Websites like Spotify is going great lengths to weed out a vast majority of the content, to put forth a short list of products that you, as their consumers would (hopefully) like. Filtering out content, or the removing the act of search to deliver content that the consumer seeks, is one of the major drivers of the popularity of recommendation engines – we need them.
The age of search has come to an end
The “Age of search” as we know it has come to an end. They say that the web is changing every day, it has moved on from search and entering the world of discovery. And, with online content growing exponentially, it is not humanly possible to screen the unfiltered firehose of information, to reach the one thing that we were actually looking for.
Let’s consider the most popular search engine Google. In 1996, Larry Page and Sergey Brin first started working on BackRub, the predecessor to Google Search. The crawler begins activity in March and in 1997, the domain Google is registered. The search option becomes available to the public in 1998, and the rest as they say, is history. Handling more than three billion searches every day, as of 2016 it remains the most popular search engine that exists in the world. So what changed? The answer, my friend, is the consumers. Data became the digital currency, and while content remained the ruler, companies who began displaying data in a meaningful way began winning as a brand.
With the advent of the new-age hyper-connected consumers, “recommendation engines” started gaining more popularity. These enabled discovery, allowing the seeker to find something wonderful, relevant to his search query that he didn’t know existed or didn’t know how to ask. It found its way to the search results. These recommendation engines would begin analyzing the behavior, browsing history and previous interactions of the seeker and use the data to draw conclusions between the product and product categories. Remember, how Playstore is now filled with recommendations?
Our undying love for personalization engines
These recommendation engines have changed the way we interact with technology, work, media, emails and so much more, these engines have enabled a creation of a personalized system of communication that we enjoy receiving. Most of us use it without even realizing it!
These engines can narrow down complex decisions to just a few, apt recommendations and the brands just love using recommendation engines because they can personalize their marketing mix and make it more engaging. Look at what Netflix, Amazon, or Facebook is doing. These companies have been able to use a combination of machine learning, personalized ranking and page regeneration to give their target audience the recommendations that get their end users hooked to the platform. Addictive as it is, companies like YouTube uses similar recommendation algorithms to make predictions – now you can understand why you see a stream of awesome videos on your Home page. That’s the power of personalization folks and that’s why we need recommendation engines.
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