What If You Could Target Mindset, Not Just Location?

As identity signals fade, brands and agencies are being forced to rethink how they target and convert audiences at scale. Seedtag’s NeuroX introduces a new approach, using AI to understand mindset not just location, potentially reshaping how local campaigns drive measurable outcomes.

If you are a multi-location brand looking to interact with customers while they’re in a buying frame of mind, Seedtag wants you to know about NeuroX. Its full name is Neuro-Contextual Exchange power by Liz AI, and it basically gives brands the right mindset along with targeting the right zip code. The promise is that NeuroX does not just zero in on people who happen to be nearby to get precision. It can do so at scale simultaneously across markets.

“It’s not category-level guessing, not zip-code spray,” said Joseph Meehan, Chief Exchange & Supply Officer at Seedtag. There is a connection between Neuro-Contextual targeting and store visits, regional demand signals, and local conversion behavior. “This is where NeuroX earns its keep,” he added.  “Our intent models are built to support mid- and lower-funnel objectives: store visits, time on site and local conversions. Neuro- Contextual is the foundational planning and buying layer across the exchange, and buyers or curators layer their addressable signals on top for targeting, measurement, and optimization.

“You don’t replace what works — you give it a stronger base to stand on. When the intent signal is there, we see up to a 35% lift in CTR and conversions versus baseline — and that’s the part local advertisers feel.”

Meehan sat down with StreetFight to explain more in-depth how it works.

With identity signals fading, many local marketers still rely on geo and behavioral targeting—how does NeuroX complement or replace those strategies?

Local marketers aren’t wrong to lean on geo- and behavioral-targeting — those are the tools they have. The problem is that signal loss has cut them off from more than half the audience, so behavioral has gotten quietly less reliable while everyone keeps pretending it hasn’t. NeuroX makes previously invisible inventory addressable by reading interest, emotion, and intent at the exchange layer — so a local plan keeps its scale in premium environments where the behavioral data isn’t there anymore. In the short term, that’s a complement: layer NeuroX over your existing geo and behavioral approach, and you stop losing the half-audience. Longer term, Neuro-Contextual becomes the foundation of planning, and the addressable signals layer on top of it, not the other way around.

How does NeuroX perform in local or regional news environments, where context can be highly nuanced or sensitive?

News is where the industry has struggled the longest, and it’s exactly where context matters most. For years the default response was broad blocklists — entire categories of news inventory pulled out of buys because keyword tools couldn’t tell the difference between coverage of a tragedy and coverage of a community recovering from one. That cost local publishers real revenue, and it cost local advertisers real reach.

What’s different with NeuroX is that Liz reads the actual nuance of what’s on the page — emotional tone, framing, intent — not just keywords. So, a regional brand can scale confidently in local news without layering on “safety” filters that don’t know the difference between sensitive content and content that simply shares keywords with something risky.

Underneath that, our Brand Safety and Brand Suitability models give each advertiser their own line on where they’re comfortable. It’s not one blunt category list applied to everyone — it’s tuned to what the brand actually wants. That’s how we keep buyers in local news at scale without sacrificing relevance or control.

Where does contextual intelligence outperform location-based targeting?

Honestly, location is fine for what location does — it tells you where a person is physically. What it doesn’t tell you is where they are mentally, and that’s where every interesting decision actually happens. In my 20+ years working in media, I’ve watched location get treated as a stand-in for intent, and it just isn’t one. Two people can sit at the same intersection and be in completely different mindsets — one researching luxury travel, the other reading about home fitness. Geo lumps them together. A media plan built on it misses both.

Can you give examples of how NeuroX unlocks previously “invisible” inventory for local publishers?

Local publishers have been telling me a version of this for years: their most engaging inventory often isn’t the most obvious page on the site. A small community sports recap, a recipe column, a how-to article — these don’t fit cleanly into standard advertiser taxonomies, but they can reach a reader in exactly the right frame of mind to act on a related offer.

CTV is increasingly important for local reach so how does NeuroX ensure relevance at the household or community level without identity-based targeting?

What we do in CTV is shift the focus from who is watching to what is being watched. Using Liz, we analyze the content itself, decoding Neuro-Contextual signals within the video stream. That lets us understand not just what a program is, but how it feels in the moment — tone, framing, emotional context.

By combining those CTV insights with what we already understand from the open web, we can enrich otherwise limited data signals and make smarter decisions about when and where ads should appear. The result is a consistent, privacy-first targeting layer that doesn’t lean on IP addresses or device IDs — which matters more every quarter, because traditional identifiers will keep fragmenting. For local advertisers planning across screens, that means precision and scale and stay on the table even as the device-ID side gets harder to count on.