Spatial.ai

Spatial.ai starts from a simple premise: two consumers with identical demographics can behave completely differently, so demographics alone are a weak basis for retail marketing and site selection. Its PersonaLive system classifies every U.S. household into 17 high-level groups and 80 behavioral segments derived from four dimensions of observed behavior — demographics, social media activity, mobile movement data, and credit card transactions. The company reports that this multi-source approach improves retail behavior prediction by an average of 17% and produces campaigns that perform up to 50% better.

The workflow runs in three steps. First, marketers identify their top segments in minutes by uploading CRM contact lists to see which segments are most valuable, or by uploading a visitation report — or simply drawing a polygon — to see which segments visit a location most. Second, they position the brand strategically using consumer spend data: comparing market share against competitors by segment and tracking how much each segment spends on different brands over time. Third, they build tailored multi-channel campaigns by viewing detailed segment portraits, personalizing ad imagery and copy, and exporting audiences to Meta, TikTok, Google, Snapchat, X, programmatic platforms, and direct mail.

Alongside PersonaLive, Spatial.ai offers Proximity for segmenting neighborhoods by social media behaviors and FollowGraph for quantifying consumer social interest at a geographic level. Typical applications include site selection, digital marketing, credit card market share analysis, and retention and expansion programs. The platform is used by more than 750 retailers, e-commerce brands, and agencies, and case studies cite clients including Colliers, HIFI Agency, AAA, SeaQuest, and Goodwill. Data is permissioned, anonymized, and aggregated, so the system describes behaviorally similar groups rather than identifying individuals.