What is Natural Language Processing (NLP)?
Natural Language Processing is a branch of Artificial Intelligence where the machines are automated to interpret, understand and translate the human language. NLP acts as a bridge between machine language and the natural (human) language of speech and text. It is a subfield of linguistic, computer science and artificial intelligence. With the help of AI, NLP breakdowns human communication and enables the computer to pull off certain tasks like grammar checking, translation, topic classification, sentiment analysis, spam detection, question answering, predictive typing, intent classification, speech recognition, chatbots, text summarization, urgency detection and virtual assistance. Here, both the input and output are in the form of written text or speech.
Today’s machines can interpret more language-based data than humans and can measure sentiment like frustration, fear, agitation or sadness with the tonal inclination of whether the freeform text if positive, negative or neutral. This sentiment analysis is done by considering the pauses between sentences and the words used. NLP is used widely in voice assistances like Alexa, Echo, Cortana, Google assistance and Siri.
How Natural Language Process (NLP) works?
NLP produces meaningful sentences and phrases as human language using two components as Natural Language Understanding (NLU) and Natural Language Generation (NLG). NLU enables analysing different aspects of a language and NLG helps in text realization, text planning and sentence planning. The former is considered harder than later. The meanings of raw data are disclosed by using automated tools and assistants of Natural Language Processing.

The Machine language algorithms learn millions of examples of text words, paragraphs and sentences written by humans. With these samples, the training algorithms gain an understanding of the ‘content’ of human speech and other modes of communication. The rigid, hand-produced rules of the database and spreadsheet help the software differentiate between various languages. This helps the non-programmers to make use of the technology and obtain useful information by computing systems or giving commands.
NLP and AI
Natural Language Processing with Artificial Intelligence is augmented to meet the shifting and complex demands of modern customers. It has undone the communication barrier between machines and humans paving the way for more opportunities for humans to accomplish what was impossible before. NLP is a branch of AI that studies how machines understand human languages. With the advancement of a recent technique called ‘word embedding’, the semantic meaning of words ascribed to an individual or group of words becomes easier to interpret.
In the progressive contextual advancement, the words are represented as vectors of numbers. This helps the machine to understand the word similarities in a very flexible way rather than simply understanding words as words. The random, context-bound and semantic rule-less nature of human language makes AI to reboot. With the Intelligent Process Automation (IPA) of AI, digital innovations allow the organisation to identify and organise a plethora of valuable information. It has made the NLP move away from its traditional pattern recognition in words toward the machine and deep learning approaches.
NLP in Digital Marketing
The technical functionality of conversational interfaces has acquired market clout. Chatbots play a vital role in marketing though they are now limited by the information fed to them in real-time. Voice search is gaining a wider audience in recent times and with the advent of Voice-only machines like Alexa, Cortana, Echo and Siri, the audience finds it easier and more comfortable to access various domains. It helps to understand the sentiment of large groups and direct group conversation and helps in brand monitoring, product analysis and competitive research. It generates effective ads with an optimized keyword, product listing and slogans with the help of text generation techniques.
One of the shear keys to modern marketing is the application and analysis of big data. NLP acts as a spam filter and spell-checker. It aids the marketers to extract qualitative customer insights and enables them to read between lines. Moreover, any unstructured and ambiguous data of customers can be analysed to be derived into a meaningful one. In all the aspects of e-commerce, start-ups, healthcare and customer service, NLP has increased its competencies and is in demand. NLP along with AI leads the best path for the next technological wave.
Conclusion:
For marketers, NLP is the main ‘go-to’ AI technology to identify trends summarize, generation of ads, lead generation and content capture. NLP is the best tool for its real-time, succour and scalable way of Digital Marketing. With sentiment analysis, the negative mentions can be mitigated. However, NLP tools are continuously evolving and adapting to new trends. Much better speech control, optical character recognition (OCR) and voice recognition will be a big area in the future.