Key Takeaways
- If a business has a storefront, you can find it on a map, even when a contact database has it filed under the wrong industry or missed it altogether.
- Category codes, brand, and opening dates make an ideal customer profile something you can filter on.
- How many locations an account has, how big they are, and how recently they opened often say more about its value than a headcount the company reported itself.
- POI data tells you where a business is and what it does. You’ll still need a contact database to find the person who signs.
- Monthly updates are what make the list useful over time. New openings give reps a reason to reach out, and closed sites drop off before anyone calls them.
Most B2B lead lists start in the same place. Someone opens a contact database, sets a few filters, and hits export. If you sell software to other software companies, that’s usually enough.
It gets shakier when your buyers own restaurants or run gyms, clinics, warehouses, or a handful of retail stores. A business like that lives at a street address, sometimes ten of them, and a firmographic database will often list it just once, under the head office.
So this guide starts somewhere else: with POI (points of interest) data, the records of where businesses physically are. We’ll build a B2B lead list from it step by step, look at where the approach breaks down, and cover the B2B lead list building tools you’ll still need next to it.
Why Does a B2B Lead List Go Out of Date So Quickly?
Sales reps already spend a big part of their week hunting for people to call. In Salesforce’s State of Sales 2026 report, which surveyed 4,050 sales professionals, representatives said prospecting takes up nearly a full workday every week. Even so, 48% said they still don’t have enough time for proper cold outreach.
The more interesting finding is about data. Among top performers, 79% said they prioritize data hygiene. Among underperformers, only 54% did. That’s a 25-point gap on something as unglamorous as keeping records clean.
Marketing teams report the same strain. Validity’s State of CRM Data Management in 2026 survey of 500 marketers found 62% of organizations lose revenue directly because of poor CRM data quality, and nearly a third of teams spend six or more hours a week fixing and reconciling records.
Meanwhile, the physical market keeps shifting. Coresight Research tracked 3,321 US store closures in the first half of 2026, according to Retail TouchPoints, down 44.1% from 5,941 a year earlier. That is still thousands of storefronts gone in six months. A list built in January and left alone describes a different market by summer.
What POI Data Brings to a Lead List (and What It Doesn’t)
A good POI dataset carries a set of attributes for each location, and several of them map directly to lead list decisions.
POI attribute | What it tells a sales team |
Category (NAICS code, category tags) | Whether the business fits your ICP, down to cuisine type or service type |
Brand and parent brand | Whether a location belongs to a chain, and how many sibling sites it has |
Address, coordinates, phone, website | Where the account is and how to reach the location |
Opened and closed dates | Whether the site is new, established, or gone |
Open hours | When a rep or field visit is likely to reach someone |
Building footprint (polygon) | Rough site size, and whether it sits inside a mall or plaza |
Names, job titles, and email addresses are missing from that table. POI data finds the account and describes it. It won’t tell you who runs operations for the 14-location franchise group that owns the store, so the steps below include a contact layer.
How to Build a B2B Lead List with POI Data, Step by Step
Picture a company that sells commercial kitchen maintenance contracts and wants to expand into Texas. Its best customers are independent and small-chain full-service restaurants open at least a year. Here is how that team would build the list.
Step 1: Describe your best customers in physical terms
Start with the accounts you’ve already closed. What kind of place were they? How many locations? Standalone building or strip plaza? How long had they been open when they bought it?
For the kitchen maintenance company, the answers might be: full-service restaurants, 1 to 15 locations, open 12 months or more, in metro areas. Each of those traits is a field in location data. A label like “mid-market hospitality company” is much harder to filter on.
Step 2: Turn the ICP into category, brand, and geography filters
Full-service restaurants map to NAICS 722511, and category tags narrow further if, say, high-volume fryer kitchens are your sweet spot. The brand field separates independents from national chains you might route to an enterprise team. Geography is a state, a few metros, or a radius around your technicians.
The store location data guide covers which fields to request from a provider.
Step 3: Pull the records and clean them before anyone sees them
A raw pull will contain duplicates, places inside places (a food court stall inside a mall), and occasionally a closed site. Use a persistent location ID such as Placekey to deduplicate across sources and to join POI records to your existing CRM accounts. Then drop anything with a closed date.
It’s the least exciting step. Skip it, though, and your reps find the duplicates themselves, one wasted call at a time.
Step 4: Score locations by what predicts value for you
Scoring is where location data pulls ahead of a contact export. A few signals that tend to work:
- Location count under one brand – A 9-location group is one sale with nine sites of revenue.
- Building size – Polygon data from a source like SafeGraph Geometry gives square footage, which often tracks with equipment volume, cleaning scope, or energy use.
- Recency – A site that opened in the last six months is still choosing vendors.
- Density – Clusters of qualifying locations make field sales and service routes cheaper.
Don’t copy these weights blindly. A pest control company and a payments provider would rank them very differently, so test the scoring against your won and lost deals before you trust it.
Step 5: Attach the people
Once the list is scored, match each record’s website domain or brand name to a B2B contact database such as Zoominfo, Apollo.io, or People Data Labs to find the owner, general manager, or regional operations lead. Domain matches are usually cleaner than name matches, because “Joe’s Grill LLC” and “Joe’s Grill” may not join.
Franchises add friction. The decision-maker may sit at a franchisee group with a different legal name than the sign on the building, so research those by hand for your top-scoring accounts.
Step 6: Push it into the CRM and carve territories
This is where POI data for lead generation starts paying off beyond the list itself. Load the scored, enriched list into your CRM with the location ID as a field, so future updates can match back cleanly. Because every record has coordinates, territories can be drawn by actual account density rather than by ZIP code lists someone made three years ago. SafeGraph’s post on using POI data for CRM enrichment and territory planning goes deeper on that workflow.
