Does the Hook Model Actually Work
The Hook Model has four stages, and the loop as a whole has not been tested. Its parts have support from older studies, each with conditions the loop does not state, and the word habit means something specific that retention figures cannot show.
Answer to the question
Does the Hook Model actually work?
The loop as a whole has not been tested. Its parts have support from older studies, each with conditions the loop does not state, and retention figures cannot show whether a habit has formed. Nir Eyal's Fitbod case was built by founders who had read the book, so it shows the model being followed, not what it contributed.
Key takeaways
- Nir Eyal's own flagship case in the 2019 edition of Hooked, Fitbod, was built by founders who had read the book, so it shows the model being followed and not what it contributed.
- In Charles Ferster and B.F. Skinner's 1957 experiments, the variable-ratio schedule produced the highest response rates and the strongest resistance to extinction of the schedules they tested, in pigeons.
- In a 2015 study led by Luxi Shen, 70 per cent of people offered an uncertain reward worth less on average finished a task, against 43 per cent offered a certain one; a 2019 follow-up found the effect held only when uncertainty resolved immediately.
- Michael Norton and colleagues found in 2012 that building something raised its value to the builder only when the labour ended in a finished product.
- Wendy Wood calls insensitivity to reward the gold standard for identifying a habit, and in a 2011 experiment led by David T. Neal, habitual popcorn eaters ate equal amounts of stale and fresh popcorn.
About nine visits a month per user is what Nir Eyal reports for Fitbod, a workout app, in Hooked. His explanation is the Hook Model. Eyal set the model out in Hooked, written as a manual for product makers. A trigger prompts an action, the action brings a variable reward, and the user then puts something into the product, such as data, content or followers, which makes the next visit more likely. After enough cycles, Eyal argues, the outside prompt gives way to a feeling, and the product is opened with no cue at all.
What the case studies can and cannot show
Hooked (2014) is a framework, built from case studies and the author's consulting work, and the case studies are products that succeeded. The newest, added to the 2019 edition, is Fitbod, a workout app. One of its founders, in Eyal's account, "read Hooked and designed an initial prototype based on the four parts of the Hooked Model". Eyal reports that the app "loses very few customers" on figures the founders gave him.
Fitbod is the Hook Model followed by a product that did well, and with no version built without it to compare, the case cannot show what the model contributed.
The book's numbers need the same care. Eyal often gives a finding without naming the researcher. The car-wash loyalty card appears as an 82 per cent higher completion rate (pp. 89 to 90), and Joseph Nunes and Xavier Drèze's 2006 paper gives the two rates behind it, 34 per cent against 19. The 82 is the relative gap, which a skimming reader takes for a percentage-point gain.
A Crossref title search on 21 October 2026 for the Hook Model by name found two 2026 papers, Wenya Wang and Yi Liu's design strategies for wearable fitness products and Iis Mariam and colleagues' case study of TikTok content virality. By their titles and records, neither is an experiment that ran the loop against a loop with a stage taken out. A title search catches only work that names the Hook Model.
Where each stage gets its support
The first two stages of the Hook Model come from the Fogg Behavior Model, B.J. Fogg's 2009 account of when behaviour happens, which Eyal credits. On that account a behaviour happens when motivation, ability and a trigger arrive together. It is also a model, and Fogg published it as one.
Variable reward has the oldest evidence. Charles Ferster and B.F. Skinner's Schedules of Reinforcement (1957) reported that the variable-ratio schedule, which paid out after an unpredictable number of responses, produced the highest response rates and the strongest resistance to extinction of the schedules they tested, in pigeons.
Consumers are less tidy: in a 2015 study led by Luxi Shen, 70 per cent of people offered an uncertain reward worth less on average finished a task, against 43 per cent offered a certain one. Shen and colleagues then described what they called the reinforcing-uncertainty effect, in four experiments published in 2019: people repeated a behaviour more often when the incentive was uncertain, even when a certain one was worth more. It held only when the uncertainty resolved immediately and only after a first repetition.
The investment phase of the Hook Model leans on the IKEA effect. Michael Norton and two colleagues had people assemble IKEA boxes, fold origami and build Lego sets, and found that people valued what they had made. The effect held only when the labour ended in a finished product. When builders watched their creations destroyed, or never completed them, it dissipated. None of the studies involved software. On the study's own terms, a profile left half filled is closer to the unfinished box than to the finished one. Where a loop of variable rewards comes from is traced in an article on [where slot machine design meets apps](https://thewhyweproject.com/articles/slot-machine-design-and-apps).
Two meanings of habit in the book
Even if the parts hold, they may not add up to a habit. Eyal opens with the cognitive psychologists' definition, behaviours "triggered by situational cues" and done "with little or no conscious thought". On page 33 he offers another: "A habit is when not doing an action causes a bit of discomfort."
insensitivity to reward is the gold standard for identifying a habit
His own way of locating a habit is frequency. The Habit Zone, a chart in the book's first chapter, plots how often a behaviour occurs against how useful the user finds it, and says a behaviour enters the zone once it has enough of both. Even a behaviour with "minimal perceived benefit" can become a habit, Eyal writes, "simply because it occurs frequently" (p. 30). He calls the chart "a guiding theory" and says "the scale of the illustration is intentionally left blank".
Habit researchers have a test for the first kind, reward insensitivity. In their account a habit is an association between a cue and a response, so a deliberate action stops when its outcome stops being wanted, and a habit does not. Wendy Wood writes that "insensitivity to reward is the gold standard for identifying a habit", and that the only way to know "is to test what happens when the reward changes" (2019, p. 126).
