As marketers, we aim to craft engaging content that meets customer needs and provides solutions. However, with rapidly changing customer preferences, traditional content optimization techniques are outdated. To better meet customer demands, we must approach content creation from a fresh perspective.
Enter Natural Language Processing (NLP), an innovation that has redefined the way we approach content design, creation, and promotion.
In this blog post, we’ll explore NLP’s capabilities and discover how to enhance your content’s relevance and impact.
Understanding NLP
What is NLP?
Natural Language Processing (NLP) is a field of artificial intelligence that empowers computers to comprehend, translate, and engage with human language, whether it’s spoken or written.
NLP involves the utilization of machine learning, voice recognition, deep learning, and statistical approaches to interpret human language. This allows computers to derive meaning, including emotions and intentions, from the language they are analyzing.
One of the most popular examples of NLP are email filters that automatically categorize your emails into groups like social, promotions, primary, or even spam based on certain words and phrases. If you had to do the same thing manually, it may have taken hours, and it’s not necessarily the most efficient use of your time. A simple example that shows you how subtle applications of NLP can help to save you a lot of time.
Why does NLP matter?
NLP can be used for a number of purposes and offers some interesting benefits. Digital marketers these days are focusing a lot on using NLP for content, strategy, creation, and marketing. You may already be lagging behind if you aren’t one of them.
For example, you can efficiently analyze and extract information from vast amounts of unstructured data using NLP. This takes the guesswork out of content creation and makes it more of a strategic and actionable initiative.
It can also save you time and effort by quickly summarizing lengthy documents. A popular example of this are tools like Gemini and ChatGPT that save hours on research by concising the vastly available research into easily digestible content.
Additionally, with NLP, you can analyze language patterns and user preferences to develop personalized content recommendations and targeted advertising, leading to better engagement and user experience.
NLP also helps you make more informed decisions by extracting valuable insights and actionable intelligence from textual data. It ensures you don’t act on a hunch and your every action is well-informed and backed by data.
How does NLP work?
NLP works in the following steps:
Step 1: The user inserts an input (a sentence or speech text) into the NLP system.
Step 2: The system breaks down the input into small parts of words, called tokens.
Step 3: The machine processes the tokens and generates a response.
How does Google use NLP?
Google uses NLP to understand search queries by breaking down the sentence structure, identifying entities (people, places, and things), and assessing the overall intent behind the search. This way, Google returns more accurate and relevant results for search queries.
NLP can also help the search engine refine results by understanding the context behind a query. For example, if you search for “best sarees online”, the NLP would identify that your intent is to buy a saree from an online store, not just read about it. Hence, it would show online stores selling sarees in search results, and not necessarily a blog article talking about sarees or how to style them.
Not only this, Google would also allow you to filter search results by your requirement, i.e., for weddings, stitched, with embroidery, or sleeveless.
Let’s take a look at the search result I got after entering the same query on Google:
In addition, Google uses NLP to build and maintain its Knowledge Graph by extracting information from text data, identifying entities, and establishing relationships between them.
It also powers Google Assistant by helping it understand language commands and questions, generate appropriate responses, and complete tasks based on your instructions.
Furthermore, NLP can be used to personalize search results and tailor ad recommendations based on past searches and user behavior.
Leveraging NLP for content relevance
Content creation isn’t easy. Making sure your content is helpful, meets Google’s quality standards and answers the needs behind user intent can be time consuming. Implementing a few practices with the help of NLP can help you approach content creation from a fresh perspective.
Understanding the intent behind keywords
While black-hat SEO practices like keyword-stuffing worked a decade ago, they’re no longer effective. To rank higher in searches and gain online visibility, you need to understand both the keyword and the intent behind it.
With that said, you should ditch the keyword stuffing and pay attention towards user intent. NLP can help you understand search intent and user needs. Craft content that truly resonates with your audience.
NLP helps you understand the intent behind the keyword by analyzing the surrounding words and sentence structure to understand the keyword context. It also identifies the grammatical role of each word in the sentence to differentiate between information and transactional searches.
For example, let’s suppose users insert two different phrases “buy shoes” and “how to buy shoes”. Both the searches have the keyword buy shoes, but the intent is different (buy shoes has a transactional intent, while how to buy shoes has an informational intent).
