Hook Model Habit Score Calculator
Score your product on the four pillars from Nir Eyal's Hooked — Trigger, Action, Variable Reward, Investment — and see your habit zone, weakest pillar, and D30 retention forecast. Free, no signup, runs in your browser.
Last reviewed: May 2026
Top fixes (3)
B = MAT — Action Sub-Engine
BJ Fogg's Behavior Model. Behavior happens when motivation, ability, and trigger meet above the Action Line.
Variable reward type — Tribe / Hunt / Self
Dominant: Tribe · all three loops present
Investment ladder (4/5 rungs)
Switching cost score: 80/100
Habit zone — frequency × utility
Self-rated: Habit Zone
6-dimension report card
Composite of trigger / action-friction / reward-variability / investment-depth / internal-trigger-migration / habit-zone-position
Retention forecast — D1 / D7 / D30 / D90
Projection from your habit score against Productivity SaaS category-typical curve. Directional, not actuarial.
What "Hooked" by Nir Eyal actually says
Nir Eyal's Hooked: How to Build Habit-Forming Products (Portfolio / Penguin, 2014, co-written with Ryan Hoover) defines a four-pillar loop that habit-forming products run their users through, over and over, until the product becomes the default response to a familiar emotional state. The hooked book is short — under 250 pages — but every chapter pivots on a single idea: external triggers get the user in the door, internal triggers bring them back, variable rewards keep the dopamine firing, and investment loads the next trigger. The frame is general enough to describe Pinterest, Slack, Strava, Duolingo, and Tinder while staying specific enough to diagnose which pillar a product is missing.
The hooked model nir eyal proposes is most useful as a structural diagnosis. Most products are not missing all four pillars — they're missing one or two, and that's where retention quietly leaks. A product can have an obsession-grade reward and still churn fast if there's no investment rung. A product can have heavy investment and still feel like a chore if the reward is predictable. The book's final chapter introduces the Manipulation Matrix, which asks two ethical questions: would you use the product yourself, and does it materially improve users' lives? Products that score yes/yes are facilitators; yes/no are entertainers; no/yes are peddlers; no/no are dealers. The same loop produces all four, so the ethical work is yours.
Eyal followed Hooked with Indistractable (BenBella Books, 2019), which inverts the framework — using the same understanding of triggers and reward to help users disengage from products designed to addict. The two books read together are the closest thing the field has to a single canonical reference on behavioral product design.
Hook Model vs cue routine reward (Duhigg's habit loop)
Charles Duhigg's The Power of Habit (Random House, 2012) names a three-step loop: a cue triggers a routine, the routine produces a reward. Eyal's Hook Model agrees on the first and last — Trigger maps to cue, Variable Reward maps to reward — but splits the routine in two and adds a fourth step Duhigg doesn't name.
Cue / Trigger
The signal that prompts the behavior. Duhigg and Eyal agree here. Eyal further distinguishes external (push, email) from internal (boredom, anxiety) and treats migration from external to internal as the primary durability metric.
Routine / Action
What the user does. Duhigg names it as a single step; Eyal attaches BJ Fogg's B = MAT formula and treats Ability (friction) as the leverage variable, since raising motivation rarely works.
Reward / Variable Reward
The dopamine moment. Eyal adds the variability constraint — predictable rewards lose their pull within days. He also classifies reward type: Tribe (social), Hunt (resource), Self (mastery).
Investment (Eyal only)
What the user puts back in to load the next iteration. Profile data, content created, a graph of followers, a reputation score, a skill they only have inside this product. Each rung increases switching cost.
Both frameworks are right. Duhigg's is closer to neuroscience and human-habit research; Eyal's is closer to product design and the lived experience of someone shipping a SaaS or consumer app. The calculator above scores against Eyal's four pillars because Investment is what makes a habit loop into a defensible habit-forming product — without it, you can be loved and still lose the user.
