In 19 days, we build a working intervention. Grounded in psychology, iterated with synthetic participants, and validated with real people.
«The best way to predict the future is to invent it.» — Alan KayPitch deck (5 slides)
Fast and low-cost: test, compare, and refine ideas, messages, and hypotheses.
Convincing approaches, we validate with real people.
Understanding people takes time. Good decisions shouldn't. That's why we combine artificial intelligence, behavioral psychology, and strategy. With synthetic users, we can test, compare, and refine ideas, messages, and behavioral hypotheses quickly and at low financial cost. Convincing approaches, we validate with real people.
The result: solutions that come together faster, reduce risk, and work in practice.
To recruit real people as fast as possible, we've partnered with TestingTime. That gets us reliable feedback from real people, quickly.
Who is your audience? What do we already know, and what do we still need to learn?
Which behavior do we want to change, and who exactly is the audience?
Compress prior research about the audience and surface blind spots.
Identify motivators and barriers along the user journey.
Play through touchpoints, motivators, and barriers end-to-end.
First ideas turn into prototypes and improve over multiple iterations.
We strengthen intrinsic motivation with targeted mechanics.
First ideas turn into prototypes and improve over multiple test loops.
The most convincing approaches get validated with real people.
For each approach, we check impact, risk, and implementation effort.
Together we prioritise the rollout and hand over the prototype.
What did we observe, confirm, or reject, we sort it out together.
Map out requirements, resources, and internal ownership.
Together with you, we surface what's still open.
Next steps, owners, and timeline.
We want everyone to attend cancer screening on time.
We want our customers to buy more organic products.
We want men to engage with mental health.
We want more people to invest their savings sustainably.
We want older people to use digital services.
We want short car trips replaced by climate-friendly alternatives.
We want a higher share of generics in prescriptions.
We want tenants to consume energy more consciously.
We want more people to donate blood regularly.
It depends on several factors: is the product digital or physical? How large is the audience? How hard is the problem? Realistically, sprints start at CHF 50,000 incl. VAT.
PhD in cognitive psychology; led UX research at the EPFL+ECAL Lab. Author of about a dozen peer-reviewed studies and creator of SBB's award-winning experience app.
Project manager for customer experience and insights at SBB, visiting researcher at UC Berkeley, and keynote speaker on putting people at the center of the AI shift. Her toolkit spans eye-tracking, behavioral data, and co-design.
Founder of The Behavior Lab GmbH for applied behavioral research. Former UN representative in Geneva for the psychology associations APA, EFPA, and FSP.
Co-founder and vice-president of the Behavior Change Network Switzerland, and former lecturer in customer and economic psychology at Lucerne University of Applied Sciences and Kalaidos University of Applied Sciences.
Award-winning serial entrepreneur. Computer scientist ETH Zurich, ex–Xerox PARC, ex-Siemens Corporate Technology.
More than forty shipped titles for museums, brands, public squares, and broadcast TV. MSc from ETH Zurich, lecturer at HWZ, and jury president of Best of Swiss Apps. Today he works as advisor, product designer, and implementer.
A 19-day work format that takes a behavior-change intervention from question to roadmap. We ground the work in behavioral science, test first in a protected environment, and validate with real people.
Instead of a months-long programme, we compress it into a focused 19-day sprint: understand the behavior, prototype and test interventions with real people, and hand over a rollout-ready roadmap. You get tested direction in three weeks, not three quarters.
19 days is short enough to keep momentum, long enough to cleanly separate understanding, prototyping, and validation, three phases of 5, 11, and 3 days.
We strengthen the motivators that pull people toward the goal and remove the barriers in their way, then prove it with real-user tests before rollout. That combination shifts behavior more reliably than adding another feature or message.
A solution tested with real users, shown to be technically feasible, and stakeholder-ready internally, set for rollout. Concretely: tested prototypes, audience insight reports, and a clear implementation plan with owners.
From CHF 50,000 incl. VAT. The exact price depends on product, audience size, and complexity.
We translate the goal into one concrete behavior and audience, design interventions grounded in behavioral psychology, and lock a primary behavioral KPI on day one, so progress is measured by what people actually do, not by self-report.
