What Is The Google Hummingbird Algorithm Update?

google_hummingbird-580x334Google announced an update to their search algorithm last week, called Hummingbird. This new algorithm was unofficially rolled out a few weeks ago; it targets complex queries and potentially impacts around 90% of searches, globally. Hummingbird represents the first time since 2001 a Google algorithm has been so dramatically rewritten. In 2010, the “Caffeine Update” was rolled out, which focused on providing results faster, but was still just an update to the existing algorithm.

Google Hummingbird’s core focus is semantic search or “conversational search” as Google calls it. Most voice search queries (from a smartphone or tablet) are question based, rather than single-keyword searches. This new algorithm addresses these types of queries, providing answers to users’ questions as quickly as possible with the most relevant results. An example query may be “what is the best place to find and eat Chicago deep dish style pizza?” Google will analyze each word in the query and may replace the keyword “place” with “restaurant” to provide relevant results to the user.

Google has already mentioned that there’s nothing new or different that SEOs or publishers need to worry about. The SEO strategy is still the same: have original, high-quality content that users want to share and ultimately connect with. Traditional signals that have been important in the past will remain important; Hummingbird just allows Google to process these signals in new and, hopefully, improved ways.

This will not affect IMI’s current SEO strategy; if nothing else, it reinforces our recommendation of constantly creating new, informative, and useful content that people want to connect with and share. It is more important than ever before to ensure that your business has a sound content marketing strategy promoting useful relevant content while finding creative ways to connect and engage with users online and offline. The new Hummingbird algorithm update is intended to enable users to find relevant content faster and with more ease, even if the query is more complex than what the site was initially optimized for.

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