Google’s rollout of artificial intelligence has many in the search engine optimization (SEO) industry dumbfounded. Optimization tactics that have worked for years are quickly becoming obsolete or changing.
The SEO industry began with people deciphering algorithm updates and determining which web pages they affected (and how). Businesses rose and fell on the backs of decisions made due to such insights, and those that were able to course-correct fast enough were the winners. Those that couldn’t learned a hard lesson.
It has only been recently that Google has possessed the kind of computational power to begin to make “real-time” updates a reality. On June 18, 2010, Google revamped its indexing structure, dubbed “Caffeine,” which allowed Google to push updates to its search index quicker than ever before. Now, a website could publish new or updated content and see the updates almost immediately on Google.
As search evolves, our approach is evolving with Google’s algorithmic changes. We analyze topics, search intention and sales funnel stages because we’re also using deep learning techniques in our platform. We highlight content relevance because Google now prioritizes meeting user intent.”
These isolated testing cycles were now very important in order to determine correlation, because day-to-day changes on Google’s index were not necessarily tied to ranking shifts anymore.
Is there a way we, as SEOs, can start to quantitatively understand the algorithmic differences/weightings between keywords? As I mentioned earlier, there are ways to aggregate this information using existing tools. There are also some new tools appearing on the market that enable SEO teams to model specific search engine environments and predict how those environments are shifting algorithmically.
A lot of the answers depend on how competitive and broad your keywords are. For instance, a brand that only focuses on one primary keyword, with many variations of subsequent long-tail keyword phrases, will likely not be affected by this new way of processing search results. Once an SEO team figures things out, they’ve got it figured out.
On the flip side, if a brand has to worry about many different keywords that span various competitors in each environment, then investment in these newer technologies may be warranted. SEO teams need to keep in mind that they can’t simply apply what they’ve learned in one keyword environment to another. Some sort of adaptive analysis must be used.
Courtesy of SearchEngineLand
