All playbooksIndustry

AEO for Local & Multi-Location Brands

A location-first plan to win "near me" and city-level recommendations across AI assistants and AI-powered local search.

Be the local answer AI assistants recommend nearby

Checkpoints

Timeframe

60 days

Built for

Local businesses, franchises, and multi-location marketing teams

Get Started for Free Check AI Visibility

What you will achieve

Citations on local and "near me" intent
Complete LocalBusiness schema with geo and hours
Consistent NAP and entity signals everywhere
Location pages built for extraction
Per-location share of voice tracking

SearchFit features used:AI Visibility TrackingGeo AuditContentSignalsTechnical Audit

Phase 0110 checkpoints

Local foundation audit

Get the local signals right before chasing content.

Run a geo audit on each location's homepage and location page.
Add LocalBusiness schema with address, geo, phone, and hours.
Ensure NAP is identical across site, profiles, and directories.
Claim and complete your Google Business Profile per location.
Add sameAs links to every local profile and directory.
Confirm AI crawlers can access location pages.
Add a map embed and clear directions on contact pages.
Validate schema and fix missing recommended fields.
List opening hours in both schema and on-page text.
Publish llms.txt pointing to location and service pages.

Phase 0210 checkpoints

Local question research

Map what people ask AI when choosing a nearby provider.

List the services and the "near me" questions for each market.
Test "best [service] in [city]" prompts across engines.
Log who gets cited per location and service.
Identify the local directories and review sites models prefer.
Tag prompts by service line and neighborhood.
Benchmark citation rate vs local competitors.
Note where reviews dominate the answer.
Prioritize the highest-revenue local prompts.
Capture seasonal and event-driven local demand.
Baseline local AI-referral traffic in analytics.

Phase 0310 checkpoints

Location & service pages

Build pages assistants can quote for each market.

Create a dedicated, unique page for every location.
Open with the services, area served, and a direct recommendation.
Add local proof: reviews, case studies, and community ties.
Answer local FAQs (parking, hours, booking, coverage).
Avoid duplicate boilerplate across locations.
Include service-area and neighborhood specifics.
Add structured data for services and reviews.
Link locations to relevant service pages.
Keep content current as offerings change.
Ensure each page is crawlable and server-rendered.

Phase 0410 checkpoints

Reviews & reputation

Local reputation is decisive for AI local recommendations.

Build a steady stream of genuine, specific reviews per location.
Respond to reviews factually and promptly.
Encourage reviews that mention services and outcomes.
Aggregate review themes into location FAQ answers.
Maintain accurate profiles on the directories models cite.
Resolve inconsistent listings and duplicates.
Surface review content in crawlable HTML.
Highlight awards and local recognition.
Monitor sentiment per location.
Track which reviews appear in AI answers.

Phase 0510 checkpoints

Track per location & scale

Manage AEO across many locations with one loop.

Track citation rate and share of voice per location.
Use Signals to prioritize fixes by location impact.
Re-test local prompts every 30 days.
Alert on competitor gains in priority markets.
Roll out winning location-page patterns to all sites.
Standardize schema and NAP across new locations.
Correlate local AI traffic with bookings and revenue.
Keep hours and offerings current everywhere.
Expand prompt coverage as you enter new markets.
Report per-market citation growth to operators.

Frequently asked questions

Increasingly. People ask assistants for nearby recommendations, and AI-powered local search rewards complete schema, consistent NAP, and strong reviews.

Complete LocalBusiness schema, consistent NAP, and an active review program usually move local citations fastest.

Standardize schema and page patterns, then track citation share per location and prioritize with Signals.

The Geo Audit checks your local signals, and tracking shows per-location share of voice so you fix the right markets first.