Step 7: Refresh on a schedule, and treat changes as signals
If your location data updates monthly, each refresh hands you two lists: new openings that match your ICP, and closures to suppress. New openings tend to be among the warmest leads in a month’s refresh, because a restaurant that opened three weeks ago probably hasn’t signed every service contract yet.
Which B2B Lead List Building Tools Work Alongside POI Data?
No single tool covers the whole job. A practical stack for location-led prospecting has four layers:
Layer | Job it does | What to check before buying |
POI data provider | Finds and describes physical accounts | Update frequency, closed-site handling, category depth, coverage in your regions |
B2B contact database | Adds names, titles, emails, phone numbers | Match rate on domains, verification method, decay policy |
CRM | Stores accounts, owners, and history | Ability to store a location ID and accept scheduled updates |
Outreach or sequencing tool | Runs the actual campaigns | Deliverability controls and CRM sync |
How do you tell which POI data providers are reliable for B2B prospecting?
Every provider claims accuracy, so test it during a trial:
- Run a closure check: Pull a city you know well and count closed businesses still listed.
- Ask for the refresh date: Find out the update cadence and when the latest release shipped.
- Spot-check brands: Compare location counts for three or four chains you sell to against their own store locators.
- Look for published statistics: Counts by category and country, plus brand freshness.
- Confirm a persistent ID: It lets each update match back to your CRM.
The POI data provider guide compares providers against criteria like these.
Refresh cadence deserves extra weight. SafeGraph’s own technical guide to Places data says many POI providers update every three to six months. That’s a vendor describing competitors, so verify it yourself. On a quarterly cycle, a new restaurant can be open for twelve weeks before it reaches your list.
Where This Approach Falls Short
Location-led lists suit some buyers far better than others.
Office-based buyers are a weaker fit
If you sell to accounting firms or software companies, the building tells you little. Firmographic and technographic data fit better.
Franchise decision-making is messy
A sign that appears on 200 buildings could belong to one owner. It could also belong to 200. POI data tells you the brand, but finding out who owns each site is a separate job, and in franchise-heavy categories like quick-service food or fitness, expect to do some of it by hand.
Home-based and mobile businesses are hard to see
Think of a plumber who works out of a van. There’s often no shopfront to map at all. Good POI datasets also leave out home-based listings deliberately, so these businesses won’t show up even when they’re real customers.
Coverage varies by country
Here’s a trap that catches a lot of teams. A provider says it covers 40-plus countries, and that’s true, but some of those countries might have a few thousand restaurants listed where you’d expect fifty thousand. So before you build a campaign around a new market, open the provider’s summary statistics for that region. How many locations does it actually have in the categories you sell to? You’ll know pretty quickly whether it’s worth it.
Honestly, if most of your best customers have a front door, that’s your starting point. 
Why SafeGraph Fits This Workflow
Go back over the steps for a second. Filtering, cleaning out duplicates, catching new openings every month: all of that only works if the data underneath is right. That’s where SafeGraph Places is built to help.
You get more than 80 million POIs worldwide, and they’re updated monthly. Each one comes with its brand and NAICS category, plus when it opened or, if it’s gone, when it closed. That last part saves you real time. A shuttered store gets marked closed and falls off your list, so nobody on your team is calling it three months later.
Then there’s Placekey. It’s an ID that sticks with a location from one release to the next. That matters more than it sounds. With it, you can match one location across your CRM, your contact data, and SafeGraph Geometry building footprints without guessing whether “Joe’s Grill LLC” and “Joe’s Grill” are the same place.
SafeGraph doesn’t supply contact data, so pair it with the contact database your team already uses.
For a worked example, SafeGraph’s Retail Brands in Miami walkthrough shows a logistics company mapping and scoring retail locations by brand and store size. If your data team will evaluate sources first, why data scientists choose SafeGraph data covers the quality checks they tend to run.
See What Your Current List Is Missing
Filter a real sample for your ICP in one city and count how many results your team has never heard of.
FAQ’s
1. How big should my first POI-based lead list be?
Smaller than you’d expect. One metro or region with a few hundred qualifying locations is plenty to start. You’ll see quickly how many locations you can match to a contact, and whether your scoring holds up once real replies come in. Then you can widen it.
2. Is it legal to use POI data for B2B outreach?
The POI records themselves are about places, like a store’s address, category and opening hours. There isn’t much personal data in that. Things change once you add names and emails on top. At that point you’re contacting people, and laws like GDPR in Europe, CAN-SPAM in the US and CASL in Canada come into play. Rules differ by market, so have your legal team check before you launch a campaign.
3. Can I use POI data for account-based marketing too?
Yes. When you group locations by brand, a chain with 30 sites shows up as one account instead of 30 scattered rows. The number of locations also gives you an easy way to tier accounts. Some teams use the coordinates to pick where to hold regional events, close to where their target accounts cluster.
4. How do I measure whether a POI-built list performs better than my old one?
Run both for one quarter in comparable territories. Start with the obvious signs of bad data: emails that bounce and phone numbers that reach the wrong business. Then compare meetings booked per hundred accounts. It’s also worth counting how many leads turned out to be closed, or never fit your profile in the first place.
My CRM already has thousands of accounts with messy addresses. Where do I start?
Clean the addresses first, using geocoded address data such as SafeGraph Address. Then match each record to POI data on address and name, and attach a persistent location ID. You’ll fix addresses and catch accounts that have closed. Often you’ll also find locations of existing customers that nobody on the team knew about.
