POI Database & Dataset Solutions in 2026: Your Complete Guide to Real-Time Location Intelligence

A phone number changes. A business quietly closes. A restaurant that opened last Tuesday doesn't exist in any dataset you can buy today. IndustryResearch.biz estimates that over 500 million updates hit POI databases globally every single year — and yet most companies still make six-figure decisions on files that were compiled months ago.

That's the whole tension in one sentence.

Everybody wants location data. Almost nobody talks about how fast it rots. This guide covers how a POI database actually works in 2026 — the providers worth paying for, the ones that aren't, the technical bits you need to understand, and why the static-vs-real-time distinction will save (or cost) you serious money. No filler. If something's bad, I'll say so.

What Is a POI Database? (Definition & Key Components)

A POI database (point of interest database) is a structured collection of data about physical business locations — names, GPS coordinates, addresses, phone numbers, emails, operating hours, reviews, social profiles, and category tags. It's the digital backbone behind every "restaurants near me" search, every fleet routing decision, every competitive landscape analysis.

That's the textbook answer. Here's the practical one: a point of interest database is only as useful as its freshness. A dataset with 50 million records sounds impressive until you realize 15% of those businesses changed their phone number last quarter, 10% shifted their hours seasonally, and another chunk moved or shut down entirely.

What separates a POI database from a plain business directory? Depth. A directory gives you a name and maybe an address. A proper business location database includes GPS coordinates down to six decimal places, website technology stacks, social media presence across platforms, review sentiment, price-range indicators, and dozens more fields. Platforms like Mapbox define POI databases as covering everything from navigation-grade coordinates to real-time attribute data.

Scrap.io lets you search 225M+ businesses across 4,000+ categories in 195 countries

And here's what most guides skip: you can build your own POI database instead of buying one. Tools like Scrap.io extract data directly from Google Maps — by geographic radius or custom polygon zone — so you're pulling live listings, not stale spreadsheets. Google Maps scraping gives you access to over 225 million businesses across 195 countries, with 70+ data fields per listing.

Where to Get Free POI Data (and What You Give Up)

Free options exist. They're just... not free in the way you'd hope. Here's where to look, and the catch attached to each:

• OpenStreetMap — huge, community-built, genuinely global. But POIs are modeled as nodes, ways, and relations, so extracting a clean business list means wrestling a raw PBF file through Overpass or PostgreSQL. No emails. No phone-type classification.
• OpenPoiMap — a friendlier OSM front-end for browsing POIs on a map. Great for a quick look. Not built for bulk export or outreach.
• Overture Maps — the Linux Foundation-backed open dataset (Meta, Microsoft, Amazon, TomTom). Serious coverage, developer-grade. Still zero contact data.
• data.gov — public-sector datasets, sometimes useful for specific categories. Coverage and freshness are all over the place.

Spot the pattern? Free POI data gets you coordinates and names. It never gets you emails, deduplication, or a freshness guarantee. For navigation or research, fine. For prospecting, you'll rebuild half of it yourself.

POI Database Market in 2026: Size, Growth & Key Trends

The numbers first. Market.us estimates the core POI data solutions market at roughly $1.47 billion in 2026, on a trajectory toward $8 billion by 2034 — the two figures track different segment definitions, so treat them as scope, not contradiction. North America held over 35% of the market, worth about $1.06 billion in revenue. Astute Analytica cuts it narrower: $246.94 million in 2023 heading to $579.26 million by 2032 at an 8.9% CAGR. Different perimeters, same direction of travel.

Software and database platforms eat up between 53% and 68% of total spending depending on whose numbers you trust. The takeaway doesn't change either way: companies aren't buying raw data anymore. They want analytics, filtering, and integration built in.

What's driving the growth? A few things converging at once. AI-powered data validation is becoming standard — providers that can't auto-detect closed businesses or flag stale phone numbers are losing contracts. Real-time update infrastructure went from "nice to have" to table stakes. And according to IndustryResearch.biz, there are now roughly 2.4 billion active POI data points globally, with 710 million in the US alone.

