How structured data works in Google Search Read more case studies from sites that have implemented structured data. Nestlé has measured pages that show as rich results in search have an 82% higher click.With search features vs non-feature AMP pages. Than on non-structured data pages, and have a 3.6x higher interaction rate on AMP pages Rakuten has found that users spend 1.5x more time on pages that implemented structured data.The Food Network has converted 80% of their pages to enable search features, and has seen a 35% increase in visits.Rotten Tomatoes added structured data to 100,000 unique pages and measured a 25% higher click-through rate for pages enhanced with structured data, compared to pages without structured data.Here are some case studies of websites that have implemented structured data for their site: Why add structured data to a page?Īdding structured data can enable search results that are more engaging to users and mightĮncourage them to interact more with your website, which are called rich results. Time and temperature, the calories, and so on. The page content for example, on a recipe page, what are the ingredients, the cooking Structured data is a standardized format for providing information about a page and classifying You can help us by providing explicitĬlues about the meaning of a page to Google by including structured data on the page. Sorry, can't share the JSON data structure with you either, it may be considered confidential.Google Search works hard to understand the content of a page. I just need a parser or diff tool that will do what I want. ![]() In terms of a code solution, any language will do. ![]() Presumably the JSON is either too complex or too large to process.Īny thoughts on best solution? Or might the best solution for now be manual analysis w/ grep for each parameter/property? Came across these:īoth failed to do what I wanted. Or maybe there's some ready made code already for that. Could write code to do it but I'd also have to spend time to do that, and test if the code works also. I could do manual search/grep but that's a pain to cycle through all the parameters inside the smaller JSON. Normal text compare doesn't do much, I'd have to reformat manually or w/ script to break up object w/ newlines, etc. The APIs return the JSON output compressed as a single line. One spans a page if you print it out via Windows Notepad. What makes this tougher is the JSON objects are huge. Unfortunately, I don't have the documentation that defines the JSON for each API. Because I want to eventually use data from one JSON output to construct the other JSON as input to an API call. Actually, I'm more interested in the shared parameters/properties within the object, not really the actual values of the parameters/properties of each object. ![]() I want to find all the interesecting data between the two objects. One JSON (the smaller one) is like a subset of the bigger JSON object. There is intersecting data between the 2 JSON objects, and they share similar JSON structure, but not identical. I have 2 JSON objects (returned from different web service API or HTTP responses). I have a problem I'd like to solve to not have to spend a lot of manual work to analyze as an alternative.
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