Every behaviour — clicking a button, starting a workout, upgrading a plan — requires three things to be present simultaneously: the person must want to do it, they must be able to do it, and something must prompt them to do it right now. Remove any one of the three and the behaviour does not happen. This is the entire model.
In 2007, BJ Fogg — a professor at Stanford's Persuasive Technology Lab — published a simple equation that would become one of the most practically useful models in product design. Behaviour happens, he argued, when three elements converge at the same moment: Motivation, Ability, and a Prompt. His formula: B = MAP. When all three are present at the right levels, the behaviour occurs. When any one is absent or insufficient, it does not — regardless of how strong the others are.
The insight that makes the model powerful is its specificity about failure. Most products fail to produce behaviours not because users lack motivation — the vast majority of people who sign up for a fitness app genuinely want to exercise — but because the ability cost is too high at the moment of the prompt, or the prompt arrives when motivation is at its lowest, or there is no prompt at all.
Fogg's most important practical insight was about the relationship between motivation and ability. These two elements trade off against each other. A behaviour with very high ability can happen even with low motivation. A behaviour with very high motivation can happen even when it requires significant ability. If you cannot increase motivation, decrease the effort required. If the effort is unavoidable, wait to prompt until motivation is high.
“Motivation is overrated. Make the behaviour easier to do and you will get more of it.”
— BJ Fogg, Tiny Habits, 2019
The Fogg model is most useful as a diagnostic lens on specific design decisions. Not “why aren't users engaging?” but “which of the three elements is the constraint in this specific screen, for this specific user, at this specific moment?” The three patterns below show how the same model produces different interventions depending on which element is failing.
The user genuinely wants to upgrade. But the interface forces them to compare three plans, read feature tables, enter card details, and confirm billing. The motivation is there. The ability cost destroys the conversion. Same user — second version collapses the entire flow into a single confirmed action.
Three plans, fifteen feature rows, then full card details. Each step bleeds motivation. Most users who reached this page with genuine intent will not complete it.
One decision. One click. Saved card means no data entry. The plan was pre-selected. Ability cost approaches zero — the behaviour fires.
Same user. Same review request. Same two-minute ask. One arrives seven days after purchase when the product has become routine and the satisfaction peak has passed. The other arrives at the exact moment the user just completed their first successful outcome — when motivation is highest.
Hi there, it has been a week since you signed up. We hope you are enjoying the experience. Could you take 2 minutes to leave us a review?
Sent 7 days after signup. The product is now routine. Motivation: low. The prompt is a stranger asking for a favour.
Delivered at the exact moment of first success. Motivation: high. The ask is 30 seconds, not 2 minutes.
When you cannot raise motivation and the ability cost is high, Fogg's prescription is counterintuitive: do not optimise the experience, shrink the behaviour. Ask for less. A user who completes one small action has committed. A user who abandoned a large one has not.
Five tasks, 22 minutes, none deliver any value. All asked of someone who has not yet decided whether the product is worth their time.
Product delivered value first. Then asked for one thing, specific to what the user is already doing — 20 seconds.
Duolingo is one of the most studied examples of the Fogg model applied to a consumer product. The target behaviour is deceptively simple: open the app and do one lesson today. But this behaviour has to happen every day for habit formation to occur — which means motivation, ability, and a prompt all need to be calibrated for the realistic version of the user, not the aspirational one.
The two notification screens below show the same re-engagement prompt for a user who has missed two days of practice. One applies the Fogg model correctly. One does not.
Shame-based message. Asks for a 'full lesson set.' High ability cost, low motivation restored. Below the action line.
Tiny ask (5 minutes), loss-aversion motivation (47-day streak), sent at the user's usual lesson time. Above the action line.
Duolingo's actual notification strategy is built explicitly around minimising ability cost. The canonical prompt does not ask for language learning — it asks for five minutes. It does not ask for a lesson set — it asks for one short exercise. The behaviour being prompted is not “make progress on your language goal” but “open the app once today.” The motivation lever is the streak — a number that activates loss aversion and creates a specific, immediate reason to act.
This is the Fogg model applied correctly: when you cannot guarantee high motivation, you reduce the ability cost until the behaviour is achievable at moderate motivation. A 5-minute lesson is achievable at 6pm on a bad day. A full lesson set is not.
The Fogg model turns conversion and engagement problems into diagnosis problems. When a behaviour is not happening at the rate you need, the question is not “how do we make users want this more?” It is “which of the three elements is the limiting factor?” Increasing motivation when ability is the real constraint wastes effort. Adding prompts when neither motivation nor ability is sufficient just creates noise.
Fogg's most actionable prescription — the one most consistently ignored by product teams — is to shrink the behaviour before trying to increase motivation. A user who takes one small action is more likely to take the next one than a user who intended to take a large action and did not.
Fogg, B. J. (2009). A behavior model for persuasive design. Proceedings of the 4th International Conference on Persuasive Technology. ACM. · Fogg, B. J. (2019). Tiny Habits: The Small Changes That Change Everything. Houghton Mifflin Harcourt. · Fogg, B. J. (2003). Persuasive Technology: Using Computers to Change What We Think and Do. Morgan Kaufmann.