The four pillars of habit-forming product design
Habit forming products run on four interlocking pillars. The calculator scores each on a 0–25 raw scale. Below 8 on any pillar caps the composite at 50; below 12 caps at 70; below 15 caps at 85. Floor enforcement is non-negotiable — averaging hides broken loops.
Trigger (20% weight)
External cues bring users in; internal cues bring them back. The migration from external dependency to internal pull is the durability metric. Below 25% unprompted returns is fragile — pulling notifications would crater retention.
Action (25% weight)
B = M × A × T. Behavior happens when motivation, ability, and trigger converge above the Action Line. Cutting friction beats writing better copy almost every time.
Variable Reward (30% weight, the heaviest)
Surprise rewards keep firing dopamine; predictable ones don't. Three flavors: Tribe (social), Hunt (resource), Self (mastery). Most products under-use one of three.
Investment (25% weight)
Five rungs of switching cost: Profile, Content, Followers, Reputation, Skill. A product without investment is loved-and-lost; the dating-app pattern.
Reward weighted highest because variable reward is the hardest pillar to retrofit — it requires real product surface, not just lifecycle messaging. Trigger weighted lowest because external triggers can be added quickly with a Customer.io campaign or a re-engagement email. Practitioners who've shipped habit-forming products will recognize this ranking; the underlying observation is that reward design is the bottleneck for almost every product team trying to convert a Vitamin into a Habit Zone tool.
Internal vs external triggers — and why migration is the real metric
An external trigger is something the product or its lifecycle messaging delivers to the user — a push notification, a transactional email, an SMS, a paid retargeting ad, even a friend's share. An internal trigger is an emotion or thought the user already has that the product has trained them to resolve by opening it. Boredom that opens Reddit. Anxiety about a streak that opens Duolingo. The thought "did anyone reply" that opens Slack. The whole point of early lifecycle work is to use external triggers to teach the user which internal trigger the product solves; once learned, the pairing fires without prompt.
The migration metric on the calculator asks what fraction of returning sessions are unprompted. Below 25% is fragile — a product that lives by notifications dies when notifications die. Between 25 and 50% is developing. Between 50 and 75% is healthy. Above 75% is self-sustaining. Most product teams underestimate how much of their D7 retention is held up by external triggers; pulling notifications for a week is a brutal but useful experiment to surface the real internal-trigger pull.
BJ Fogg's B = MAT and the Action pillar
BJ Fogg, who founded the Stanford Behavior Design Lab and later wrote Tiny Habits (Houghton Mifflin Harcourt, 2019), gave Eyal the Action pillar. The formula is B = MAT: behavior occurs when motivation, ability, and a trigger converge above an Action Line. The model has a counter-intuitive implication for product teams — when behavior fails, raising motivation almost never works. The leverage variable is Ability, which in product terms means cutting friction.
Cutting one step from a sign-up flow almost always beats writing a better headline. Pre-filling a form field beats explaining why filling it matters. Skipping a confirmation step beats adding a reassuring microcopy. The B=MAT gauge in the calculator above plots all three components separately. If your product's M × A × T product is below 0.4, the Action Line is broken — most users will never complete the loop, no matter how strong the reward they'd see if they did. Fix Ability first, then Trigger-present, then motivation last.
Variable reward types: Tribe, Hunt, Self
Eyal classifies variable rewards into three flavors. Tribe rewards are social signals — likes, follows, comments, mentions, the kudos count on a Strava segment. Hunt rewards are resource-foraging signals — the next item in an infinite feed, the deal in your inbox, the search-result that pays off, the pull-to-refresh that reveals something new. Self rewards are mastery signals — leveling up, finishing a problem set, beating yesterday's pace, completing a skill tree. The product psychology insight is that the three reward types target different human motivators, and most products lean heavily on one while neglecting the other two.
