There is a lot of buzz around Natural Language Processing (NLP) nowadays, particularly on the role of NLP in marketing. We are living in the age of data, and much of that data is in the form of human language. NLP provides the opportunity to understand and extract useful information from all this data, augmenting various areas of your life, especially business. And marketers are very keen on capitalizing on this information for their gains.

According to a report by nRoad, 163 zettabytes of data will be generated by 2025, and about 80% of that will be unstructured.

In this blog, we’ll explain NLP’s significance for today’s businesses showcasing its top benefits, applications, and use cases that make it so imperative for contemporary marketing and sales practices. So, let’s begin with:

What is Natural Language Processing in Marketing?

Many see NLP as something quite complicated. But the truth is that you don’t need a degree in computer science or linguistics to benefit from NLP technology.

In fact, almost all of you use it several times a day already. It activates the spam filter in your email, the automatic correction in your spell checker, and the answers you get from your smart home devices like Apple’s Siri or Google Assistant.

On a broader level, natural language processing is a subdomain of artificial intelligence (AI) and machine learning (ML). It assists machines in understanding, analyzing, and acting upon instructions in human language.

Today’s NLP programs can translate text into different languages, respond to text and audio commands, and process large amounts of text in real-time. Most NLP applications are programmed to understand the text passed on to them and perform tasks based accordingly.

Gmail can be one of the best NLP examples here. It relies on NLP to extract information from your emails and populate events to Google Calendar.

As AI technology advances, the number of NLP apps for marketing also adds up. Resultantly, big data is more accessible, and companies can achieve impressive performance gains regarding sales and marketing objectives.

How Does Natural Language Processing Work?

Artificial intelligence is the key here. NLP works by using AI to take information from the real world, through text or audio, and process it so that computer programs can understand it and act on it.

The first step is to provide information for artificial intelligence. Depending on the app, this could be an email, blog post, social media chat, or other types and forms of spoken or written language.

The NLP application then analyzes the words and sentences, also considering the surrounding words and the whole sentence structure. The aim is to understand the truest meaning of each word and sentence.

The final step involves the app determining the meaning of the input text with the intent of using this information for several different purposes.

For marketers, NLP provides the opportunity to capitalize on the vast amount of data available and deliver more value at every point of contact with consumers.

Top Benefits of NLP in Marketing

Some experts are of the view that this type of technology does not bring great benefits to the marketing realm since they are unable to generate sales. However, we dare contradict such opinions based on years of experience in the industry.

The truth is that the application of technologies like natural language processing in marketing does not necessarily seek to achieve sales, but rather other compelling benefits for marketing departments, such as the following:

     1. Process Automation for Saving Time and Effort

There can be an endless array of marketing-related repetitive processes that natural language processing can help optimize. In most cases, these processes do not usually add value to the department or company, but they need to be done anyways.

Therefore, the use of certain NLP models helps increase the productivity of these departments, allowing businesses to redirect efforts to activities that add real value to the company.

     2. Streamlining Workflows

Other types of activities that do add value to the company or the marketing department can be complex and involve limitations in the speed of their execution.

Through certain natural language processing models, help can be provided to those responsible for the activity that allows them to streamline these essential and valuable activities that only humans can carry out.

     3. Improved Decision-Making

Often, decision-making must be done by taking into account a large set of data. And in the case of NLP, the data is the texts. Can you imagine having to make a decision about the online reputation of a company based on a campaign with hundreds of thousands of comments? Said decisions would be biased and would not attend to the full reality of the set of opinions.

NLP in marketing helps businesses to evaluate large amounts of texts and extract summarized data that allows a marketing team to make better decisions after a thorough analysis.

NLP Applications in Marketing

NLP can support your marketing strategy in many ways, but here we will focus on using NLP for major marketing concerns like branding, content, customer success, lead generation, and so forth.

     1. Capturing Leads More Effectively

Thanks to chatbots, natural language processing has the power to attract potential customers and ultimately convert them into repeat customers.

So if your company website doesn’t have a chatbot with NLP capabilities, you’re missing out on a significant amount of conversions and potential sales.

One of the reasons that make chatbots extremely useful is that they give prospects the personalized attention they crave. Also, because they can use NLP to understand and respond to customer inquiries, there’s no need to have real, live assistants on the front line of your website.

NLP’s ability to refine automated responses by constantly training and improving the machine in distinguishing various customers’ needs can help you save a considerable amount of time, effort, and money on your marketing endeavors.

     2. Sentiment Analysis to Assess Your Audience’s Reaction Towards Your Brand

As a marketer, you spend a considerable amount of time evaluating audience reactions to your content. And, as is well known, if the content performs well, it leads to high levels of engagement and an increase in conversions, thus setting a standard for the content and future goals of your company.

