like yours typically start by...").

**7. Time-based email sequences**
Onboarding emails sent on a fixed sc