{
  "@type": "Article",
  "author": {
    "name": "AI Visibility Solutions",
    "@type": "Organization"
  },
  "@context": "https://schema.org",
  "headline": "Are You Making These JSON-LD Schema Mistakes?",
  "publisher": {
    "url": "aiovisibility.com",
    "name": "AI Visibility Solutions",
    "@type": "Organization"
  },
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [
      "h1",
      ".article-summary",
      "article p:first-of-type"
    ]
  },
  "areaServed": [
    {
      "name": "Los Angeles",
      "@type": "City"
    },
    {
      "name": "San Diego",
      "@type": "City"
    },
    {
      "name": "Austin",
      "@type": "City"
    },
    {
      "name": "Denver",
      "@type": "City"
    },
    {
      "name": "Salt Lake City",
      "@type": "City"
    },
    {
      "name": "Las Vegas",
      "@type": "City"
    },
    {
      "name": "San Francisco",
      "@type": "City"
    }
  ],
  "articleBody": "JSON-LD schema is super powerful for AI visibility, but it's also easy to mess up if you're not careful. Avoiding these common mistakes can make a huge difference in how AI systems interpret and cite your business. First up is using generic or incorrect schema types. This is like trying to fit a square peg in a round hole! Using `Article` for a product page, or missing crucial `LocalBusiness` markup for your location pages, confuses AI. Always map each page to its most specific and accurate schema.org class.\n\nNext, embedding conflicting or partial JSON-LD snippets. If you're using multiple plugins or tools that all try to add schema to the same page, you can create a mess of ambiguity. AI won't know which data is primary or correct. A unified, carefully planned approach is best here. Third, failing to connect entities with `@id`. This is crucial! Isolated bits of structured data don't tell AI the whole story. You need to link authors to articles, local branches to the main organization, and products to their brand using `@id` to establish clear relationships.\n\nAnother big one is outdated or inconsistent data in your JSON-LD. If your business hours, address, or product details change, but your schema doesn't, AI will be citing old, incorrect information. Implement a regular audit schedule, perhaps quarterly, to keep everything aligned. And finally, not validating your structured data. It’s like writing code without ever testing it! Syntax errors, missing required properties, or type mismatches will prevent AI systems from even using your markup. Always use structured data testing tools before deployment. If these challenges sound familiar or your site has a lot of complex content, getting an expert to help design and manage your schema strategy can save you from a lot of headaches and really boost your AI discoverability.",
  "datePublished": "2026-07-26"
}