u/gillygangopolus

I built Stackra, a website grader for small businesses. So many of the major website audit tools focus on speed, CVW, and toss in a few add more backlinks recommendations.

Here's the thing.

If you're building a plumbing website in Brooklyn, NY you don't need backlinks.

You don't actually need to worry about CVW (your site likely doesn't get enough traffic to qualify for CrUX).

The speed of your site is only important on mobile.

What you need is a clean hero, quality CTA's, user friendly forms, GBP optimization (NAP).

Stackra detects your platform, bases the recommendations on your business type, and gives you a comprehensive review from three perspectives (CMO - Conversion and Trust, SEO - Search Visibility, and CTO - Technical Confidence).

If you're using GA/GSC/BingWM, you can tie those in with one click (all visible in one dashboard).

I've also built a dataset with records on over a million US websites, broken down by category/subcategories, platforms, tools, and more.

Check it out, let me know what you think!

I built Stackra, a website grader for small businesses. So many of the major website audit tools focus on speed, CVW, and toss in a few add more backlinks recommendations.

Here's the thing.

If you're building a plumbing website in Brooklyn, NY you don't need backlinks.

You don't actually need to worry about CVW (your site likely doesn't get enough traffic to qualify for CrUX).

The speed of your site is only important on mobile.

What you need is a clean hero, quality CTA's, user friendly forms, GBP optimization (NAP).

Stackra detects your platform, bases the recommendations on your business type, and gives you a comprehensive review from three perspectives (CMO - Conversion and Trust, SEO - Search Visibility, and CTO - Technical Confidence). It then gives you 10-12 actual recommendations with walkthroughs on how to implement the solutions.

If you're using GA/GSC/BingWM, you can tie those in with one click (all visible in one dashboard).

I've also built a dataset with records on over a million US websites, broken down by category/subcategories, platforms, tools, and more. If you're looking to see what other businesses are using for their sites, it's a great place to start.

Check it out, let me know what you think!

I built Stackra, a website grader for small businesses. So many of the major website audit tools focus on speed, CVW, and toss in a few add more backlinks recommendations.

Here's the thing.

If you're building a plumbing website in Brooklyn, NY you don't need backlinks.

You don't actually need to worry about CVW (your site likely doesn't get enough traffic to qualify for CrUX).

The speed of your site is only important on mobile.

What you need is a clean hero, quality CTA's, user friendly forms, GBP optimization (NAP).

Stackra detects your platform, bases the recommendations on your business type, and gives you a comprehensive review from three perspectives (CMO - Conversion and Trust, SEO - Search Visibility, and CTO - Technical Confidence).

If you're using GA/GSC/BingWM, you can tie those in with one click (all visible in one dashboard).

I've also built a dataset with records on over a million US websites, broken down by category/subcategories, platforms, tools, and more.

Check it out, let me know what you think!

I recently got a fun warning from Bing about my indexing strategy. I had generated a large set of analytics pages that I never intended to rank.

My thinking was:
noindex = don't index
follow = still let search engines discover useful links and content for citations and whatnot

Turns out that was the wrong approach. Bing still crawled hundreds of those pages before seeing the noindex, and that unnecessary crawl activity contributed to reduced crawling elsewhere on the site.

The lesson wasn't just "use nofollow." It was to avoid exposing large volumes of low-value URLs in the first place. Keep them out of sitemaps, don't surface them through internal navigation if they don't need to be discovered, and use noindex only when search engines actually need to access the page.

https://preview.redd.it/xfxu8izttxah1.png?width=877&format=png&auto=webp&s=dd64e507789ef204593028be92efddef543aa85a

I was tinkering with mine before I quickly burned through credits. It’s flaky, but with some prompts a little scary how much it can tell you in a few minutes.

Save this in your shortcuts (click the ...settings on the upper right of Claude in Chrome). Create a prompt, make sure to target the homepage. Save.

Open a new window and run. Holy smoke Batman.

PROMPT — Start

You are an SEO/AEO/GEO auditor. Audit this site as an AI/search crawler would see it.

