Original Data & Expert Content

Original data and expert content refers to information that only you can produce — proprietary research, first-hand analysis, unique datasets, professional opinions, and deep domain expertise that can't be found anywhere else.

This includes: - Proprietary market data and trend analysis from your business operations - Expert opinions and analysis based on years of hands-on experience - Original research, surveys, or studies you conduct - Case studies and real-world results from your work - Unique product comparisons or technical evaluations - Industry insights derived from your proprietary data

AI systems have a hierarchy of source trust. At the top: original data and expert analysis. At the bottom: rewritten Wikipedia articles and generic blog posts.

When multiple sources cover the same topic, AI systems preferentially cite: - Content with proprietary data points (numbers, statistics, findings) - First-hand expert analysis with demonstrated experience - Sources that provide information unavailable elsewhere - Content with clear author credentials and expertise signals

This is the "E" (Experience) and first "E" (Expertise) in E-E-A-T. AI systems are increasingly sophisticated at distinguishing genuine expertise from content farms.

**1. Mine your own data** Every business has proprietary data. Examples: - E-commerce: Price trends, inventory analysis, customer preferences - Services: Project outcomes, industry benchmarks, case study results - Content: Original research, surveys, interviews with experts

**2. Demonstrate expertise in writing** ``` <!-- Generic (low citation value) --> "Vinyl records should be stored vertically."

<!-- Expert (high citation value) --> "After handling over 10,000 records in 20 years, I've found that records stored at more than a 3-degree tilt develop warping within 18 months. Vertical storage with 15-20 records per shelf divider is the sweet spot." ```

**3. Create data-driven content pieces** - Annual/quarterly market reports - Product comparison matrices with original testing - Price guides based on your actual transaction data - Trend analyses with proprietary datasets

**4. Add author credentials** Every piece of expert content should clearly state who wrote it and why they're qualified. Include years of experience, relevant background, and specific expertise areas.

**5. Use structured data for credibility** Add Article schema with author (Person), datePublished, and publisher (Organization) to all expert content.

- Relying primarily on Wikipedia or other secondary sources instead of original expertise - Not attributing content to a specific expert author - Making claims of expertise without demonstrating it in the content itself - Publishing data without context, methodology, or source attribution - Creating content that reads like it could have been written by anyone (generic)

- Google's Helpful Content guidelines — What makes content "people-first" - E-E-A-T documentation in Google's Search Quality Evaluator Guidelines - Content Marketing Institute — Research on original data content performance