AI for SEO is at a tipping point where the technology used by big corporations is increasingly within reach for smaller businesses.
The increasing use of this new technology is permanently changing the practice of SEO today.
But is it right for your business? These are the surprising facts.
What Is AI For SEO
AI, or artificial intelligence, is already a part of our daily lives. Anyone who uses Alexa or Google Maps is using AI software to make their lives better in some way.
Popular writing assistant Grammarly is an AI software that illustrates the power of AI to improve performance.
It takes a so-so piece of content and makes it better by fixing grammar and spelling mistakes and catching repetitive use of words.
AI for SEO works similarly to improve performance and, to a certain degree, democratize SEO by making scale and sophisticated data analyses within reach for everybody.
How Can AI Be Used In SEO
Mainstream AI SEO platforms automate data analysis, providing high-level views that identify patterns and trends that are not otherwise visible.
Mark Traphagen of seoClarity describes why AI SEO automation is essential:
“A decade ago, the best SEOs were great excel jockeys, downloading and correlating data from different sources and parts of the SEO lifecycle, all by hand.
If SEOs were doing that today, they’d be left in the dust.
By the time humans can process – results have changed, algorithms updated, SERPs shifted, etc.
And that’s not to mention the access and depth of data available in this decade, fast-paced changes in search engine algorithms, varying ranking factors that are different for every query, intent-based results that change seasonally, and the immense complexity of modern enterprise websites.
These realities have made utilizing AI now essential at the enterprise level.”
AI In Onsite Optimization
AI SEO automation platform WordLift helps publishers automate structured data, internal linking, and other on-page-related factors.
Andrea Volpini, CEO of WordLift, comments:
“WordLift automatically ingests the latest version of the schema vocabulary to support all possible entity types.
We can reuse this data to build internal links, render context cards on web pages, and recommend similar content.
Much like Google, a publisher can use this network of entities to let the readers discover related content.
WordLift enables many SEO workflows as the knowledge graph of the website gets built.
Some use WordLift’s NLP to manage internal links to their important pages; others use the data in the knowledge graph to instruct the internal search engine or to fine-tune a language model for content generation.
By automating structured data, publishing entities, and adding internal links, it’s not uncommon to see substantial growth in organic traffic for content creators.”
AI For SEO At Scale
AI for SEO can be applied to a wide range of activities that minimize engaging in repetitive tasks and improves productivity.
A partial list includes:
- Content planning.
- Content analysis.
- Data analysis.
- Creation of local knowledge graphs.
- Automate the creation of Schema structured data.
- Optimization of interlinking.
- Page by Page content optimization.
- Automatically optimized meta descriptions.
- Programmatic title elements.
- Optimized headings at scale.
AI In Content Creation
Content creation consists of multiple subjective choices. What one writer feels is relevant to a topic might be different from what users think it is.
A writer may assume that a topic is about Topic X. The search engine may identify that users prefer content about X, Y, and Z. Consequently, the content may experience poor search performance.
AI content tools help content developers form tighter relationships between content and what users are looking for by providing an objective profile of what a given piece of content is about.
AI tools allow search marketers to work with content in a way that is light years ahead of the decades-old practice of first identifying high-traffic keywords and then building content around them.
AI In Content Optimization
Search engines understand search queries and content better by identifying what users mean and what webpages are about.
Today’s AI content tools do the same for SEO from the entire content development workflow.
There’s more to this as well.
In 2018 Google developed what they referred to as the Topic Layer, which helps it understand the content and how the topics and subtopics relate to each other.
Google described it like this:
“So we’ve taken our existing Knowledge Graph—which understands connections between people, places, things and facts about them—and added a new layer, called the Topic Layer, engineered to deeply understand a topic space and how interests can develop over time as familiarity and expertise grow.
The Topic Layer is built by analyzing all the content that exists on the web for a given topic and develops hundreds and thousands of subtopics.
For these subtopics, we can identify the most relevant articles and videos—the ones that have shown themselves to be evergreen and continually useful, as well as fresh content on the topic.
We then look at patterns to understand how these subtopics relate to each other, so we can more intelligently surface the type of content you might want to explore next.”
AI content tools help search marketers align their activities with the reality of how search engines work.
AI In Keyword Research
Beyond that, they introduce content workflow efficiency by enabling the entire process to scale, reducing the time between research and publishing content online.
Mark Traphagen of seoClarity emphasized that AI tools take over the tedious parts of SEO.
Mark explained:
“seoClarity long ago moved from being a data provider to leveraging AI in every part of the SEO lifecycle to move clients quickly from data to insights to execution.
We use:
AI in surfacing insights and recommendations from different data sources (rankings -> SERP opportunities -> technical issues)
AI in delivering the most accurate data possible in search demand, keyword difficulty, and topic intent — all in real-time and trended views
AI in content optimization and analysis
AI-assisted automation in instant execution of SEO enables changes at massive scale.
The future of AI in SEO isn’t AI “doing SEO” for us, but rather AI taking over the most time-consuming tasks freeing SEOs to be directors implementing the best-informed actions at scale at unheard of speeds.”
A key value of using AI for SEO is increasing productivity and efficiency while also increasing expertise, authoritativeness, and content relevance.
Jeff Coyle of Market Muse outlines AI’s benefits as creating justification for how much is budgeted for content and what value it brings to the bottom line.
Jeff commented:
“When more of the content strategy you budget for turns into a success, it becomes immediately apparent that using AI to predict content budget needs and drive efficiency rates is the most important thing one can invest in for a content organization.
For operations, human resource efficiency is the top priority. Where do you have humans performing manual tasks for research, planning, prioritizing, briefing, writing, editing, production, and optimization? How much time is lost, and how many feedback or rework loops exist?
Data-driven, predictive, defendable content creation and optimization plans that yield single sources of truth in the form of content briefs and project plans are the foundation of a team focused on using technology to improve human resource efficiencies.
For optimization, picking the content to update, understanding how to update it and whether it needs to be parlayed with creation, repurposing, and transformation are the critical advantages of using AI for content analysis.
Knowing if a page is high quality, exhibits expertise, appeals to the right target intent, and is integrated into the site correctly gives a team the best chance to succeed.”
Drawbacks And Ethical Considerations
Publishing content that is entirely created by AI can result in a negative outcome because Google explicitly prohibits autogenerated content.
Google’s spam guidelines warn that publishing autogenerated content may result in a manual action, removing the content from Google’s search results.
The guidelines explain:
“To be eligible to appear in Google web search results (web pages, images, videos, news content, or other material that Google finds from across the web), content shouldn’t violate Google Search’s overall policies or the spam policies listed on this page.
…Spammy automatically generated (or “auto-generated”) content is content that’s been generated programmatically without producing anything original or adding sufficient value; instead, it’s been generated for the primary purpose of manipulating search rankings and not helping users.”
There’s no ban on publishing autogenerated content and no law against it. Google even suggests ways to exclude that kind of content from Google’s search engine if you choose to use that kind of content.
But using automatically generated content is not viable if the goal is to rank well in Google’s search engine.
Can Google Identify AI-Generated Content?
Yes, Google and other search engines can likely identify content that is entirely generated by AI.
Content contains word use patterns unique to both human and AI-generated content. Statistical analysis reveals which content is created by AI.
The Future of Tools Is Now
Many AI-based tools are available that are appropriate for different levels of users.
Not every business needs to scale its SEO for hundreds of thousands of products.
But even a small to medium online business can benefit from the streamlined and efficient workflow that an AI-based content tool offers.
More resources:
Featured image by Shutterstock/Master1305
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