Local SEO is the highest-intent surface in search. "Coffee near me," "best plumber in Miami," "urgent care open now" — buyers are minutes from a purchase or a call. The audit finds the leaks in that funnel.
Local audits used to be a Google Business Profile checklist plus a NAP consistency scan. In 2026 the audit has three layers. The classic local pack. Apple Business Connect and the map layer beyond Google. And the AI answer layer, where ChatGPT and Perplexity and Google AI Overviews increasingly answer "best near me" before the buyer sees a single map pin.
1. Google Business Profile
Completeness first. Primary category — the single highest-leverage field, get it wrong and no other fix compensates. Secondary categories. Hours, holiday hours, service area, attributes, products, services. Photos updated within the last 90 days. Q&A monitored and answered.
Check for suspensions and verification status. Check for duplicate listings — the second-most-common local audit finding. Confirm the profile is verified through the correct account and that account has the right ownership chain. Ownership disputes are a slow bleed most audits miss.
2. NAP consistency across the citation ecosystem
Name, address, phone. Consistent everywhere. Yext, Whitespark, or BrightLocal will surface inconsistencies across the citation ecosystem — Apple Business Connect, Bing Places, Yelp, Facebook, Foursquare, TripAdvisor for hospitality, Healthgrades for medical, Avvo for legal, industry-specific directories for everything else. Every mismatch is a signal to Google that the entity may not be authoritative.
3. Reviews
Volume, velocity, and recency. A location with 40 reviews and none in the last six months loses to a competitor with 12 reviews and three this month. Rating distribution. Keyword frequency in reviews — reviews are a semantic signal, and the vocabulary customers use is what the algorithm reads.
Response rate on both positive and negative reviews. Google's own guidance treats responses as an engagement signal. More important: the response is public content that future prospects and AI engines read.
4. Local landing pages and on-page
One page per location. Unique content on each — not a template with the city name swapped in. Embedded Google Map. LocalBusiness schema with the correct @type subclass — Restaurant, MedicalClinic, LegalService, LodgingBusiness. Address, phone, hours, geo coordinates, and openingHoursSpecification all in the schema. Reviews or aggregateRating where legitimately earned.
5. Local link and mention signals
Local news coverage, chamber of commerce listings, sponsorship pages, local blog mentions. These are the entity signals that separate a location that exists from a location that matters. An audit that only checks toxic backlinks is auditing defense. The local audit checks offense.
6. Apple Business Connect and the map layer beyond Google
Apple Maps drives the default map on every iPhone. Apple Business Connect is where that presence is managed and it is undersubscribed by most brands — meaning the audit finds a filled-out Google Business Profile and an empty Apple Business Connect. Waze, Bing Places, and the in-app maps inside Yelp and TripAdvisor round out the map layer.
7. The AI answer layer
Query the top 20 local buying prompts inside ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. "Best [category] in [city]." "[Category] near [neighborhood]." "Where should I get [service] in [city]." Log which businesses each engine names, from which sources, and whether the audited brand appears at all.
The engines cite from local news, Reddit threads, review aggregators, industry directories, and the brand's own site. If those sources don't say the brand is the answer, the AI engines don't either. The audit surfaces those citation gaps and the fix is content and PR, not just schema markup.
Deliverables
A prioritized fix list, a 30 or 60-day sprint plan, a monitoring dashboard tracking local pack rankings, review velocity, citation consistency, and AI mentions. Reruns quarterly. Local moves fast — competitors open, close, rebrand, and pile on reviews on a monthly cadence.
The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.
