How does Natural Language Processing Take Audience Engagement to the Next Level

NLP helps technology make sense of human language in numerous forms. In this text, we explain how it works and how it can be used to boost conversions and help with the production of relevant content.

How does NLP (Natural Language Processing) Take Audience Engagement to the Next Level

    Are you looking for ways to maximize the impact of your business’s digital marketing efforts, resulting in more clients, profits and growth? 

    Look no further than Natural Language Processing (NLP).

    Think of it as the technology that allows computers to make sense of human language.

    NLP is what makes it possible for a virtual assistant like Alexa to play your favorite song on command, or turn off your lights using just your voice. 

    Today’s world has readily integrated the use of NLP to make tasks quicker and more enjoyable for users.

    That being said, how can NLP be utilized to enhance your business’s digital marketing practices? 

    Let’s find out.

      What Is Natural Language Processing (NLP)?

      Simply put, Natural Language Processing is the technology that allows machines to communicate with humans. 

      It is a type of artificial intelligence that enables Siri to understand your questions and empowers Google to deliver search results — even when you misspell a few words.

      NLP isn’t a new concept. In fact, preliminary NLP studies took place during the 1950s.

      In the 70+ years since its inception, NLP has become more than just a new and exciting way to input information into computers and other technological devices.

      Natural Language Processing has become a highly valuable tool that not only makes machines understand human language but also assess the information that they receive.

      These advancements have made NLP a valuable element for digital marketers and a wide range of other marketing professionals. 

      After all, the more information you gather about your audience’s preferences, interests and habits, the easier it is to sell them your products or services.

      What’s the Difference Between NLP, AI and Machine Learning?

      These terms represent unique concepts within the world of artificial intelligence.

      Artificial Intelligence

      AI encompasses a wide range of technology that allows computers to display intelligence, typically through problem-solving. 

      Artificial intelligence algorithms have the power to help machines engage in decision-making tasks. 

      What is more, AI has the ability to sort and analyze real-time data to inform decisions.

      Machine learning

      It’s a branch of AI that allows machines to progressively improve their accuracy through evolving algorithms and data. 

      Machine learning permits a computer to beat you at chess or a Tesla vehicle to drive itself. 

      It is meant to imitate humans’ learning process, constantly adapting to improve itself, make intelligent predictions and uncover insights.

      Natural Language Processing

      NLP is yet another branch of artificial intelligence that helps computers understand human language. 

      One of NLP’s primary functions is to receive an input of spoken language and turn it into a written format. 

      Additionally, NLP can be used to process written language inputs, such as a Google search. 

      Even if a word is misspelled, it allows the computer to understand what you most likely meant to say and produce relevant results.

      How Does Natural Language Processing Work?

      NLP is achieved by breaking down input language into small pieces that can be processed, analyzed and given meaning using text vectorization. 

      Text vectorization transforms the language input into something that the computer can understand.

      The computer then uses algorithms to identify and process language rules — for example, the tendency for an adjective to precede a noun in the English language or the fact that one word can have multiple different meanings.

      For a computer to make sense of a question or a command that’s spoken or written in human language, it must utilize what are called syntactic and semantic analyses.

      Syntactic analysis 

      This type of analysis helps machines compare classic grammar rules with users’ language inputs. 

      With syntactic analyses, the computer can start to identify patterns that are understood in human language, as well as those that don’t make sense.

      Semantic analysis

      On the other hand, semantic analysis involves the actual meaning associated with the language inputs. 

      It uses algorithms to track interpretations of different words as well as sentence structures. 

      As a result, the machine can understand language in the same way that humans do. 

      Semantic analyses provide context so that the computer has a better chance of providing users with an appropriate response based on their input.

      Is NLP Present in Your Everyday Life?

      Yes! 

      In today’s increasingly digital world, NLP plays a significant role in many individuals’ everyday lives. 

      The sheer convenience that Natural Language Processing provides makes it an ever-present force in modern technology. 

      Whether you know it or not, NLP is most likely present in your home, your office, your car — and the list goes on.

      ➤ A few modern-day examples of NLP include online translation tools, smartphones’ talk-text function and the ability to say “Hey, Siri” and ask any question that pops into your head. 

      However, this is just the tip of the iceberg when it comes to NLP in everyday life.

      Have you ever wondered how your emails get automatically sorted into different filters, whether it’s “Social” or “Promotional”? 

