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Digital Health
Digital health engagement tends to peak early and fade quietly. We help digital health companies understand why users drift, design products that support lasting self-management and define predictive KPIs that connect daily behavior to clinical and commercial outcomes.
The people side of digital health.
Digital health products promise continuous support for conditions that unfold over years: diabetes, hypertension, heart disease, chronic pain, depression and anxiety. The pattern most teams know well is engagement decay. Users enroll with real motivation, log readings and complete lessons for a few weeks, then open the app less often until they stop. The product has not failed technically. It has asked people to sustain a new behavior without enough attention to ability, timing and meaning in the context of their lives.
Inside the company, product, clinical, data science and commercial teams often hold different definitions of success. Clinicians care about outcomes and safety, product teams track active users and feature use, and sales teams need evidence that employers, health plans and providers will accept. Without shared, behavior-based KPIs, teams optimize for different signals, and the engagement metrics that look healthy on dashboards may have little relationship to whether members actually manage their condition better.
The market has matured. Buyers now expect evidence of sustained use and measurable health improvement, not download counts. Integration with care teams, remote monitoring devices and payer workflows adds complexity. AI coaching and personalization create new possibilities and new ethical questions about persuasion. Companies that understand digital health engagement as a behavioral science problem, and measure it accordingly, are better positioned to retain members, earn clinical trust and demonstrate value to the organizations that pay for them.
What leaders are up against.
Engagement decay after the first weeks
Early enthusiasm carries new users through onboarding, then real life intervenes. Notifications become noise, logging feels like a chore and progress stalls. Teams often respond with more content or more reminders, which can accelerate disengagement. The underlying question, which behaviors predict who will persist, usually goes unanswered because the data has not been examined through a behavioral lens.
Self-management that does not fit daily life
Chronic illness self-management asks people to monitor, adjust medication, change diet and stay active, often while managing work, family and fatigue. Products designed around an ideal user overlook the routines and constraints of real patients. When the recommended behavior is too hard or poorly timed, even motivated members fall away and blame themselves.
Vanity metrics that buyers do not trust
Daily active users, session counts and content completion are easy to report and hard to connect with health outcomes. Employers, health plans and provider partners increasingly ask for evidence that engagement translates into better control of a condition. Without predictive KPIs that link behavior to outcomes, renewal conversations rely on narrative rather than proof.
Onboarding that loses people before value appears
Many digital health products ask for device pairing, health history, goals and permissions before members experience any benefit. Each step is a chance to drop off. Onboarding often reflects internal requirements instead of the user's first meaningful win, which means the people who most need support may never reach it.
Persuasion without clear ethical boundaries
Streaks, rewards, social features and AI coaches can motivate healthy behavior, but they can also create pressure, guilt or dependence. Digital health teams need principles for when persuasion supports a person's own goals and when it crosses into manipulation, especially for vulnerable populations living with serious or stigmatized conditions.
Where we focus.
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Engagement signals and behavioral types
We analyze product event data alongside clinical and enrollment data to find the early behaviors that predict persistence and the points where members drift. Behavioral segmentation then groups users by how they engage, not by demographics, so teams can design different pathways for the people who need structure, those who need flexibility and those who need human contact.
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Self-management product design
Drawing on clinical health psychology and behavioral medicine, we redesign core routines such as logging, medication tracking and activity goals so they fit real lives. That means smaller starting behaviors, better anchoring to existing habits and prompts that arrive when a person can act. Each change is framed as a testable hypothesis rather than a feature request.
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Onboarding and first-value design
We map onboarding step by step, measure where members leave and redesign the sequence around a first meaningful win, such as a useful insight from a first reading. Usability testing with representative patients surfaces confusion early, and A/B tests confirm which changes improve activation without sacrificing data quality or clinical safety.
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Outcome-linked predictive KPIs
We help product, clinical and commercial teams agree on a small set of behavior-based KPIs that predict health outcomes and renewal. These measures give leaders an earlier, more credible view of program performance and give buyers evidence they can evaluate. Dashboards make the measures usable in weekly decisions rather than quarterly reports.
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Ethical persuasive technology review
We review engagement mechanics, messaging and AI coaching behavior against principles from persuasive technology and self-determination theory. The review identifies features that support autonomy and competence and flags those that may create pressure or shame. Teams leave with practical design standards they can apply to future features and experiments.
The social good at stake.
Digital health can extend support to people who live far from specialists, cannot take time off for frequent visits or feel stigma about seeking care. That promise is realized only if people keep using the product long enough for it to help. Behavioral science advances the mission by designing for real lives, sustaining engagement through meaning and competence rather than pressure, and measuring whether daily behavior actually improves health. It also keeps persuasion honest, ensuring that technology helps people pursue their own goals for managing chronic illness with dignity.
Frequently asked questions.
Why does digital health engagement drop off, and can it be prevented?
Drop-off usually reflects a mismatch between what the product asks and what people can sustain in their daily lives. Some decline is natural as members build routines, so the goal is not constant use but the right behaviors at the right frequency. We identify which early behaviors predict persistence and design pathways that support them. No approach eliminates attrition, but it can be understood, measured and reduced through testing.
Do you work with clinical teams as well as product teams?
Yes. Our roots are in clinical and health psychology and behavioral medicine, so we are comfortable working with medical directors, clinical researchers and care coaches alongside product managers, designers and data scientists. Much of the value comes from aligning these groups on shared, behavior-based measures of success that respect clinical evidence and product realities.
Can behavioral science help us show value to employers and health plans?
It can help you build a more credible case. We define predictive KPIs that link member behavior to health outcomes and design experiments that isolate the effect of specific product features. That evidence supports renewal and sales conversations with buyers who want more than engagement counts. We do not promise particular outcomes, but we help you measure them rigorously.
Relevant services.
Digital Health Product Design
Behavioral and experience design for digital health products, focused on sustained engagement, usability for real patients and evidence of behavior change.
ExploreHealth Behavior Change Design
Evidence-based health behavior change design for programs, products and services that help people start and sustain healthier routines.
ExploreOnboarding & Activation Design
Find the early activation moments that predict long-term retention, then redesign the first experience so new customers, members and users reach value quickly.
ExploreBehavioral Segmentation
Group customers, users, members and patients by how they actually behave, so every journey, message and service moment fits the people it is meant to reach.
ExplorePersuasive Technology Design
Design apps and digital experiences that help people build habits and reach their own goals, with transparent prompts, ethical review and rigorous testing.
ExplorePredictive KPI Design
Replace lagging and vanity metrics with behavior-based leading indicators that forecast results and give teams something they can actually influence.
ExploreFurther reading.
Habit Formation for Products and Organizations
How habits form, why they matter for products and organizations, and how to design cues, routines and contexts that help valuable behaviors persist over time.
Read
The Ethics of Persuasive Technology
Where persuasion ends and manipulation begins in digital products and services, and practical principles for designing behavior change that respects people's interests and autonomy.
ReadLet’s talk about the people problem in front of you.
Every engagement begins with a conversation. Tell us what you are facing and we will tell you, candidly, how we would approach it.
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