Tinder is Hunt-and-Tribe-strong but Self-weak — there's no mastery loop. Notion is Self-strong but Tribe-weak — the mastery of a complex tool earns no social recognition. Strava is Tribe-strong via kudos and Self-strong via PRs but Hunt-weak — there's no surprise feed. The diversity ternary plot in the calculator above places your product as a point inside an equilateral triangle and flags which of the three reward types you're missing. Adding a missing type is one of the highest-leverage product-psychology moves available — it expands the audience by drawing in users whose dominant motivator wasn't already served.
The investment ladder: 5 rungs of switching cost
Investment loops are the behavioral design move that turns a habit loop into a habit-forming product. Each rung the user climbs increases the cost of leaving:
- Profile. Name, photo, role, preferences. Cheap to ship, cheap to abandon — but the price of admission for the higher rungs.
- Content. Notes the user wrote, files the user uploaded, designs the user produced. The user's past work is now hostage to the product.
- Followers. A graph of teammates, friends, audience. Social investment that compounds — leaving means leaving relationships.
- Reputation. Karma, ratings, tenure, status, public history. Rebuildable elsewhere only at significant time cost.
- Skill. The user becomes faster or better at the product over time — keyboard shortcuts, mental model, intuition that doesn't transfer.
Slack hits four of five (profile, content, followers, reputation; skill is partial). Notion hits all five — that's why it has the deepest switching cost in the modern productivity stack. Tinder hits one (profile only) — it's why match-cycle churn is fast. Habit design that doesn't ladder up the rungs ships engagement that doesn't convert to retention. The ladder visualization above shows which rungs your product owns.
Habit Zone vs Vitamin vs Painkiller-only
Eyal's 2D habit zone matrix maps perceived frequency (uses per week) against perceived utility (importance). Four quadrants result, each with a different product strategy:
Habit Zone — high frequency × high utility
Daily use, indispensable. Slack, Duolingo, Reddit, WhatsApp. Earnable through all four pillars firing in sequence.
Vitamin — low frequency × high utility
Weekly or situational use, important when triggered. TurboTax, Notion-for-occasional-writers, weekly retro tools. Not failure — just a different product shape. Don't over-notify.
Painkiller-only — high frequency × low utility
Returns often but the user wouldn't miss it if it disappeared. Episodic, not loved. The path forward is investment loops to convert frequency into commitment.
Forgettable — low frequency × low utility
No clear cue, no daily reason to return. Most early-stage products live here until they earn a pillar. The fix is rarely all four pillars at once — pick the weakest and ladder up.
The matrix in the tool above places your product alongside Slack, Notion, Duolingo, Strava, Tinder, and Quora as anchor points. Knowing your nearest peer matters because the upgrade path differs by zone — moving from Vitamin to Habit Zone is a frequency problem, while moving from Painkiller-only to Habit Zone is an investment-loop problem.
Slack, Notion, Duolingo, Strava, Tinder, Quora through the Hook Model lens
Six anchor products mapped against the four pillars to make the framework concrete. Each is also a preset in the calculator so you can compare your scores directly.
Slack — Habit Zone exemplar
Daily cadence, Tribe-dominant reward (the @mention notification), four investment rungs, low Action friction. The internal trigger is the "did anyone reply" thought — the product manufactures it within a week of joining a busy workspace.
Notion — investment-dominated
Modest reward variability but five-of-five investment rungs. Retention runs through switching cost, not daily dopamine. The Reward pillar is Self (mastery of a complex tool).
Duolingo — trigger and reward dominated
Notification king with manufactured streak-anxiety as the internal trigger. Variable Reward runs all three flavors — Tribe (leaderboard), Hunt (lesson surprise), Self (XP). Three of five investment rungs.
Strava — Tribe-extreme reward
Tribe rewards via kudos and segment leaderboards are the strongest social-reward loop in any consumer app. But Action friction is high (you have to do the workout first) — that's why Strava is Vitamin for casual users and Habit Zone only for power users.
