The End of the Search Era

A short history of web search

Long before the monopoly of Google was a fact, the beginning of web search was marked by the creation of early engine prototypes like Archie, Veronica and later on, Yahoo!, starting in the early 1990s. Newer models of search engines have since enjoyed decades of high usage and prosperity when it comes to providing web users around the world with the desired information at their fingertips, on top of offering advertising opportunities to businesses.

In the early days, search engines worked with exact keyword phrase matches only, rendering them only marginally more useful than typing in a website’s exact URL. Today, they are powered by advanced technology, including machine learning and artificial intelligence. Still, there has been a notable decline in web searches and search engine usage in the past few years. This signals an end to the search era as we know it and marks the beginning of a new phase of searching for both web users and search engine providers.

Feed and apps vs. search

The decline in web searches is largely due to the changing ways, in which consumers search. While most web users still use search engines like Google and Bing to locate things of interest, many are turning to social media channels and dedicated apps to search for things. For example, most hotel and vacation property searches today take place on websites and mobile applications like Booking.com or Airbnb.com, while people searches take place on the websites or apps of Facebook, Twitter or LinkedIn. When looking for flight tickets, apps and dedicated websites like Skyscanner or Kiwi are most often utilized, despite Google’s fledgling market entrance with Google Flights. When looking for household items, many users go directly to portals like Amazon or Alibaba/Ali Express, rather than searching the world wide web for them.

While website vs. in-app searches still depend mostly on user preference and whether a desktop or a mobile device is utilized, many are transitioning away from traditional search engines and switching to searching for specific articles or services in dedicated, third-party mobile apps or widgets. While this trend hardly marks the end of search engines altogether, it is certainly going to affect the way search results are presented to consumers.

Predictive search and other search trends

Contrary to the way search largely worked until recently, search algorithms and AI are becoming more predictive, personal and intuitive. The introduction of Google’s auto-complete feature (now also adopted by many e-retail and booking websites) was a taste of what was coming, in terms of search engines telling us what we are looking for, instead of the other way around. The introduction of voice search was a pre-cursor to today’s predictive search functionality as well, though, it still relied on user input and keyword matching.

Unlike this way of delivering results, with predictive search users should no longer have to type in or say keywords out loud – search engines, feeds, and apps will already know what they are looking for before the search takes place, and can thus suggest it to them. This type of deep knowledge of the user is, of course, based on past user behavior, interactions with other apps, and various third-party data integrations.

With the decline in the share of web search, the importance of content SEO (search engine optimization) is also shifting. For example, Google Now serves as a personal assistant that can predict our deepest desires – and having content optimized for search engines does not have a significant bearing on its functionality or effectiveness. Rather than optimizing for search engines, going forward, businesses would need to optimize for convenience and utility. In other words, they would need to figure out how to make it easier for aggregate booking or e-retail providers (Google included) to sell their products and services, at the cost of commission, of course.

Privacy concerns

All this utility and convenience come at the price of privacy, of course. For predictive search to work, machine learning needs to have access to heaps of up-to-date information about user searches, websites and apps visited, actions performed, and more. While convenient, this is not necessarily in line with recent privacy regulations in Europe, such as GDPR and the upcoming e-privacy laws, which are likely to restrict third-party cookie tracking even more. Thus, the future of predictive search is somewhat in question, as there are many privacy concerns to be overcome.  

Nevertheless, investing in innovative algorithms and in-app search technology that make it easier for users to locate your products or services on owned or third-party portals, is certainly a good idea.

 Contact the Pegus team of experts,if you are interested in making your business or enterprise app more searchable.

 

Copywriter inadanova.com