Below are the search results I obtained when I entered the query “buy shoes”:
On the other hand, one of the results I received was a how-to article when I entered the query “how to buy shoes”:
The search queries show different results when they contain the same keyword because NLP detects the separate intentions and shows appropriate results.
NLP also identifies the intent behind keywords by recognizing entities like people, places, and organizations in a sentence. Let’s take a look at another example.
Suppose you enter the query “buy shoes from Amazon” instead of just “buy shoes” on Google. The NLP system will now determine that you only want to buy shoes from Amazon, nowhere else. As a result, it will only show shoes from Amazon as you can see in image below:
Understanding the intent behind keywords helps you create content your customers care about.
Going back to the example above, if you’re Amazon, it would make sense to integrate long-tail, transactional keywords like “buy shoes online” or “buy shoes from Amazon” to ensure your site reaches customers that are actually interested in buying. Integrating informational keywords would be of little use for Amazon as it does match the intent of their site offering.
Finding the intent behind keywords isn’t as challenging as you may think. Many tools are available on the market for that very purpose: I personally use SEMRush.
You can also use the following strategies while using NLP to optimize your content:
- Salience score: A metric that helps you determine the importance of specific terms or entities within content.
- spaCy: An NLP technique that helps you recognize user intent by analyzing verbs and nouns in search queries, ensuring you create content that matches their requirements.
Using sentiment analysis to optimize content
A great piece of content speaks to your target audience’s emotions. It is content people generally enjoy reading and can incite action. So, it’s essential to understand the sentiments of your target audience before you create content for them.
NLP helps you understand your audience’s emotions and attitude towards your brand by analyzing language and context to assign positive, negative, and neutral scores to text or audio data.
There are tools like Emplifi that use deep learning to automatically analyze text and classify sentiments. You can even use Sprout Social, Brandwatch, and Hootsuite Insights to monitor and compare audience sentiment across different platforms.
The impact: You get an idea of what customers feel about your brand and take proactive action if the sentiment is not in your favor.
Chewy, a pet supplies company, is a brilliant example of this. They’ve received a rating of 3.6/5 on Trustpilot based on 9,747 reviews.
Based on the fact that 82% of responses rated them as excellent, one could feel that their brand was performing well. However, it didn’t offer any actionable insights to improve their services. That’s why they used a sentiment analysis tool to analyze the sentiments behind each review.
Here are the results:
- The number of customers with negative sentiment (40.8%) is slightly higher than customers with positive intent (38.2%). Also, a majority of the audience (21%) has a neutral sentiment about the brand, which is a matter of concern.
- Most of the negative sentiments are about pricing and product quality.
The image below explains all the insights in detail:
These insights helped Chewy build a roadmap for improvement and establish itself as the reputed brand it is today.
“Listen to your customers, not competitors.”
– Joel Spolsky, Co-founder of Trello & Stack Overflow
Joel’s advice packs a punch as customers can be a goldmine of information and offer a lot more valuable insights. Hence, you must listen to your audience and use NLP sentiment analysis to gauge audience reaction & optimize content for better engagement.
Employing semantic analysis to create contextually relevant content
One thing you must know, if you’re serious about creating impactful content, is that content creation is not just about surface-level understanding of words and phrases. Mindlessly stuffing keywords into your content will get you nowhere. Instead, you need to have an in-depth understanding of keyword semantics and context, and you must use them in your content wisely and naturally.
You can use NLP techniques like Latent Semantic Analysis (LSA) to semantically analyze your content. It analyzes the text to identify words which are frequently used, helping you effectively understand content even if different word variations are employed.
This enables you to create content that appears more natural and engaging to read.
Let’s go a little deeper with an example.
Suppose you’re writing a blog article on “healthy eating habits”. If you use the same keyword again and again, for example “healthy eating”, the flow of the content will look and sound a bit forced and that is where you risk losing your reader as they would likely bounce for lack of feeling a genuine connection.
To avoid this, you can use LSA to identify related keywords like “balanced diet”, “meal planning”, “healthy meals”, “nutrient-rich foods”, etc. Now, instead of using the same repetitive terms throughout the text, you can intersperse these different variations, making it more engaging to read.
Personalizing content experiences to improve engagement & conversion rates
Readers love it when you personalize your content to their individual interests and preferences.
