Signup Onboarding Audit

/signup-onboarding-audit — pre/intra-product friction audit

Audit the journey from "first click on Sign Up" through "first aha moment" with sharp heuristics on field friction, time-to-value, activation-metric definition, and checklist patterns.

This is the measurement half of the audit-triage pair. The triage counterpart signup-onboarding-incident-response is deferred per .claude/rules/audit-triage-pairing.md until a client triggers the build (likely ClientCo Q3 activation work).

When to invoke

• Activation rate is below the team's gut threshold and the cause is unclear.
• A signup flow has visible drop-offs in analytics and prioritization is needed.
• An onboarding sequence (in-product checklist, email triggers, tooltips) hasn't been audited since launch.
• A client is preparing for a growth push and wants the activation engine inspected before scaling acquisition.

Do NOT invoke when:

• The product has no signup (sales-led only) — sales-process audit instead.
• The activation metric is undefined — define it first via the activation-metric definition step, then audit.

Workflow

Step 1 — Define the activation metric

The single specific action that correlates with retention. Examples:

• B2B SaaS: "User invited 1 teammate within 7 days" or "User completed 1 core workflow within 14 days".
• Vertical SaaS: "User connected their primary data source within 24 hours" (ClientCo: "connected first client account") or "User generated their first report".
• Marketplace: "User completed first transaction within 30 days".

If the client cannot name the activation metric, that's the first finding. No further audit until defined — measuring against an undefined target produces theatre, not signal.

Step 2 — Signup field audit

Catalog every field on the signup form. For each, classify:

Sharp rules:

• 3 or fewer fields → single-step form OK.
• 4+ fields → multi-step with progress indicator.
• Password requirements visible upfront (don't ambush at submit).
• Mobile: large touch targets, autofill-friendly field types (type="email", autocomplete="email").
• "Takes 30 seconds" messaging sets expectations and reduces abandonment.

Step 3 — Onboarding flow audit

Map the path from signup confirmation to activation-metric hit. For each step, score:

• Time-to-value contribution: does this step move the user closer to the aha moment or away?
• Friction: how many decisions / inputs / waits does it impose?
• Necessity: would removing this step lose anything?

Sharp rules:

• Checklist length: 3–7 items. Fewer feels trivial; more overwhelms.
• Order by impact: highest-leverage step first, not easiest.
• "Do, don't show" — interactive completion beats tutorial videos.
• Tour length: 3–5 steps maximum before exhaustion.
• Celebrate completions visibly (progress bars, confetti, badges).

Step 4 — Multi-channel coordination

Onboarding ≠ in-product only. Audit the email triggers, in-app prompts, and /in-app-popups overlays in coordination:

• Day 0 email (immediately post-signup): pointer to the next critical step.
• Day 1 trigger (if no activation): friction-removal nudge specific to the stuck step.
• Day 3, 7 triggers: per-state, not per-time.

Misalignment (email says "do X" while in-product says "do Y") is a common finding.

Step 5 — Priority-ranked recommendations

Score each recommendation on Impact × Ease (5 × 5 = 25 max):

Top 3 land in the action queue; below that goes to a backlog.

Step 6 — A/B hypotheses for /ab-testing

Each high-priority recommendation becomes an A/B hypothesis in the format from /ab-testing:

"Because [observation], we believe [change] will cause [outcome] measured by [metric] within [timeframe]."

Example:

"Because 47% of users drop off at the company-size field, we believe removing the field will increase signup completion by 25% measured by signup-completion-rate within 2 weeks."

Hand off the formatted hypotheses to /ab-testing for sample-size calculation and test design.

{Product / Client} signup + onboarding audit

Activation metric

• Defined: ✅ {metric statement} / ❌ {first finding: define this}

Signup field audit

Onboarding flow audit

• Step 1: {description} — {time-to-value contribution: high/med/low} — {friction: high/med/low} — {keep/cut/reorder} -...

Multi-channel coordination findings

• Email Day 0:...
• In-product trigger Day 1:...
• Coordination misalignment: {if any}

Priority-ranked recommendations

• P0: {top 3 recs with Impact × Ease scores}
• P1: {next 3-5 recs}
• Backlog: {rest}

A/B hypotheses (formatted for /ab-testing)

• H1: Because..., we believe..., measured by..., within...
• H2:...

---

## Integration with other skills

- **Upstream:** `/analytics-tracking-plan` provides the event taxonomy needed to measure drop-offs; `/product-messaging` defines the value-prop the signup form sells against.
- **Downstream:** Hypotheses feed `/ab-testing` (test design + sample-size math); in-product overlay redesigns feed `/in-app-popups`.
- **Triage half (deferred):** `signup-onboarding-incident-response` per `.claude/rules/audit-triage-pairing.md`. Backlog noted; build when a client triggers an incident-mode use case.

---

## Anti-patterns

- ❌ Audit without an activation metric. You're measuring noise.
- ❌ Recommend "redesign the signup page" without per-field reasoning. Friction is field-level.
- ❌ Prioritize by ease alone (easy wins) instead of impact × ease.
- ❌ Audit signup or onboarding alone, not both. The handoff is where most friction lives.
- ❌ Tutorial-heavy onboarding when "do, don't show" applies.

---

## Attribution

This skill merges and adapts patterns from [`coreyhaines31/marketingskills/signup/SKILL.md`](https://github.com/coreyhaines31/marketingskills/blob/main/skills/signup/SKILL.md) and [`coreyhaines31/marketingskills/onboarding/SKILL.md`](https://github.com/coreyhaines31/marketingskills/blob/main/skills/onboarding/SKILL.md) (MIT license, © Corey Haines / Conversion Factory). Adapted to Genesys operator voice; merged into one audit skill per user direction. Triage half deferred per audit-triage-pairing rule.

---