Online Medical Marketing Blog

How Will Google's Machine Learning Algorithms Impact Your Medical Practice's SEO Strategy?

Written by Jonathan Catley | Feb 2, 2017 5:00:00 AM

As Google continues to invest in machine learning technology, medical marketers will need to reevaluate their website content if they don’t want to be penalized.

I recently came across an interesting article by Eric Enge, writing for Search Engine Land, about how Google’s machine learning technology will impact search engine optimization (SEO) best practices.

As the technology continues to advance, medical marketers will need to take proactive measures in increasing both the quantity and quality of content on their website pages — or risk being buried in the search engine results, cut off from prospective patients looking for health-related information or treatment options. Here’s what you need to know.

It’s All About the User Experience

Google’s investment in machine learning comes as part of a larger push among search engines to better understand complex sentences and “natural language.” In addition to improving the quality of search results in general, one of the key drivers of this trend is the rise of speech-recognition technology and voice search.

Last year, 40% of adults conducted at least one voice search per day. What’s more, 20% of Google’s mobile searches are now voice-based queries, and that number is expected to rise to at least 50% by 2020. Recognizing this shift early on, Google rolled out Hummingbird, its first machine learning algorithm, back in 2013, which was replaced by RankBrain in 2015.

Google's hope is that these advancements will help it gain a better understanding of user intent, along with the ability to evaluate content quality more efficiently and accurately. Moreover, as consumer preferences continue to shift, the algorithm will be capable of evolving and adapting with minimal human intervention.

Quality Content Will Win the Day

According to Enge, “Google (and other engines) are interested in leveraging user satisfaction/user engagement data as well. Though it’s less clear exactly what signals they will key in on, it seems likely that this is another place for machine learning to play a role.”

For example, Google has already acknowledged it uses click through rate (CTR) as a “quality control” factor (though many believe it directly impacts ranking). However, it’s probable that the behavior of a user once they arrive on your site will now be factored into the equation more heavily. How long did the user stay on the page? How many other pages did they visit on your site?

As Google’s algorithms become more adept at analyzing content quality, and the measure of content quality becomes increasingly based on user engagement data, medical marketers will need to ensure that all of their web pages are optimized to meet the needs and preferences of their target audience, i.e., the people who land on them. Enge lists five key areas that should be evaluated in order to thrive in this new SEO environment:

  1. Is the symptom- or treatment-related information present on the page?
  2. Is it prominently displayed and written in a digestible way?
  3. Can supporting or related information be easily located on the page?
  4. Does the page project an air of expertise and credibility to your prospective patients?
  5. How engaging and intuitive is the design and layout of your page?

At the end of the day, we’re effectively dealing with the same basic set of rules — it’s just that Google’s investment in machine learning means it’s become better at enforcing them than ever before. What’s more, as its understanding of nuance and natural language advances, that ability will continue to improve exponentially over time.