In part one of our AI-enabled SEO series, we focused on content creation. There is much more to cover when it comes to what AI has the potential to do for B2B SEO. AI for content development seems to be where everyone's mind goes first, but AI for SEO goes beyond content. A holistic view will help you to identify additional opportunities.
Internal linking is an area of SEO focus for B2B sites, especially large sites, that can be very effective in driving performance, but it is also very challenging to manage at scale for large enterprise sites. Generative AI tools are not much help in this regard unless you want to import data into Google Sheets and use a ChatGPT plugin. Even then, it’s a clumsy solution.
There are content creation tools like SEO Content.ai that suggest internal links based on AI semantic analysis. And other AI SEO tools can help automate internal linking at scale using similar principles like SEOClarity’s internal link automation feature. If you are using WordPress, plugins like Linksy or AutoLinking can accomplish the same goal.
There are a variety of solutions available to manage internal links at scale using AI. Because internal links are highly effective for B2B sites with a lot of thought leadership content, and because those sites are often hard to manage at scale while constantly accounting for new content that is being produced, I would recommend evaluating the feasibility of implementing an AI internal link solution for almost any large site.
Several different tactics can be employed to help sites attract and acquire relevant links that increase SEO performance. Most of these techniques involve some sort of outreach which requires contact information about the target sites, publishers or authors. Identifying the people, and their contact information, that are going to have the greatest probability of interacting with you in a way that ends up generating a link to your site is a time-consuming and sometimes difficult task.
Fortunately, AI tools are now being developed that automate this research and improve the accuracy of finding the right information. AI tools like Hunter can be used to identify site owners to reach out to for links, bloggers to reach out to for guest blog opportunities, or social influencers to reach out to for partnerships that might result in link-building opportunities.
In addition to identifying contact information, generative AI tools like ChatGPT can help create personalized outreach emails based on company name, contact information, purpose of the outreach, and title of the proposed guest blog post. This is especially true if you integrate ChatGPT into Google Sheets.
I anticipate link building being a space that AI continues to advance in over the next year.
Another area of B2B SEO that promises to be impacted by AI going forward is analytics, data analysis, and SEO reporting. Using AI to create better data-driven decisions is still a work in progress but it continues to advance with new AI tools being released every month that expand use cases.
The most popular analytics platform on the market today is Google Analytics which just made the transition to GA4. There are some inherent AI and machine learning capabilities within this tool including data modeling. The most visible are the new Analytics Insights features which are AI-driven. This new functionality allows GA4 to use AI to surface important observations about your data in a conversational way that lends itself to easier understanding and better utilization of data driving business decisions and website performance.
In addition to AI being used for GA4 to augment reporting and data analysis, other analytics vendors offer solutions that leverage AI in other ways. Companies like AnswerRocket and Tellius are alternatives leveraging AI to better understand web performance (including SEO) and identify growth opportunities.
The ability to use natural language to correlate multiple data points and see patterns and trends that a human wouldn’t be capable of identifying is probably the most exciting use case for AI-driven analytics. Especially as it relates to B2B SEO where multiple touch points, across multiple channels, from multiple people within the same organization, make it exceedingly difficult to understand the content segments and user trends that are having the greatest impact on successful business outcomes.
Both of these tools and others are leading the charge to leverage AI to overcome challenges and make better use of the analytics data that we have to drive success.
One of the interesting applications of AI, as it relates to SEO reporting, is the ability of some tools to give greater insight into what keywords are driving organic traffic. Keyword Hero uses machine learning and AI to bring some visibility back to keywords that Google used to show but now labels “not provided”. Getting greater visibility into keyword referral data helps make better data-driven decisions around new content, prioritization of SEO activities, potential PPC opportunities, and brand versus non-brand performance.
Predictive analytics is another area where AI technology is changing how we can use data to drive performance. AI can analyze past data to predict future trends, helping businesses stay ahead of the curve and adapt their SEO strategies accordingly.
The most common use of predictive analytics and modeling right now is in GA4 with Consent Mode activated and the reporting identity set to “Blended”. This allows Google to report on how much traffic it thinks your site might have gotten over a certain period of time but isn’t showing in your analytics data because of people who opted out of being tracked.
Currently, this data is subject to two big problems that make it hard to use, especially at the URL level. Data thresholding for URLs that don’t get enough traffic (Google omits their traffic numbers to prevent discovery of personal information) and how Google models the data at the URL level make this data fairly inaccurate at this point of GA4. However, this situation is likely to improve over time.
In the B2B space, using ABM tools like 6sense that can identify and aggregate data for company interactions across multiple touch points and then use AI and machine learning to predict which of those companies is most likely to buy, can provide sales teams with a competitive advantage on how to prioritize their outreach for maximum results. These AI-powered insights also help companies to understand which content is driving the most engagement for high-intent interactions and can inform the content team what kind of content they should prioritize producing. It also informs the SEO team which keywords are mapping to those same intent signals.
This is a hugely valuable lens to be able to look at SEO performance through because not all leads are created equal. In B2B, the volume of traffic a keyword may drive is often less important than the quality of that traffic. AI Predictive Analysis, and the eventual validation of those predictions, give marketers focused on B2B SEO more confidence in their prioritization of keywords and content.
As we've explored throughout this series, artificial intelligence (AI) is no longer a futuristic concept; it's a powerful reality that's transforming the world of Search Engine Optimization (SEO) and, by extension, driving B2B growth. From keyword research, content optimization and creation, to data analytics and analysis, AI is revolutionizing the SEO landscape.
Keeping track of new AI tools and the new features and functionality they offer, understanding the caveats to those value propositions, and effectively employing those tools within the context of a successful B2B SEO program is critical to be able to stay competitive moving forward.
The integration of AI in SEO is shaping the future of online visibility and search. Embracing AI and incorporating it into SEO strategies is no longer an option but a necessity for B2B businesses aiming for growth.
The journey will continue to be challenging and the unprecedented change will be difficult to keep up with, but the potential rewards — increased visibility, improved user experience, more efficient use of time, and greater SEO performance — are well worth the effort.