PersonaLive

Quick Answer

PersonaLive (from Spatial.ai) is a segmentation system that classifies every US household into one of 80 behavioral segments, grouped into 17 higher-order "families", based on live social, mobile, and web signals. It helps you segment customers by what they actually do online and offline.

Overview

PersonaLive combines behavioral signals (social, mobile, web) with individual demographics to build psychographic and geodemographic profiles that are more dynamic and current than traditional survey-based systems. It is designed for customer segmentation, marketing activation, site selection, spend and market share analysis, and enriching CRM data with behavioral profiles.

Key Features and Data Signals

Feature	What It Offers
Real-time / live behaviors	Tracks recent signals: social media behavior, mobile device visitation, and web visitation, updated more frequently than static survey or census data
80 segments in 17 families	Households are assigned to one of 80 detailed behavioral segments, rolled up into 17 families for higher-level summaries
Rich metadata per segment	Each segment includes demographics (income, age), behavioral propensities (store visits, social follows), social topics, and live visitation trends
Household-level classification	Each household maps to exactly one segment; if a household changes (moves, life events), its segment may update
Delivery and activation tools	Append segment labels to first-party data, analyze which segments are most valuable, and export audiences to marketing platforms

Data Structure and Taxonomy

• Families and segments: 17 families at the higher level, each containing multiple segments. Families correspond to broad lifestyle and economic strata (for example "Ultra Wealthy Families", "Young Professionals", "Blue Collar Suburbs", "Sunset Boomers").
• Segment codes: Each segment has a code like A01, B03, or D02. The first letter denotes the family; the number ranks the segment within its family, often by income. For example, segment D02 is #RoaringRetirees, part of the Suburban Boomers family.
• Indexing and propensity scores: Indexes use a base of 100 (the US average) to show how much more or less likely a segment is to exhibit a behavior, such as visiting a store type or following a brand, compared with the average household.

Use Cases

• Customer base segmentation: enrich CRM or first-party customer data to see which segments your customers fall into and which are your highest-value segments
• Digital marketing and audience activation: build custom audiences using segment labels and tailor creative to segment preferences
• Site selection and trade area analysis: assess which segments dominate or visit specific locations, and project demand for new locations by segment
• Market intelligence and benchmarking: compare segment composition across geographies and track emerging behavior trends

Related Topics

• Data Bundles Overview
• Spatial.ai Proximity
• Understanding Demographics Data