Now put that next to the industry stat. Reports throw around 710 million US "POI data points." Our own index — live, deduplicated, business-only — counts 25,778,600. The gap? That's what happens when you count every bench, bus stop, and parking meter as a "point of interest." Real businesses you can actually sell to are a much smaller, much more honest number. Nobody publishes that number. We just did.

Location intelligence as a discipline has matured past the "interesting experiment" phase. Astute Analytica reports that 78% of businesses now use POI data in some capacity. The question isn't whether to invest in poi data solutions — it's which provider to pick and how much to pay.

Top POI Database Providers Compared (2026)

This is the section most POI articles skip, because naming competitors is uncomfortable. But you can't make a smart decision without comparing options. I've used or tested most of these — including our own, listed here in full disclosure.

Quick takes on each:

SafeGraph is strong for foot-traffic analysis and academic research. Their Places dataset covers US locations well. Weakness: pricing is opaque and leans enterprise. Not ideal if you just need contact details for outreach.

HERE Technologies and TomTom are navigation-first. Excellent for automotive or logistics. But if you're after emails, social profiles, or review data for lead gen? Wrong tool. Don't bother.

Foursquare merged with Factual a few years back and has solid venue-level data. Their foot-traffic analytics compete with SafeGraph. Pricing gets steep fast for smaller teams.

Outscraper does Google Maps scraping on a pay-per-result basis. Decent for one-off projects. But it lacks the advanced filtering that makes extraction actually efficient — you pay for everything, including the junk you don't need. (We wrote a full Outscraper alternatives comparison if you want the details.)

Mapbox is a developer favorite for building map interfaces. Their POI data is good for display. Not built for B2B prospecting.

Placer.ai is the best on the market for foot traffic. Genuinely. But there's no contact data — no email, no social handles, nothing. For prospecting, it's simply the wrong category of tool.

CARTO is a spatial-data catalog, not an extractor. You buy third-party datasets through their platform. Excellent for analysis, useless for outreach.

Esri is the GIS reference. Powerful, expensive, mapping-first. If you don't do GIS, you're paying for functions you'll never open.

Scrap.io — full disclosure, this is our platform — extracts real-time data from Google Maps with filters applied before export. So you're not paying for 200,000 records when you only need the 3,000 restaurants in Phoenix with email addresses and 4+ star ratings. The cost difference versus the Google Maps API can hit 90% savings on large extractions. If you want the wider field, here are 10 of the best Google Maps scrapers in 2026.

Business Applications of POI Datasets

Everybody lists the same five use cases in these articles. I'll list them too — but with actual examples you can verify, not hypotheticals.

Marketing & Sales Intelligence

Back in 2025, DataPlor launched a global mobility product that uses POI data for consumer-movement analytics. The product gives brands visibility into foot-traffic patterns around competitor locations — basically answering "where are my potential customers going instead of coming to me?"

On a smaller scale, poi data for marketing is how agencies build hyper-local campaigns. Instead of buying a generic "restaurants in Texas" list, you extract only restaurants in Dallas with fewer than 50 Google reviews, no Instagram presence, and a WordPress site. That's a cold-email list that practically writes its own pitch. Retail mapping and location-based lead generation follows this exact playbook. And if you sell reputation management, finding companies with negative reviews turns low star ratings into qualified leads — businesses rated 2.5–3.5 stars are the sweet spot.

Competitive Analysis & Site Selection

Walmart uses POI data solutions for sales forecasting by location — internal models correlating nearby business density, competitor proximity, and demographic overlays with per-store revenue (sourced via Astute Analytica's 2024 industry report). Airbnb, meanwhile, integrates point of interest data directly into its search-ranking algorithm. Listings near high-rated restaurants, attractions, and transit hubs get boosted. That's location intelligence at platform scale.

For smaller operators, the logic is identical. A franchise evaluator eyeing potential sites runs geomarketing strategies — pulling competitor locations, checking saturation, spotting underserved pockets. Good site or bad site often comes down to POI density within a half-mile radius.

Healthcare & Emergency Services

Healthcare networks use POI datasets to map clinic-coverage gaps. Where are the underserved ZIP codes? Which areas have high population density but low provider-to-patient ratios? This isn't theoretical — it's how regional health systems plan expansions and decide where to send mobile health resources. Emergency services benefit too: routing that incorporates real-time POI data can shave critical minutes off response times. When every second counts, a location intelligence database that reflects reality (not last quarter's snapshot) isn't a nice-to-have.

