5 Ways NLP Can Boost Your Marketing in 2020

The tremendous growth of unstructured data from various sources is flooding databases. Natural Language Processing (NLP) mines valuable data from the large quantities of unstructured data, allowing computers to make sense of human language. NLP is a branch of Artificial Intelligence that makes it possible to understand not only of words but the concepts that link them to make meaning. 

Experts believe that some of the most revolutionary uses of NLP will center on its applications in the field of marketing. As marketing relies heavily on words to convey messages, this is not surprising. In fact, large innovative marketing companies are already relying on NLP techniques. Here are six ways NLP can boost marketing. 

1. Sentiment analysis

Sentiment analysis is one of the capabilities of NLP that’s widely used by marketers and it has many interesting applications. It is sufficiently advanced to be able to give insights into how people feel about a brand. 

For instance, imagine you are talking to a friend about a new laptop you bought. NLP is able to extract the data from what you’re discussing and your sentiment (satisfied, good, bad, etc). A positive or negative sentiment implied in a social media post can help marketers to target people in a more effective way. 

Sentiment and volume of mentions can result in actionable analytics if the data is accompanied by demographic information and calibrated on expected reach. This can lead to solutions like more targeted marketing campaigns and social segmentation.

Someone who tweets that a friend is driving a new Suzuki Swift and he is seriously thinking about buying one is expressing a propensity to purchase. When marketers are able to identify ‘propensity’ signals, this can lead to social prospecting solutions. Social prospecting solutions need NLP capabilities to sift out any passing mentions of a brand and focus on real intent to purchase.

NLP capabilities are going beyond being able to just match keywords and are now able to take into account the context of a mention. State-of-the-art NLP systems are able to extract the handles of people who have shown an expression of interest in a purchase or a brand on a social media platform.

Spark NLP is open-source and offers state-of-the-art NLP libraries and full APIs in Scala, Python and Java. Natural language processing examples include sentiment analysis, entity recognition, automated image processing and much more.

2. Voice search

When it comes to digital services, there’s a barrier to access for people who can’t type or aren’t comfortable typing. Voice search has become increasingly popular and it is estimated that over half of online searches will use voice in the next year or two. This makes voice an important element for marketers going forward. 

Speech recognition is an NLP technology you use every time you ask Siri or other virtual assistants a question. Your spoken words are converted into data a computer is able to understand. 

Natural language generation is the technology you use every time Siri answers your question, and it involves outputting information as a human language. Semantic search means you can ask a natural question without having to formulate it in a specific, unnatural way. 

3. Chatbots

Most websites today have a pop-up chat box on the home page and these chatbots will continue to be an important aspect of digital marketing in 2020. 

NLP can improve the performance of chatbots and customer experience improves as a result of their usability. They can also increase conversions and sales when combined with targeting and marketing psychology. 

Surveys show that Chatbots will be used for 85% of customer service by 2020. Some of the top benefits of chatbots are 24-hour service, instant response to inquiries, and answers to simple questions. Of course, most chatbots are not yet able to respond to more complex queries but they can pass customers on to those who are able to help. 

Retailer Asos reported a 300% increase in orders when using a fashion chatbot they call Enki. 

4. Automated summarization

Going back to the amount of text data faced by marketers every day, information overload is a real obstacle. With automated summarization, it is possible to create short, accurate summaries of longer text documents, thus reducing reading time. 

Companies who produce long-form content such as e-books and whitepapers might be able to leverage automated summarization to break down content and make it shareable on social media. Reuse of existing content in this way saves time. 

Automated summarization of multiple documents can be a powerful tool to gain insight into current trends. 

Automatic summarization can also be an ally for marketers when they want to produce a video script incorporating research from many sources. 

5. Market intelligence

The core of market intelligence is using many sources of information to create a broad picture of customers, competition, the existing market, and growth potential for new products or services. Sources of raw data include surveys, social media, sales logs etc. 

Say, for instance, someone is planning a shopping spree to buy a luxury watch. NLP techniques are able to analyze topics and keywords and segment a user into a specific category. Using this knowledge allows web content to be personalized to the person’s interests, increasing the likelihood of conversion and purchase. 

Personalized and conversational marketing are two trends that are increasingly popular and NLP helps marketers to provide this. As this can be done at scale, it can help marketers to quickly come up with strategies. 


Most marketers are excited about the possibilities of NLP. We are moving into an era when marketing will increasingly rely on leveraging insights from a largely unexploited source of unstructured data. This will enable them to react in real-time to customers and be more proactive with their marketing strategies. 

NLP-powered tools are evolving and providing practical ways to make use of big data in a sustainable and scalable way. Marketers can’t afford to ignore APL if they want to remain competitive and take advantage of the new opportunities it presents. 

Edward Huskin is a freelance data and analytics consultant. He specializes in finding the best technical solution for companies to manage their data and produce meaningful insights.