How to Optimize Language Models for Brand Content

When The Washington Post uses artificial intelligence to create 850 articles in one year, it’s clear that AI has its foot in the door of the content creation realm. Granted, the articles didn’t necessarily show up on the first page of the search engine results pages, but they did get clicks.

For a growing number of companies and content practitioners, automating content production seems like a no-brainer. However, if your content is inaccurate, poorly written, or doesn’t have enough substance to attract an audience, the money you’re spending on the tech goes down the drain.

Optimization is critical for visibility, but can you optimize the language models that AI tools use to produce content that shows up on the SERP? It’s possible with an up-front investment in training the model to include keywords.

What about brand terms and style rules? Can language models be trained to output content that closely matches your typical style and brand personality?

Discover how marketers use AI in content creation and ways to teach these systems to create content that gets results. Content marketing is hard, but if you can harness the strengths of language models and AI, your job gets a little easier.

Know This Before You Try To Optimize Language Models

Before we get into optimizing language models, let’s talk about how you can put language models to use in content marketing. These models are at the heart of machine learning for the written word in AI-generated digital text.

Language models incorporate information from multiple sources to predict each word within a sequence. The more input these systems receive, the more they “learn.”

Diagram demonstrating how to optimize language models to produce text outputs.

Image Source:

The Evolution of Robot Speak

Initially, language models sounded like robots. It was not difficult to figure out that you were interacting with an artificial intelligence system.

As with all things technological, times have changed. Natural language processors don’t just rely on grammar and syntax rules. They learn from inputs that provide models for natural languages.

This new way of processing opens the door to opportunities for brands and marketers. When 64% of consumers want a connection with the brands they use, and 73% think AI can improve customer experiences, it’s hard not to see the benefit of using natural language models in content marketing.

Diagram showing how marketers use AI, demonstrating the potential benefits of learning to optimize language models.

Image Source: Forbes 

The Role of Language in SEO

It’s also easier to optimize language models that can learn how your audience uses language. SEO strategy these days is about more than just using the right keywords. You also need to understand search intent and relevance.

With enough training, natural language models can pick up on the context of keywords used in natural language structures. The challenge is knowing when the program gets it well enough to implement it in your marketing efforts.

Train AI To Generate Optimized Content

You have three ways to look at optimizing the content that language models generate. In each instance, the programs require significant data input to learn.

Keyword Optimization

When you consider how to optimize language models, the first step you’ll likely take is to teach it to pick up on relevant target keywords and how those words and phrases are used in the context of written content.

With keyword optimization, the processor searches a database or the internet for the words you are training it on. When it discovers content that contains them, it can scan the text to see how the authors use them.

After training, it can generate content that mimics the context and language of those articles. Ideally, the training would increase the possibility of creating content that ranks for your targeted keywords.

Topic Optimization

You can optimize language models around topics your audience is interested in. When you conduct this type of training session, you’ll want to establish parameters so that the program learns how to generate text that meets your goals.

You can approach topic optimization by:

  • Training the AI on texts found on the internet for topics you identify
  • Training it to find articles that answer questions your audience might have
  • Segmenting your audience and training the AI on subjects specific to each segment

In each instance, you feed the AI the data it seeks from the internet or another database.

Brand Optimization

In the first two examples of how to optimize language models, the system pulls data down from a large universe of content from multiple sources. Using what it learns, it produces text that basically sounds like a human wrote it, but the voice will be generic.

Some AI content generation programs like Writer provide a more personalized approach. You optimize the AI to produce content that reflects your brand, including its voice, style, tone, and topics.

To train the model, Writer’s language model is fed existing brand content that has performed well. The more contextual data and information included, the better, so a content inventory with URLs, metadata (topics, keywords, etc.), and performance data will be very helpful for language model optimization.

If the thought of trying to pull together a content inventory (think blog, web, email, and social content) with performance data to feed to the AI platform is a bit overwhelming, you’re certainly not alone. Luckily, users of DivvyHQ can output an inventory like this in seconds. With the combined capabilities of content reporting and performance analytics, optimizing a language model can be accomplished in no time.

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Keep This in Mind When Using AI To Create Content

There are a few things to keep in mind when you optimize language models to produce content. While NLM processors are pretty good at creating human-sounding language, they have limitations.

Understanding the strengths and weaknesses of AI-generated content allows you to use it to your advantage while avoiding the pitfalls that could result in low-ranking content. AI can’t completely replace humans in content creation, but it can significantly boost productivity.

Prepare To Optimize Language Models With DivvyHQ

DivvyHQ’s cutting-edge content operations platform cuts the chaos of preparing for AI-generated content. Our platform houses everything you need in one central hub.

It takes minutes to filter your content inventory to retrieve only the categories you need, and not much longer to gather the analytics. When you are ready to optimize language models, DivvyHQ is here to optimize your efforts. Request a demo to see efficiency in action.