Michigan · Detroit

Detroit dispensary AEO. Michigan's largest cannabis retail market, read differently by every AI assistant.

Detroit sits ahead of Grand Rapids by dispensary count, with the densest storefront footprint running from Corktown through Eastern Market and out the Woodward corridor. ChatGPT, Perplexity, Gemini, and Google AI Overviews each answer a Detroit cannabis query with a different short list. This page is what the answers look like today, and what changes once the $500 audit lands.

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Retail landscape

Three Detroit clusters the AI assistants distinguish.

Detroit is dense enough that a submarket-level query, not a city-level query, is what most shoppers type. Each cluster cites its own surface graph, and the coverage gaps cluster along with them.

Corktown
The west-of-downtown retail spine. The AI assistants surface Corktown stores on most Detroit city-level queries, and NAP divergence along Michigan Avenue is the most common coverage gap on a Detroit audit.
Eastern Market
The historic market district. The neighborhood-level citation graph around Eastern Market is the second most-cited Detroit surface in a practitioner sweep, and a missing schema.org/LocalBusiness prop on a wholesale-and-retail hybrid lets competitors own the answer.
Woodward corridor
The longest-running commercial spine in southeast Michigan. A Woodward Avenue address is the single most-cited Detroit surface in many sweeps, and a missing street-level schema on the corridor lets the model read your brand as absent.

AI answer-engine visibility

How Detroit dispensaries get named by the assistants.

The Detroit audit queries every prompt a Michigan cannabis shopper actually types. Three things Detroit owners should care about most: the queries that fire, the answers the assistants give back, and what the report changes.

Which queries Detroit owners should care about

Three shopper prompts that surface a Detroit dispensary, and a competitor.

  • "best dispensary near downtown Detroit"

    The signature where-can-I-find prompt a Detroit shopper types. ChatGPT and Google AI Overviews both answer it, and neither repeats the same dispensary twice. The citation graph on the result is sparse.

  • "Detroit recreational dispensary open late"

    A late-night flavored query that lands inside Perplexity and Gemini most consistently. Hours-and-distance is the axis the assistants read, and the city-level answer ignores your actual ZIP.

  • "dispensary Detroit MI with delivery"

    A delivery-flavored map-pack-adjacent query. The AI Overview sits above the local pack and reads the same citations, so a delivery-page schema gap reads as an AEO gap here too.

What the assistants currently surface

Three named competitors that own the Detroit answer this month.

Practitioner narrative: what a sample sweep surfaced this month, not a live model run. Named competitors and the surfaces doing the work.

Owns the answer
House of Cannabis

Surface doing the work

houseofcannabis.net/menu. schema.org/Product on every SKU

Why the assistants cite it

Structured menu, a Wikidata tie, and a fresh GBP make up the citation triple the assistants reward most often on Detroit city-level queries.

Owns the answer
SKYMINT

Surface doing the work

skymint.com/locations/detroit. Parent entity page plus a per-store page

Why the assistants cite it

Multi-license brand-level entity work carries weight in Gemini and Google AI Overviews when a shopper asks what dispensaries a brand operates in Detroit.

Owns the answer
Bloom Cannabis

Surface doing the work

bloomcannabisco.com. Multi-store Livingston-county brand

Why the assistants cite it

A city-edge brand whose NAP reads as Detroit across the assistant layer. The brand captures Detroit-adjacent ZIP queries without a Detroit storefront, and the audit names it.

What changes once the audit lands

Three shifts the report produces on a Detroit dispensary.

A citation map you can name by submarket
Every Detroit query that currently names a competitor becomes a Finding row in the audit. The report names which submarket the citation owns, which surfaces get cited, and which surfaces your dispensary is invisible from.
A menu the assistants will lift from
schema.org/Product on every SKU. Strain, THC%, terpene profile, and price live in the JSON-LD. Once the menu is quotable, two of the four assistants land inside 30 to 60 days.
A NAP record the entity graph agrees with
A single canonical record a citation vendor can reconcile to. The Detroit-specific permutations of your store name stop reading as two dispensaries to the model.
“Detroit is dense at the storefront level, but the AI answer changes by submarket. The audit's job is to name the submarket you should care about, the competitor that owns the answer there, and the surface that needs to ship to take it back.”
— Randi Bagley, dispensaryAEO

Michigan markets we serve

Five Michigan cities. One geo landing page per market.

Grand Rapids and Detroit are the first two of five Michigan geo landing pages on the same template. Ann Arbor, Lansing, and Kalamazoo land on the same template, with the cluster names, license tier, and AI narrative swapped per city.

  • Grand Rapids

    Coming soon

  • Detroit

    Coming soon

  • Ann Arbor

    Coming soon

  • Lansing

    Coming soon

  • Kalamazoo

    Coming soon

$500 audit · Detroit-specific · ~2-week turnaround

Get the Detroit audit. The $500 report is yours regardless.

Two weeks. Every Detroit prompt a Michigan cannabis shopper types. A written citation-gap report naming which assistants cite your dispensary, and which competitors own the answer.

Get my $500 audit

Budtender, owner, or marketing lead. Any of you can submit.