Real Estate & Urban Planning

Real estate investors correlate business location data with property valuations. More diverse POI types nearby — restaurants, gyms, retail, services — generally tracks with higher commercial property values. Urban planners use the same data for transit-stop placement, zoning, and infrastructure priorities.

Logistics & Supply Chain

Back in October 2024, Ampeco partnered with ChargeHub to integrate POI data for EV charging-station discovery across North America — mapping charging infrastructure against route data, a direct application of poi datasets in the EV logistics space. And in January 2025, Astronics launched its SkyShow Server using real-time POI data to display interactive in-flight maps. Niche? Sure. But it shows how wide the application spectrum has gotten.

Real-Time vs. Static POI Databases: Why It Matters

Here's where most buying decisions go wrong.

Static POI databases work like this: a provider crawls sources, cleans records, packages them, sells you a snapshot. That snapshot might be two weeks old. Might be two months. By the time it reaches your CRM and your team starts dialing, you're working with information that's actively decaying.

According to the Bureau of Labor Statistics, roughly 20% of new businesses fail within the first year. That's just closures — it doesn't count businesses that change their phone number, shift their hours, or move. Seasonal businesses adjust hours constantly. Companies rebrand, relocate, swap phone systems. A static dataset starts losing accuracy the moment it's compiled.

The result? Bounced emails. Dead phone numbers. Wasted ad spend on closed locations. Missed opportunities from businesses that opened after your file was cut.

Real-time POI database extraction pulls from live sources — primarily Google Maps, where owners update their own listings. A business changes its hours this morning; you can extract that updated record this afternoon. Want the mechanics? We broke down how real-time extraction actually works in a dedicated guide.

How bad does the decay get? B2B contact lists degrade at roughly 2–3% per month. After six months, 15–20% of records are flat-out wrong — bounced emails, disconnected phones, businesses that moved or closed. After a year? That number can easily hit 30%. Two thousand dollars on a "premium" directory that's already a quarter stale by the time your team touches it. Not a hypothetical. That's the math on any static list older than 90 days.

The community feels this pain out loud. Across GIS and OpenStreetMap threads — like the ones on r/gis and r/openstreetmap — the same complaints keep surfacing: OSM extraction is fiddly, free datasets go stale, and paid providers won't tell you when a record was last verified. The pattern is consistent enough that it's basically a genre.

The filtering angle matters too. With static datasets, you pay for everything and sort later. With real-time extraction, you filter before you download. Only businesses with verified emails in a specific metro? Two clicks. That can cut your per-lead cost by 80% compared to buying bulk datasets. Here's the country-level workflow in action:

Oh, and one more thing people miss: static databases can't show you new businesses. A restaurant that opened last Tuesday won't appear in a January dataset. Real-time extraction catches those new listings immediately — which, for agencies chasing newly opened businesses, is sometimes worth more than the rest of the database combined.

How to Choose the Best POI Database Provider

Picking a POI database provider comes down to six things. In order of importance:

Data freshness. Ask every provider the same question: "When was this record last verified?" If they dodge or say "quarterly," that's your answer. For outreach, lead gen, or competitive monitoring, anything older than a week introduces risk. Professional tools versus DIY approaches break down the freshness gap in detail.

Coverage breadth and depth. Volume isn't the game. You need the right fields for your use case. Lead gen needs emails, phones, social profiles, website data. Market research needs foot-traffic estimates, review sentiment, category tags. Navigation needs coordinates and road proximity. Make sure the provider covers what you actually need — not just "millions of records." The complete guide to extracting Google Maps data walks through which fields matter for which use cases.

Filtering before export. This separates budget-friendly tools from money pits. Can you filter by business category (from the full list of 4,000+ Google Maps categories), by geographic zone, by presence of email or website, by rating threshold, by open/closed status — all before you pay? If not, you're overpaying for noise.