A pair of field experiments led by David T. Neal in 2011 ran that test with popcorn. Habitual popcorn eaters at a cinema were minimally influenced by their hunger or how much they liked the food, and they ate equal amounts of stale and fresh popcorn. They did so only in the cinema, the setting tied to the habit, and only when eating with their dominant hand. People with weaker habits ate because of motivations such as liking the popcorn.
Nine visits a month cannot separate a habit from a repeated choice. Someone who opens an app nine times because it still pays off is making a repeated choice. Someone who opens it from a cue, whatever it pays, is in a habit. The book's case studies report no test that would tell the two apart, and a snack at a cinema does not show that apps behave like popcorn. What the popcorn study supplies is the design of the test. The Norton and Neal papers were read here at the level of their abstracts.
What the loop works on, and who judges it
Eyal is direct about what the loop works on. Internal triggers, the feelings that bring a user back unprompted, form most strongly around negative emotion: boredom, loneliness, frustration, indecision, fear of missing out (pp. 48 to 49). He calls the internal trigger "the brass ring of habit-forming technology". The support he cites for the link between heavy internet use and low mood is a 2012 correlational study of 216 students at one university, which cannot show that people reach for a product because they feel low.
The loop is also judged by the maker. Eyal's ethics test, the Manipulation Matrix, asks whether the product materially improves the user's life and whether the maker would use it. Both questions are answered by the maker, with no outside check. Return visits record that people came back. Whether they would endorse coming back is a different measurement, and Wanting Is Not Liking takes up why the two can come apart. Eyal's later book, Indistractable (2019), treats the same discomfort as the thing to manage: find the emotion that comes before the distraction, write it down, and explore it with curiosity.
When anyone offers the Hook Model as proof, ask which stage was measured, against what comparison, and whether the outcome was return visits or use that survives a change in reward. Until then, the loop is a design recipe, not evidence.
Common questions
Does the Hook Model actually work?
Its parts have support from other settings, but the loop as a whole has not been tested. Fitbod, the case Eyal offers in the 2019 edition of Hooked, was built by founders who had read the book, so it shows the model being followed, not what it contributed.
Is the Hook Model backed by research?
It borrows from research: Ferster and Skinner's schedules of reinforcement (1957) and the IKEA effect, reported by Michael Norton and colleagues in 2012. The loop that joins them is Eyal's own framework, and each borrowed finding has conditions the loop does not state.
How can you tell whether a product has formed a habit?
Test whether use continues when the reward changes. Wendy Wood calls insensitivity to reward the gold standard, and in a 2011 cinema experiment led by David T. Neal, habitual popcorn eaters ate equal amounts of stale and fresh popcorn.
Sources
Eyal, N., with Hoover, R. (2019). Hooked: How to Build Habit-Forming Products. Penguin Business, updated edition; first published 2014 by Portfolio/Penguin. ISBN 978-0-241-18483-7.
Nunes, J. C., & Drèze, X. (2006). 'The endowed progress effect: how artificial advancement increases effort.' Journal of Consumer Research, 32(4), 504-512. doi:10.1086/500480.
Eyal, N., with Li, J. (2019). Indistractable: How to Control Your Attention and Choose Your Life. BenBella Books.
Fogg, B. J. (2009). 'A behavior model for persuasive design.' Proceedings of the 4th International Conference on Persuasive Technology, Article 40. doi:10.1145/1541948.1541999
Ferster, C. B., & Skinner, B. F. (1957). Schedules of Reinforcement. Appleton-Century-Crofts. doi:10.1037/10627-000
Shen, L., Fishbach, A., & Hsee, C. K. (2015). 'The Motivating-Uncertainty Effect: Uncertainty Increases Resource Investment in the Process of Reward Pursuit.' Journal of Consumer Research, 41(5), 1301-1315.
Shen, L., Hsee, C. K., & Talloen, J. H. (2019). 'The Fun and Function of Uncertainty: Uncertain Incentives Reinforce Repetition Decisions.' Journal of Consumer Research, 46(1), 69-81. doi:10.1093/jcr/ucy062
Norton, M. I., Mochon, D., & Ariely, D. (2012). 'The IKEA effect: When labor leads to love.' Journal of Consumer Psychology, 22(3), 453-460. doi:10.1016/j.jcps.2011.08.002
Neal, D. T., Wood, W., Wu, M., & Kurlander, D. (2011). 'The Pull of the Past: When Do Habits Persist Despite Conflict With Motives?' Personality and Social Psychology Bulletin, 37(11), 1428-1437.
Wood, W. (2019). Good Habits, Bad Habits: The Science of Making Positive Changes That Stick. Farrar, Straus and Giroux. Reward insensitivity quotation, p. 126.
Katikalapudi, R., Chellappan, S., Montgomery, F., Wunsch, D., & Lutzen, K. (2012). 'Associating Internet Usage with Depressive Behavior Among College Students.' IEEE Technology and Society Magazine, 31(4), 73-80. doi:10.1109/MTS.2012.2225462.
Wang, W., & Liu, Y. (2026). 'Wearable Fitness Product Design Strategies Based on Hook Model.' 2026 International Conference on Intelligent Engineering and Next-Gen Healthcare Systems (IEHNS), IEEE. doi:10.1109/IEHNS68708.2026.11606683.
Mariam, I., Ardita, A. R., Pratiwi, I. C., Nurdina, H., & Sofa, N. (2026). 'Analysis of Trigger and Action in the Hook Model on TikTok Content Virality: A Case Study of PT XYZ.' In AI Powered Control Systems in Fintech, Studies in Systems, Decision and Control, Springer Nature Switzerland, pp. 969-979. doi:10.1007/978-3-032-13119-5_82