Fogg behavior model
Also known as: B=MAP, B=MAT
Behavior happens when Motivation, Ability, and a Prompt converge at once.
What it means
The Fogg Behavior Model states that a behavior occurs only when three elements come together at the same moment: sufficient Motivation, adequate Ability (the ease of doing it), and a Prompt that triggers the action — summarized as B = MAP. The mechanism is captured by an action line: motivation and ability trade off against each other, so a behavior that is very easy requires little motivation while a hard behavior requires a great deal, and a prompt succeeds only when the person is above that threshold at the instant it arrives. A central practical implication follows from this trade-off: because motivation is unreliable and hard to raise, it is usually more effective to increase ability by making the behavior simpler than to try to pump up motivation. The model also classifies prompts — sparks for the unmotivated, facilitators for those who lack ability, and signals for those already able and motivated — so that the right kind of trigger is matched to the situation. It matters in product design, habit formation, and persuasive technology, where diagnosing which of the three elements is missing tells the designer exactly where to intervene.
How it works
At the center of the model is a geometric claim. Plot how motivated a person is against how easy an action is for them, and a curved action line, or activation threshold, separates the situations where a prompt will trigger the behavior from those where the same prompt fails. Because the line curves rather than running straight, the two inputs trade off against each other: a very easy action can be triggered at low motivation, while a demanding one needs high motivation before any prompt will work. All three inputs must coincide in a single moment, or nothing happens. Fogg then sorts prompts by which input is scarce. A spark carries a motivational element for someone able but unmotivated; a facilitator reduces effort for someone motivated but unable; and a signal is a bare reminder for someone already above the line on both counts. Much of the framework's appeal is diagnostic. When a wanted behavior does not occur, it points to whichever of the three elements is missing rather than to the actor's character or willpower, which turns a vague complaint about low engagement into a specific design question.
Origins and formulation
The model comes out of Fogg's work at Stanford, where in the late 1990s he founded what became the Persuasive Technology Lab, later the Behavior Design Lab, to study how computers influence attitudes and actions. His 2003 book Persuasive Technology set out the broader field of captology, the design of computing products intended to change behavior. The behavior model itself was formalized in a short paper at the 2009 Persuasive Technology conference, presented as a practical framework for designers rather than as a tested theory. In its original wording the three factors were motivation, ability, and triggers, giving the mnemonic B = MAT. Fogg later standardized the third term as prompt, partly because trigger carried unwanted connotations, producing the now-common B = MAP; the relabeled version anchors his 2019 trade book Tiny Habits, which applies the model to personal habit formation through very small actions attached to existing routines. It is worth being clear about what kind of object this is. The 2009 paper introduces the model by argument and illustration, not by experiment, and much of its influence has flowed through design practice and popular writing rather than through a program of hypothesis testing.
What the evidence shows
Because the model is a design heuristic, the useful question is less whether B = MAP has been confirmed as a law and more how well interventions built on it perform, and whether its specific claims, above all the motivation-ability trade-off, have been tested directly. On the second point the record is thin: the action line is a helpful picture, but it has not been calibrated or falsified in controlled work, and the model offers no units in which motivation or ability could be measured. On the first point the evidence is genuinely sparse. A 2025 scoping review in BMC Public Health searched several major databases for health interventions applying the model and found only six studies meeting its criteria, spanning reproductive health, vaccination, chronic-disease self-management, general wellness and adherence. Those studies reported positive results, for instance an antenatal weight-management program that reported lower rates of gestational diabetes and a vaccination intervention that reported higher stated intent, but they are few, heterogeneous, mostly short-term, and typically lack long follow-up. Crucially, they test whole programs designed with the model, not the model's mechanism, so a good outcome cannot separate the framework from the many other choices baked into each intervention. The individual ingredients rest on firmer independent ground: reducing friction reliably raises follow-through, well-timed cues change behavior, and motivation influences action. The model's contribution is to organize these known levers, and the reviewers note it remains underused and under-tested in public-health research.