Advanced filters let you target only the businesses that match your criteria before exporting

Export formats and integrations. Your business location database is useless if it can't plug into your workflow. CSV and Excel are baseline. API access matters for automation. CRM integrations (CRM automation guide) and no-code connectors (Make.com tutorial) turn a dataset into a pipeline.

Pricing transparency. If you have to "book a demo" to learn the price, budget an extra 3x whatever you expected. Enterprise pricing works for enterprises. If you're a 15-person agency or a solo consultant, you need clear per-month or per-lead pricing. Scrap.io starts at $35/month on an annual plan ($49/month without commitment). SafeGraph and HERE are "contact sales" territory.

Legal compliance. We'll cover this next, but your provider should be transparent about data sourcing, GDPR compliance, and how they handle opt-out requests.

POI Data Extraction: Technical Implementation

Three main approaches exist for getting POI data into your systems. Each has tradeoffs.

Pre-built datasets (SafeGraph, TomTom, etc.) are the easiest. You buy access, download, integrate. The drawback: you're locked into their update schedule, their fields, their coverage gaps. And you pay for everything, including records you'll never use.

API-based extraction (Google Places API, HERE API) gives you programmatic access. Great for developers. The Google Places API charges $32–$40 per 1,000 results and caps individual queries at 120 results. For large-scale projects — every dentist in California, say — costs add up fast. And if you're storing identifiers long-term, read our guide on Place ID vs CID vs Google ID before you build anything — picking the wrong one will break your database eight months later. Geocoding APIs cover the coordinate side.

Platform-based scraping (Scrap.io, Outscraper) sits in the middle. You get the comprehensiveness of Google Maps data without writing code or babysitting API quotas. Scrap.io specifically handles deduplication, email enrichment from business websites, social-profile matching, and Google Maps coordinates extraction — all in the same run.

For automation, the workflow usually looks like: extract → filter → enrich (emails, social, tech stack) → export to CRM → trigger outreach. Tools like Make.com or Zapier handle the glue.

The enrichment step deserves a closer look. Raw POI data from Google Maps gives you what businesses publish — name, address, phone, hours, reviews. But the real outreach value comes from layering on data scraped from their websites: email addresses, social handles, tech stacks, and email data specifically from Google Maps. That jump from "business listing" to "qualified prospect" is where poi data extraction gets genuinely profitable.

Data Quality — The Part Nobody Likes Talking About

Not all extracted data is equal. A free scraper that dumps 100,000 records into a CSV gives you volume. A quality platform gives you clean volume — deduplicated, validated, with freshness timestamps showing when each record was last verified. The difference shows up in your bounce rate. Fresh data from quality providers runs 95%+ deliverability. Six-month-old static lists? You'll be lucky to hit 70%.

Always validate a sample before running a full campaign. Pull 100 records, spot-check phone numbers, verify a handful of emails. If the quality holds, scale up. If it doesn't, switch providers before you burn your sender reputation.

Legal & Compliance Considerations for POI Data

Two frameworks matter here: GDPR (EU) and CCPA (California). Both regulate how personal data — including business contact information — can be collected, stored, and used.

The short version for POI data extraction: scraping publicly available business information from platforms like Google Maps is generally legal for commercial use in both the US and EU, as long as you're only collecting data that businesses have voluntarily made public. The landmark HiQ v. LinkedIn ruling (Ninth Circuit) established that accessing publicly available data doesn't violate the Computer Fraud and Abuse Act, even when it conflicts with a platform's terms of service.

That said, "legal" and "smart" aren't always the same thing. Best practices: only collect data businesses have published publicly themselves; follow GDPR requirements for storage, processing, and right-to-deletion if you're handling EU business data; comply with CAN-SPAM and CCPA opt-out rules for outreach; document your sources and methods. And if you're scaling to large volumes across jurisdictions, consider consulting a data-privacy attorney.

The practical reality? Google's enforcement typically maxes out at temporary IP blocks for aggressive scraping. Legal action is rare and reserved for fraud or infrastructure damage. But using a platform that manages rate limiting and compliance for you (instead of building your own scraper) removes most of the risk. For a deeper dive, our piece on whether it's legal to scrape Google Maps covers the case law and compliance strategies in detail.

