{"id":14735,"date":"2022-06-29T12:49:48","date_gmt":"2022-06-29T12:49:48","guid":{"rendered":"https:\/\/www.searchenginejournal.com\/google-algorithm-history\/freshness-algorithm\/"},"modified":"2022-06-29T12:49:48","modified_gmt":"2022-06-29T12:49:48","slug":"google-freshness-algorithm-everything-you-need-to-know-via-sejournal-martinibuster","status":"publish","type":"post","link":"https:\/\/marketingnewsbox.com\/?p=14735","title":{"rendered":"Google Freshness Algorithm: Everything You Need To Know via @sejournal, @martinibuster"},"content":{"rendered":"

Google\u2019s Freshness Update was a significant ranking algorithm change<\/a> that introduced the trend of making the search results more precise and responsive to user intent.<\/p>\n

The result of the update was the ability to add time as a relevance measure for search queries. This enabled Google to surface content that is trending, regularly occurring (like a yearly event), or subject to frequent updating (like new product models).<\/p>\n

The Freshness Update was made possible by the infrastructure changes introduced by the Caffeine Update<\/a>, which enabled Google to scale up web indexing at an unprecedented scale, enabling Google to surface the most up-to-date content that is <\/span><\/span>literally<\/span><\/span> up-to-the-minute relevant<\/span><\/span>.<\/span><\/p>\n

The algorithm update was announced on November 3, 2011.<\/p>\n

Google\u2019s official blog post announcement<\/a> stated that the change impacted about 35% of search queries and noticeably affected approximately six to 10% of search queries.<\/p>\n

That is a significant change in how webpages are ranked.<\/p>\n

Why Is It Called Freshness Algorithm?<\/h2>\n

The \u201cfreshness\u201d name for this update is directly taken from the official Google announcement:<\/p>\n

\n

\u201cGoogle Search uses a freshness algorithm, designed to give you the most up-to-date results.\u201d<\/p>\n<\/blockquote>\n

What Made This Algorithm Update Possible<\/h2>\n

A reason why Google released the Freshness Update was that the new Caffeine indexing system provided Google the ability to process more webpages faster.<\/p>\n

The Caffeine infrastructure made it possible for Google to provide fresh results with a higher degree of relevance by using a more granular definition of what freshness means.<\/p>\n

Specifically, Google determined that some queries have three different kinds of time-related relevance factors.<\/p>\n

The three kinds of time-related queries are:<\/p>\n

    \n
  1. Recent events: <\/strong>These are search queries that relate to trending or current events, generally news related.<\/li>\n
  2. Regularly recurring events: <\/strong>Google\u2019s announcement gave the example of annual events, elections, sports scores, TV shows, and corporate earnings reports.<\/li>\n
  3. Frequent updates: <\/strong>These are time-related queries for topics that frequently update but aren\u2019t events or trending topics. Examples are search queries for products that are frequently updated.<\/li>\n<\/ol>\n

    Freshness For Trending Topics And Recent Events<\/h2>\n

    Trending Topics<\/h3>\n

    Google shows fresh results for certain queries, particularly if they are trending.<\/p>\n

    Here\u2019s an example with the keyword LIMoE<\/a>, which is the name of a Google algorithm:<\/p>\n

    \"FreshScreenshot from search for [limoe], Google, June 2022<\/span>\"Fresh<\/div>\n

    LIMoE is a keyword phrase that didn\u2019t exist until recently. In the above example, Google is showing the freshest search result.<\/p>\n

    Recent Events<\/h3>\n

    When the algorithm was released there was no such thing as the Top Stories<\/a> news section for current events.<\/p>\n

    Google simply showed news results related to recent events at the top of the search results.<\/p>\n

    Today, Google will show a Top Stories<\/em> section when a search query has a recent event type<\/em> of relevance component.<\/p>\n

    For example, a search query for Ukraine surfaces the following search result:<\/p>\n

    \"recentScreenshot from search for [ukraine], Google, June 2022<\/span>\"recent<\/div>\n

    The Top Stories feature is shown for recent events that are trending. This is an example of the Recent Events type of fresh result.<\/p>\n

    Freshness For Regularly Recurring Events<\/h2>\n

    This kind of freshness relates to events that happen on a regular basis but aren\u2019t necessarily trending.<\/p>\n

    Google used the example of a search query that is related to sports as a recurring event type of search query.<\/p>\n

    A search for NBA surfaces recent sports scores:<\/p>\n

    \"SportsScreenshot from search for [nba], Google, June 2022<\/span>\"Sports<\/div>\n

    The recurring events freshness type will have to be updated regularly. A sports event will have to be updated on a daily or weekly basis when the sport is in season.<\/p>\n

    A presidential election recurring event will have to be updated every four years.<\/p>\n

    Frequent Update Freshness<\/h2>\n

    The third type of freshness is related to search queries about topics that are always updated, like queries related to product reviews.<\/p>\n

    For example, the Samsung Galaxy phone has been around for many years and has cycled through multiple models.<\/p>\n

    Ideally, when searching for Samsung Galaxy Review, the best result will be reviews about the latest models.<\/p>\n

    This is a search result for that search query:<\/p>\n

    \"ProductScreenshot from search for [samsung galaxy review], Google, June 2022<\/span>\"Product<\/div>\n

    Query Deserves Freshness (QDF)<\/h2>\n

    Google\u2019s Freshness Algorithm update was not the first time Google used time-related relevancy ranking factors.<\/p>\n

    In 2007, Amit Singhal (then a Google engineer and a senior vice president), introduced the Query Deserves Freshness (QDF) algorithm in an interview with the New York Times.<\/p>\n

    In a New York Times interview he explained what QDF was:<\/p>\n

    \n

    \u201cMr. Singhal introduced the freshness problem, explaining that simply changing formulas to display more new pages results in lower-quality searches much of the time.<\/p>\n

    He then unveiled his team\u2019s solution: a mathematical model that tries to determine when users want new information and when they don\u2019t.<\/p>\n

    (And yes, like all Google initiatives, it had a name: QDF, for \u2018query deserves freshness.\u2019)<\/p>\n

    \u2026THE QDF solution revolves around determining whether a topic is \u2018hot.\u2019<\/p>\n

    If news sites or blog posts are actively writing about a topic, the model figures that it is one for which users are more likely to want current information. \u201c<\/p>\n<\/blockquote>\n

    The difference between QDF and the Freshness Algorithm Update is that the QDF algorithm appears to have been more limited in scope and less nuanced than the Freshness Algorithm.<\/p>\n

    In a Nutshell: The Difference Between QDF And Freshness Algorithm<\/strong><\/h3>\n