--- title: Archetypes subtitle: Labels that capture traits and persona --- ![Archetypes Hero](/images/products/archetypes/archetypes-hero.webp) {% use-cases items="Segmentation, Targeting, Product Recommendations, Analytics/BI" /%} ## Introduction Turn complex health data into human-readable labels. Instead of numbers, get categories like "Night Owl", "Short Sleeper", or "Highly Active"—derived from weeks of behavioral data. Perfect for segmentation, personalization, and understanding your user base at a glance. --- ## Key Features {% cards smCols=2 %} {% card title="Human-Readable" description="Complex data becomes intuitive labels like 'Night Owl' or 'Highly Active'" /%} {% card title="Segmentation-Ready" description="Group users by shared behaviors for targeted campaigns and offers" /%} {% card title="Personalization Fuel" description="Power recommendations and UX based on behavioral profiles" /%} {% card title="Adaptive" description="Updates weekly and monthly to reflect changing behavior" /%} {% card title="Retroactive" description="Get 2 weeks of historical archetypes immediately on integration" /%} {% card title="Smartphone Compatible" description="Most archetypes work without wearables—phone data is enough" /%} {% /cards %} --- ## How It Works Sahha analyzes weeks of health data and assigns users to behavioral categories. Unlike daily scores, archetypes smooth out short-term fluctuations to reveal stable patterns. They're refreshed weekly and monthly. There are two types of archetypes: ![Types of Archetypes](/images/products/archetypes/archetypes-explained.webp) #### Ordinal Archetypes (Ranked Progression) Ordinal archetypes represent a ranked scale, where values move from lower to higher states in a meaningful order. Each level in the archetype reflects an increase in the measured behavior. - Example: `sleep_duration` - `very_short_sleeper` → `short_sleeper` → `average_sleeper` → `long_sleeper` - What it means: As users get more sleep, they progress toward higher sleep duration categories. - Why This Matters: - Enables comparisons between different user groups and population benchmarks. - Helps identify trends and improvements over time. #### Categorical Archetypes (Distinct Groups) Categorical archetypes group users into distinct categories without any hierarchical ranking. Unlike ordinal archetypes, these categories are independent of each other and do not imply a progression. - Example: `sleep_chronotype` - Categories: `early_bird`, `night_owl`, `intermediate` - What it means: These categories describe natural sleep-wake tendencies but are not ordered from "worse" to "better" or "less" to "more". - Why This Matters: - Useful for segmentation and personalization (e.g., optimizing app notifications based on chronotype). - Provides insights into natural inclinations rather than performance-based measures. By having both ordinal and categorical archetypes, Sahha provides a comprehensive view of measurable behaviors (e.g., activity level, sleep efficiency) to inherent traits (e.g., chronotype). This approach enables more actionable information for a variety of use cases. --- ## List of Archetypes | Archetype | Type | Possible Values | Periodicity | Description | Requires Wearable | | --------------------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------ | ----------------- | | activity_level | Ordinal | `sedentary`, `lightly_active`, `moderately_active`, `highly_active` | Weekly, Monthly | Overall level of physical activity including movement and exercise. | No | | exercise_frequency | Ordinal | `rare_exerciser`, `occasional_exerciser`, `regular_exerciser`, `frequent_exerciser` | Weekly, Monthly | How often the individual exercises. | No | | mental_wellness | Ordinal | `poor_mental_wellness`, `fair_mental_wellness`, `good_mental_wellness`, `optimal_mental_wellness` | Weekly, Monthly | Mental wellness and resiliency based on physical activity, sleep, and stress indicators. | No | | overall_wellness | Ordinal | `poor_wellness`, `fair_wellness`, `good_wellness`, `optimal_wellness` | Weekly, Monthly | Overall wellbeing across all aspects of health. | No | | primary_exercise | Categorical | Most frequent exercise (e.g., running, weightlifting, yoga) | Weekly, Monthly | Most commonly performed exercise. [See possible exercise types](/docs/get-started/data-dictionary/exercise-types) | No | | primary_exercise_type | Categorical | `strength_oriented`, `cardio_oriented`, `mind_body_oriented`, `hybrid_oriented`, `sport_oriented`, `outdoor_oriented` | Weekly, Monthly | Categorizes the primary exercise into strength, cardio, sports, etc. | No | | secondary_exercise | Categorical | Second most frequent exercise (e.g., swimming, cycling, hiking) | Weekly, Monthly | Second most commonly performed exercise. [See possible exercise