Have you ever wondered why Google can answer all your questions?
Search “Places to Eat” and the results are lists of the top restaurants in Singapore.
Search “Donald Trump” and the top result is the latest news revolving around Donald Trump.
Search “How tall is the Singapore Flyer” and you are answered straightaway (165m FYI)
How Google Works?
Google Search Mission is to Organize the world’s information and make it universally accessible and useful. Simply put, Google crawls websites on the web using robots called spider. It indexes all the crawled websites. Every time a user searches, Google uses its ranking algorithms to pick out the most relevant websites from its index. Watch a 3-minute video on how Google Search works here!
Google Search Algorithms
Check this link out for a Timeline of Google Search Algorithms. Google makes updates to its ranking algorithm almost every day. Here’s a summary of the major algorithms it has updated over the years,
- PageRank (First ever Algorithm)
- 2003: Crackdown on sites that manipulate links as votes
- 2010: Account Signals from social media
- 2011-2015: Panda Algorithm. Demote ad-heavy & Thin Content
- 2012-2016: Penguin Update. Took a swing at websites using spammy tactics, keyword stuffing
- Machine Learning + Semantic Search: Interpreting what we really mean when type them
Google can answer our questions because it is getting better at Semantic Search – interpreting what the user really means when he / she types something.
Semantic Search
Google tries to understand the entire phrase / sentence that you typed, instead of just matching websites with the keywords inputted.
Types of Google Searches
People search Google with various intentions. Following is a summary of the types of searches, referenced to 2 papers on User Intents on search engines (Jansen, Booth & Spink, 2007) & (Rose & Levinson, 2004)
| Transactional (DO) | Buy Something, Download, Sign Up |
| Informational (KNOW) | List – Places to Eat, Travel, Amsterdam Universities Locate – McDonalds, MRT Station Advice – Help quit smoking, how to draw portraits Directed (Closed Questions) – What is the height of Eiffel tower? Directed (Open Questions) – Why are metals shiny? Undirected – Color Blindness |
| Navigational (GO) | Install Firefox Navigate to Tesla.com |
Informational Search makes up 50-80% of all searches. A search for McDonalds will show you a Google Maps preview with your location and McDonalds chains nearest to you. A search for the height of Eiffel tower yields an instant answer. Clearly the ranking algorithm is altered based on your search intent.
As Google got better, people expected more from Google. With the huge traffic of searches and constant refinement of their algorithms, Google can interpret your search intents. So, what’s next?
What’s next for Google?
Google just launched Accelerated Mobile Pages (AMP) Stories for web content creators to deliver content in a creative and engaging manner to users. Check it out here!
Google is also improving its Search Engine Results Pages (SERP). Google aims to optimize the display of information so that users are given what they are looking for instantaneously.
The Search Engine Results Page (SERP) is presented just like an independent webpage. When you search for “Elon Musk” you will see the Knowledge Graph, latest news and latest social media posts on top of the relevant websites.
Quick Questions are derived from the most frequent searches and presented to a user on the Search Engine Results Page!
Search for “Hotels” and you will see a map with prices plotted! This is a new improvement to the SERP. You can even filter hotels by dates and by prices on the Google Search Page itself.
Wrapping Up
The act of “Googling” has been so intertwined with our lives that we do not question how Google (a website) can answer any of your questions. Keep a look out for the AMPS and changes to SERP when you Google in future!
References
Jansen B.J., Booth D.L., & Spink A. 2007. Determining the User Intent of Web Search Engine Queries.
Retrieved from https://dl.acm.org/citation.cfm?id=1242739
Rose D.E., Levinson D. 2004. Understanding User Goals in Web Search
Retrieved from https://dl.acm.org/citation.cfm?id=988675
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