Just pulled this from google Found this very helpful in my early days online, I do not take credit for this. It's from 2012 but the core is very useful to keep in mind when building sites. Cant post the actual Url, anyways. To the article Algorithms You want the answer, not trillions of webpages. Algorithms are computer programs that look for clues to give you back exactly what you want. For a typical query, there are thousands, if not millions, of webpages with helpful information. Algorithms are the computer processes and formulas that take your questions and turn them into answers. Today Google's algorithms rely on more than 200 unique signals or "clues" that make it possible to guess what you might really be looking for. These signals include things like the terms on websites, the freshness of content, your region and PageRank. Search Projects There are many components to the search process and the results page, and we're constantly updating our technologies and systems to deliver better results. Many of these changes involve exciting new innovations, such as the Knowledge Graph or Google Instant. There are other important systems that we constantly tune and refine. This list of projects provides a glimpse into the many different aspects of search. Answers Displays immediate answers and information for things such as the weather, sports scores and quick facts. Autocomplete Predicts what you might be searching for. This includes understanding terms with more than one meaning. Books Finds results out of millions of books, including previews and text, from libraries and publishers worldwide. Freshness Shows the latest news and information. This includes gathering timely results when you're searching specific dates. Google Instant Displays immediate results as you type. Images Shows you image-based results with thumbnails so you can decide which page to visit from just a glance. Indexing Uses systems for collecting and storing documents on the web. Knowledge Graph Provides results based on a database of real world people, places, things, and the connections between them. Mobile Includes improvements designed specifically for mobile devices, such as tablets and smartphones. News Includes results from online newspapers and blogs from around the world. Query Understanding Gets to the deeper meaning of the words you type. Refinements Provides features like "Advanced Search," related searches, and other search tools, all of which help you fine-tune your search. SafeSearch Reduces the amount of adult web pages, images, and videos in your results. Search Methods Creates new ways to search, including "search by image" and "voice search." Site & Page Quality Uses a set of signals to determine how trustworthy, reputable, or authoritative a source is. (One of these signals is PageRank, one of Google's first algorithms, which looks at links between pages to determine their relevance.) Snippets Shows small previews of information, such as a page's title and short descriptive text, about each search result. Spelling Identifies and corrects possible spelling errors and provides alternatives. Synonyms Recognizes words with similar meanings. Translation and Internationalization Tailors results based on your language and country. Universal Search Blends relevant content, such as images, news, maps, videos, and your personal content, into a single unified search results page. User Context Provides more relevant results based on geographic region, Web History, and other factors. Videos Shows video-based results with thumbnails so you can quickly decide which video to watch. The Evolution of Search Our goal is to get you to the answer you're looking for faster, creating a nearly seamless connection between you and the knowledge you seek. If you're looking to deepen your understanding of how search has evolved, this video highlights some important features like universal results and quick answers. Experiments: From Idea to Launch A typical algorithmic change begins as an idea from one of our engineers about how to improve search. We take a data-driven approach and all proposed algorithm changes undergo extensive quality evaluation before release. Engineers typically start by running a series of experiments, tweaking small variables and getting feedback from colleagues until they are satisfied and ready to release the experiment to a larger audience. Search Quality Rating Guidelines This document is a version of our Search Quality Rater Guidelines, which gives evaluators examples and guidelines for appropriate ratings. The document focuses on a type of rating task called "URL rating." In this kind of task, the evaluator looks at a search query and a result that could be returned. They rate the relevance of the result for that query on a scale described within the document. Sounds simple, right? As you can see, there are many tricky cases to think through. Download Now (English only) Graph showing the process of narrowing down experiments into actual, launched Algorithm changes Precision Evaluations 118,812 The first phase is to get feedback from evaluators, people who evaluate search quality based on our guidelines. We show evaluators search results and ask them to rate the usefulness of the results for a given search. Note: These ratings don't directly impact ranking. Side-by-Side Experiments 10,391 In a side-by-side experiment, we show evaluators two different sets of search results: one from the old algorithm and one from the new, and we ask them for details about which results they prefer. Live Traffic Experiments 7,018 If the evaluators' feedback looks good, we move forward with a "live traffic experiment." In these experiments, we change search for a small percentage of real Google users and see how it changes the way they interact with the results. We carefully analyze the results to understand whether the change is an improvement to the search results. For example, do searchers click the new first result more often? If so, that's generally a good sign. Launches 665 Finally, our most experienced search engineers carefully review the data from all the different experiments and decide if the change is approved to launch. It sounds like a lot, but the process is well refined, so an engineer can go from idea to live on Google for a percentage of users in 24 hours. Based on all of this experimentation, evaluation and analysis, we launched 665 improvements to search in 2012. Data from 2012 Found this helpful tidbit on searchenginelanddotcom[B/] Ranking Signals Say goodbye to the typical Google Panda updates. Panda is now baked in as one of Google's core ranking algorithm. Barry Schwartz on January 12, 2016 at 9:27 am google-panda-name3-ss-1920 Google Panda, one of Google's most significant spam-fighting algorithms, launched in February 2011, is officially part of Google's core ranking algorithm. It is unclear exactly when this happened; we at Search Engine Land are trying to find out. Jennifer Slegg posted a Panda guide that was vetted by Google's PR team, and part of that included a statement that said Panda is now part of Google's core ranking algorithm. Here is that statement: Panda is an algorithm that's applied to sites overall and has become one of our core ranking signals. It measures the quality of a site, which you can read more about in our guidelines. Panda allows Google to take quality into account and adjust ranking accordingly. Gary Illyes from Google confirmed the authenticity of this quote. For one thing, this means Google will likely never confirm another Panda update for us in the future. The last confirmed Panda update was Panda 4.2, which was expected to roll out over "several months." Well, now that algorithm is baked into their main algorithm. We still have a lot of questions around what this means. Is the core ranking algorithm updating in real time? It doesn't seem so, as we just reported this morning on a new core ranking algorithm update that ran over the weekend. That update seems to have had some Panda signals in it, based on my analysis of the reports in the SEO community. We are also trying to find out approximately when Google incorporated Panda into their core algorithm and what that means. I estimate that it happened in late 2015, but I am trying to get something on the record from Google. As we hear more, we will update you. Postscript: Just to be clear, Gary Illyes from Google updated us on Twitter saying the Panda/Core update stuff here is not real time.