{"id":113390,"date":"2014-07-31T14:47:00","date_gmt":"2014-07-31T19:47:00","guid":{"rendered":"https:\/\/www.dacgroup.com\/google-pigeon-strengthens-local-search\/"},"modified":"2024-12-21T05:55:05","modified_gmt":"2024-12-21T10:55:05","slug":"google-pigeon-strengthens-local-search","status":"publish","type":"post","link":"https:\/\/www.dacgroup.com\/en-gb\/insights\/blog\/local-search\/google-pigeon-strengthens-local-search\/","title":{"rendered":"Google \u201cPigeon\u201d Update Strengthens Local Search Abilities"},"content":{"rendered":"

The Update<\/b><\/h2>\n

News broke on July 25th<\/sup> that Google was rolling out a fairly hefty new update to their US-English results. Those that broke the news, Search Engine Land<\/a>, have unofficially named it Pigeon. It\u2019s quite a fitting name as the update concerns itself with local search and pigeons have homing tendencies. All very fitting.<\/p>\n

\"Pigeon<\/a><\/p>\n

What does it do?<\/b>\u00a0<\/b><\/h2>\n

The update looks to link…<\/p>\n

\u201cdeeper into [Google\u2019s] web search capabilities, including the hundreds of ranking signals they use in web search along with search features such as Knowledge Graph, spelling correction, synonyms and more.\u201d It also has better accuracy over distance and location rankings<\/i>\u201c.<\/p><\/blockquote>\n

What that basically means is it is a vast improvement on Google\u2019s previous search capabilities within Google Maps. This was often seen as an area of weakness, bearing in mind the comprehensive machine learning demonstrated by their main web search. This update runs deeper than just Google Maps, though. It looks to improve the distance and location ranking parameters in Google Web Search. Thus adding weight to locality in place of, in some cases, authority. \u00a0<\/b><\/p>\n

Why the change?<\/b><\/h2>\n

With the continued growth of mobile search, locality is becoming an ever more important decider in relevance of results. This update acknowledges that fact and looks to address the weighting of location searches. Google looks at the semantics of your search to work out whether a local search is appropriate to your query. The most obvious way of signalling this to the search engine is to include a location name in the search. This can be as specific or as broad as you would like it to be. The more granular you go, the more relevant result you will be served. It gets cleverer than that though. Through machine learning the search engine can make certain assumptions about searches and decide whether it is best serving location-relevant results or broader search results. A hat tip to Search Engine Round Table<\/a>, who pointed out that the search term \u201cIce Cream\u201d showed vastly different results from three days before the update when compared to the day of the update. See the image they provided below [Ignore the red arrow, this is a hangover from a previous blog post.]<\/i>\u00ad\u00ad\u00ad\u00ad<\/p>\n

\u00a0\"Pigeon<\/a><\/b><\/p>\n

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