Information Gain is the newest concept in Search Engine Optimization (SEO) and the interpretation is varying. It is basically being viewed in three perspectives. One is with respect to machine learning, another is through Google’s patent developments and lastly from the theory of information foraging.

In the first case the Information Gain plays an important role in training algorithms and particularly in the decision trees. However, the concept remains a bit complex for those who deal the least in programming and data science.

In the second perspective it refers to a significant Google patent that was granted in 2022 and introduced a method for evaluating content similarity as well as adjusting ranking accordingly. This means it is strictly about the strategy of Google in combating duplicate or unoriginal content.

Now let us talk about the information foraging theory part that was popularized by Peter Pirolli’s book. It draws intriguing parallels between how animals look for their food and how humans navigate through vast amounts of information to make informed decisions.

Lately, Google showed interest in this information foraging theory. It acknowledged the challenges faced by information overload. Decision-making sometimes become time-consuming and cumbersome due to so much of information available on the web.

Leveraging generative AI is the response of Google to the challenge as it is capable in providing immediate answers to search queries. This reduces the need for users to visit individual websites. Hence, it aims to streamline the decision-making process.

The shift from traditional search engine to AI search engine is a significant evolution in SEO strategies. SEO professionals can now focus more on optimizing content in order to facilitate information extraction for humans as well as machines. They have to rely less on Google algorithm.