Ground rules:

- If data does not exist, do not cite it. If an expected function is missing, flag it. Be direct and critical; back every judgment with something you actually retrieved.

- You are auditing what a NON-JS bot sees. Do not score client-rendered state.

- Two layers, kept separate:

- RAW HTML = the server's initial response before the page's own scripts run. This is what bots and AI crawlers index. It is authoritative for title, meta, and JSON-LD.

- RENDERED DOM = the page after JavaScript. Use it ONLY to sanity-check structure (headings, visible copy) and to catch your own extraction errors. Never quote meta/schema from here.

- How to get RAW HTML without running the page's scripts: fetch the URL and read the response text (a fetch returns the served HTML and does NOT execute the fetched page's JS). If you cannot obtain the raw response for a URL, say so for that URL and mark its head-dependent lines n/a — do not substitute the rendered DOM.

- If a value looks broken or cut off mid-word (e.g. "Stackra" where "Stackra's" is expected), suspect your own extraction first. Read the attribute as the raw bytes between the outer double quotes — do not split on inner quotes/apostrophes. Re-check against the rendered DOM before calling it a site defect.

- Record the audit date. Note that the live site may lag the source repo; findings reflect the deployed build, not current code.

Step 1 — Sample.

Pull /sitemap.xml. If more than 50 URLs, audit a representative sample: the homepage, up to 15 money/conversion pages, up to 5 blog posts (if a blog exists), up to 5 product/platform pages (if they exist), and a spread of remaining templates. Avoid auth/admin/disallowed paths. List the exact URLs you audited before scoring.

Step 2 — Extract (per page, from RAW HTML).

Quote verbatim: <title> (+ char count, including any " | Brand" suffix), <meta name="description"> (+ char count), and every <script type="application/ld+json"> block's u/ type value(s). Then record H1(s), the H2/H3 outline, and the 5–10 keywords/long-tail phrases that literally appear in the title, H1, meta, and section headings (do not invent intent — only terms present in the markup).

Step 3 — Score. Show points earned per line, and cite the specific evidence for each.

SEO — 40 pts

- Title tags: keyword-forward, unique, under 65 char total incl. brand suffix (10)

- Meta descriptions: present, unique, under 155 char, with a value prop (5)

- H1 present and topical (one or many is fine per Google) + logical H2/H3 hierarchy (10)

- Internal linking + descriptive URLs (5)

- Core schema present and valid for the page type, e.g. Organization/WebSite site-wide, BlogPosting on articles, FAQPage where Q&A exists (10)

AEO — 30 pts

- Homepage hero communicates purpose above the fold (10)

- Content pages open with a direct 40–80 word answer to the page's implied query (10)

- Question-style headings that match real search queries (5)

- FAQPage/HowTo schema present where the content supports it (5)

GEO — 30 pts

- Citable: concrete stats, dates, named sources, author attribution (10)

- Page delivers on its own promise: the body actually answers the query the title/H1/meta advertise, no bait-and-switch (10)

- AI-crawlable: robots.txt blocks no major AI bot (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) AND the scored content is present in the RAW HTML, not JS-only (10)

Scoring of unverifiable lines: if you could not retrieve the evidence for a line (e.g. raw head unavailable, robots.txt unreachable), mark it n/a, drop its points from that section's denominator, and normalize. Example: meta desc (5) n/a → score SEO out of 35, then scale to 40. Never award partial credit as a hedge for missing data, and never dock a page for your own retrieval gap.

Scoring rule: score only what you observed on the sampled pages. Do not infer defects from the site's own blog, changelog, or marketing copy.

Step 4 — Output exactly:

AUDIT DATE: [date] | PAGES SAMPLED: [n]

OVERALL: [X]/100

SEO: [X]/40 ▓▓▓▓▓░░░░░

AEO: [X]/30 ▓▓▓▓▓▓░░░░

GEO: [X]/30 ▓▓▓░░░░░░░

Grade: A / B / C / D / F

What's working — 3 bullets, each citing a specific page + observation.

