Scaling B2B SEO; AI Content & Programmatic SEO Tactics To Dominate Search Engines & Lower SEM Costs

Of all of the marketing channels available to the modern B2B marketer, SEO in many ways remains one of the most perplexing – In many ways SEO still lives in an earlier incarnation of the internet where links are traded and dubious, hard to measure and hard to gauge tactics were used to try and dominate the SERPS. Yet SEO has vast potential to feed your marketing funnel and lower your SEM investment, whilst letting your brand benefit from the trust that high Google rankings can uniquely deliver.

When you add in that its often perceived that the query volume for B2B terms are too low, SEO falls into the back-burner of the different media approaches available. Yet when many of FunnelFuel’s clients are able to invest upwards of $1m per month on paid search, its intriguing that the organic approach still remains such a small part of the bigger picture. Especially when the insights it brings can help with programmatic advertising and delivering content led experiences into the content web based on robust first party data.

The benefits are clear, but what does a modern B2B approach to SEO look like, leveraging AI content creation and programmatic SEO?

Today we’re exploring the concept of programmatic SEO for B2B. You’ll likely be much more familiar with the term ‘programmatic’ when it comes to media buying and programatic advertising, but the concept as it pertains to SEO is actually much more one of content generation, and leaning in on the ChatGPT led world of AI-content creation to cover more ground with many more highly optimised pages targeting specific keyword variations.

Therefore, arguable Programmatic SEO is the route to scaling SEO. To effectively expand your SEO, Programmatic SEO could be the answer. “All” you have to do is create a massive amount of pages – occasionally reaching hundreds of thousands – focusing on a single keyword pattern. Clearly this would be so incredibly cost inefficient and expensive in years gone by the tactic would never have even been considered, but again, now we live in a world where AI is making SEO-unique content (if not quite great content) available for pennies in the pound.

Therefore, previously, programmatic SEO was only accessible to organisations receiving content from user-generated sources (UGC), e-commerce vendors (products), or data providers (SaaS) since these companies did not have to produce content themselves. The major obstacle to SEO progression has been the generation of content.

Integrators faced a hindrance in generating content themselves despite being able to produce a plethora of standardised pages. Human written words are costly, human written words that you’d actually want your B2B prospects to read are cripplingly expensive

Content creation bottlenecks can be vastly reduced with AI tools, enabling companies to implement programmatic content effectively, even in the absence of user-generated content, products or data.

Besides boosting traffic, these tools allow companies to conduct SEO split tests on programmatic content, optimise longtail queries and enhance customer acquisition costs through retargeting. Therefore the modern marketer sees this programmatic SEO as a spearhead for their other biddable media channels, meaning an AI written longtail content piece could trigger a marketing cascade and deliver the right to play and address that topic.

Integrators can benefit from Programmatic SEO.

Employing programmatic SEO involves generating multiple pages with a uniform structure, aimed at capturing a particular search pattern.

Betterteam created a plethora of job description pages as an illustration.

Causal provides an extensive library of formulas for Excel and Google Sheets, consisting of a whopping total of 1,000 pages.

Gusto offers a multitude of payroll calculators designed for various states.

All three of these illustrations are not aggregators, but rather integrators. The method for generating content for each programmatic page varies significantly.

The process of generating programmatic content involves five steps that remain consistent.

  1. Establish a specific set of query syntax or patterns that align with your product.
  2. Determine the page elements (such as features) that cater to the users’ purpose and those that have proven to be effective.
  3. The writers will then execute the content writing while the engineers may construct a calculator, as needed.
  4. Upon completion, the product will be shipped out for testing.
  5. Proceed with split testing procedures and make modifications accordingly.

The SEO strategy is centered around the product, which integrates the website as an essential component. The emphasis lies on creating landing pages instead of a content-oriented marketing approach that prioritises a content hub or blog.

Programmatic SEO is presented with a pair of fresh obstacles.

AI is revolutionising the way SEO works, as evidenced by one of the aforementioned examples utilising ChatGPT-4 to produce all its content. The success of this strategy has prompted some of my clients to adopt similar tactics, and it’s likely that more companies will follow suit.

Nevertheless, there are two fresh obstacles that surface: ensuring high standards of quality on a larger scale and monitoring the traffic generated by less popular SEO keywords. The latter can open up the longtail of traffic but many of these terms will generate a handful of queries per year, so your usual approaches to monitoring their business impact need to reflect this challenge

CNET recently discovered that AI tools are prone to hallucinations and are not always accurate when it comes to simple facts. Although AI performed well, it still got basic facts wrong, which could be attributed to the lack of human quality control. This situation raises questions about the effectiveness of Google’s fact-checking algorithms, but the overwhelming truth remains that editing and fact-checking cannot be automated at this time. This becomes a challenge if your objective is to create a LOT of content – the fact remains you cannot simply ask an AI tool to make content, and then simply copy, paste and publish.

When generating numerous pages with AI, whether it’s a hundred or thousands, who assures that the information provided is precise and dependable?

Human editors remain the ultimate fix. While they can’t comb through all pages, they can at least review a few samples. I believe that more scalable options for fact-checking will soon emerge in the market. In the meantime, plagiarism detectors such as Copyleaks, Unicheck, and similar tools can already offer some much-needed respite.

Some brands may take a more pragmatic approach. Putting the wider content live, with some robust sampling, and then editing, improving an enhancing the pages which start to get SERP traffic could offer a practical solution. If the page ranks, make it better, if it doesn’t, leave it be until if/when it does. Circle back in 3 months and look at SEO data to check which pages are getting close to the ranking and traffic driving action, and then improve them.

Achieving better quality outcomes involves dedicating time towards refining the prompt. I’ve found that several individuals hastily settle for their initial results, without exploring other possibilities. It takes around 10-20 iterations, or sometimes more, to obtain favorable outcomes. When applied on a large scale, thorough testing and modification of the prompt yield significant benefits.

Due to privacy concerns within search console, monitoring longtail traffic has become quite arduous, with over 50% of queries being filtered. A large website belonging to one of my clients, which has hundreds of millions of indexed pages, obtains an excess of unaccounted for longtail traffic, rendering Search Console obsolete. Although the server-side can tackle traffic tracking alone, pinpointing longtail keywords and monitoring their ranking is a challenge beyond solution.

To optimise tracking, it is recommended to divide traffic and rankings measurement. Analyse the channel-based traffic for both organic and inorganic sources and rely on third-party trackers for monitoring keyword rankings. Often, using sound judgement can help determine which query a page is prioritising.

In my humble opinion, AI content has a bright future despite the new obstacles that may arise. Although it may shift search patterns slightly, the benefits of enhancing SEO efficiency through its implementation outweigh the potential drawbacks.


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