A Comprehensive Guide to Snippets

# Snippets in Google Search * Snippets are short descriptions or excerpts from a website that appear in Google search results. * They were introduced by Google in 1998. * Snippets are created automatically based on the site's content and the query terms. * Key query terms are highlighted in bold within the snippet. * Example: A search for "what is the number of x- and y-intercepts that quadratic functions may have" highlights the words number, x-, y-intercepts, quadratic, functions, have, and may in bold in the search results snippets. * A quadratic function has at most two x-intercepts, corresponding to the number of solutions a quadratic equation can have (2, 1, or 0). * Quadratic functions have exactly one y-intercept. # Elementary Facts About Google Snippets * If a snippet begins with ellipses (....), it indicates that the snippet was excerpted from a larger body of text and text preceding the ellipses was omitted. * When ellipses follow at the end of the snippet, the snippet was truncated. * The maximum length of a snippet is 156 characters. * Google uses the meta description (if there is one) as the default for a snippet. * If there is an Open Directory Project listing for a website, Google uses its meta description over the meta description in the web page. * The Open Directory Project, which used human editors to organize websites, closed as of March 2017. # Google Snippet Lifecycle Changes * **Classic snippet:** * Web Result Architecture includes Title, Content, and Attribution. * **Adding images in 2016:** * Images are relevant to the query. * Placement is on the right. * Images are secondary to the title/snippet. * Galleries support contentful pages. * Users visit a greater diversity of sites. * **Adding videos in 2018:** * Video is relevant to the query. * Preview indicates if video is dominant or supportive. * Video metadata informs user experience. * **Adding Sitelinks:** * Links are relevant to the query. * Links extracted algorithmically, often menus or from site structure. * Drives traffic into a diverse set of sites. * Sitelink-images help users. * Pithy links are better understood. * **Adding Entity Facts:** * Relevance to needs around the entity. * Facts extracted algorithmically, often from tables or lists. * **Adding Tables and Lists:** * Pages with dominant tables/lists. * Helps users contrast content. * Structure and position on the page guides the preview. # More Facts on Snippets * Snippets are computed at query time. * They vary depending upon the query. * The content that ends up in the text snippet can come from anywhere on your page, such as the first sentence, last sentence, footer, or call out box. * If Google determines your site is a discussion forum, it may include the number of posts, number of authors, and the date of the last post. * If Google determines your site is a scholarly article, it may include the author and year or the author and "Cited by" information. # Snippets Can Vary for a Single Site * Snippets can vary for a single site depending on the query. * Example: The query "what cholesterol levels mean" produces a snippet that includes a long snippet and a People Also Ask (PAA) section. * A different query, such as "cholesterol Cleveland Clinic," produces the same first result but a different snippet. # Snippets as Summarization * Snippets are an instance of summarization. * Automatic summarization by computer is a traditional subject of information retrieval. * Automatic summarization is also part of machine learning and data mining. * Document summarization tries to create a representative summary or abstract of the entire document by finding the most informative sentences. * There are two general approaches to automatic summarization: * **Extraction:** Extractive methods work by selecting a subset of existing words, phrases, or sentences in the original text to form the summary. * **Abstraction:** Abstractive methods build an internal semantic representation and then use natural language generation techniques to create a summary that is closer to what a human might express. * Research to date has focused primarily on extractive methods, which are appropriate for documents, images, and videos. # Featured Snippets * Featured snippets are Google's attempt to answer the query right on the search results page. * Introduced in 2016, Google wants to give the user an immediate answer so they don't have to search the actual results. * Featured snippets show up above the #1 ranked spot and typically appear above the fold. * Google pulls snippet answers from pages that rank on Page 1 of the results for that query (spots #1 through #10). * The page that wins the featured snippet isn't necessarily the #1 result. Google picks the excerpt from the page that best answers the query in a simple, concise format. ## Three Types of Featured Snippets 1. **Paragraph featured snippet:** * Provides a direct answer to the query in paragraph form. * Example: Definition of marketing automation from HubSpot. 