Top 5 fixes ranked by impact — each: page, the problem, the one-line fix, which score it lifts.

Per-page table — URL | SEO /10 | AEO /10 | GEO /10 | biggest observed issue. (Per-page columns are each normalized to /10; the site sub-scores above use the full 40/30/30 rubric — they will not sum identically, that is expected.)

Rules: every score cites what you actually saw. No scores without evidence. Do not rewrite content or emit JSON-LD in this pass — diagnostic only. Any n/a line must say why.

PROMPT — End

I've sliced myself a dataset with about 1.2 million "cleaned" US websites in BiqQuery. Seeing lots of questions on FAQ Schema, and figured I'd drill down a bit. Happy to answer any questions on how this was obtained.

Corpus (~1.2 million US websites, HTTP Archives/CrUX/Overture/Wappalyzer)

Platform	n	FAQ % (n true)	LocalBusiness % (n true)	Organization % (n true)	Schema desc % (n true)
Duda	34,242	4.9% (1,666)	26.2% (8,985)	4.0% (1,376)	29.3% (10,022)
Webflow	19,835	3.6% (708)	9.3% (1,835)	18.3% (3,637)	29.0% (5,760)
WordPress	505,521	3.0% (15,253)	9.6% (48,524)	62.9% (317,752)	69.3% (350,359)
Shopify	72,063	2.1% (1,491)	2.4% (1,764)	82.7% (59,578)	12.2% (8,802)
BigCommerce	4,840	1.9% (93)	4.6% (223)	12.9% (623)	8.4% (408)
Wix	100,061	0.7% (662)	56.8% (56,863)	2.2% (2,218)	5.0% (5,001)
Squarespace	89,196	0.6% (576)	80.5% (71,825)	47.7% (42,574)	12.2% (10,873)
Weebly	19,674	0.2% (46)	1.1% (208)	0.9% (186)	1.6% (308)
GoDaddy	22,186	0.0% (1)	57.0% (12,645)	0.4% (99)	0.1% (21)

Takeaways:

• FAQ schema is a non-event everywhere, but WordPress/Webflow/Duda lead at 3-5%, while GoDaddy is essentially zero (1 out of 22,186 sites) and Weebly is barely above it (0.2%). Builder-tier platforms basically never expose FAQ schema, whether by template limitation or by users never finding the setting.
• LocalBusiness schema is a platform-default story, not a behavior story. Squarespace (80.5%), GoDaddy (57.0%), and Wix (56.8%) auto-inject LocalBusiness schema into their templates — that's why DIY builders dominate this metric even though they trail everywhere else. WordPress and Webflow, despite being "more SEO-capable" platforms, sit at under 10% because LocalBusiness isn't a default and requires a plugin/manual setup.
• Organization schema is a WordPress and Shopify story. Shopify auto-emits Organization schema for nearly every store (82.7%), WordPress hits 62.9% (likely Yoast/RankMath plugin defaults), and everyone else falls off a cliff — Wix, Weebly, GoDaddy all under 5%.
• Schema descriptions split cleanly along CMS vs. site-builder lines. WordPress leads at 69.3% (again, SEO plugin ecosystem), Webflow/Duda sit around 29%, and the no-code builders (Wix, GoDaddy, Weebly) are all under 5%.

Started out with a question, how do I spend $300 in free GCC credits, and how much could I do with it. I started with figuring out how to query HTTP Archives, pulling CRuX data to correlate sites, and learning a bit about BigQuery along the way. I went from ~12 million total sites and pared that down to 1.5 million that I could verify were live, had enough data to be able to classify/categorize, and then built a front end to access the highlights.

So far, I've been focused on identifying key business segments with missing opportunities, classic one click misses, some schema mapping for business type, and wondering why in the world any sane business owner would use Weebly.

What would YOU want to know?

I’ve cleaned a website corpus from about 11 million to 1.5 million US sites that are categorized by business type and platform.
What would you want to know first?