Sahha has launched Archetypes — a new product that transforms passively collected health and lifestyle data into dynamic behavioral profiles for each user.
Where health scores describe the current state (“your sleep quality is 72”), and biomarkers describe the physiological signal (“your resting heart rate is 58 bpm”), Archetypes describe the person. Who is this user? Are they a night owl or an early riser? Do they exercise consistently or in bursts? Do they favor strength training or outdoor cardio? Are their sleep patterns stable or erratic?
These aren’t self-reported labels. They’re computed from observed behavioral data — continuously updated as patterns evolve.
Why behavioral profiling matters for health apps
Most health and fitness apps know surprisingly little about who their users are in behavioral terms. They know age, gender, and perhaps a few onboarding survey responses. But the behaviors that drive engagement, retention, and health outcomes — sleep timing, activity rhythm, exercise preferences, recovery patterns — are inferred poorly or not at all.
This gap creates a one-size-fits-all problem. A morning workout recommendation sent to a consistent night owl isn’t just unhelpful — it signals that the app doesn’t understand the user. A recovery protocol designed for endurance athletes misses the mark for someone whose primary activity is weekend hiking.
The traditional solution is onboarding surveys. But self-reported behavioral data is unreliable, static, and creates friction. People overestimate their exercise frequency, misidentify their sleep patterns, and don’t update their preferences as habits change.
Archetypes solve this by deriving behavioral profiles from what users actually do — passively, continuously, and without asking.
How Archetypes work
Archetypes are computed from the same passive data Sahha already collects through its SDK: sleep events, activity data, step patterns, exercise sessions, and device usage signals from smartphones and wearables.
The system identifies recurring patterns across multiple behavioral dimensions and classifies users into archetype categories that reflect their actual habits. These classifications are dynamic — a user who shifts from irregular sleep to a consistent early-riser pattern will see their Archetype update accordingly.
Sleep Patterns
The Sleep Patterns archetype captures overall sleep behavior as a composite of timing, duration, consistency, and quality signals. It provides a high-level characterization of how someone sleeps — not just how much.
Wake and Bed Schedules
This archetype specifically identifies chronotype and timing consistency. It distinguishes between early risers, night owls, and those with variable schedules — and it captures how consistent those patterns are across weekdays and weekends.
Exercise
The Exercise archetype characterizes workout behavior across multiple dimensions: frequency (daily, several times per week, occasional), type preference (strength, cardio, outdoor, mixed), and consistency. This enables product teams to match exercise-related features and content to how users actually train.
What this enables for product teams
Personalization without surveys
Archetypes provide segmentation data that previously required user surveys or manual input. Product teams can personalize experiences from day one of data collection, and the personalization improves as more behavioral data accumulates.
Intelligent engagement timing
Knowing a user’s chronotype and activity patterns lets apps time notifications, challenges, and content delivery to moments when the user is most receptive. A sleep insight delivered at bedtime to a night owl. A workout suggestion sent during their usual exercise window. An achievement notification timed to when they typically check their phone.
Empathetic user experiences
The most engaging health apps feel like they understand the user. Archetypes enable product teams to build experiences that acknowledge and adapt to individual behavioral patterns rather than imposing generic recommendations.
Cohort analysis and product intelligence
Beyond individual personalization, Archetypes give product teams a lens into their user base composition. What percentage of users are consistent exercisers vs. occasional? How do sleep patterns distribute across the user base? How do behavioral profiles correlate with retention and engagement? This data informs product strategy, not just individual UX.
Accessing Archetypes
Archetypes are available through both the Sahha API and the Developer Dashboard. API documentation covers the available archetype categories, response formats, and query patterns.
In the Developer Dashboard, each user profile now displays Archetype data alongside existing scores and biomarkers — giving a behavioral context layer to the quantitative health data.
Archetypes are available in both Sandbox and Production environments. Developers can start exploring them immediately with sample profiles or by integrating the Sahha SDK into their app.