If you imagine Google Search is a car, then this is an engine replacement
NEW DELHI, INDIA: It has been a while since Google had changed its search algorithm as an overhaul; last time was 2001. If you imagine Google Search is a car, then this is an engine replacement. Previously, there have been some transmission and gear box changes i.e. Caffeine (Jun 2010), Panda (Feb 2011), and Penguin (Apr 2012).
But this time, Hummingbird implementation was announced on Google's 15th anniversary (Sept 26, 2013).
Google has been trying to deliver the best Semantic search (i.e. not just throwing up index pages related to the keywords used, but providing relevant contextual results). Hence, Knowledge Graph matrix was extensively utilized in this deployment. To become truly Semantic and beat the likes of Siri (i.e., Apple OS voice indexing protocol too), Google Voice Search is using the android platform to harvest data that provides contextual meaning to words and phrases.
Example: If I search for "CMO, ABC Company", I'm probably looking for the Chief Marketer of ABC Company. The old school Boolean search might throw up "No Results Found" or "Contact Us page of ABC Company's website"; whereas, the Semantic search would list the LinkedIn or name/contact of "SVP/VP Marketing of ABC Company".
From the data source perspective, all Google applications and platforms are gathering index shards to fuel Maps, Glass, G+, Apps (Free+Enterprise), Enterprise Search, YouTube, Picasa, etc. - all these sources are gathering derivative meanings of words and tagging them to images, documents, and sounds bytes.
They are simultaneously cross mapped to human sentiments and cognitive computing protocols. If you remember IBM Watson in Jeopardy, one didn't have to explicitly say the "reference meanings" of pronouns, the computer was able to derive the contextual meaning of who was referred to as "he/she" - the same is the goal of Semantic search.
How it affects Search and Content Marketing:
1. Removing Redundancy: If you pitch multiple collateral/assets for the same subject/topic, low-influencing digital assets might be filtered out
2. Increased Metadata Dependency: Whether it is a PDF, a webpage, an image, a flash or RSS, MRSS, Social data ... if you have not optimized properly with adequate tagging, anchoring, bookmarking, and meta description, your collateral(s) will slowly phase out from top results
3. Author Rank: Hummingbird will give a lot of weight to the author rank of the content. Your content might be pure gold, but if it's published by a ‘social/web nobody' it might be buried under the "in-circle publishers'" posts
David Yauncy Fri Oct 25 at 06:46 PM
Saw this from Twitter, this article is comprehensive enough for all the Marketers to realize - Digital advertising and SEO are interlinked and we must keep our budget cushioned to embrace this change in the Advertising Value Chain. Thanks Chirantan for this article, much appreciated. Also, I'm interested to know what "Avinash Kaushik Kaul" asked about cognitive computing in semantic search.
Avinash Kaushik Kaul Fri Oct 25 at 03:24 PM
Hi Chirantan, This is well written article, thank you for putting your thoughts together. IBM Watson uses cognitive computing, will Google use the same technology in semantic search?
Adrian Lerouche Fri Oct 25 at 02:24 PM
The "Increased Metadata Dependency" is significant for Enterprise Marketing and document optimization. Thanks to Chirantan Ghosh we get some clarity on the technical SEO mumbo jumbo. I would be interested to figure out how this meta-data dependency can be utilized to our advance as an online marketer
John Bell Fri Oct 25 at 02:19 PM
This is a very insightful article for Digital Marketers would like to ask the author how he redefines strategy for his clients based on the Google Hummingbird deployment
Kapil Fri Oct 18 at 04:16 PM
Searal is good search platform. Read this article to get to know more - http://searchingdev.tumblr.com/post/64377427195/right-website-for-search-query