Machine Learning For Organic Growth

How can you improve your link building strategy?

Which modern techniques can help you boost organic growth?

What are the most important link metrics to consider for organic search visibility?

Google knows, and its machine learning capabilities know – but do you?

With Google now able to understand the broader context of your content through machine learning and natural language understanding, we see that relevancy significantly impacts your search rankings.

It’s time to use machine learning’s progress in relevancy to help you tailor your link building strategy.

On October 26, I moderated a webinar with Beth Nunnington, VP of Digital PR and Content at Journey Further, and Steve Walker, Technology Director.

Nunnington and Walker demonstrated how relevant branded content is the key to increasing visibility and traffic for winning SEO performance, with machine learning in mind.

Here is a summary of the webinar. To access the entire presentation, complete the form.

Key Takeaways

• Focus on improving keyword relevance through digital PR.
• Don’t rely on volume or ‘domain authority’ metrics for measuring success.
• Understand that the relevance of your link profile can give you a competitive advantage.
• ‘Link bait’ creative campaigns will only get you so far.
• Product-focused PR gets results and can be used to target specific areas.

[Get access to the full on-demand webinar] Instantly access the webinar →

Top Considerations For Organic Growth

Link and content relevance can drive organic performance.

And when it comes to building relevance, there are four key areas of relevance that you need to consider:

• Audience interest.
• Brand authority.
• Keyword relevance.
• Topical relevance.

When it comes to developing your digital PR or content marketing strategy, topic relevance must be one of your biggest focuses.

[See how Ikea does it] Instantly access the webinar →

Next up is link building.

Google thinks relevance is important, and John Mueller mentions that the total number of links doesn’t matter.

Image created by Journey Further, Oct 2022

So, if the number of links doesn’t matter, how do you measure relevance?

Machine learning can help with that. Here’s how.

How To Use Machine Learning To Measure Relevance

Machine learning allows you to measure and understand content at scale.

With the use of tools, you can get a quantitative score that can measure the relevance of an article.

By submitting the entire link profile of your website into these tools, machine learning can then read all of those links, plus all those articles that have the links within them.

Then, you’ll get a list of the most prevalent topics, keywords, entities, sentiments, and scores.

With it, you can gain insights into topics, themes, and concepts that you can use to improve your strategies.

Image created by Journey Further, Oct 2022

[See in machine learning in action] Instantly access the webinar →

Drive Organic Growth With Relevance

Several studies have shown that relevancy positively correlates with organic market share.

The key to driving quality over quantity is to focus on content relevant to the keywords you want to rank for and your target audience.

[Find out how a search engine and a robot view the backlink profile of a business] Instantly access the webinar →

[Slides] Smarter Link Building: How To Use Machine Learning To Accelerate Organic Growth

Here’s the presentation:

Join Us For Our Next Webinar!

How To Build A Winning MarTech Stack In 2023

Join iQuanti’s Vishal Maru, VP of Digital Solutions and Shaubhik Ray, Senior Director of Digital Analytics, as well as Tealium’s Josh Wolf, Director of Partner Solutions Consulting, as they discuss the implications, pros, and cons of the leading MarTech platforms.

Image Credits

Featured Image: Paulo Bobita/Search Engine Journal