Matt Diggity EEAT

Understanding Google’s Quality Evaluator Guidelines and EEAT

This tool is built to help you refine your content in line with the standards set by Google’s Search Quality Evaluator Guidelines. Central to the approach is the concept of EEAT—Expertise, Experience, Authoritativeness, and Trustworthiness—which Google uses to assess content quality. If your content isn’t meeting these benchmarks, you may find that competitors are ranking higher despite similar keywords.

Building the "Matt Diggity EEAT - v1.2" App

Step 1: Gathering Foundational Knowledge and Content

The app begins by retrieving relevant guidance from a document on the Google Search Quality Evaluator Guidelines. This ensures that the subsequent analysis is firmly rooted in industry-approved insights. By leveraging this resource, you establish a baseline for what constitutes high-quality content.

Next, the app uses a series of web scraping functions to extract content from your full website and three of your top competitors. Each competitor’s page is assumed to be performing strongly for your target keyword. The scraped content serves as a real-world benchmark, capturing both the tone and information depth that resonates with search evaluators.

Step 2: Analyzing and Comparing Content

The core of the process is handled by an AI-driven Chat Model. The system is instructed to first consider the retrieved quality guidelines, then analyze your content and compare it against the competitor content. This comparison is strictly within the context of the evaluators’ benchmarks, and the model is tuned to exclude generic SEO advice. Instead, it focuses on pinpointing areas where your content may be lacking, offering clear, actionable improvement points such as increasing detail in specific sections, improving credibility signals, or enhancing the demonstration of expertise. The output is a detailed list of tailored action points focused on aligning your content more closely with recognized quality standards.

Customizing the App for Your Needs

• Refining Input Parameters: Adjust the inputs to include additional competitor URLs or more specific content segments from your own site. This ensures that the analysis is as detailed as possible.

• Expanding Document Sources: Integrate more guidelines or case studies from your knowledge base to provide the AI with a broader context when evaluating content.

• Fine-Tuning the AI Prompt: Customize the Chat Model prompt to focus on particular aspects of EEAT that are most relevant to your niche. For example, you can emphasize the provision of expert opinions or the clarity of the user intent.

• Layering Additional Analysis: Consider chaining additional functions to further analyze sentiment or readability once the initial action points are generated, to get an even more comprehensive overview.

Running the App at Scale

1. Prepare a CSV file containing your content URLs along with the URLs of your competitors and the target keyword for each entry.

2. Upload the CSV in the Bulk Runs section of Moonlit Platform and map the appropriate columns to the app's inputs.

3. Execute the bulk process, allowing the app to iterate over multiple sets of URLs and generate tailored action points for each case.

Get Started with Moonlit Platform

Moonlit Platform empowers you to create content analysis and improvement tools—like the "Matt Diggity EEAT" app—with minimal code and maximum efficiency. Sign up for Moonlit Platform today to build, customize, and scale your own suite of AI-powered SEO tools.