Walk into almost any marketing meeting and you will still see reports built around website sessions, impressions, and campaign ROAS. Meanwhile, your customers are in their cars asking their phones for “gas near me with clean bathrooms” or “24-hour convenience store with hot food.”
The new “digital shelf” for convenience retail sits in maps, AI assistants, and “near me” results. If your locations do not appear there with accurate, rich information, you are invisible at the exact moment a visit is up for grabs.
This article looks at how that discovery stack works today. Then it lays out a practical plan for making every store in your network digitally searchable, current, and AI ready.
Local Discovery has Shifted to Maps and AI Assistants
Local search is no longer a side channel. It is the front door.
Recent data shows
- Around 40% of Google searches have local intent
- Over 1.5 billion searches every month include “near me” wording
- 98% of US consumers search for local businesses online, many doing so multiple times a week
- 86% of people look up the location of a business in Google Maps before visiting
For gas stations and C-stores, that behavior is even more pronounced. Drivers already have maps open. They browse pins, prices, photos, and ratings while sitting at a red light. Maps results and AI answers effectively are your forecourt signage.
At the same time, AI assistants are stepping in between customers and search results. People increasingly ask tools like ChatGPT, Gemini, and other AI agents to “find a gas station with diesel, open 24 hours, on my route” instead of manually scrolling through pins. These tools scan maps, local listings, reviews, and increasingly structured feeds to pick a small set of recommendations.
If your store data is thin, outdated, or inconsistent, you will lose to the brand that invested in getting this right.
How “near me” and AI Ranking Really Work for C-stores
No one outside the major platforms has the full algorithm. Still, most rankings for local gas and convenience searches revolve around three pillars.
1. Relevance to the Query
Does your digital footprint clearly say what you offer
- Fuel types
- Car wash
- EV charging
- Foodservice categories
- ATM, lottery, money services
- Seating, Wi-Fi, restrooms
AI agents and maps crawlers are trying to match intent. If the user asks for “E85 near me” and your listing never mentions E85, you will not be considered, even if you sell it.
2. Proximity and Convenience
For “near me” queries, distance still matters. One study found that 72% of consumers visit stores within a five-mile radius after a local search.
For a category like gas and convenience, routing and on-the-way convenience matter as much as raw distance. That makes correct geolocation, entrance placement, and routing notes important. “Right off exit 12” can be the difference between a visit and a pass.
3. Prominence and Trust Signals
AI assistants and map packs lean hard on trust features
- Review volume and star rating
- Photo quality and recency
- Listing completeness
- Consistent hours and attributes across sources
“Near me” queries have grown more than 900% in recent years. Customers trust complete, well maintained profiles more than sparse ones.
For C-stores, that means a store with updated photos, clear attributes, and steady reviews will win attention even if fuel prices are similar.
What Makes a C-store Location “AI Readable”
Think of AI agents as very fast, very picky shoppers. They do not guess. They promote locations that are clear, consistent, and well documented.
To be AI readable, each store needs four layers of data working together.
1. Clean NAP and Core Listing Data
At a minimum, every location should have
- Accurate name, address, and phone (NAP)
- Correct map pin and entrance location
- Verified hours, including holiday rules
- Category tags that match real services (gas station, convenience store, car wash, etc.)
This sounds basic. In practice, many C-stores inherit messy data from legacy systems, acquisitions, and franchise structures.
2. Rich Attributes that Match Real Trips
C-store trips are highly purpose driven. Coffee on the way to work. A bathroom and snack stop on a road trip. A quick grocery fill-in. Your attributes need to reflect those jobs
- Amenities. Restrooms, seating, Wi-Fi, air pump, vacuum, EV charging
- Safety and access. Well lit, 24-hour, staffed, security cameras
- Food and beverage. Fresh food program, made to order, grab-and-go, branded QSR partners
- Payments. Mobile wallets, fleet cards, loyalty programs
Most maps platforms support these details inside their listing structures. AI assistants are already reading them.
3. High Quality, Current Visuals
Visuals are not just for human shoppers. They increasingly feed models that summarize your store offering.
Research suggests that video will account for much of AI search visibility by 2030, with assistants pulling clips, highlights, and answers from video libraries.
For C-stores, that means
- Exterior shots that show pumps, entrances, and signage
- Interior photos that clarify cleanliness, assortment, and food quality
- Short videos touring the store, highlighting foodservice, and confirming real conditions
A text listing that says “clean restrooms” carries less weight than a 20-second video recorded last week showing them.