Using it in practice
In application the model is run as a checklist against a specific behavior at a specific moment. First name the behavior precisely; then ask whether the person is motivated, whether the action is easy enough, and whether anything prompts it. The standard counsel is to suspect ability first. Motivation fluctuates, Fogg describes a motivation wave that crests and falls, and it is costly and unreliable to raise, so making the action smaller and easier is usually a more dependable lever than exhortation. That is the logic behind shrinking a behavior to something that can be done in seconds, and behind attaching a new prompt to an existing routine so the cue is already reliably present. The prompt taxonomy tells designers what kind of trigger to send: a reminder is wasted on someone who lacks the ability to comply, where a facilitator is needed, and a motivational push annoys someone who was already going to act, where a plain signal would do. The same lens works as a post-mortem. When a funnel leaks or a habit fails to stick, the model asks which element was absent at the decisive moment, which tends to yield a concrete fix, such as removing a step, changing the timing, or lowering the effort, rather than a general resolution to try harder. Its limitation as a tool mirrors its simplicity: it says little about where motivation comes from, about social and environmental opportunity, or about sustaining a behavior once prompted.
Related but distinct
The Fogg model is one of several frameworks that decompose behavior, and it is easy to conflate them. The COM-B model and its Behaviour Change Wheel, from Susan Michie and colleagues, also place capability and motivation at the center but add opportunity, the social and physical environment, as a separate necessary condition, which the Fogg model largely folds into ability; COM-B grew out of an effort to synthesize many intervention theories and is the more academic instrument. Persuasive Systems Design, from Harri Oinas-Kukkonen and Marja Harjumaa, overlaps in spirit but catalogues software features that persuade rather than positing a threshold for action. Nudge approaches share the emphasis on making the desired option easier, but work mainly through how choices are arranged, often without any explicit prompt. And the cue-routine-reward habit loop describes how a repeated behavior becomes automatic over time, whereas the Fogg model describes a single instance of action; the two are complementary, since Fogg's prescription for building habits is to engineer easy, well-prompted single actions until they consolidate. Kept apart, each answers a different question; blurred together, they invite the mistake of treating the tidy Fogg diagram as if it were the whole science of behavior.
Examples
A well-timed notification (prompt) succeeds only if the action is easy enough and the person cares enough.
A media app wants a willing but lapsed user to return. The model treats this as a signal problem, not a motivation one: a well-timed reminder at a moment the person is free lands above the threshold, whereas a heartfelt motivational message aimed at someone who had already decided to come back mostly wastes the opportunity.
An online tax-filing service sees users drop out midway. They intend to finish but the form is long, so the scarce element is ability rather than motivation; auto-filling known fields and cutting the number of screens lifts completion far more than adding another reminder would.
A pharmacy wants patients to take a daily medication. Rather than rely on push notifications, it turns the prompt into a physical anchor by placing the pill organizer beside the morning coffee maker, so an already-motivated, already-able patient meets a reliable cue inside a routine that happens every day.
A subscription service has customers who could upgrade in two clicks but feel no urgency to. Here the scarce input is motivation, so a spark, a clearly time-limited framing shown at the point of decision, raises momentary motivation just enough to carry the easy action over the line.
First described in B. J. Fogg (Stanford).
Key references
- Fogg, B. J. (2009). A behavior model for persuasive design. In Proceedings of the 4th International Conference on Persuasive Technology (Persuasive '09) (Article 40, pp. 1-7). Association for Computing Machinery. doi.org/10.1145/1541948.1541999
- Fogg, B. J. (2003). Persuasive technology: Using computers to change what we think and do. Morgan Kaufmann. openlibrary.org/books/OL8606524M/Persuasive_Technology
- Fogg, B. J. (2019). Tiny habits: The small changes that change everything. Houghton Mifflin Harcourt. openlibrary.org/books/OL27906569M/Tiny_Habits
- Duarte-Anselmi, G., Crane, S. M., Armayones Ruiz, M., & Villalobos Dintrans, P. (2025). Behavioral science meets public health: A scoping review of the Fogg behavior model in behavior change interventions. BMC Public Health, 25, Article 3468. doi.org/10.1186/s12889-025-24525-y
- Michie, S., van Stralen, M. M., & West, R. (2011). The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science, 6, Article 42. doi.org/10.1186/1748-5908-6-42
- Oinas-Kukkonen, H., & Harjumaa, M. (2009). Persuasive systems design: Key issues, process model, and system features. Communications of the Association for Information Systems, 24, Article 28. doi.org/10.17705/1CAIS.02428