Natural Language Processing (NLP) has been around for half a century, and it’s starting to gain serious ground in the marketing technology space. NLP, in its most basic definition, is an area of computing that seeks to interpret, understand, and manipulate language so computers can make sense of human (also known as “natural”) language. On the surface, it may seem unrelated to marketing, but NLP applications have a direct impact on many marketing capabilities, most notably, segmentation and targeting, messaging, and machine learning and artificial intelligence.
How is it used?
At its core, Natural Language Processing allows us to analyze and make sense of unstructured data so we can make insightful and actionable decisions, often in real-time. This can have a huge impact on marketers for a number of reasons. For one, it opens up possibilities to understand and create language through automation. Second, it gives us an increased ability to extract, understand, and utilize text and natural language, which will augment our current state of relying mainly on structured data.
The ability to understand and manipulate speech and text has enabled capabilities such as speech recognition, sentiment analysis, language translation, and even machine learning. Things we use everyday — Siri, Alexa, Google Voice, etc. — are all powered by NLP and its technologies. A number of intelligence tools we rely on daily use NLP without us even realizing it. If you’re using a chatbot, you’re likely interacting with NLP technology. If your service and/or social platforms can decipher positive versus negative comments, you’re benefiting from NLP. Lastly, if you’re like most marketers, and you are using some form of intent or predictive technology, you’re likely relying on machine learning and NLP to make those predictions.
How is it beneficial for marketing?
Let’s dive deeper into NLP and why (and how) you should utilize it to augment your current marketing initiatives.
NLP gives marketers the ability to analyze and recognize themes and topics within threads of text and data. One common use of NLP is within the social space. Many social marketing technologies allow you to “listen” for common threads, phrases, or themes within social media channels, online news and platforms, and company systems. This gives you the ability to find relevant information about your company, competitors, products, and services. It also allows you to better determine interests and preferences of your audience which you can then utilize in your marketing messaging and content. Keep this in mind when reviewing products that inherently engage with your audiences. Understand their ability to read common language and use that information to guide future engagement.
Similarly to topic extraction, sentiment analysis takes listening one step further by not only deciphering language, but also determining the feeling behind the words. Sentiment analysis allows marketers to see which threads/comments/feedback is positive versus negative, related to specific issues, and showing certain opinions. This type of attitude tracking can directly impact your analysis of data, alerting you to shifts in trends, reactions to your organization, concerns about your services, etc. If coupled with the right technology, sentiment analysis can be used to automatically route contacts to the right teams — sales, customer services, or product development.
Targeting and Optimization
With NLP’s ability to read and understand text, it gives marketers a chance to better understand how their audience defines and searches for products and services. NLP can help you identify the keywords, search phrases, and common themes used for your business and industry. This alone can be a game-changer since it not only helps you fine-tune your personas and strategies, but also assists in defining your messaging approach. You can personalize your content to specifically speak to your audience using the terminology they use themselves. As technology advances, we will see more and more tools that not only read and interpret language, but also help marketers develop personalized content on the fly — think artificial intelligence and hyper-personalization.
Beyond messaging, there are similar benefits related to SEO, keyword detection, and chatbot interaction. NLP can be used to analyze specific data points and interactions with customers, in addition to online search, so you can improve your SEO strategy both in text and technical attributes. Some tools will even make automatic updates to your website based on learnings from NLP-powered capabilities. Similarly, chatbots can be optimized based on questions and conversations being posed over time. These can then be translated into automatic responses directing people to the right online page or supplying the right contact information.
Voice and Text
One of the most well-known uses of NLP today is voice recognition. We are all accustomed to asking Siri for assistance, Alexa to turn on our lights, and Google Voice to find the nearest pizza place. As marketers, we need to think how voice recognition can assist our customers in their interactions with our organization. Would our website or app benefit from voice recognition? Do our services lend themselves to some form of linguistic engagement? If so, how can we leverage that capability to not only aid our customers, but also provide us with real-time insights that we can leverage for ongoing marketing efforts? Similarly text generation can help marketers optimize everything from keywords, SEM advertising, product pages, banner ads, etc.
Where do I start?
Now that you know a bit about NLP, spend more time understanding its capabilities and how it may fit into your overall marketing strategies. Assess your current technology stack to see which platforms offer NLP, machine learning, and artificial intelligence capabilities that you can start to explore and analyze. If you’re an Oracle customer, Oracle CX Marketing tools utilize NLP in a number of ways across a multitude of products for real-time analysis, personalization, and predictive insights. In addition, Oracle’s Virtual Assistant integrates seamlessly with Service Cloud to support natural, real-time interactions in a number of ways while Oracle’s Digital Assistant Platform deploys advanced conversational tools to multiple channels including, web, mobile, and messaging platforms.
As always, if you’re looking to advance your marketing strategy and technologies, Relationship One is here to help.