A historical listing of all major search algorithm updates done by Google.

Google the magical search engine that almost always fetches relevant results for whatever it is that you are searching for.

 

We have been discussing the factors Google uses to rank webpages since the past few weeks.

 

Those who have been following us might already know about Google’s search algorithm PageRank.

 

PageRank has gone from a simple word-to-word document matching to the beast that we have been talking about in the past few days.

 

Going through many iterations and updates with constant research and development.

Although the core algorithm remains the same. It has seen multiple algorithm updates.

 

We will be looking at the history of PageRank’s algorithm updates till date.

 

Update name	Issues fixed
Florida Update	keyword stuffing, using multiple sites under the same brand, invisible text, and hidden links
Jagger Update 1, 2 & 3	backlink-focused updates meant to crack down on unnatural link building, paid links, and other types of spam
Big Daddy Update	handled technical issues such as URL canonicalization and redirects
Vince Update	Competitive keyword terms to favour first page rankings for big brand domains vs. previously ranking sites (typically less authoritative sites, affiliate sites, and sites that had won this coveted visibility purely through SEO efforts).
Caffeine Update	a new web indexing system that allowed Google to crawl and store data more efficiently, resulting in 50 percent fresher results
MayDay Update	an algorithmic change to how Google assessed which sites were the best match for long-tail queries
Panda Update	ending the “content farm” business model as it existed at the time
Panda Update 2.0	This update incorporated additional signals, such as sites that Google users had blocked
Panda Update 3.0	added some new signals into the Panda algorithm and also recalculated how the algorithm impacted websites
Freshness Update	to better determine when to deliver search results that are fresher (e.g., current events, hot topics, recurring events) to be more relevant to searchers
Page Layout Update	targeted websites with too many ads above the fold
Venice Update	Search results based either on the searcher’s physical location or IP address. Also, Google could better detect whether a query or webpage had local intent or relevance.
Penguin Update	algorithm change meant to downrank websites engaging in aggressive webspam (e.g., keyword stuffing, unnatural linking) that violated Google’s Webmaster Guidelines
Exact Match Domain Update	algorithm update focused on ridding the SERPs of spammy or low-quality exact match domains
Payday Loan Update	targeted spammy queries mostly associated with shady industries (including super high interest loans and payday loans, porn, casinos, debt consolidation, and pharmaceuticals)
Hummingbird Update	a way to better understand and return the most relevant results to more complex queries as a result of the growth of conversational search (i.e., voice search)
Pigeon Update	local search update
Mobile-Friendly Update (or “Mobilegeddon”)	meant to reward mobile-friendly websites with better search rankings and provide better results to searchers on mobile devices
Quality Update (or “Phantom Update”)	Websites with content quality issues, as well as too many ads, seemed to be impacted the most by this update
RankBrain	a machine learning algorithm that filters search results to help give users a best answer to their query
Mobile-Friendly Update (#2) (or “Mobilegeddon 2”)	increases the effect of the ranking signal
Penguin Update 4.0 & Core Algorithm Integration	Penguin devalued links, rather than downgrading the rankings of pages
Fred	This major algorithm update seemed to mainly target low-value content.
Maccabees Update	Google confirmed several minor changes to the core algorithm during the timeframe, but downplayed the significance of the period of flux
A “Small” Update	Google said it was a general ranking update and wasn’t specifically targeting any sites.
Unconfirmed Halloween Update	Google ramping up its use of neural matching
BERT Update	The biggest change to Google search in the past 5 years. Google uses BERT models to better understand search queries. Google said this change impacted both search rankings and featured snippets and BERT (which stands for Bidirectional Encoder Representations from Transformers) will be used on 10 percent of U.S. English searches.
BERT (Worldwide)	BERT was beginning its worldwide rollout, and included the following languages: Afrikaans, Albanian, Amharic, Arabic, Armenian, Azeri, Basque, Belarusian, Bulgarian, Catalan, Chinese (Simplified & Taiwan), Croatian, Czech, Danish, Dutch, English, Estonian, Farsi, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Latvian, Lithuanian, Macedonian Malay (Brunei Darussalam & Malaysia), Malayalam, Maltese, Marathi, Mongolian, Nepali, Norwegian, Polish, Portuguese, Punjabi, Romanian, Russian, Serbian, Sinhalese, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tajik, Tamil, Telugu, Thai, Turkish, Ukrainian, Urdu, Uzbek, and Vietnamese.
Featured Snippet Deduplication	webpages in a featured snippet position will no longer be repeated in regular Page 1 organic listings

 

Although not a comprehensive or thorough list. We have covered almost all major algorithm updates that Google has made to its search algorithm.

 

Thanks for reading. Hope to see you again.

 

Reference: SEJ – Search Engine Journal