Health, finance, energy, mobility, public sector, retail, and insurance. It fits wherever outcomes hinge on behavior, not just another feature.
Design Sprints focus on product solutions. We focus on behavior change, with behavioral science, synthetic testing, and a roadmap rather than a hi-fi mockup.
No. Gamification is one tool of many. We pick from nudges, defaults, commitment devices, social proof, and game mechanics depending on audience and behavior.
We build LLM-based personas conditioned on research data and demographics. They act as a first-pass filter for prototypes, surfacing logic gaps and saving real testers' time.
No. They help us sort quickly. We validate every recommended solution with real humans. Real people have the final word.
Yes. AI-assisted workflows coordinate synthetic personas, prototype generation, test analysis, and reporting in parallel. That shortens learning cycles.
Via observable behavior: conversion, click-through, adherence, actual usage. Self-reports complement but never replace behavior.
Drive that comes from within, autonomy, competence, purpose. Solutions that tap intrinsic motivation outlast external rewards.
We don't deliver a pretty shell. We deliver tested behavior change. Design is the means, not the goal.
You do. All deliverables, prototypes, and roadmaps transfer to the client.
We stand for methodological quality, clear tests, and useful learning. We do not promise exact KPI lifts because serious impact measurement depends on context.
A 90-minute clarity workshop: sharpen the behavioral goal, focus the audience, define success metrics. Then we start with personas and data.
Yes, with independent teams. We deliberately share learnings across sprints.
Ideally to existing research, analytics, and CRM insights, anonymised is often enough. Confidentiality is standard.
UX research surfaces problems. We solve them behavior-first, prototyped, and prioritised. The result is an executable roadmap.
Yes. B2B buying behavior is often as emotional and time-constrained as B2C, with extra stakeholder dynamics we model explicitly.
Yes. Mass behavior can be modelled up front with synthetic personas and checked with real-user tests.
Absolutely. Internal knowledge accelerates every sprint. We recommend a sponsor and an insights owner from your side.
Locked on day 1: one primary behavioral KPI, one or two driver KPIs, and a guardrail metric against unwanted effects.
We narrow it. One sprint tackles one clearly defined behavior in one clearly defined situation. Big themes become multiple sprints.
Yes. It combines published findings from behavioral economics, social psychology, HCI, and gamification with empirical on-site testing.
AI speeds up research, persona construction, prototype generation, and analysis, but it replaces neither domain expertise nor real-user tests.
No. Where humans are better, empathy, ethical judgment, stakeholder relationships, humans stay at the helm.
We follow a pro-autonomy stance: solutions must benefit the person, be transparent, and preserve choice. Dark patterns are off-limits.
Yes, at rollout. Inside the sprint we use qualitative tests and small quantitative samples for faster learning.
We design for long-term effects via intrinsic motivation and habit loops, and recommend measurement setups that track effects over months.
Yes, for example health, finance, and pharma. We involve compliance and legal teams during the sprint, not only at the end.
Yes. Your research data stays in Switzerland by default; AI inference is available via EU/CH endpoints.
A solution validated with real users, technically feasible, and internally decision-ready. It is ready for the next rollout step.
Design Thinking is a mindset, we're a format. The two are compatible, we add science, speed, and tests.
Concrete points of contact between a person and an offer, push notification, letter, website, conversation. Each touchpoint is a behavior-change lever.
Motivators pull people toward a goal. Barriers hold them back. Impact comes from boosting motivators and reducing barriers, usually both.
Yes, cue, routine, reward. But only for pro-social applications. We reject manipulative hooks.
You decide the next step. We optionally offer measurement setups, coaching, and follow-up sprints for scaling.
We plan every sprint to produce at least three testable interventions and an executable roadmap. KPI lifts are measured after rollout.
Within two weeks of briefing, as soon as NDA, brief, and data access are in place.
A time-boxed work format with clear goals, fixed phases, and a concrete output.
A testable version of the solution. It does not need to be final, but it shows whether the approach holds.
AI-assisted personas that simulate first reactions. They do not replace tests with real people.
A metric for observable behavior, such as signup, usage, purchase, or return.
A small change to the decision context that makes helpful behavior more likely while preserving choice.
Early learning in a test environment before effort and risk rise in the real market.
