Behavioral analytics for e-commerce that explains the why.
Who built this
Frictionless is built by Enrico Böker, a behavioral psychologist with a B.Sc. in Wirtschaftspsychologie from FHM Bielefeld. The framework extends academic research on consumer decision-making into a practical diagnostic tool for e-commerce stores.
Public research identity: ORCID 0009-0008-9991-1117.
The mission
Most e-commerce dashboards measure outputs (sessions, conversion-rate, AOV). None of them measure the cognitive frictions that produced those outputs in the first place. Frictionless reverses the lens: instead of describing what happened, it diagnoses the psychological mechanism that caused it. Loss aversion. Decision paralysis. Trust deficit. Value ambiguity. Mobile friction. Urgency absence. Cognitive overload.
The research foundation
- Daniel Kahneman — Loss aversion, dual-process theory, anchoring. From Thinking, Fast and Slow and Kahneman & Tversky 1979.
- Robert Cialdini — Social proof, scarcity, authority. From Influence (1984) and follow-on research.
- Barry Schwartz — Paradox of choice, decision paralysis. From The Paradox of Choice (2004).
- Don Norman — Affordances, signifiers, error tolerance. From The Design of Everyday Things (1988).
- Baymard Institute — Two decades of empirical e-commerce UX research, particularly checkout-flow studies.
- John Sweller — Cognitive load theory (1988); applied to form complexity and information density.
- Carl Hovland — Source credibility (1953); applied to trust signals and badge legitimacy.
The methodology
Every Frictionless analysis is a 60-second static + behavioral scan that runs 23 deterministic pattern detectors across 7 WHY-categories. The same store always produces the same score. No machine-learning black-box; every signal is auditable.
- Live behavioral pixel (cookieless) for ongoing data on installed stores
- Continuously benchmarked across 83+ stores (and growing)
- Technical detail: /developers
- Live data: /benchmarks
- Framework reference: /blog/23-friction-patterns-framework
Academic foundation
The FIMaC model (FOMO-Induced Model of Affect-Driven Consumption Behaviour), developed during the founder's B.Sc. thesis at FHM Bielefeld, serves as the theoretical foundation for the affect/urgency layer of the framework.
Contact
Further reading
- The 23 Friction Patterns Framework — research citations + per-category prevalence (Kahneman, Cialdini, Schwartz, Norman, Baymard).
- The Forced Account Creation Study — 88% of 83 stores fail this, including Patagonia, Dr. Martens, Allbirds.
- The 50ms rule of first-impression conversion — why pre-conscious judgment dominates trust.
- Why DACH e-commerce stores fail at checkout — region-specific friction patterns.
- Programmatic access: /developers — API + bookmarklet + pixel-snippet documentation.
- Live data: /benchmarks — score distribution + pattern prevalence across the dataset.