Point of Interest (POI) data is the structured catalog of real-world places that powers modern location analytics — every foot-traffic read, geofence audience, and site-selection model starts with whether the underlying place record is accurate. This guide is the working reference for buyers evaluating POI data in 2026: what it is, how it is built, where it breaks, and how to compare vendors without relying on marketing record counts alone.
Key Takeaways
POI data is place truth (identity + footprint + category), not raw GPS pings — mobility panels answer *who moved*; POI answers *where the business is*.
Polygon-primary geofences materially reduce false-positive visits versus centroid-plus-radius in dense retail (30–40% typical).
Procurement should test refresh cadence, brand hierarchy, and same-address disambiguation on *your* chains before signing.
Compliant sourcing and sensitive-location exclusions matter as much as coverage when POI joins to consented mobility (FTC enforcement context).
What Is Point of Interest (POI) Data?
A POI record represents a business or facility at a location: name, address, category, operational status, and a geographic footprint used for measurement or targeting. Historically, POI catalogs grew from yellow-pages-style listings; today enterprise buyers expect polygon boundaries, franchise-to-parent mapping, and NAICS-aligned category tags so analytics can roll up by industry. Without that structure, a mobility vendor’s visit count is un-auditable — you cannot explain whether a spike is demand, a polygon bleed, or a stale closure.
Types of POI Data
Chain / brand points — individual store locations with brand and parent-company hierarchy for competitive reads.
Polygon footprints — building or leasehold shapes used for visit attribution (preferred for retail, malls, mixed-use).
Centroid + radius fallbacks — cheaper geometry for isolated sites; risky in dense corridors.
Visit-attribution layers — mobility joins that count devices against POI polygons (requires both POI and panel quality).
Dwell and OD overlays — time-on-premise and origin-destination when POI joins to global mobility.
How POI Data Is Collected (and Why Methodology Matters)
Collection blends licensed business registries, satellite and aerial imagery, web-scraped hours and status, and human validation for high-value categories. Some vendors infer places purely from device clusters — fast to scale, weak on brand identity and closures. Enterprise programs separate place maintenance from mobility observation: the POI file should refresh on its own lifecycle (open/close/rebrand) even when panel size fluctuates. GSDSI sourcing methodology documents consent posture for downstream joins; the IAB Tech Lab data transparency framework is the external reference many legal teams cite in RFPs.
Common Use Cases by Industry
Retail and QSR teams benchmark share-of-visit, trade-area overlap, and whitespace markets using POI polygons plus mobility. OOH and CTV buyers build geofence audiences and closed-loop attribution from screen exposure to store visit (OOH + CTV deep dive). CRE investors underwrite sites with foot-traffic and origin-destination cuts anchored to parcel-faithful polygons. Public sector agencies need NAICS-consistent place typologies for planning studies. In each case, the POI layer is the join key — see GSDSI POI & Geofencing for field-level specs.
How to Evaluate a POI Data Provider (10 Criteria)
Coverage for your geographies and categories (not global totals).
Polygon fidelity on dense retail and multi-tenant addresses.
The POI catalog itself is generally not personal data, but almost every high-value use case joins POI to device-level mobility. Post-FTC location-data enforcement, buyers should confirm sensitive-category exclusions, retention limits, and deletion SLAs in both contract and engineering. Place data from providers that faced public scrutiny on collection methodology carries reputational risk in regulated industries — compliant sourcing is a differentiation angle SafeGraph and Foursquare buyers now explicitly diligence.
Glossary of POI Data Terms
Geofence — virtual boundary; polygon preferred over radius for attribution.
Centroid — lat/long pin; cheap but bleeds visits in multi-tenant sites.
Dwell — time spent inside a geofence; stop-detection rules matter.
Change delta — incremental file of opens/closes/edits since last refresh.
Place vs POI — colloquial overlap; procurement should specify polygon + hierarchy.
A database of real-world places (stores, venues, facilities) with locations, categories, and boundaries used for maps, analytics, geofencing, and foot-traffic measurement.
How is POI data different from mobility data?
POI defines where businesses are; mobility data describes device movement. Visit analytics require joining both on stable POI identifiers with polygon-quality geofences.
What should I ask for in a POI sample?
Your exact chain list or NAICS slice, polygon geometries, hierarchy fields, refresh dates, and a change-delta example covering recent openings or closures.
Is POI data the same as place data?
Often used interchangeably in marketing, but enterprise RFPs should specify polygon footprints, brand hierarchy, and refresh — not just lat/long pins.