Context
Our client, a leading French mutualist insurer, was observing a significant gap between the traffic driven to its online quote journey and the final transformation rate. Classic UX optimisations (speed, responsive design, form simplification, step reduction) had been executed with discipline and were no longer moving the needle on conversion.
The problem
Classic UX optimises navigation fluidity, not decision fluidity. Yet an auto insurance subscription journey is not measured in clicks or seconds, it is measured in decision load. Visitors do not drop off because a form is long: they drop off because at a specific moment, the cognitive effort required exceeds their motivation to continue.
Three biases are systematically underestimated by standard UX audits: cognitive load at the pricing decision (the visitor has no reference to judge whether 600 € is expensive or not), distrust when the amount is revealed (which triggers an alternative search rather than a subscription), and the peak-end effect (final satisfaction depends less on journey length than on emotional peak and ending).
Our approach
Behavioural audit of two journeys (mobile and desktop), conducted by a consultant using Krakn's 9-category friction grid. Each screen assessed on nine dimensions, frictions scored on intensity (1 to 5) and criticality (estimated impact on conversion).
Analysis through the peak-end rule (Kahneman, Fredrickson, Schreiber & Redelmeier 1993). Identification of the two most decisive moments for memory and decision: the emotional peak (usually the moment the price is revealed) and the end of the journey (usually the recap before validation). Verification that these two moments are designed specifically, not merely averaged with the rest.
Activation of social proof (Cialdini 1984, 2001) on screens with high decision load, at moments where the visitor is looking for an external signal to validate their choice.
Prioritisation of recommendations by estimated impact on conversion. Recommendations classified in three waves (high impact / low effort, high impact / high effort, medium impact / variable effort).
Results
Post-optimisation user test:
- 98% of users rated the journey clear (4-5 out of 5)
- 82% expressed intent to subscribe
- Ergonomics score: +2.17 points
- Trust score: +2.44 points
- Product interest score: +1.83 points
The strongest gain is on trust, which validates the initial diagnostic: the problem was not ergonomics, it was decision load at the pricing moment.
What this case illustrates
A subscription journey is not measured in clicks, it is measured in decision load. Reducing the number of steps improves completion rate without necessarily improving transformation. Those are two different KPIs answering two different logics: completion follows ergonomic fluidity, transformation follows decision fluidity.
The peak-end rule predicts that final satisfaction is driven by two moments only: the emotional peak and the ending. A journey designed to be evenly average will underperform a journey strategically intense on those two moments.
Frameworks used
System 1 / System 2 (Kahneman 2011), peak-end rule (Kahneman et al. 1993), social proof (Cialdini), choice architecture (Thaler & Sunstein 2008), cognitive load. See the glossary.
Frequently asked questions
What is the difference between a UX audit and a behavioural audit?
A UX audit assesses navigation fluidity: number of clicks, speed, visual clarity, accessibility. A behavioural audit assesses decision fluidity: cognitive load, psychological frictions, biases activated on each screen, memorability. UX audits optimise completion. Behavioural audits optimise transformation. On a mature journey, UX gains are marginal and behavioural gains can be significant.
How does Krakn assess frictions on a digital insurance journey?
Through a nine-category friction grid (cognitive, emotional, social, ergonomic, decisional, contextual, motivational, memory-related, identity-related) applied screen by screen. Each friction is scored on intensity and criticality, then prioritised by estimated impact on conversion.
What is the peak-end rule applied to a subscription journey?
The peak-end rule (Kahneman et al. 1993) shows that memory of an experience is mostly shaped by two moments: its emotional peak and its end. Final satisfaction depends less on the average quality of the journey than on the quality of these two specific moments. The operational consequence is that these two moments require dedicated design, not uniformly distributed effort.
How many friction categories does Krakn use for its audit?
Nine: cognitive, emotional, social, ergonomic, decisional, contextual, motivational, memory-related, identity-related. This grid covers the full psychological spectrum of the visitor, whereas classic UX grids focus only on ergonomic and cognitive dimensions.
Which channels were audited?
Mobile and desktop. Both channels activate partially different cognitive biases (memory load is stronger on mobile, decision load is stronger on desktop), and a rigorous behavioural audit cannot rely on only one of them. Want to audit your digital journey through a behavioural lens? Let's talk →