4. Structured Feeds, Not One-off Updates
This is where a CRSTBL-style feed enters the picture. Instead of hand editing 200 Google Business Profiles and hoping other platforms catch up, you maintain one structured, machine-readable feed that contains each store’s current truth
- Today’s hours and closures
- Active promos and fuel discounts
- Current food offerings and dayparts
- Service status. Car wash down, EV chargers full, kitchen closed
AI agents, search engines, and partner apps can read this feed directly. That turns your locations from “static listings” into living data sources.
Why Video is the New Price Sign at the Street
On the street, your price sign and canopy do the heavy lifting. In AI driven discovery, video plays a similar role.
Video does three things text and still images struggle to do
- Prove reality
- A quick store walkthrough filmed yesterday gives stronger confidence than a three-year-old photo.
- Convey atmosphere
- Lighting, cleanliness, staff behavior, and queue length all show up instantly.
- Answer common questions in context
- “What does your hot case look like at 7 a.m. on weekdays”
- “Can I easily pull in with a trailer”
As AI agents learn to parse and summarize video at scale, they will increasingly draw on this content when answering “best gas station near me for clean bathrooms” or “late-night food near me on this route.”
If your competitors have a library of short, structured clips and you have a logo and a few exterior photos, you know who AI will favor.
Building a CRSTBL-style feed for every store
For CMOs and operators, the idea of maintaining all this data manually is a nonstarter. The only sustainable approach is to treat store information as a product, not an afterthought.
A CRSTBL-style approach looks like this
- Create a single source of truth
- Central database or platform that holds every attribute for every location.
- Clear owners for fuel data, foodservice, hours, and promos.
- Standardize the schema
- Decide which fields matter for discovery, AI agents, and partners.
- Map those fields to Google, Apple, Waze, Yelp, and other platforms.
- Automate updates
- Connect POS, price signs, and back-office systems where possible.
- Use simple store-level workflows for quick updates. Closed pumps, out-of-order car wash, temporary kitchen shutdown.
- Generate AI-ready content
- Script and capture short, repeatable videos by location type.
- Attach metadata to each clip. Store ID, date, time of day, featured departments.
- Feed that content into your central system so AI agents can connect it to each store.
- Monitor how you appear in AI and maps
- Regularly check how your brand shows up in Google Maps, Apple Maps, Waze, and AI assistants for key “near me” phrases.
- Track where AI is recommending competitors over you and look at the underlying data gap.
This is exactly the kind of problem CRSTBL is built to solve. A central feed that keeps stores “AI current” without turning marketing and ops teams into full-time listing managers.
A Practical Rollout Plan for Operators
If you are responsible for a chain of 10 or 500 stores, a practical plan matters more than theory. Here is a phased approach that fits most C-store organizations.
Phase 1. Get the Basics Right for Your Top 20% Stores
- Audit NAP, hours, and pin placement for your highest volume or flagship locations.
- Fix obvious errors and claim any unverified profiles.
- Add at least five good photos per store. Exterior, interior, restrooms, food, and forecourt.
This alone will often lift visibility and conversion on maps searches.
Phase 2. Standardize Attributes and Amenities
- Define a clean list of attributes you want every store to carry.
- Roll out a simple form or integration for store managers to confirm.
- Prioritize categories that drive high intent searches. EV charging, car wash, hot food, restrooms.
Phase 3. Introduce Lightweight Video for Priority Clusters
- Start with one region or banner and film short, consistent clips.
- Post them where you already manage content, then work toward a structured feed.
- Track changes in engagement from maps views and direction requests before and after.
Phase 4. Move Toward a Live Data Feed
- Centralize your store data in one platform.
- Set up scheduled syncs to major maps and listing partners.
- Add hooks so AI agents and partners can read that feed in near real time.
Owning the Digital Forecourt
Local search is no longer just an SEO problem. It is a revenue and guest share problem.
When
- Near me searches number in the billions each month
- Most customers check maps before choosing where to stop
- AI assistants increasingly act as gatekeepers to those choices
Then the question for C-store leaders is simple.
Will your brand show up as a clear, trusted, well documented option when a driver asks for their next stop?
Brands that treat store data, video, and structured feeds as core marketing assets will win more than better reporting. They will win incremental visits at the pump, higher basket sizes inside the store, and stronger loyalty over time.
You already invest in signage, merchandising, and in-store experience. The next step is to make sure the digital shelf at the gas pump tells the same clear, current story, every single day.
