YouTube Video
Brands with thousands of locations show up in Google's top three about 36% of the time. ChatGPT recommends those same locations 1.2% of the time. Same stores, same brands, and a billion people a day are now asking AI where to go.
In this video, I break down why AI skips the biggest multi-location names in the country, how it actually decides which location to recommend, and the corporate versus local franchise fight that's been holding this back for years. I also run a live demo asking ChatGPT for an auto shop near me, where not one of the big national brands got recommended.
This is the same approach my team uses to help multi-location brands get found as search moves out of Google and into AI. If you run more than one location and you're not sure how you're showing up, this is where to start.
You will learn:
— Why AI often writes its own search query with brand names before it looks anything up, and what that means for you
— Which signals actually move local visibility now: review recency, response rate, star ratings, and photos, all managed location by location
— Why turning local operators loose backfires, and how one rogue listing can trigger FTC fines over $50,000 each
— The three things corporate and local teams must put in writing so every location shows up without corporate losing control
Chapters:
00:00 — Introduction
01:02 — Chapter 1: How Corporate vs Local Franchise Ownership Actually Works
03:36 — Chapter 2: Why Franchisees Are Suing Corporate
05:17 — Chapter 3: How AI Picks Local Businesses to Recommend
10:15 — Chapter 4: Why Disconnected Local Marketing Backfires
13:17 — Chapter 5: Multi-Location Marketing at Scale
Want to see how your brand shows up? Put your brand name into Ubersuggest and it will show you where you appear, where competitors appear, and where the gap is.
If you manage multiple locations and want help closing that gap at scale, go to npdigital.com and talk to our team.
In this video, I break down why AI skips the biggest multi-location names in the country, how it actually decides which location to recommend, and the corporate versus local franchise fight that's been holding this back for years. I also run a live demo asking ChatGPT for an auto shop near me, where not one of the big national brands got recommended.
This is the same approach my team uses to help multi-location brands get found as search moves out of Google and into AI. If you run more than one location and you're not sure how you're showing up, this is where to start.
You will learn:
— Why AI often writes its own search query with brand names before it looks anything up, and what that means for you
— Which signals actually move local visibility now: review recency, response rate, star ratings, and photos, all managed location by location
— Why turning local operators loose backfires, and how one rogue listing can trigger FTC fines over $50,000 each
— The three things corporate and local teams must put in writing so every location shows up without corporate losing control
Chapters:
00:00 — Introduction
01:02 — Chapter 1: How Corporate vs Local Franchise Ownership Actually Works
03:36 — Chapter 2: Why Franchisees Are Suing Corporate
05:17 — Chapter 3: How AI Picks Local Businesses to Recommend
10:15 — Chapter 4: Why Disconnected Local Marketing Backfires
13:17 — Chapter 5: Multi-Location Marketing at Scale
Want to see how your brand shows up? Put your brand name into Ubersuggest and it will show you where you appear, where competitors appear, and where the gap is.
If you manage multiple locations and want help closing that gap at scale, go to npdigital.com and talk to our team.
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