2. **List featured snippet:** * Presents information in a bulleted or numbered list. * Example: List of best college websites. 3. **Table featured snippet:** * Displays data in a table format. * Example: Google aviation jobs. * A fourth type might be video snippets. # Modifying Your Page to Produce a Featured Snippet * Becoming a featured snippet can be achieved by simple on-page adjustments that very clearly define the topic to users. * One of the goals of the featured snippet is to fuel voice search. * To optimize for featured snippets: 1. Look for a place in your content to add a "What Is [Keyword]" heading tag. 2. Use the "is statement" e.g., "Agile methodology is a type of project management process, mainly used for software development..." 3. Define the topic in 2 or 3 sentences. 4. Match the featured snippet format: paragraph, bulleted or numbered list, table. 5. Don't use first person, e.g., "Our avocados have many health benefits . . ." # The Challenge of Organic Search * For the query "CRM software", there are often 4 paid ads, a featured snippet paragraph, a People Also Ask section, and a portion of the #1 ranking organic result above the fold. * **Conclusion:** it is harder than ever to be found in the organic search results. * "Above the fold" refers to a search engine results page ranking on the first page that is visible without having to scroll down # Extracting a Snippet: An Example * Demonstrates how Google extracts snippets, using the example of the query "Tesla reports financial results" and an article from the New York Times. * Highlights that the snippet may use parts of the article and equate related terms. # Extracting a Snippet is Not Always Easy Nor Obvious * Presents an example of extracting a snippet where the meta-description is used instead of content directly from the article # How Does Google Generate Snippets? * One way to find out is to go to patents.google.com and search for all patents with the term "snippets" assigned to Google. * Many are patent applications still being reviewed by the patent office. # US Patent 8,145,617 * Title: Generation of document snippets based on queries and search results * Filed: 2005 * Awarded: 2012 * Abstract: A document retrieval system generates snippets of documents for display as part of a user interface screen with search results. The snippet may be generated based on the type of query or the location of the query terms in the document. Different snippet generation algorithms may be used depending on the query type. # Some Guidelines for Snippet Generation * **Location Based Rules:** * Based on the location of the query terms in page. A paragraph or a portion of a paragraph might be chosen as search results snippets based on the length and distance of the paragraph from the start or end of pages. * Every paragraph that includes the query terms is given a score based on the length of the paragraph and the distance of the paragraph from a predetermined location in the document, such as the beginning or the end of the document. * Documents that include abstracts, executive summaries or comprehensive introductions are identified and used to create a snippet. * Similarly, the ends of pages can be used if they include a conclusion or summarization * **Language Dependent Rules** * How much of the paragraph are punctuation characters * Whether the paragraph ends with punctuation or proposition * Whether any of the words in the paragraph is overly long * The number of bold or italicized words in the paragraph * **Rejection rules** * Are shorter than a certain threshold * Are mostly punctuation, or have punctuation above a certain threshold * Contain italicized or bold words above a certain threshold # US Patent 8,145,617 Defines an Algorithm for Snippet Generation * The algorithm: 1. Identify the paragraphs that include the query terms. 2. Score the paragraphs as described below determining the paragraph with the highest score 3. Return the phrase in that paragraph that includes the query terms * Quoting from the Detailed Description * The snippet algorithm selects a paragraph that is near the beginning of the document if there is an abstract, executive summary, or long introduction. The end of the document is used when there is a conclusion or summarization at the end * Scoring includes: * paragraphs shorter than threshold score 0; * k-th paragraph from the start gets a score of kth\text{-position Factor} + \text{max(actual paragraph length, maxParagraphLen)} * The paragraph with the highest score is selected for the snippet # US Patent 8,631,006 * Snippets can be based on a User's Profile * System and Method for Personalized Snippet Generation * Filed: April 14, 2005 * Awarded: Jan. 14, 2014 * Abstract: * Snippets of text are generated based in part on a user's profile. An item, such as a document, is examined to identify terms related to the user's profile. A term profile for an identified term is compared to a user's profile. * The more closely related the identified term is to the user's profile, the higher a similarity score will be. Alternatively, terms found in a document may have a user profile score which may be obtained by looking the term up in the user's profile. * Terms having high profile similarity scores or high user profile scores are used in identifying snippets which may be relevant to a user. The high scoring terms may be added to search terms and provided to a snippet generator # Featured Snippets Results in Google Web Search: An Exploratory Study - Strzelecki, Rutecka * **Table 1. Type of featured snippet.** * Paragraph snippets are the overwhelming type | featured type | frequency | percentage | | ------------- | --------- | ---------- | | paragraph | 114465 | 70,05% | | list | 46509 | 28,46% | | table | 2438 | 1,49% | * **Table 2. Ranking position for featured snippet** * Position 1, the second position on the SERP Is most common | position | frequency | percentage | | -------- | --------- | ---------- | | 0 | 485 | 0,30% | | 1 | 79867 | 48,87% | | 2 | 30618 | 18,74% | | 3 | 20878 | 12,78% | | 4 | 14469 | 8,85% | | 5 | 9582 | 5,86% | | 6 | 2860 | 1,75% | | 7 | 1909 | 1,17% | | 8 | 1319 | 0,81% | | 9 | 860 | 0,53% | | 10 | 554 | 0,34% | * **Table 3. Other snippets displayed along with featured snippet** | params | frequency | percentage | | ----------- | --------- | ---------- | | image thumbs | 102934 | 62,99% | | site links | 41348 | 25,30% | | brand | 24214 | 14,82% | | wiki | 18675 | 11,43% | | ads | 3148 | 1,93% | | name | 2850 | 1,74% | | map | 1807 | 1,11% | | city | 1062 | 0,65% | | news | 107 | 0.07% | # Google's People Also Ask (PAA) Feature * Introduced in 2015 for desktop and mobile * In one study, the "People Also Ask" box appeared on 364 keywords out of 1,788, 20%.\n # People Also Ask (PAA) is Growing Fast * The "People Also Ask" box is a Google universal SERP result that answers questions related to the searcher's initial query. * It is a cousin of the featured snippet * Each PAA box contains anywhere from one to four related questions which expand to reveal answers that Google has pulled from other websites * The site's URL appears below each answer, along with a "Search for” link, which guides the user to a Google SERP of the PAA question. * Use of PAAs are growing faster than snippets according to https://moz.com/blog/infinite-people-also-ask-boxes # Rich Snippets * In 2009, Google announced Rich Snippets, a mechanism for website developers to include information that Google's results algorithm will display as a snippet * The mechanism calls for embedding structured data in web pages with the objective of displaying the structured data to a user in a visually outstanding way. * Rich Snippets give users a convenient summary information about their search results at a glance. # Rich Snippets Examples: People Snippets * Provides an example of how snippets describe pages containing information about individuals on Facebook, LinkedIn, and Google. # Rich Snippets Examples: Events * the Filmore theatre can highlight future concerts by regularly updating their webpage with the latest rich snippet information # Advantages of Rich Snippets * **Webmasters:** Provides webmasters the ability to add useful information to their web search result snippets to help Google make sense of their bits. * **Purpose** Provides more information to a user about the content that exists on page so they can decide which result is more relevant for their query. * Two good reasons for using rich snippets 1. **Additional traffic to a webpage** With extra information people tend to rely more on a particular search result with linked data, thus an increasing number of impressions noted on sites with Rich Snippets. 2. **Higher Click Through Rate** An increasing number of higher click-through rate for pages with Rich Snippets was experienced as shown in a paper by Kavi Goel, Pravir Gupta * Easy to add simple lines of Markup to existing HTML, no affect to visual appearance of the webpage. # A Joint Effort by Google, Yahoo! And Bing * In June, 2011 Google, Yahoo, and Bing agree on a single standard * They establish the website schema.org which defines the mechanism for creating rich snippets * They decide to standardize on microdata format * A shared vocabulary makes it easier for webmasters and developers to decide on a schema and get the maximum benefit for their efforts. # Rich Snippet Technology Definitions * Google suggests using the microdata formalism for snippets * Two other formalisms for creating rich snippets have been suggested: * RDFa (Resource