RobotWhen Google announced it has developed an artificial intelligence (AI) system as part of its Hummingbird algorithm, online marketers were put on red alert.

Codenamed RankBrain, the latest instalment of Google’s search algorithm and uses machine learning technology to give the capacity to become more intuitive.

In short, Google’s search engine will get intuitively smarter the more information it learns. The machine learning algorithm will become a major player in the way searchers interact with web pages.

The SEO of the future

Traditionally, SEO has focused on keyword targeting and anchor text to flag up web pages. Hummingbird was designed to change all that by recognising the context of search terms and matching them to longtail keywords.

Hummingbird didn’t work so well, partly because marketers or searchers did not understand how it worked, and now we find out, probably because Google’s search technology was insufficient.

Enter BrainRank, an algorithm that identifies the signals potentially without the need for specific keywords. With AI, search engines could possibly deliver results based on how searchers interact with the results.

For example, if a searcher clicks on a url page from the list of results, but returns to the search results relatively quickly, search engines may stop ranking that site in results in relation to the search, deeming the page less relevant to the query.

The emphasis for marketers then rests squarely on the need for quality content that has specific focus, aligned with user intent.

Predictive search

The second major signal is predictive search. It is already happening. If you check how the weather is going to be fairly often, you will start getting notifications for the forecast without even asking for it.

This is the intuitiveness of machine learning. A user’s search engine becomes customised for them on a personal level.

Sooner rather than later, Google will be serving content on a plate to readers without them even asking for it.
Predictive search will learn from user behaviour and track preferences across multi-media platforms; shopping interests, entertainment preferences, content preferences etc…

The challenge for online marketers is to focus on personalising content for customers to ensure they visit your website more than your competitors.

Now machine learning capabilities in search engines have been thrown into the online equation, marketers are challenged with new ways of developing their marketing strategy so you continue to reach customers.