How AI can automate SEO tasks at scale


Artificial intelligence, machine learning and neural networks are major buzzwords in the SEO community today. Marketers have highlighted the ability of these technologies to automate time-consuming tasks at scale, which can result in more successful campaigns. However, many professionals often have difficulty distinguishing between these concepts.

“Artificial intelligence is essentially the term that defines all space,” said Eric Enge, President of Pilot Holding and a former director at Perficient, in his presentation SMX further. “Machine learning is a subset of that [AI] tuned around certain algorithms.”

Natural Language Processing (NLP) is another system that has been used for SEO tasks in recent years. It mainly focuses on understanding the meaning behind human language.

“NLP is about helping computers better understand language the way a human does, including the contextual nuances,” he said.

With so many development technologies available, marketers should learn how to apply them to their campaigns. Here are three ways AI and its branches can automate SEO tasks at scale.

AI can meet customers’ long-tail needs

Enge indicated a customer search to learn from Bloomreach, who found that 82% of the B2C buyer experience is spent searching and browsing. This leaves room for many long-tail searches that are more niche and therefore often overlooked by marketers.

Bloomreach’s proprietary AI tool is primarily focused on extracting insights from this discovery phase, Enge explained. It can identify website content that is under-utilized and matches long-tail searches from customers.

“AI improves pages by presenting more related pages that aren’t currently linked to,” he said, “or potentially even creates new pages to fill in the gaps in those long-tail needs and create a better customer experience.”

Source: Eric Enge and Bloomreach

Marketers can use AI systems to generate more relevant pages based on these long-tail interests. However, there are some limitations that you should be aware of.

“Just be careful not to create too many new pages,” Enge said. “There are certainly cases where too many sides can be bad. But if used correctly, it can be very effective.”

AI can enable automated content creation

Enge shared some information about GPT-3, a popular AI language model, to demonstrate AI’s content creation capabilities. While impressive, he noted how a system like this can spiral out of control when it doesn’t correct restrictions.

“She [AI systems] not a real-world model at this time,” he said. “They only have the data they were trained on. They don’t have perspective or context for anything, so they can make really bad mistakes, and when they write, they tend to be biased.”

“The wonderful thing about the internet is that it contains all the information in the world – the terrible thing about the internet is that it also contains all the disinformation in the world,” he added.

Despite these weaknesses, AI systems hold promise. Continuous improvements in these technologies can help marketers scale their content efforts to meet customer expectations.

GPT-3 in particular can generate content in a variety of formats, allowing SEOs to focus more on optimization efforts.

“You can use it [GPT-3] to create new content,” Enge said. “You have to make a lot of effort and bring in a lot of specialist knowledge. It may or may not be cheaper than writing from scratch, depending on how good you are.”

AI can use deep learning to build current authority

Having topical authority means your site is a perceived expert on a specific topic. This is one of the factors that many SEOs believe is vital to improving rankings, which is why so many have harnessed the power of AI.

Enge pointed to seoClarity, which uses an AI tool called Content Fusion to help brands write with more authority to highlight those deep learning skills: “The approach is to use deep learning to break down entities and words.” to identify that will help you build authority on an issue,” Enge said. “It extracts intentions, entities, terms and potentially related topics. Then they apply their machine learning models specific to your market space.”

Deep learning content fusion pipeline
Source: Eric Enge and seoClarity

The deep learning capabilities provide marketers with a clearer view of their brand’s domain, which can then be used to further develop their web properties. Setting up an automated deep learning system can provide them with new data to demonstrate EAT (Expertise, Authoritativeness, Trustworthiness).

Each AI integration looks different, but each has the potential to enhance your SEO efforts through automation and machine learning.

“There’s an incredible amount happening out there with AI,” Enge said. “Some of these you can handle yourself if you’re willing to do the programming; in other cases, you can use tools. It depends on you.”

Watch the full SMX Next presentation here (free registration required).

New in search engine land

About the author

Corey Patterson is a contributing editor for MarTech and Search Engine Land. With a background in SEO, content marketing and journalism, he covers SEO and PPC industry news to help marketers improve their campaigns.


Comments are closed.