NLP can help you deliver personalized content experiences by analyzing reader behavior, preferences, and interactions, and creating an Ideal Customer Profile (ICP). This profile consists of detailed information about your target customers such as their likes, dislikes, goals, challenges, etc. Once you have the ICP ready, you can adjust your content to match their interests. Or better yet, create content specifically designed to cater to their interests.
The result: Your content never misses the mark. Instead, it becomes highly engaging, valuable, and personalized. Your session times and page views increase, and your conversion rates skyrocket.
Picture yourself as a fashion retailer looking to improve your content marketing strategy. NLP can help tailor your content to meet their interests.
For example, if all your collected data points to someone who likes and often searches for jeans, you can deliver articles related to “how to style jeans”, promotional offers on denim, and fashion collections directly to their email. You can even curate personalized collections for visitors on your website; increasing the probability of purchase and in turn your conversion rates.
Relying on user feedback & behavior analysis to optimize content
User feedback ensures that your content meets the needs and preferences of your readers. However, collecting feedback is not as simple as it looks. Most of the time, users give vague feedback, making it challenging to identify areas for improvement.
NLP extracts valuable insights from the user feedback on your content to see if it’s positive, negative, or neutral. It also helps you identify recurring issues and themes mentioned by users, making it easy to see where your content lacks. You can even identify what aspects of your content resonate with them by identifying types of articles that have received the most praise.
Armed with these valuable insights, you can adjust the tone and style of your content to improve it based on the feedback. You can also cover topics that resonated with them more frequently, ensuring they keep coming back.
What does this look like in practice? If you have a blog, you may have already received feedback like “The blog is interesting” and “Oh! I don’t like the blog. It’s too boring” on your blog posts. Such feedback is often vague and offers little, to no, practical insight for improvement.
NLP can solve this problem by helping you send personalized surveys to users in which you ask specific questions, such as what they liked about the content, what they didn’t, and what suggestions they would offer to improve it.
Once you have the responses, analyze the gathered feedback to identify recurring themes, sentiments, and suggestions. In the end, you’ll have far better actionable insights that can take your content to a whole new level.
Optimizing metadata to improve search visibility
Ever wondered why your quality content doesn’t rank well? It could be because the meta title and meta descriptions are so vague that search engines can’t index them properly. To solve this, you must ensure that the meta tags accurately reflect the content of your blog.
NLP can be used to analyze your content to identify what your blog is really about and in turn select appropriate keywords and phrases that you can include in your meta tags. As such, the meta tags on your content appeal to both users and search engines, increasing your chances of ranking higher.
For example, let’s say you’re writing a blog on top eCommerce seo trends to follow in 2024. With NLP, you can identify related keywords like artificial intelligence, voice commerce, IoT, or green commerce.
When you include these keywords in your blog’s meta data, it would closely match the search query of people who want to read it. Thus, you’d see a likely jump in click-through rates, which sends signals to search engines indicating that your web page is relevant and should appear higher in the SERPs.
Better content organization through topic modeling
Managing content on a small scale is easy. However, as you start producing more and more content, it becomes challenging to keep track of everything. That’s when you need a powerful system that can facilitate the process.
You can use NLP to analyze the pattern of words across your site or blog to identify the cluster of frequently used words. As a result, you can organize the entire database by themes and patterns present. Also, you can recommend content to your website visitors better by suggesting content based on their interests.
Let’s imagine you have a technology blog containing 1520 articles about various topics like cybersecurity, DevOps, Mobile Application Development, Cloud Computing and UI/UX design. If you have to manually organize all this content into categories, it may take you forever.
However, NLP can facilitate the process by identifying recurring patterns or themes related to the topics mentioned above. Based on this data, you can create the corresponding categories or tags. Now, whenever users visit your website, you can suggest posts that align with their preferences.
Conclusion
Content marketing has significantly changed over the last few years. Tactics that worked a while ago are no longer as effective. Whether you work in a company or offer professional SEO services independently, you may become obsolete if you’re approaching content creation with a traditional mindset.
To succeed and create content that makes an impact, you must approach content creation from a different perspective. You need to understand the intent and context behind keywords and leverage the findings to create content that resonates with your target audience. By now, you can see how NLP can help you with this.
Now, it’s time to put what you’ve learned into practice. The more you do that, the more you’ll learn!