Tinder — reward-dominated, weak investment
Lowest-friction Action in any consumer product (one swipe). Variable Hunt + Tribe reward. But only one investment rung (Profile) — which is exactly why match-cycle churn is so fast. The dating-app pattern.
Quora — Forgettable
Notification-dependent (weak internal trigger), modest utility, Hunt-only reward, two investment rungs. Informational rather than habit-forming, which is fine — but reflects why retention runs lower than the engagement metrics suggest.
Frequently asked questions
What is the Hook Model from Nir Eyal's Hooked book?
The Hook Model is a four-pillar loop — Trigger, Action, Variable Reward, Investment — defined by Nir Eyal in his 2014 book Hooked: How to Build Habit-Forming Products (Portfolio / Penguin, co-written with Ryan Hoover). External triggers like push notifications get a user in the door; internal triggers like boredom, FOMO, or anxiety bring them back without prompting. The Action pillar uses BJ Fogg's Behavior Model (B = Motivation × Ability × Trigger) to predict whether the user will actually complete the loop. Variable rewards — the surprise dopamine spike — are the most controversial pillar. Investment is what the user puts in, which raises switching cost and loads the next trigger.
How do you measure if a product is habit-forming?
A defensible measurement scores each of the four pillars separately, enforces a floor on the weakest pillar, and projects retention against a category-typical curve. The four-pillar method matters because a habit only forms when all four chambers fire in sequence — a 95 on Reward paired with a 12 on Trigger doesn't average to 53.5, the chain is broken and the loop doesn't close. The tool above scores Trigger, Action, Reward, and Investment on a 0–25 raw scale each, weights them 20/25/30/25 into a composite 0–100, and caps the composite when any pillar drops below 15. That floor enforcement is the difference between a habit-forming-product score that matches reality and one that flatters bad designs.
What's the difference between the Hook Model and the cue routine reward habit loop?
Charles Duhigg's cue routine reward loop, from The Power of Habit (Random House, 2012), names three steps: a cue triggers a routine, the routine produces a reward. Nir Eyal's Hook Model agrees on the first and last — Trigger maps to cue, Variable Reward maps to reward — but adds two distinctions. First, Eyal splits the routine into Action and explicitly attaches BJ Fogg's B = MAT formula to it. Second, Eyal adds a fourth pillar Duhigg doesn't name: Investment, the work the user puts back in to load the next iteration of the loop (a profile, content, followers, reputation, skill). Investment is the rung that converts a habit loop into a habit-forming product, because each pass through the loop makes the next pass easier.
What are the four pillars of the Hook Model?
Trigger (the cue — external like a push notification, internal like boredom), Action (what the user does — Motivation × Ability × Trigger), Variable Reward (the surprise — Tribe like social signals, Hunt like resource foraging, Self like mastery), and Investment (what the user puts back in — profile, content, followers, reputation, skill). The four pillars must fire in sequence; missing any one breaks the loop. Most products score well on two or three but drop on the fourth, and that fourth is where retention quietly leaks.
What's an internal trigger and why does it matter?
An internal trigger is an emotion or thought that prompts the user to open the product without an external nudge — boredom that makes a user open Reddit, FOMO that pulls them into Instagram, anxiety about a streak that drives them back to Duolingo. External triggers (push, email, SMS) bring users to the product the first time; internal triggers are what make the habit durable. The migration metric on the calculator above asks what percentage of returning sessions happen unprompted. Below 25% is a fragile loop — pull notifications and retention craters. Above 50% is healthy. Above 75% is self-sustaining.
What does the BJ Fogg Behavior Model have to do with the Hook Model?
BJ Fogg, who founded the Stanford Behavior Design Lab and later wrote Tiny Habits (Houghton Mifflin Harcourt, 2019), gave Eyal the Action pillar. His formula is B = MAT — behavior happens when motivation, ability, and a trigger converge above an Action Line. The product implication: when the loop fails on the Action pillar, raising motivation almost never works. Cutting friction (raising Ability) and making sure the trigger arrives at the moment of capability are the leverage moves. The B=MAT gauge in the tool above plots all three components separately and shows the product against the Action Line.
