Natural Language Processing (NLP): Revolutionizing Marketing Content Strategy

In a previous blog post, we discussed the changes that are happening with content strategy - specifically how to show up in an AI search vs. a Google search.

I was talking to some colleagues - one was a financial advisor and one was another marketing consultant - about the information I'd found and read them this fact from the blog:

Unlike traditional search engines that rely on keywords to index and display results, AI search uses natural language processing (NLP) to understand user intent and deliver personalized responses. Instead of returning a list of links, AI search often provides a direct answer, making it crucial for businesses to ensure their information is accessible and accurate.

This prompted the financial advisor to ask, "Wait. What's NLP?"

Well, heck. I hadn't done a lot of in-depth research on that. Looking at the explanation, I thought I had a pretty good idea. But if we're going to try to incorporate it into our content...I guess we should know exactly what it is.

According to Amazon Q, "Natural language processing (NLP) is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language. Organizations today have large volumes of voice and text data from various communication channels like emails, text messages, social media newsfeeds, video, audio, and more. They use NLP software to automatically process this data, analyze the intent or sentiment in the message, and respond in real-time to human communication."

But, again...I needed more explanation (that whole "intent" thing was confusing to me). So I turned to - what else? - ChatGPT and asked for examples.

Voice Assistants

Examples: Siri, Alexa, or Google Assistant.

• You can say, "What’s the weather like today?" and the assistant understands your question, finds the answer, and responds in spoken language.

Spam Filters for Email

Example: Gmail’s "Spam" folder.

• NLP scans emails to identify spam by looking for specific patterns, like common scam words or phrases.

Chatbots and Customer Support

Example: Online chat support for your bank or a store.

• If you type, "I forgot my password," the chatbot recognizes the intent (you need password help) and responds with instructions.

Social Media Sentiment Analysis

Example: A company checking Twitter for feedback.

• NLP tools analyze tweets to determine if people are happy, angry, or neutral about a product, helping companies adjust their strategies.

Language Translation

Example: Google Translate.

• NLP enables automatic translation of text or speech from one language to another, like translating "Hola, ¿cómo estás?" into "Hi, how are you?"

Text Predictions

Example: Typing on your phone or in an email.

• When you start typing, "Can you send..." and your phone suggests "me the report?", it’s using NLP to predict what you’re likely to write.

Voice-to-Text Features

Example: Dictating a text message instead of typing.

• NLP processes your spoken words and converts them into written text.

Why Do Organizations Use NLP?

Businesses generate a lot of data from emails, text messages, social media posts, call recordings, etc. It would take too long for humans to review all this data, so they use NLP software to:

Understand Intent: What is the person asking or trying to do?

Example: A customer writes, "Where’s my order?" The system identifies they need order tracking.

Analyze Sentiment: Is the message positive, negative, or neutral?

Example: Analyzing reviews to see if customers like a product.

Respond in Real-Time: Provide instant replies without waiting for a human.

Example: Chatbots answering basic questions 24/7.

How NLP Changes Content Creation

I know your head might be swimming at this point but stick with me because I'm LOVING this change.

For so many years, content marketing has been focused on the almighty keyword and that didn't always translate into helpful content. Back in the day, web designers used all kinds of tricks (I'm not judging - that's just how things were done) to land in those coveted top spots of a Google search.

NOW the focus is on more personalized content that has the audience in mind - which is how it should be. No, I'm not going to entirely get rid of keywords, but that's not the goal anymore. The content needs to be thoughtful, personal, and readable.

• Context and Intent: Instead of simply using the keyword “content marketing,” NLP encourages creating articles that address questions like “How does content marketing benefit small businesses?”

• User-Centric Approach: Content must now align closely with the needs, language, and search behaviors of the audience.

• Natural Language: Writing should mimic how people naturally speak or type, emphasizing clarity and readability.

• Broader Coverage: Google’s algorithms increasingly reward content that thoroughly covers a topic, providing users with a one-stop resource.

Again, Don't Abandon Your Keywords Altogether

Yes, you still want your keywords in there (and from a marketing standpoint, it probably helps you stay focused on the point of your content). But there is a difference:

• A keyword-based strategy might target “best running shoes 2025.”

• An NLP-driven strategy would create content that answers, “What are the best running shoes for marathon training in 2025?” and include related subtopics like durability, comfort, and price comparisons.

Things are changing but, in my opinion, this is a good shift. All marketing should be about the client, not solely about your ranking. I love that good content that's conversational and useful will be rewarded. We're ALL consumers and we are all constantly looking for good information.

Won't it be great when the articles that pop up when we search are actually HELPFUL and not just filler???