      ➤ NLP has the power to analyze your emails and determine where they all belong.

      Yet another example is predictive text, which might appear while you’re writing an email or a text message. 

      ➤ The ability of your computer or phone to predict what you’re most likely to say next is based on its capacity to process and analyze past language inputs.

      Furthermore, NLP is present in any digital function that requires a machine to process or understand language. 

      ➤ If you want to use the “Visual Voicemail” function on your phone, which allows users to read voicemail messages instead of listening to them, NLP is at work.

      How is NLP Used in Digital Marketing?

      Natural Language Processing’s ability to analyze — and even predict — language inputs reveals a wide range of information about users’ characteristics, interests, needs and preferences.

      To digital marketers, this is highly valuable information that simultaneously identifies a company’s target audience and helps optimize marketing practices to convert them into paying customers.

      In this way, NLP helps digital marketers achieve a number of goals, whether it’s producing more effective content or choosing the best keywords.

      Take a look at the following ways that NLP can be used to enhance your business’s digital marketing efforts.

      Capture leads more effectively

      Thanks to chatbots, NLP has the power to attract leads and, ultimately, turn them into paying customers.

      If your company’s website doesn’t have a chatbot with NLP capabilities, you’re missing out on a considerable number of potential conversions and sales. 

      Chatbots are extremely useful because they give prospects the personalized attention that they crave.

      However, because chatbots can use NLP to understand and respond to customer queries, there’s no need to have real, live representatives on the front lines of your website. 

      With the ability to refine automated responses and train the machine to distinguish various customer needs, NLP can save you time, money and frustration on your website.

      Gauge your audience’s reactions

      As a digital marketing professional, you spend a considerable amount of time gauging audience reactions to your content. 

      Content that performs well, resulting in high engagement and a boost in conversions, sets the bar for your company’s future content and goals.

      On the other hand, content that performs poorly shows you what your audience doesn’t respond to, which is just as important to know.

      NLP helps you determine how your audience feels about your content by tracking and analyzing the language they use to respond to it or describe it.

      Target the right keywords

      Any experienced marketer knows that succeeding in today’s digital market depends on the ability to identify the keywords that your audience is searching for.

      By using the right keywords in your content, you are likely to rank better in search engine results, ultimately leading to higher conversions, profits and brand recognition.

      NLP has proven an irreplaceable tool in helping digital marketers choose the perfect keywords to engage their audiences.

      That’s because it allows them to check which kind of results are generated by variations of related keywords.

      For example, the Search Engine Result Page (SERP) will be very different with you look for “advertising”, “advertising courses”, and “what is advertising”. 

      You need to know these kinds of subtleties to pick the combination of keywords that best respond to a search intent.

      Produce hard-hitting content

      In the same way that Natural Language Processing allows marketers to track the best keywords for their audience, it also proves a valuable asset for content creation.

      The most successful content captures prospects’ attention by referencing current events, responding to prospects’ needs and generally staying relevant in a chaotic marketplace.

      NLP can help digital marketers stay in constant conversation with their audience. 

      This could be achieved by tracking the hottest topics or performing an audit on your content to see what’s missing from your arsenal.

      With NLP, you can make sure that your content is never “old news”.

      Expand your audience with virtual assistants

      Virtual assistants are part of many people’s lives.

      They come in the form of home assistants like Alexa, Siri or a number of other smart speakers.

      Utilizing NLP in your digital marketing practices means expanding your audience — and virtual assistants can help you do just that.

      They give you access to highly personalized consumer data that helps orient your content toward the most fitting audience. 

      And spoken requests to virtual assistants can provide a range of relevant keywords that let marketers hone in on their target audience.

      Wrap Up: Harnessing the Power of Natural Language Processing For Professional Success

      As one of the many branches of artificial intelligence, NLP is an impactful tool that allows digital marketers to better serve their target audiences and expand their reach.

      In fact, it can be used to boost customer conversions, find pertinent keywords and perform sentiment analysis among prospects, to name a few applications.

      Ready to learn more about incorporating artificial intelligence into your digital marketing efforts?

      Then watch this super relevant recorded webinar on the role of AI in marketing!

      Share
      facebook
      linkedin
      twitter
      mail

      Subscribe to our blog

      Sign up to receive Rock Content blog posts

      Related Posts

      Want to receive more brilliant content like this for free?

      Sign up to receive our content by email and be a member of the Rock Content Community!