Fogg behaviour model

BJ Fogg’s behaviour model (developed at Stanford’s Behaviour Design Lab) compresses the question “why didn’t they do the thing?” into three variables:

B = MAP

Behaviour = Motivation × Ability × Prompt

All three are needed simultaneously. If any one is zero, the behaviour doesn’t happen. Motivated and prompted but unable? No conversion. Able and prompted but not motivated? No conversion. Motivated and able but not prompted (at the right moment)? Still no conversion.

The model elegantly explains why CRO tests often fail without obvious reason. You raised motivation with better copy but the form is still too long (ability problem). You simplified the form (ability) but the CTA is buried below the fold (prompt problem). You moved the CTA up (prompt) but the visitor doesn’t yet care about your offer (motivation problem).

What each variable looks like in CRO

• Motivation - how much the visitor wants the outcome. Driven by the offer, the framing, the perceived value, the urgency. Highest leverage point but slowest to move.
• Ability - how easy it is to do the thing. Form length, page speed, friction, complexity of the decision. Easiest to fix and often the cheapest test.
• Prompt - whether the call to action is in front of them at the right moment. Button placement, exit-intent triggers, lifecycle email timing, retargeting frequency.

The high-leverage move depends on which is the bottleneck. If your visitors are bouncing without engagement, motivation is the problem. If they’re engaging but not converting, ability is. If they’re reading the whole page but not clicking, prompt is.

Why “make it simpler” is usually the right first test

Of the three, ability is the cheapest to move. Cutting form fields, removing friction, simplifying the decision - these are mechanical changes with predictable lift. Motivation work is creative and harder to test. Prompt is usually a second-order effect (you can’t prompt someone with no motivation).

So the standard CRO sequence is: simplify (ability), then strengthen (motivation), then refine prompts. Most programmes that “plateau” have hit the ceiling on ability and need to start working on motivation, but the team keeps shipping more friction-reduction tests because that’s what they know how to test.

Things people get wrong

• Only ever testing ability. Friction-reduction tests are addictive because they reliably win small, but they hit a ceiling and don’t move average conversion as far as motivation work does.
• Testing motivation without enough sample size. Motivation changes (copy, value props, framing) tend to interact strongly with traffic temperature and segment, which means more variance and more sample needed.
• Treating prompts as the whole problem. “Move the button” tests are sometimes right but the underlying issue is usually motivation or ability further up.
• Confusing the model with funnel mechanics. Fogg is about the individual decision, not the funnel. You can apply it at every step.