PersonaLive Data Overview
Overview
PersonaLive is a segmentation system that classifies every U.S. household into one of 80 behavioral segments grouped in 17 higher-order “families” based on live data. Spatial.ai uses behavioral signals (social, mobile, web) combined with individual demographics to develop psychographic / geodemographic profiles that are more dynamic and current than traditional survey-based systems.
It is designed for use cases such as customer segmentation, marketing activation, site selection, spend / market share analysis, and enhancing CRM with behavioral profiles.
Key Features & Data Signals
| Feature | What it Offers / Why It Matters |
|---|---|
| Real-Time / Live Behaviors | Tracks live / recent signals: social media behavior, mobile device location (visitation), web visitation. Because these are updated more frequently than static survey or census data, PersonaLive can adapt to changes in consumer behavior. |
| 80 Segments ⟹ 17 Families | Households are assigned to one of 80 detailed behavioral segments. Those are rolled up into 17 families for higher-level summarization. Useful when you want granularity vs when you want simpler grouping.s |
| Rich Metadata per Segment | For each segment there is: demographic data (income, age, etc.), behavioral propensities (visiting certain stores, following certain social accounts, etc.), social topics, live visitation trends, etc. |
| Household-Level Classification | Each individual household is mapped to exactly one segment. If households change (move, life events), their segment may update. |
| Delivery & Activation Tools | Ability to append segment labels to first-party data (customer lists, store visitation), analyze which segments are most valuable or underrepresented, activate by exporting audiences into marketing platforms. |
Data Structure & Taxonomy
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Families & Segments: 17 families (higher level), each containing multiple segments. Families often correspond to broad lifestyle / demographic / economic strata (e.g. “Ultra Wealthy Families,” “Young Professionals,” “Blue Collar Suburbs,” “Sunset Boomers,” etc.)
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Segment Codes: Each segment has a code like
A01,B03,D02, etc. The first letter denotes the family; the number helps rank/order within family (often by income or related metrics). For example segment D02 is #RoaringRetirees, part of Suburban Boomers family. -
Indexing & Propensity Scores: The system uses indexes (base 100 = U.S. average) to show how much more/less likely a segment is to exhibit certain behaviors (store visitation, following a brand on social, etc.) compared with the average.
Use Cases / Applications
PersonaLive lends itself well to:
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Customer base segmentation: enriching CRM or first-party customer data to see which segments your customers fall into; understanding who are your highest-value segments.
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Digital marketing targeting / audience activation: building custom audiences in Meta, Google, etc. using segment labels; tailoring creative & messages to segment-based preferences.
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Site selection & trade area analysis: assessing which segments dominate or visit certain physical locations; projecting demand in new locations by segment.
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Market intelligence & benchmarking: comparing the composition of segments across geographies; seeing emerging trends in behavior or social topics for specific segments