Playbook · Early fit
Early fit × Discover
Turn earned attention into owned triggers and put proof from the first similar customers where visitors hesitate. Value-carrying invites let normal use recruit the next users.
- M2 Early fit
- How do we put every new user on the path that retained users took?
- Discover
- Why would the right people try it?
M2 × Discover
The playbook
Goal. First tries from the right people at a sustainable cost per activated user.
Diagnose. The trigger-type mix of sign-ups and sessions; spike-cohort day-30 retention after press or launches; whether there is proof where visitors are unsure; which worries stop a first try.
Moves. Convert each earned spike into an owned trigger (install, opt-in, saved item) HK-TRG07 (Hooked Ch.2); show proof from the first similar customers INF-T-SP-17 (Influence Ch.4, p.107); lead with core value and the one most relevant cue INF-T-FN-15 (Influence Intro); add anxiety reducers (guarantees, no card, free cancellation); make invites carry value to non-users HK-TRG08 (Hooked Ch.2).
Exit. Visit-to-activated at or above its band, with new-cohort day-7 retention holding. Discover never outranks Start while activation is leaking.
Lead with these moves
- TechniqueEvidence grade D. Practitioner framework or anecdote: plausible, untested.Practitioner heuristic
Turn paid and earned spikes into owned triggers
capture the attention you rented
Ads and press bring bursts of visitors that fade. Give every spike a landing flow that earns an owned channel (an account, an install, an email or push opt-in), and judge the spike by its D30 retention, not its visits.
- TechniqueEvidence grade B. Moderate evidence: solid studies with some limits.
Proof from similar others
people like you
Choose testimonials, case studies and usage data by the visitor's industry, role, size, country, language or experience level, and let users filter reviews by "people like me". People follow those who resemble them far more than generic crowds.
Also in season
- Evidence grade C. Limited evidence: few or small studies.Invites that carry value to the person invitedvalue-carrying invites
- Evidence grade B. Moderate evidence: solid studies with some limits.Value before the askgive first, then ask
- Evidence grade B. Moderate evidence: solid studies with some limits.Informative samplereal free sample
- Evidence grade B. Moderate evidence: solid studies with some limits.Value before sign-up: let people try the coretry before registering
- Evidence grade C. Limited evidence: few or small studies.Lead with the core valuevalue-first message
- Evidence grade C. Limited evidence: few or small studies.Most relevant cue first for overloaded usersone clear cue under pressure
- Evidence grade B. Moderate evidence: solid studies with some limits.Real reason on every askreason-backed request
- Evidence grade B. Moderate evidence: solid studies with some limits.Conformity Anchors (GT#58)true peer benchmarks
- Evidence grade B. Moderate evidence: solid studies with some limits.Positive norms, never 'many people do the bad thing'positive peer-norm copy
Not now
- Scale paid acquisition while activation leaksFix the setup leak first: new paid users would hit the same broken first session.
- Small copy or button A/B testsAt your volume a small tweak would take months to read.
- Cash bounty per inviteSmall cash rewards can backfire; make the reward more of the product.
How to measure it
Questions to answer first
- After press, a launch or a store feature, what was that cohort's day-30 retention compared with your organic cohorts?
- Does each type of visitor see proof from people like them (same role, size, use case)?
- Where are visitors most unsure (pricing, sign-up, checkout), and what honest evidence do they see right there?
- When someone uses your product, does it deliver something useful to people who don't use it yet?
- What value does a visitor get before you ask for an email or a card, and after how many steps?
- Does every request on the landing and sign-up path (email, card, permissions) come with a real, specific reason?
- What worries stop visitors from trying (setup effort, cost, data, getting locked in), and what would remove each one?
- Does each session record what brought it in (paid, earned, relationship, owned, or nothing), separately from the channel?
Limits
What we don’t claim
- The Hook Model is a practical design tool, not a validated or complete theory of behavior.Hooked, Introduction
- Octalysis is a practitioner framework built from observing games, not a validated scientific model.Actionable Gamification Ch.15, pp.399-400
- Seasons are defaults for the cell. Evidence from your own product can move a technique in or out of season.
- A playbook names candidate moves; which one goes first depends on the binding constraint in your product.
Sources
Hooked · Nir Eyal
Ch.2
Influence · Robert Cialdini
Ch.4, p.107 · Ch.2, p.17 · Intro · Ch.1, p.4
Actionable Gamification · Yu-kai Chou
Ch.9, p.224
Source IDs: HK-TRG07INF-T-SP-17HK-TRG08INF-T-RC-01INF-T-FN-15INF-T-EP-03GT#58
Book content is paraphrased, never quoted at length. Last verified October 24, 2026.
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