A web search engine is a software system designed to search for information on the web and the search results are generally presented in a line of results often referred to as search engine results page (SERPs). The information may be a mix of web pages, images, and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories, which are maintained only by human editors, search engines also maintain real-time information by running an algorithm on a web crawler.

Why is search so influential? Because search is one of the best ways to find content and the absolute best way for a marketer to determine consumer intent.

AI

Google wants site owners to focus on developing great content — clear, accurate, highly-readable content that other site owners want to link to. The way modern engines make this determination is by using advanced natural language processing, artificial intelligence and machine learning. 310 These evolving technologies enable the search engines to understand content without relying on a small set of specific keywords and phrases. Google has invested heavily in this area, as evidenced by the plethora of white papers and research posted on its ‘Machine Intelligence’ website. One aspect of today’s search engines that makes them very different from their predecessors is that advances in artificial intelligence and machine learning have enabled them to understand content and its underlying concepts independently of specific keywords. This renders null and void the old concept that one must focus on keywords specific to a certain kind of content in order to be found via search engines. In today’s landscape, exact keyword matches are less influential than ever before as engines can understand the relationships between words that are semantically related.

There are three key areas in which AI can improve SEO performance:

1. Insights

2. Automation

3. Personalization

AI can process and analyze data at a scale simply not possible for humans. This makes it an essential complement to any search strategist, as AI can deliver the information we need to make informed decisions out of noisy, unstructured data. AI can be used to glean SEO insights in the following ways:

• Understand underlying need in a customer journey.

• Identify content opportunities.

• Define opportunity space in the competitive context.

• Map intent to content.

• Use structured data and markup.

• Invest in more long-tail content.

• Ensure content can be crawled and surfaced easily by all user-agents.

• Automation.

SEO is a labor-intensive industry that requires a huge amount of attention over the long term. Where we can automate tasks to receive the same output, we could produce ourselves, we should make this a top priority. The time saved through automation can be applied to the areas that require our skills, like strategy and creative content. Ultimately, AI can be used for SEO personalization in the following ways:

• Create content by persona, customer journey stage and delivery mechanism.

• Enhance user experience and conversion through personalization.

• Use semantically specific pages to associate query and intent.

• Use personalization and audience lists to nurture leads across search and social.

• Use AI to help publish content at the right times on the right networks.