Playbook · Idea / prototype to Searching (pre-PMF)
Idea and Searching × Pay
Learn what people would pay before engineering how they pay: willingness-to-pay conversations, one simple plan, and a token fee instead of free for expert services. Where the purchase itself is the value event, honest checkout levers are in season from the first customers (stores have their own Pay cell).
- M0 Idea / prototype
- Is there a real itch, felt often enough?
- M1 Searching (pre-PMF)
- Who, if anyone, is it a must-have for?
- Pay
- Is paying the natural next step for an invested user?
M0-M1 × Pay
The playbook
Goal. Know what the loving segment would pay for, without pressuring a loop that doesn't exist yet.
Moves. Willingness-to-pay conversations with the users who'd be most disappointed; one simple plan; for expert services, a small token fee instead of free; write the business model next to every habit metric HK-MON12 (Hooked Ch.8).
Rule. For products that earn from ongoing use, heavy pressure to pay waits until users reach the devoted cadence; plan structure and clear pricing are always in season. Cash mode (runway under six months or revenue as the top metric) brings depth pricing and trials forward and states the retention risk.
Lead with these moves
- TechniqueEvidence grade D. Practitioner framework or anecdote: plausible, untested.
A token fee instead of free for expert services
small fee as a quality signal
For expertise and high-stakes services, a modest fee or paid pilot can work better than free, because people judge quality by price when they cannot judge it directly. Chou's experience: a free audit made a client hesitate, where a few hundred dollars would have signaled value.
Not now
- Hard paywall before the habitA paywall before the habit converts some and loses the rest.
- Annual-plan discountsLocking people in before the habit forms just delays the churn.
- Limited-time discounts to convertDiscounts pull in buyers who leave when the discount ends.
- Premium-first pricing pagePricing tactics come after people value the product.
- Honest-deadline conversion momentAn honest deadline helps only after people have had their win.
- Lowball or drip pricingLate fees and lowballs convert now and come back as refunds and chargebacks.
How to measure it
Questions to answer first
- How do customers pay you today: a subscription, freemium, one-time purchases, a cut of transactions, a sales contract, or ads?
- How many months of runway do you have, and is revenue your number-one metric right now?
- Which features matter only to your most devoted users, and are those what you charge for?
- What type of person benefits most from your product? Describe them as specifically as you can.
- Does the paywall show up before or after a user's first big win, and does it block the core action or only extra depth?
Variant · B2B sales-led
Idea and Searching × Pay · Sales-led B2B
Before fit, revenue work is design partners and a paid pilot with clear success criteria. The pilot price tests willingness to pay; the success criteria test value.
Moves. Recruit design partners from the segment that feels the pain most; sell a paid pilot with written success criteria and a decision date; record why deals stall. Pricing-page tactics wait for a product people already value.
Not now
- Annual-plan discountsLocking people in before the habit forms just delays the churn.
- Premium-first pricing pagePricing tactics come after people value the product.
- Honest-deadline conversion momentAn honest deadline helps only after people have had their win.
- Lowball or drip pricingLate fees and lowballs convert now and come back as refunds and chargebacks.
How to measure it
Questions to answer first
- Pick the most recent customer who switched to you from something else. What was going on for them right before they began searching?
- What type of person benefits most from your product? Describe them as specifically as you can.
- If you shut down tomorrow, who would be genuinely upset, and how many such customers could you name?
- How do customers pay you today: a subscription, freemium, one-time purchases, a cut of transactions, a sales contract, or ads?
- How many months of runway do you have, and is revenue your number-one metric right now?
Variant · E-commerce / DTC
Idea and Searching × Pay · E-commerce
When the purchase is the value event, honest checkout work is in season from the first customers: proof from similar buyers at the moment of doubt, all-in pricing with honest defaults, and anxiety reducers.
Why it's in season early. For stores, the purchase is the value event, so honest checkout levers don't wait for a habit.
Moves. Proof from similar buyers at the moment of doubt INF-T-SP-12 (Influence Ch.4, p.98) INF-T-SP-17 (Influence Ch.4, p.107); all-in prices and honest defaults F04; guarantees, delivery dates and free returns as anxiety reducers F07 HK-ACT07 (Hooked Ch.3); live, true stock and deadlines only INF-T-SC-01 (Influence Ch.7, p.180); one add-on after the main choice, unchecked, with a running total.
Guardrails. Refunds, discount dependence and the first-seen vs final price gap.
Lead with these moves
- TechniqueEvidence grade B. Moderate evidence: solid studies with some limits.
Proof at the moment of uncertainty
proof placed where people hesitate
- TechniqueEvidence grade B. Moderate evidence: solid studies with some limits.
Proof from similar others
people like you
Also in season
Not now
- Lowball or drip pricingLate fees and lowballs convert now and come back as refunds and chargebacks.
- Loyalty tiers without devaluationTiers work once a large repeat base exists.
- Subscribe-and-saveA subscription offer needs repeat buyers first; prove the second order.
- Countdown timers that resetFake urgency converts once and returns as refunds and distrust.
How to measure it
Questions to answer first
- At checkout, what reassures a first-time buyer: reviews from similar buyers, a guarantee, the all-in price, a delivery date?
- Where are visitors most unsure (pricing, sign-up, checkout), and what honest evidence do they see right there?
- What worries stop visitors from trying (setup effort, cost, data, getting locked in), and what would remove each one?
- How often, and by how much, is the final price at checkout higher than the first price a buyer saw?
- When buyers can add extras, do those appear only once the main purchase is chosen, one by one, not pre-selected, with the total updating as they go?
- How do customers pay you today: a subscription, freemium, one-time purchases, a cut of transactions, a sales contract, or ads?
Limits
What we don’t claim
- The Hook Model is a practical design tool, not a validated or complete theory of behavior.Hooked, Introduction
- 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.1 · Ch.8 · Ch.3
Influence · Robert Cialdini
Ch.4, p.98 · Ch.4, p.107 · Ch.3, p.43 · Ch.7, p.180
Shopify store conversion benchmarks (about 2,800 stores) · Littledata, 2023
Benchmark confidence C. A secondary source.
Source IDs: HK-MON12HK-MON01F07INF-T-SP-12INF-T-SP-17F04INF-T-CC-34INF-T-SC-01HK-ACT07
Book content is paraphrased, never quoted at length. Last verified October 24, 2026.
Your product
Find the stage your product is stuck in
A playbook shows what is usually right at this cell. Gamify It checks it against your own product and picks the one move that matters now. Connecting is free; a Pro subscription starts it.