Understanding Google NLP: A Detailed Guide

Last Updated on Jul 17, 2023

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    Natural language processing (NLP) provides valuable insights for the digital marketing industry. It helps to collect data for targeted campaigns through customer feedback and searches. 

    How does a single concept do such great things?

    By determining the “what, why, and how” of a scenario, we can target our marketing strategies. These adjustments create an approach that helps consumers make informed decisions.

    We know this sounds like a whole lot of nerdy computer science talk. So let’s break it down to understand what natural language processing is. Discover what it means for your marketing strategy.

    Key takeaways

    • NLP simplifies data interpretation and helps Google categorize content for search results.
    • Sentiment analysis impacts SEO, with positive words improving content analytics and search rankings.
    • NLP enhances digital marketing through keyword identification, targeted messaging, social media insights, trend prediction, and content creation.
    • Tips for using NLP: utilize Google’s NLP API demo, focus on salient keywords, implement relevant linking, provide concise answers, and keep content simple and readable.
    • NLP optimizes content marketing by leveraging the power of words, enhancing strategies, and achieving better results.

    What is Natural Language Processing (NLP)?

    This form of machine learning helps us gather and interpret data to understand text. It simplifies data interpretation to understand the structure and meaning of text.

    Google uses natural language understanding (NLU) to analyze and categorize content for improved problem solving. 

    So what does this mean?

    Well, you know how search engines present results based on the questions readers ask? Search engines identify relevant entities in content created with NLP techniques. With this data Google can then present the content as an answer for the relevant query.

    Google’s BERT (Bidirectional Encoder Representations from Transformers) is the latest NLP algorithm. Based on AI, it understands queries as humans would process them. It grasps the context of phrasing and intent using sentiment analysis.

    What does sentiment mean for SEO?

    Sentiment refers to the feeling or undertone of a piece of text or search query. The type of words used determines if it has a positive, neutral, or negative sentiment. Here are a few examples:

    Negative sentimentUnsatisfied, terrible, bad, disgusting, hate
    Positive sentimentGreat, fantastic, good, wonderful

    Google ranks the content on your site based on sentiment and matches it to the search query. Choosing your words carefully has a significant impact on your content’s analytics

    6 Uses of NLP in digital marketing

    Combined with computational linguistics, search engines use machine learning methods to study and interpret the human language. By studying everyday speech, they understand intent, motivation, and the buyer’s journey. 

    So, how can this help improve your operation’s digital marketing efforts? 

    1. Relevant keywords 

    We all know how search engines work: type in your question and it’ll suggest results that may have the answer. 

    How do search engines do this? Through natural language processing. 

    Through natural language understanding, Google categorizes the text data published on a website. When you put a query into the search bar, Google identifies the published text as the answer. 

    How? Through keywords.

    NLP identifies the correct interpretation of the text published on your website. It identifies the keywords according to popular words in the text. Search engines then categorize this text data according to search relevance. 

    This language processing then identifies commonalities between your site content and customers’ interests. 

    2. Targeted messaging

    With NLP applications, you can identify and keep up with customer interests. 

    Why is this important?

    This data provides a clear and comprehensive view of your target audience. With an understanding of what your customers want, you can target advertising campaigns.

    Targeted messaging encourages customers to take the next step on their buyer’s journey. 

    For ecommerce platforms, targeted messaging helps to reduce abandoned carts and facilitates sales. A third of the industry’s revenue comes from product recommendations. 

    3. Social media observations

    Monitoring social media reveals your customers’ pre- and post sale habits. Natural language processing helps us track trends, determine demands, and target marketing efforts. 

    Using natural language processing, you can determine the best timing for your messages.

    4. Getting ahead of trends

    Not only does NP help us identify trends but also get ahead of them. This data comes from the news and other relevant sources. 

    5. Creating content

    Natural language processing helps us understand trends and target our marketing efforts accordingly. This includes through content creation. 

    Using AI apps to generate content speeds up the creation process. Develop a platform for your brand through helpful, relevant and entertaining content. 

    Whether writing for user experience or content strategy, use NLP to steer you in the right direction. Through topic extraction, you’ll identify themes that your audience is looking for. 

    By assessing conversations online (websites, social media, forums), you can identify your audience’s interests. With this data, you can target content so it reaches the right people. 

    6. User experience 

    With natural language processing, we can determine the intent behind content. But, how does this help us create the best customer experience? 

    Through customer feedback, of course!

    Sites using language analytics compile data about client experiences, expectations, and needs met. 

    Using NLP also encourages the customers to engage, ultimately driving up conversion rates. 

    Take this research one step further with sentiment analysis. Gather data on brand monitoring, product assessment, and competitor research. It also identifies how best to communicate with your audience.

    Tips for using natural language processing

    We’ve discussed the why, now let’s get to how. Help your digital marketing strategy by implementing these techniques

    Google’s NLP API demo

    Google has provided an NLP API demo to help you make the required improvements. Put your text in the tool and allow it to show you how you can adjust the text for better SEO performance. 

    Better salience

    We all know that keywords are vital to the content’s SEO performance. However, using variants of target keywords isn’t as effective as it used to be. 

    Now, using indicator keywords are crucial for NLP SEO. They’re used to generate context and build up to keywords, increasing the text’s salience.


    An effective linking strategy has become more vital than ever before. It’s not enough to just add links to your content, it needs to be relevant too—whether internal or external.

    External links should come from authoritative sources and relate to the content. Their placement should also fit in the article’s flow and the anchor must apply to the source page and the article. 

    Answer the question

    Reducing the distance between questions and answers is a crucial tip. Remember that you’re creating content for readers more than google. Keeping answers brief and to the point makes it scannable for readers and Google. You don’t have to be abrupt, but avoid going off track with a long-winded story. 

    Keep it simple

    With Google using BERT to crawl pages, it’s essential to keep the content simple. Not only does it need to determine if the text is relevant but also if it answers the question being asked.

    Avoid using long, complicated sentences. BERT shouldn’t need extra steps to create a connection between words. The Hemingway Editor is a fantastic tool to help you create a succinct text that gets to the point.

    Readable content

    Engage readers and answer questions through readable content. Here are some basic aspects to consider when improving readability:

    • Create a logical structure so the article sounds natural. The heading hierarchy should create a natural flow. 
    • Keep the content relevant to the average Joe. Avoid using industry specific jargon that only an expert would understand. 
    • Proofreading is your best friend! Ensure that you’ve corrected any spelling and punctuation errors. It sounds insignificant, but actually it’s vital when writing for Google’s E-E A-T model.
    • Stick to the point and keep content relevant. Always confirm your research against other sources to ensure accuracy.
    • For conciseness and better readability, stick to one idea per sentence. Statements that ramble are hard for readers and Google to understand. 

    Plan structure strategically

    When planning the structure of content, do so with an NLP strategy in mind. Through your article, you must display expertise and sound natural. 

    Define your headers carefully and determine where they’ll go. Ensure that they define the content to follow and that it flows with NLP.

    NLP is crucial to your content marketing success

    Words have the power to influence actions, ideas, emotions, and behaviors. So why not use them wisely? Get the best results for your efforts by using natural language processing techniques.  

    At Grassroots Content, we understand these strategies can leave you feeling overwhelmed. Our team of experts are ready to help you plan your content calendar.
    Contact us today to see how we use effective NLP techniques. Your content marketing strategy will thank you for it.