What is variable reward in product design?
A variable reward is one whose size or timing is unpredictable on each loop iteration — a slot-machine pull is the canonical example, but so is the next item in an infinite feed, the next Tinder match, or the next batch of likes on a Strava segment. Eyal classifies them into three flavors: Tribe (social signals — likes, follows, comments, mentions), Hunt (resource foraging — feed scrolling, search payoffs, deal hunting), and Self (mastery — leveling up, beating yesterday's score, finishing a sprint). The product-psychology insight is that predictable rewards lose their dopamine pull within days, while variable rewards keep firing the same neurochemistry for years. Most products under-use one of the three reward types; the calculator flags which one is missing.
What's the Habit Zone in product design?
The Habit Zone is Eyal's 2D matrix where perceived frequency (uses per week) meets perceived utility (importance). High frequency × high utility = Habit Zone (Slack, Duolingo). Low frequency × high utility = Vitamin (TurboTax — useful when needed, no daily pull). High frequency × low utility = Painkiller-only (a one-shot tool you keep returning to but never love). Low × low = Forgettable. The calculator above plots your product on the matrix alongside Slack, Notion, Duolingo, Strava, Tinder, and Quora as anchor points so you can see how far you are from your nearest habit-zone peer.
How do investment loops increase user retention?
An investment loop is a rung the user climbs that increases switching cost. The five rungs in order of ascending depth: Profile (name, photo, preferences), Content (notes, files, designs the user produced), Followers (a graph of teammates or audience), Reputation (karma, ratings, tenure, status), and Skill (the user becomes faster or better at the product over time). Slack hits four of five — profile, content, followers, reputation. Notion hits all five. Tinder hits one. The behavioral-design thread is that a product without investment loops can be loved and still lose its user — the dating-app pattern of high engagement per session and fast variety-seeking churn. The ladder visualization above shows which rungs your product owns.
Is my SaaS product a habit or a vitamin?
Habit-forming products fire on a daily or near-daily cadence and run all four pillars. Vitamin products solve a real problem but on a weekly or situational cadence — the user values them when triggered, but no daily cue exists. The calculator distinguishes the two by composite score and trigger cadence. A score above 80 with all four pillars clearing 15/25 lands in Habit Zone. A score 60–80 with three pillars clearing 12/25 lands in Vitamin. The practical implication: vitamin products are not failures — they're sufficient if the underlying frequency need is weekly. The mistake is to chase Habit Zone when the actual user need is monthly, which produces over-notification and churn.
Can you give examples of habit-forming products?
Slack is the canonical Habit Zone product — daily cadence, low friction, Tribe-strong reward, four investment rungs. Duolingo runs trigger and reward at near-game level, with streak-anxiety as the manufactured internal trigger. Strava is Vitamin-leaning for casual users but Habit Zone for power users — Tribe rewards via kudos and segments, three investment rungs. Notion is investment-dominated — modest reward variability but five investment rungs make it the highest switching-cost product on the matrix. Tinder is reward-dominated with one investment rung, which is why it churns faster than its engagement metrics suggest. Quora hits low frequency and modest utility — informational, not habit.
How accurate is this habit score?
The score is a structural diagnosis, not a retention prediction. It tells you which pillars your product runs on and which it's missing — useful when retention data is too thin to draw conclusions, when redesigning a flow, or when comparing a product against a habit-forming peer. The retention forecast is directional: it scales a category-typical D1/D7/D30/D90 curve by your composite score. It is not a substitute for measuring your actual retention curve in Mixpanel, Amplitude, or first-party telemetry. Use the score to spot the weakest pillar; use your real data to confirm whether fixing that pillar moved retention.