But how does natural language processing help here? It’s very simple. This technology makes it easy for you to assess the way your audience deems your content by identifying and analyzing the language they use to respond to or describe it.

Sentiment analysis is one of the most popular NLP applications for marketing purposes. This type of model is very useful if you want to analyze on a large scale the emotions that your brand, a campaign, or a competitor transmits.

It consists of using the comments as a data source with which to generate the NLP model. Said comments are previously tagged based on the different emotions detected in the comments. Once a sufficient volume of comments has been tagged, the model is trained with which the new comments produced can be analyzed.

With this model, each new opinion can be evaluated automatically without constant review by a person, and the specialist will limit himself to reviewing the results of the automatic analysis and drawing conclusions.

     3. Polarity Analysis

Polarity refers to whether the comments are positive, negative, or neutral. It is a type of model very similar to sentiment analysis, but it differs in that the text is analyzed around polarity and not emotions.

In this case, the labeling of the comments is also required since these are the data with which the model works to learn. We recommend using this type of model as a trigger for possible reputation crises in social networks. So that if the model suddenly detects an anomalous increase in negative opinions about the brand or campaign to be carried out, you can put yourself on alert to detect where the problem is arising from.

     4. Content Segmentation

Content segmentation is based on the classification of content by categories. But if you had to be tagging different types of content all day, you’ll probably waste a lot of your time on it.

This is where the segmentation of content based on its text similarity comes in as an effective and fast way to classify written content, thanks to the advances in natural language processing techniques.

     5. Automatic Translation

Although today it is still not perfect, Automatic Translation, also referred to as Machine Translation (MT), is expected to evolve with every passing day. We have all used automatic translation systems and have been helped by them in more than one situation.

So, it is quite logical to believe that automatic text translation can be a very useful tool for marketing.

Last year, the machine translation industry brought in $ 40 billion.

Here are a few examples of how MT helps businesses:

  • Google Translate translates more than 100 billion words every day

  • Facebook (now Meta) uses MT to enable the automatic translation of posts/comments
  • MT allows eBay to process cross-border transactions and connect buyers and sellers worldwide.

  • Microsoft is a pioneer in creating advanced machine translation engines with AI that help Android and iOS users to translate seamlessly.

     6. Email Classification

Another very useful application of natural language processing in marketing is related to email. Specifically, customer service departments receive large amounts of emails that they manage in a linear fashion. It is something that does not necessarily have to be that way.

Well, through the NLP, you can classify the emails received in the inbox based on their degree of urgency, spam emails, promotions, etc. This ultimately helps contact centers to increase their productivity, but above all, their relevance in the service.

     7. Investing in the Right Keywords

Any experienced marketer knows that success in today’s digital marketplace depends on being able to identify the keywords your audience is searching for.

And it is that by using the right keywords in your content, you are likely to rank better in search engine results, which ultimately leads to higher conversions, profits, and brand recognition.

For its part, NLP has proven to be an irreplaceable tool in helping digital marketers choose the perfect keywords to engage their audiences.

This is because it allows them to see what kind of results are generating variations of related keywords. For example, the search engine results page (SERP) will look very different if you search for “advertising”, “advertising courses”, or “what is advertising”.

So, you need to know these kinds of subtleties to choose the mix of keywords that best responds to search intent.

     8. Improved Content Production

Just the same way natural language processing allows marketers to track down the best keywords for their audience, it also proves to be a valuable asset for content creation.

It’s well known that the most successful content captures prospects’ attention by referencing current events, responding to prospects’ needs, and generally staying relevant in a chaotic market. And it is that the NLP can help digital marketers maintain a constant conversation with their audience.

This can be achieved by tracking the hottest topics or conducting a content audit to see what is missing from your arsenal. Thus, with NLP, you can ensure that your content is never out of date.

     9. Expanding Your Audience with Virtual Assistants

Virtual assistants have become an integral part of most of us today, and currently, they come in the form of home assistants such as Alexa, Siri, or in different types of smart speakers.

For this reason, using NLP in your marketing practices means expanding your audience since virtual assistants will help you achieve it.

They have the ability to give you highly personalized access to consumer data, which in turn helps target your content to a more suitable audience.

What’s more, spoken requests to virtual assistants can provide a variety of relevant keywords that allow marketers to target their target audience.


NLP in marketing is something that every CMO should have on their radar. It gives you a handful of options and uses cases with the ability to automate and optimize to improve cross-channel performance.

NLP-based tools and applications make big data more accessible and valuable for marketers. It allows you to reach out to your consumers, provide a better user experience and improve the effectiveness of your advertising and marketing campaigns.

If you need help integrating NLP technology into your digital strategy, our experts at RevolveAI will pleasantly surprise you with their simple and innovative AI solutions.