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Best Buy Isn't Even a Showroom for Amazon Anymore

Patrick Duggan
Mar 12
5 min read

# Best Buy Isn't Even a Showroom for Amazon Anymore

**Published:** March 12, 2026

**Author:** Patrick Duggan, DugganUSA LLC

**Category:** AIPM / Analysis

For years, the knock on Best Buy was that it was Amazon's showroom. Customers would walk in, touch the TV, ask the questions, then buy it on their phone for $30 less while standing in the aisle.

That was a burn. But at least it meant people showed up.

The new problem is worse: AI models don't show up at all. And Best Buy's website can't tell them why they should.

We Audited the Entire Best Buy Estate

We ran MedusAIPM — our AI Presence Management tool — against every Best Buy domain we could find. MedusAIPM queries GPT-4o, Gemini, and Perplexity directly, then crawls your website for structural AI-readiness. Combined score out of 95.

|--------|----------|-----------|---------|---------------|-----------|

| **bestbuy.com** | **42/95** | **3/95** | 0 | 0 | 0 |

| **geeksquad.com** | **41/95** | **3/95** | 0 | 0 | 0 |

| **bestbuybusiness.com** | **57/95** | **37/95** | 5 | 35 | 20 |

| **corporate.bestbuy.com** | **61/95** | **60/95** | 80 | 60 | 95 |

| **bestbuyhealth.com** | **69/95** | **85/95** | 80 | 75 | 95 |

Read that table again.

The corporate site has LD-JSON at 80. Meta tags at 95. Semantic HTML at 60. Someone on the corporate communications team actually implemented Schema.org structured data, OpenGraph tags, and proper HTML semantics.

The health vertical — bestbuyhealth.com — is even better. Structure score of 85. LD-JSON at 80. Meta tags at 95. Semantic HTML at 75. Somebody did the work. Somebody knew what they were doing.

And then nobody — *nobody* — carried that work to bestbuy.com or geeksquad.com. The two domains that actually make the money. The two domains that 90,000 employees and $43 billion in revenue depend on.

Structure score: **3**.

The Competence Theater

This isn't a capability gap. The people who built corporate.bestbuy.com and bestbuyhealth.com clearly know how to implement structured data for AI crawlers. They literally did it. The Schema.org markup exists. The OpenGraph tags exist. The semantic HTML exists. On two domains that almost nobody visits.

The flagship store — the one with 19.2% market share in consumer electronics, the one customers actually use — has none of it. Zero LD-JSON. Zero semantic HTML. Zero meta tags. The robots.txt didn't even parse.

This is what competence theater looks like. The capability exists inside the building. It just never made it to the product that matters.

What AI Models Actually Say About Best Buy

GPT-4o knows who Best Buy is. Everyone does — it's a household name. Awareness score: 85/95. But when asked "would you recommend bestbuy.com?" GPT gave it a **3 out of 10 confidence rating**:

> *"My confidence in recommending BestBuy.com for a specific industry would be around 3 out of 10."*

Three out of ten. For the largest specialty consumer electronics retailer in the world.

Perplexity was kinder — 10/10 confidence, but with a critical caveat: it would only recommend Best Buy for consumer electronics specifically, and flagged their "narrow focus" as a limitation.

Gemini refused to recommend at all: *"As an AI, I do not have personal opinions or the ability to recommend companies."*

Best Buy's AIPM-NPS (Net Promoter Score from AI models) is **33**. For context, that's the same as Kohl's. A $43 billion technology company has the same AI recommendation score as a department store.

The Amazon Showroom Problem, Evolved

The old showroom problem was physical: customers used Best Buy stores to evaluate products, then bought elsewhere. Best Buy's response was price matching. It worked — sort of.

The new problem is digital and invisible. When someone asks ChatGPT "what's the best place to buy a TV?" or "should I get my laptop repaired at Geek Squad?" — the model doesn't visit bestbuy.com. It checks what it knows. And what it knows is built from:

1. **Training data** — a snapshot that goes stale

2. **Web crawling** — which requires structured data to be useful

3. **Real-time search** — which pulls meta tags, LD-JSON, and semantic markup

Best Buy's training data is fine today. Everyone knows who they are. But when GPT-5 and Gemini 3 re-crawl the web and rebuild their knowledge? Best Buy's site gives them *nothing* to work with. Literally zero structured data on the flagship domain.

Amazon's site, by contrast, is a machine-readable paradise. Every product has Schema.org markup. Every category has structured data. Every page has OpenGraph tags.

Best Buy used to be Amazon's showroom. Now it's not even that. It's becoming invisible to the systems that are replacing search entirely.

Geek Squad: The $43 Billion Company's Free Offering

Geek Squad is Best Buy's services arm — installation, repair, tech support. It's the thing that's supposed to differentiate Best Buy from Amazon. You can't get a Geek Squad tech from a cardboard box.

geeksquad.com scores **41/95 combined** with a structure score of **3/95**. Zero. Across the board.

The service that is supposed to be Best Buy's competitive advantage over pure e-commerce has the same AI presence as a parked domain.

When someone asks an AI model "should I use Geek Squad or an independent repair shop?" — the model has nothing from geeksquad.com to inform its answer. No structured data describing their services. No FAQ schema answering common questions. No Organization schema explaining who they are.

Meanwhile, every independent repair shop with a WordPress site and a Yoast SEO plugin has better structured data than a Fortune 500 company's flagship service brand.

The Fix Is Embarrassingly Simple

Here's the thing that makes this painful: the fix takes an afternoon.

We know, because we did it. DugganUSA — a two-person startup with zero revenue — has a structure score of 86/95 across our public pages. We added Organization LD-JSON, FAQPage schema, OpenGraph tags, semantic HTML, and proper meta descriptions in a single session.

Best Buy's corporate team already knows how. They proved it on corporate.bestbuy.com (60/95) and bestbuyhealth.com (85/95). Someone just needs to copy the pattern to the domains that actually make money.

Estimated effort: one developer, one afternoon, five domains.

Estimated cost of not doing it: ask the AI models in 18 months.

Audit Your Own Domain

MedusAIPM is in enterprise beta. If you want to know how AI models see your brand before they re-crawl:

**API:** `POST analytics.dugganusa.com/api/v1/aipm/audit`

**Free tier:** [epstein.dugganusa.com/pricing](https://epstein.dugganusa.com/pricing)

Your website might be a showroom for nobody.

*MedusAIPM is Patent #102 in the DugganUSA portfolio. Part of the MEDUSA product suite.*

*DugganUSA LLC | Saint Paul, Minnesota | dugganusa.com*

**Methodology:** All audits conducted March 12, 2026 using MedusAIPM v1.0.0. AI perception scores from GPT-4o, Gemini 2.5 Flash, and Perplexity Sonar. Structure scores from automated homepage crawling. Combined = 60% perception + 40% structure. Epistemic cap: 95/95.

*Her name was Renee Nicole Good.*

*His name was Alex Jeffery Pretti.*