
Substack
CMS
WordPress
CMSSubstack and WordPress are both popular choices, but they serve different needs. Substack is a CMS with a traditional, manual approach to building, while WordPress is a CMS that prioritises developer or designer control.
Below you'll find a side-by-side breakdown of detection signals, AI scores, and technical fingerprints — plus our honest take on which builder wins for different use cases.
How we detect Substack vs WordPress — see our methodology: AI Influence Score calculation, evidence tiers, and fingerprint signal types.
| Category | CMS | CMS |
| AI Score | 20/100 — Traditional | 20/100 — Traditional |
| Detection Signals | 5 patterns | 10 patterns |
| Script Detection | 2 patterns | 3 patterns |
| CDN Detection | 1 domains | 1 domains |
| Header Detection | — | 2 headers |
| Sites Detected | 25 scans | 9,863 scans |
| Best For | Blogs & content-heavy sitesTry Substack → | Blogs & content-heavy sitesTry WordPress → |
| Official Website | Visit | Visit |
CMS
Substack is a cms with an AI Score of 20/100 (Traditional). Our detection engine uses 5 signal patterns to identify Substack-built sites.
CMS
WordPress is a cms with an AI Score of 20/100 (Traditional). Our detection engine uses 10 signal patterns to identify WordPress-built sites.
Substack is a newsletter-focused content management and publishing platform used primarily by independent writers, journalists, and media creators who monetize their content through paid subscriptions. The platform has a distinct technical footprint that makes it reliably identifiable: our detection engine recognizes Substack-powered sites through a combination of 2 script patterns, 1 CDN domain, 1 HTML pattern, and 1 meta tag pattern embedded in the page source. These signals — including characteristic script references tied to Substack's CDN infrastructure and specific HTML markup and meta tag conventions consistent across all Substack publications — allow for high-confidence identification regardless of whether a site uses a custom domain. Substack operates as a fully hosted platform, meaning publishers do not manage their own server infrastructure, which keeps the technical signature highly consistent and predictable across deployments. This uniformity makes Substack one of the more straightforward CMS platforms to detect accurately, as its front-end delivery relies on centralized assets that appear on every publication regardless of custom branding or domain configuration.
WordPress is an open-source content management system powering everything from personal blogs to large-scale enterprise websites, making it the most widely deployed CMS on the web and a primary target for accurate fingerprinting. AIWebsiteDetector.com identifies WordPress installations using a layered set of technical signals, including 3 distinct script patterns, 2 HTML structural patterns, 2 HTTP response headers, 2 meta tag patterns, and 1 CDN domain reference — collectively providing high-confidence detection across both default and heavily customized deployments. These signals typically manifest as characteristic markup in page source, identifiable request headers returned by the server, and script references tied to WordPress core or its content delivery infrastructure. Because WordPress supports thousands of themes and plugins that can obscure surface-level indicators, the multi-signal approach ensures reliable identification even when administrators attempt to minimize the platform's visible footprint. WordPress itself is free and open-source, but hosting costs vary widely — from shared environments to managed WordPress hosting — meaning the same CMS signature can appear across dramatically different infrastructure setups, a nuance the detection engine accounts for when evaluating header and CDN patterns.
/substackcdn\.com/i while WordPress uses /wp-content\/uploads/i — making CDN domain analysis one of the most reliable ways to distinguish them.Choose Substack if…
Choose WordPress if…
Our Pick — Based on 9,888+ detections
Detected 395× more often than Substack across our database of scanned sites.
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