Getting Started with POI Database Solutions

Don't start by extracting every business in North America. That's a great way to blow your budget on data you'll never touch.

Start with one city, one industry, one use case. Maybe you're a web agency targeting restaurants without websites in Austin. Or a SaaS company mapping competitor customers in the Bay Area. Or a franchise operator evaluating Phoenix.

Whatever it is — define your ideal customer profile first. Then extract only the POI data that matches. Filter aggressively. Export a test batch of 100–500 records. Run your outreach. Measure response rates, deliverability (should be 95%+ with fresh data), and conversion to meetings. Not sure where to click first? Here's the two-minute onboarding:

Once you've validated the approach, scale. One city to a state. One category to adjacent ones. The beauty of real-time extraction is that scaling doesn't require buying a bigger dataset — you just run more targeted searches. Track ROI from day one: cost per lead, response rate, meetings booked, deals closed. Most businesses using fresh poi datasets see payback within the first month. If the numbers don't work on a small test, they won't magically improve at scale. Fix the targeting first.

One common mistake: extracting too broad, too early. "All businesses in California" sounds powerful, but you'll drown in data before you've figured out what converts. Specificity beats volume at every stage. A list of 500 perfectly targeted businesses will outperform a dump of 50,000 random ones. Every time.

Building an AI workflow instead of a spreadsheet one? You can feed POI data straight to your AI agents and skip the export entirely. For the broader B2B picture, geolocation data for B2B marketing and business database search tools are worth a read.

FAQ

What is a POI database?

A POI (point of interest) database is a structured dataset of detailed information about business locations — names, addresses, GPS coordinates, phone numbers, emails, operating hours, reviews, and category classifications. Unlike basic directories, modern POI databases carry dozens of fields per record and can be updated in real time from sources like Google Maps.

How do I get POI data?

Three main methods: buy pre-built datasets from providers like SafeGraph or HERE Technologies; use the Google Places API for programmatic access ($32–$40 per 1,000 results); or use extraction platforms like Scrap.io that pull real-time data from Google Maps with advanced filtering. The best approach depends on your volume, budget, and whether you need real-time freshness or can work with periodic snapshots.

What are the best POI data providers in 2026?

The top providers include SafeGraph (foot traffic, US focus), HERE Technologies (navigation, global), Foursquare (venue data), TomTom (automotive), Mapbox (developer-focused), Placer.ai (foot-traffic analytics), CARTO and Esri (spatial/GIS), Outscraper (pay-per-result scraping), and Scrap.io (real-time Google Maps extraction with 70+ fields). The right choice depends on your use case — lead gen, analytics, navigation, or development.

Is POI data extraction legal for commercial use?

Extracting publicly available business data from platforms like Google Maps is generally legal under US and EU law. The HiQ v. LinkedIn ruling confirmed that scraping public data doesn't violate the Computer Fraud and Abuse Act. However, you must comply with GDPR, CCPA, and CAN-SPAM when storing and using the data for outreach. Always work with providers who source data transparently and honor opt-out requests.

What data fields are included in POI datasets?

Comprehensive POI datasets typically include: business name, full address, GPS coordinates, phone numbers, email addresses, website URL, social media profiles, business category and sub-categories, operating hours, price range, star rating, review count, photos, and open/closed status. Advanced providers also extract website technology stacks, domain age, and social engagement metrics.

How much does POI data cost?

Pricing varies wildly. Enterprise providers like SafeGraph and HERE typically require annual contracts in the $10,000–$50,000+ range. The Google Places API charges $32–$40 per 1,000 requests. Real-time extraction platforms like Scrap.io start at $35/month (annual) or $49/month without commitment for 10,000 credits. Pay-per-result tools like Outscraper charge per record. For most small-to-mid-size businesses, platform-based extraction offers the best cost-per-usable-lead ratio.

What is the difference between POI data and business directory data?

Business directories provide basic listing info — usually just name, address, and phone. A POI database goes much further: GPS coordinates, email addresses, social profiles, review data, operating hours, photos, category tags, website technology, and more. Think phone book versus comprehensive business-intelligence profile. That depth directly impacts what you can do — directories are for looking things up, POI databases are for making strategic decisions.