Beyond the Pin Drop

Writer: Michael Schoen
Date: October 29, 2026

Estimated reading time: 6-minute read

For a decade, precise GPS told advertisers exactly which store a phone was standing in. It was accurate to about 13 feet, roughly the size of a parking space. Draw a fence around your location, draw another around a competitor’s, and you could count who walked in after seeing your ad.

Then a handful of states stepped in. Maryland, Oregon, Virginia, New Jersey, and Connecticut now ban the sale of precise geolocation data, which they define as anything more exact than about 1,750 feet. In practice, that turns a pin on a parking space into an area roughly two-thirds of a mile across. The push has support from lawmakers in both parties, Consumer Reports, EPIC, the Center for Democracy and Technology, and state attorneys general. But momentum is uneven: California’s governor recently vetoed a similar ban.

In those states, the unit of location has changed. Yesterday it was the store. Today it’s the whole neighborhood the store sits in.

That leaves advertisers with locations in those states asking the same question: am I paying for reach that’s wasted beyond my target audience, and can I still prove a visit?

Precise location isn’t gone everywhere, and more states may follow or not. But where the laws apply, the exact-location button is off, and the real risk is working with a platform that has no answer for it.

The Legislative Landscape

As of October 2026, five states ban the sale of precise geolocation data, and at least three more are weighing similar bills. California came close: lawmakers passed a ban on selling sensitive data, including precise location, but Governor Newsom vetoed it on September 27.

How the Market Responded, and Why It Falls Short

Most of the industry answered the new laws by blurring the location or widening the radius. That complies with the law, but it leaves local advertisers with a weaker product.

The stakes are high. Roughly 240,000 multi-location businesses, including corporate brands, franchisees, regional and local businesses, co-ops, and the agencies that plan for them, are asking whether they’re paying for wasted reach. If a visit can’t be measured, a media plan can’t be defended store by store.

Here’s what the market’s response looks like:

• Leading location data providers now publish their own limits for regulated states. Targeting is available only at a radius of one mile or more, and on-premise targeting, neighborhood targeting, audience building, and visit tracking are switched off.
• General-purpose DSPs target by metro area or ZIP code, or lean on the same third-party segments.

The problem is that an area two-thirds of a mile wide can cover your store, the gas station across the street, and the nail salon next door. Most platforms still run the same match as before, but they have no precise map of the store to check that area against. The match becomes a guess, and you pay for impressions served to people who were never near your door.

And every platform is following the same rules, but not every platform kept the same features. Many dropped the tools local advertisers rely on most: targeting near a specific store and measuring who walked in.

There’s also a deeper issue. When location is licensed from a partner, you can only do what that partner allows. When their rules change, so does your campaign.

Location Was Never Our Only Signal

Simpli.fi was purpose-built to optimize across 100+ signals. Precise GPS was one of them, never the only one.

We believe the right answer to these laws is a platform built around behavior near locations, not a single coordinate. This pattern isn’t new: cookies were restricted, then IDFA, and now GPS precision. Diversified signals aren’t just compliant, they’re more durable.

What this means for Simpli.fi’s advertisers: if you have locations in both regulated and unregulated states, you don’t need a separate plan for each. Because every signal can be throttled up or down on its own, we can optimize each market differently. Location comes down where it’s restricted and stays in use where it’s allowed, and the other signals carry more of the work, all within one plan and one unified report.

Inside Signal-Level AI

Simpli.fi already had these strengths in place before these laws passed. We call it Signal-Level AI, and it’s what keeps a regulated-state campaign working.

Signal-Level AI works like this: every signal, including GPS, search, sites visited, and household purchases, is maintained on its own. None are blended into a named segment, and each stays visible from targeting through optimization to reporting. Each can be dialed up or down independently, which matters most when you’re advertising in a regulated state.

The foundation of our signals:

• 14 million mapped storefronts. This map was built independently of any device signal, so the privacy laws don’t touch it. Instead of guessing, we check each approximate location against a precise outline of your store. If the two overlap, the device is eligible, and ping volume, recency, and the other signals below decide how much weight it gets.
• 12 billion GPS signals, refreshed continuously. That volume and recency matter. One blurry ping says little about who was near your location, but several consistent pings over an hour or a day tell a much stronger story.
• 100+ signals that fill in the picture. Search, context, site visits, and purchase behavior aren’t restricted the way GPS precision is. They show who’s interested and why, and Signal-Level AI weighs each one against your goal as the campaign runs.
• 130 million mapped U.S. households. Simpli.fi’s identity graph connects households and devices, providing the foundation for cross-device attribution. In regulated states where foot traffic attribution is unavailable, it enables matchback attribution by connecting client-provided transaction data to campaign exposure.

The same approach carries across channels. Whether you’re running programmatic, CTV, audio, or DOOH, you plan, activate, and measure in one platform, in every state you advertise in.

Precise Location Is Restricted. Results Don’t Have to Be.

A handful of states now limit precise location data, and others may follow. Advertisers in those states don’t have to give up on local results. Simpli.fi pairs a precise map of 14 million storefronts with billions of GPS data points and 100+ signals, so campaigns stay targeted wherever you advertise. Measurement changes where foot-traffic attribution is restricted: our household graph connects campaign exposure to your own transaction data, so you can still tie spend to sales. You run one plan and get one report across every state.

To learn how Simpli.fi’s Signal-Level AI can help you, connect with us at hi@simpli.fi.

Michael Schoen Chief Product & Technology Officer | Simpli.fi Michael Schoen is the Chief Product & Technology Officer for Simpli.fi. In this role, Michael has responsibility for engineering and product development. Most recently, he was the General Manager and Executive Vice President, Marketing Solutions at TransUnion / Neustar, where he was responsible for developing and perfecting a unified marketing intelligence platform that enables companies to win in the connected age. Michael oversaw the end-to-end system of identity, helping companies know everything they can about customers and prospects, create spectacular customer experiences, and analyze what worked and how to make it better. His leadership has been instrumental in architecting the industry’s most authoritative and real-time marketing platform, built on trusted identity across people, places, and things. Prior to joining Neustar in 2014, Michael was the EVP, Product at Cadreon, IPG’s cross-channel audience measurement, management and buying platform. Michael was responsible for driving the product strategy, development, and technology partnerships that enabled Cadreon’s offerings across all addressable media. Prior to joining Cadreon, Michael was General Manager, Advertising Platforms and VP, Product & Technology at LookSmart, where he was responsible for building out a paid search platform and a publisher syndication business. Michael holds an AB in Computer Science from Harvard College and an MBA from UCLA.