Description Framework - in Attributes) * Microformat Encoding # Schema.org Vocabulary * Schema.org defines an object hierarchy * The most general item type is Thing with properties: name, description, url, and image * Person, Place and Organization are types of Things * More specific items inherit the properties of their parent * Some commonly used types include: * Creative works: book, movie, music recording, recipe, TV Series * Embedded object: image, video * Event * Organization * Person * Place, Local Business, e.g. Restaurant * Product, Offer, Aggregate Offer * Review, AggregateRating # Entities in Rich Snippet Encodings * Entities supported by Google Rich Snippets as of now.... * Software applications * Breadcrumbs * a breadcrumb trail on a page indicates the page's position in the site hierarchy. A user can navigate all the way up in the site hierarchy, one level at a time, by starting from the last breadcrumb in the breadcrumb trail * for example, Books > Authors > Ann Leckie > Ancillary Justice * Events * Music * Businesses and Organizations * People * Products * Recipes * Review Ratings * Reviews: should include: item being reviewed, reviewer rating, date * Videos: Facebook Share # Rich Snippets: Microformats vs. Microdata * Microformats use only existing HTML, e.g. the class attribute in HTML tags (often or

) to assign brief and descriptive names to entities and their properties * Microdata extends HTML5 by introducing new attributes like itemprop # A MicroData Example: A Web Page About the Movie Avatar * To begin, identify the section of the page that is "about" the movie Avatar. To do this, add the itemscope element to the HTML tag that encloses information about the item, and you can specify the type of item using the itemtype attribute. * By adding itemscope, you are specifying that the HTML contained in the

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block is about a particular item. # Avatar Example Continued * The itemprop attribute is used to label properties of a movie such as actors, director, ratings. * For example, to identify the director of a movie, add itemprop="director" to the element enclosing the director's name. # MicroData Markup for "Pirates of the Caribbean" * Includes * Movie name * Description * Director * Author * Actors * rating # More Examples: Clarifying Hard to Understand Content * The element has attributes: dates, times and durations: * markup for a concert and markup for an enumeration are presented # tools * Web interface tool for creating rich snippets: https://technicalseo.com/tools/schema-markup-generator/ * Google offers a tool for testing rich snippets # Google Introduces New Tags for Snippet Control(1) * The robots meta tag is added to an HTML page's ; here are some new tags: * "nosnippet" * This is an existing option to specify that you don't want any textual snippet shown for this page. * "max-snippet: [number]" * New! Specify a maximum text-length, in characters, of a snippet for your page. * "max-video-preview: [number]" * New! Specify a maximum duration in seconds of an animated video preview. * "max-image-preview: [setting]" * New! Specify a maximum size of image preview to be shown for images on this page, using either "none", "standard", or "large". * They can be combined, for example: * # Google Introduces New Tags for Snippet Control(2) * A new way to help limit which part of a page is eligible to be shown as a snippet is the "data-nosnippet" HTML attribute on span, div, and section elements. * With this, you can prevent that part of an HTML page from being shown within the textual snippet on the page. * To opt out of featured snippets * The nosnippet tag blocks all snippets (featured snippets and regular snippets) for the tagged page. * Text marked by the data-nosnippet tag won't appear in featured snippets (or regular snippets either). * If both nosnippet and data-nosnippet appear in a page, nosnippet takes priority, and snippets won't be shown for the page. # Summary * Snippets can be divided into five categories 1. Regular snippets, displayed in organic search results 2. Rich snippets come from structured data dictionary schema.org including RDFa, Microdata or JSON 3. Google News, created automatically from news feeds to Google 4. Entity types, come from the KnowledgeGraph, are constructed object and concepts including people, movies, places, events, books, etc 5. Features snippets, determine that a page contains a likely answer to the user's question; the snippet is displayed. In four different forms: paragraph, table, ordered list, unordered list # Extending Schema.org to handle PAA * QAPage focuses on a specific question and its answer(s) * Question, a specific question from a user seeking answers online or collected in a FAQ document * How To, instructions that explain how to achieve a results by performing a sequence of steps