Machine learning models and upskilling SEO

Lee Wilson, head of services and SEO at Vertical Leap, has had enough of organisations putting together elaborate campaigns, content and metrics which ultimately don’t go anywhere. All that wasted effort from businesses who have the right intentions. So what are the biggest mistakes companies can make?

“Fundamentally, this occurs as content is created based on assumption, gut feel, plus broader perceptions that ‘it seemed like the right thing to do at the time’,” Wilson (left) tells MarketingTech. “What this methodology inevitably leads to are companies frustrated by ineffective blogs, community hubs, and large volumes of digital content that underperforms or fails to contribute at all towards company goals or objectives.”

The result of this frustration is Data-Driven Marketing Content: A Practical Guide, published this month, which aims to give an overview and examples of how, in the data deluge teams face today, there are strategies that can be utilised across the board.

The key is that the book goes through the journey from data to content rather than the other way around, exploring machine learning models as well as devising a data-driven ecosystem across channels. Wilson argues that marketers’ knowledge of machine learning has ‘skyrocketed’ and that general knowledge of the concepts can be applied to various strategies, such as influencing sales and conversions, and where and why there are drops in the sales funnels. From this, data science specialists can be deployed to take it to the next level.

“The more machine learning becomes part of the business culture and approach, the easier it becomes to justify the increased investment towards dedicated data science and related specialisms,” says Wilson. “Agencies can play a useful role with the accessibility and access to these bespoke roles without all of the investment as part of agile delivery approaches and wider access to expertise provision.”

As with Lifescale, another recent book covered by this publication, the book is written with the complete journey in mind, including mis-steps. Chapter five focuses on understanding why initial data-driven content approaches aren’t working. Wilson notes the rationale. “The notion of self-assessment is paramount with practical business and guides such as this, because people need to try to be objective, honest, and open to change, so that they can quickly identify and act on the obstructions preventing them from generating greater returns from their content efforts,” he says.

In January, MarketingTech published a piece from William Kammer, director of SEO at Clearlink, who posited that SEO professionals needed to upskill and immerse themselves in a data education. For Wilson, this approach makes perfect sense for anyone looking to go through the book. “A data mindset is a fundamental part of SEO, and I see data as the foundation from which SEO delivers almost all of their insights, actions and meaningful touchpoints with their customers and campaigns,” he explains. “Data enhances everything when it comes to SEO, content, and business, providing it is reliable, accurate, and useful.”

Ultimately, the book can be consumed both as a full piece and in bitesize chunks. For Wilson, it can also be seen as a self-help guide – assuming of course the motivation is there to transform content strategies through data.


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