The Growing Importance of Large Language Models in Digital Marketing

In this article, we’ll define what an LLM is, its evolution, why it’s influencing digital marketing, how it will continue to reshape search marketing and its limitations. Read on to learn about how LLMs will affect your workstream.

An LLM is a type of AI built on deep learning and transformer architectures that can understand and generate human-like content based on the training it receives from vast amounts of data.

Deep learning provides a general framework that mimics the human brain's neural network, so LLMs can receive masses of data for training. The transformer architecture, introduced by Google in 2017, allows LLMs to understand and generate human language by processing content and context at scale.

Although LLMs have the spotlight now, they’ve been around for many years. Experiments on computational natural language processing in the 1950s produced the first ever chatbot in 1966. In the last decade, transformer architectures have enabled hands-on large language models (practical, applied learning models like ChatGPT) to significantly evolve and develop a long list of capabilities.

LLMs have not only introduced new and improved ways of working, but they have also changed the way we approach paid media advertising, SEO and content and email marketing.

• Content creation

Salesforce data shows that 76% of digital marketers use a generative AI language model for basic content creation, and 71% for content ideation. Hands-on large language models are being used for content creation because they are a time-saving tool for drafting copies, leaving more time to focus on strategic planning and refining the quality of the AI-generated copy.

• Automation

LLMs are incredibly useful for automating routine tasks, such as:

- Drafting content and email campaigns

- Testing ad copy

- Customer and audience segmentation

- Personalizing content

- Keyword research

- Automating customer service through chatbots

- Understanding data and creating reports

Automating manual and time-consuming tasks dramatically increases efficiency.

• Personalization

User-centric personalization is now vital for customer engagement, and according to HubSpot data, 72% of digital marketers use AI for personalization. Formerly, with manual segmentation methods, individual customer preferences were often missed, as were conversion opportunities. With AI-powered email and content marketing platforms, audiences are automatically segmented by their behaviors and characteristics, which can also be updated in real time, ensuring you catch the right people with the right content.

• Market research

You may have noticed in your keyword research that new tools are being developed on your go-to platforms, like Semrush’s AI Visibility Toolkit. Not only do tools like these aid your SEO, but their high-performance capabilities make your keyword research and competitor analysis strategies much more effective and efficient. AI-powered research tools can also look at social media trends and market reports to provide predictive analytics and actionable insights.

• The evolution of chatbots

Chatbots are now the go-to automated customer service method because they provide satisfactory conversational AI solutions. They’re able to maintain human-like conversations, seamlessly integrate with Customer Relationship Management (CRM) systems and offer personalized product recommendations. For instance, Amazon’s use of AI-powered chatbots has resulted in improved accuracy, quicker response and resolution times and higher customer satisfaction.

Even though we’ve already seen radical changes across digital marketing, especially within content and email marketing, the growing impact of LLMs shows no signs of slowing down.

• The rise of zero-click searches

The popularity of AI language models like ChatGPT, Gemini and Google’s AI Mode, which directly synthesize search answers without the need to click through to a website, known as a zero-click search, has dramatically reduced overall organic traffic. However, this also means that website traffic now generates high-conversion rates. This shift in user behavior has meant that we need to change the way we approach SEO, focusing on promoting EEAT, structuring content for extractability and directly addressing the search query.

• AI visibility vs SERP rankings

Because of the rise in zero-click searches, having AI visibility is arguably becoming more important than ranking number one in the SERPs. Despite SERPs and AI summaries not being directly related, if your page ranks in the top 10 SERPs, it can often appear in AI overviews. Therefore, holding any top 10 position could now be just as lucrative as holding the top spot because you’ll likely be in the AI-generated summary.

• Predictive analytics will lead the way

Predictive analytics uses historical interactions, browsing and purchase data to recognize patterns in consumer behavior and provide data forecasts on conversions, clicks and churn rates. These predictions lead to actionable recommendations for targeted and personalized marketing campaigns. Using data-driven analytics transforms your current campaign into a more efficient and effective strategy, which will perform better for your business.

Although LLMs have significantly improved in the last few years, especially regarding their automation capabilities, there are still some challenges and limitations which mean you should use them with caution.

LLM benefits include:

• They are adaptable – They can be tailored to your specific needs, whether you want to synthesize a data dump into a digestible report or draft basic copy for your blog.

• They’re high-performance – They’re able to quickly generate responses and complete tasks, and as they’re a massive data store that is constantly being trained and evolving, they’ll only become quicker.

• LLMs increase efficiency – They can complete time-consuming tasks in minutes, such as keyword and competitor research, creating ad or content copy and generating draft social media posts.

• They’re easy to train – LLMs are relatively easy to train because they rely on data dumps and regular usage. If you provide your LLM with enough information, like details about your campaign, goals and relevant data, then it can generate a well-informed response.

• LLMs are creating smarter SEO – LLMs are getting better at understanding the nuances in consumer behavior and language, not only allowing you to create content that better aligns with your audience, but also helping you to think like a search engine.

However, LLMs are not completely reliable and have some drawbacks:

• Improper training – If LLMs are trained with biased, outdated or incorrect data, they can generate content that is not only factually incorrect but could also be harmful to users.

• They can be inconsistent – There have been instances where the same prompt is entered into an AI language model like ChatGPT or Gemini multiple times, and each time it generates a slightly different answer.

• Content quality – Despite having AI content generator tools that draft copy for you, they aren’t always the best quality or optimized for the search intent or topic.

• AI hallucinations – This is a real and concerning phenomenon where AI models generate information that may look or sound factually correct, but is actually completely false. Always fact-check responses you receive from LLMs.

• Ethical implications – By far the biggest concern, AI often generates content without correct citations or references, which can bring about copyright and ownership issues, as well as GDPR compliance problems.

It’s perfectly acceptable to use LLMs in some form or another as a digital marketer because they streamline workflows, create precise personalization's and automate tasks. However, involving a human in the responses and work generated by AI language models is essential.

You want your website to come across as authoritative and trustworthy, and using AI-generated content that is likely mass-produced and low quality can negatively impact your site's crawlability and SEO performance. This is why LLMs must be leveraged responsibly, and AI language models should be used to enhance your marketing strategies and campaigns – not run them.

Want to make sure your business has AI visibility and that you’re leveraging LLMs to improve your marketing strategies? Get in touch with our technical team today for more information on how Zelst can help.