Natural language processing (NLP) is a field of artificial intelligence (AI) that focuses on identifying, understanding and using human languages which is analyzed by computers to achieve a practical level of understanding. Many business domains have invested significant capital into the applied data science and machine learning (ML) technologies required to power their systems and NLP is one of the most evolving solutions.
Today, the digital conversations, be it voice bots or chatbots, that happen through the banking, customer service, marketing and other fields are driven by the application of NLP. The mass adoption of AI in everyday lives is triggering the use of smart appliances enabled with text-to-speech ability, spell checkers, search engines, translation tools and voice assistants and these work around NLP technique.
Tech research firm Juniper Research predicts that voice-based ad revenue could reach $19 billion globally by 2022.
How is NLP helpful in Marketing?
Marketing is heavily dependent on words to convey messages across the consumer crowd, which means it is directly or indirectly dependent on NLP.
Below are some use cases of NLP application in marketing:
- Efficient Content Generation: NLP can easily deal with unstructured or raw social media data. With the help of NLP, marketers can determine what content will resonate with followers on social networks and similarly brand marketers can identify their key influencers. This is an effective way to empower social media marketing.
- Improved SEO: Keyword Detection can be used to create or improve Search Engine Optimization (SEO) techniques. NLP helps to automatically detect important words from the data and match it against the current SEO keywords. This will help in improving SEO for a website, content or a social media page.
- Chatbots for capturing leads: NLP-based chatbots represent an opportunity to remove human workforce from repetitive and mundane tasks. It is capable of solving customer issues, especially in situations where immediate answers are expected. The banking, e-commerce and customer support sectors have been using them with great effect for several years.
- Competitive Analysis: This analysis is important for entering into the market and to get a broad understanding of the market like who the competitors will be and who the potential customers are. NLP-powered engines can considerably streamline the process of scanning the competitors. It can automate summarization for early identification of trends and thus, uncover meaningful relationships.
- Sentiment Analysis and Brand Awareness: To develop a business strategy, understanding consumer’s sentiment is essential. Sentiment analysis is used to evaluate positive and negative reviews aimed at a brand. NLP-based software can be used to analyze social media content, product reviews and customer reviews to develop data insights. The algorithms work by building sentiment analysis models from comments and positive, negative or neutral words are then filtered using classifiers. Using this data business and marketers can improve their decisions for developing strategies and forecasting demand for goods and services.
- Voice Assistance: Voice search has become increasingly popular in recent years, from smartphones powered by Siri, Alexa and Google Assistant. NLP is used for speech-to-text translation. It matches the output with the database and returns the answers after text-to-speech translation. Using voice search as a marketing channel, companies can enhance their marketing activity and engage in a wider audience.
65% of 25-49 year olds speak to their voice-enabled devices at least once per day.
NLP is set to continue being one of the main AI technologies for marketers, with applications ranging from trend identification and summarization, content and ad generation, and conversational lead capture. It can maximize productivity, streamline operations and can derive value to businesses.
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