types](/docs/get-started/data-dictionary/exercise-types) | No | | sleep_duration | Ordinal | `very_short_sleeper`, `short_sleeper`, `average_sleeper`, `long_sleeper` | Weekly, Monthly | Typical sleep duration relative to recommended norms. | No | | sleep_efficiency | Ordinal | `highly_inefficient_sleeper`, `inefficient_sleeper`, `efficient_sleeper`, `highly_efficient_sleeper` | Weekly, Monthly | How effectively the individual maintains uninterrupted sleep. | Yes | | sleep_pattern | Categorical | `consistent_early_riser`, `inconsistent_early_riser`, `consistent_late_sleeper`, `inconsistent_late_sleeper`, `early_morning_sleeper`, `chronic_short_sleeper`, `inconsistent_short_sleeper` | Weekly, Monthly | Overall sleep behavior based on timing and consistency. | No | | sleep_quality | Ordinal | `poor_sleep_quality`, `fair_sleep_quality`, `good_sleep_quality`, `optimal_sleep_quality` | Weekly, Monthly | Long-term quality of sleep based on duration, regularity, recovery, and debt. | No | | sleep_regularity | Ordinal | `highly_irregular_sleeper`, `irregular_sleeper`, `regular_sleeper`, `highly_regular_sleeper` | Weekly, Monthly | Consistency in sleep timings. | No | | bed_schedule | Ordinal | `very_early_sleeper`, `early_sleeper`, `late_sleeper`, `very_late_sleeper` | Weekly, Monthly | Typical bedtime. | No | | wake_schedule | Ordinal | `very_early_riser`, `early_riser`, `late_riser`, `very_late_riser` | Weekly, Monthly | Typical wake-up time. | No | Browse our [comprehensive data dictionary](/docs/get-started/data-dictionary) to view all available outputs beyond just archetypes. --- ## Output Schema Archetypes are delivered as a JSON object with the following fields: {% api-example %} {% api-panel %} {% api-property field="id" type="UUID" description="Unique identifier for the archetype assignment" /%} {% api-property field="profileId" type="UUID" description="Unique identifier for the user profile" /%} {% api-property field="accountId" type="UUID" description="Identifier for the account linked to the profile" /%} {% api-property field="externalId" type="UUID" description="External profile identifier for integration" /%} {% api-property field="name" type="string" description="Name of the archetype (e.g., sleep_duration)" /%} {% api-property field="value" type="string" description="Assigned category name (e.g., short_sleeper)" /%} {% api-property field="dataType" type="string" description="Type of archetype: ordinal or categorical" /%} {% api-property field="ordinality" type="integer" description="Numerical representation of the category" /%} {% api-property field="periodicity" type="string" description="Frequency: weekly, monthly, or quarterly" /%} {% api-property field="startDateTime" type="datetime" description="Start of the time period for this archetype (ISO 8601)" /%} {% api-property field="endDateTime" type="datetime" description="End of the time period for this archetype (ISO 8601)" /%} {% api-property field="createdAtUtc" type="datetime" description="Timestamp of when the archetype was created" /%} {% /api-panel %} ```json {% title="Example Response" %} { "id": "91ced284-5355-57f0-b162-1ac920a42371", "name": "sleep_duration", "value": "short_sleeper", "dataType": "ordinal", "ordinality": 1, "periodicity": "monthly", "startDateTime": "2025-01-01T00:00:00+13:00", "endDateTime": "2025-01-31T00:00:00+13:00", "createdAtUtc": "2025-02-01T13:08:53.322886Z" } ``` {% /api-example %} --- ## FAQ {% faq %} {% faq-item question="How are Archetypes different from Health Scores?" %} Health Scores provide numerical values (e.g., 0.0-1.0), while Archetypes classify users into predefined categories. Archetypes offer a more intuitive interpretation of long-term behavior. {% /faq-item %} {% faq-item question="How does ordinality work?" %} Ordinality represents the ranking of each category, with lower values indicating less and higher values representing more. For example, `sleep_duration`: 0 = very_short_sleeper, 1 = short_sleeper, 2 = average_sleeper, 3 = long_sleeper. {% /faq-item %} {% faq-item question="How frequently are Archetypes updated?" %} Archetypes are generated at the end of each week, month, or quarter, depending on the appropriate periodicity. {% /faq-item %} {% /faq %} --- ## Getting Started {% action-cards %} {% action-card icon="code" href="/docs/connect/api" title="API" description="Query archetype assignments for any profile" /%} {% action-card icon="bell" href="/docs/connect/webhooks" title="Webhooks" description="Receive archetypes as they're assigned weekly or monthly" /%} {% /action-cards %} --- ## Support For additional assistance or more detailed information on Archetypes, please contact [support@sahha.ai](mailto:support@sahha.ai) or reach out in the [slack community](https://join.slack.com/t/sahhacommunity/shared_invite/zt-1w0fmfbvk-qUwQ83tJgXyjT9XSxJvKIw).