Most of us know the old adage in business: Customer is the King. In the words of great management guru, Peter Drucker – “the purpose of a business is to find customers”. If your customer isn’t happy, neither are you! But how can you serve a customer who doesn’t know or understand your language? If your customer is unable to understand your language, then how do you think he/she will communicate with you? Language has become one of the key imperatives to reach the right customer and communicate with them. Companies globally have been investing massive amounts of money in technologies that could allow them to communicate with the customers in a language they are familiar with. Isn’t that amazing!! So how can technology or a system understand a human language, decipher the words, sentences, understand the meaning, context and respond with a correct solution? Natural Language Processing (NLP) seems to be the right technology that could address these business needs. What does NLP mean and how businesses across the globe are leveraging its benefits? We shall see in the below article.
Defining Natural Language Processing (NLP)
It is the language component of Artificial Intelligence. In simple words, it is the technology that allows humans to communicate with machines. NLP is widely known to be com
putational linguistics that combines technology like Artificial Intelligence (AI), Machine Learning (ML) and natural languages spoken by humans. NLP has proved to a communication bridge between humans and machines. So, the next time you say Hey Alexa! What’s the weather today? or Hey Siri! Tell me a Starbucks café nearby, remember there is a complex algorithm behind it that allows Siri or Alexa to respond.
With the implementation of semantic search as opposed to keyword-based search, it is possible for the search engines to learn associations between the words and understand the context and meaning of the query to provide a right response. This is all made possible because of the NLP technology.
Why Natural Language Processing (NLP) could be the future of business?
NLP has the great ability to extract insights from human texts and understand human emotions exactly. Example: If someone says, the coffee was amazing, NLP can decipher that human emotion is happy at present. Similarly, NLP technology can also differentiate between different emotions like sad, joy, angry, annoyed etc. This understanding of emotions by the system is termed as sentiment analysis. Emotions drive customer choices, and companies must track these emotions and understand the customer better to provide them with enhanced services. The sentiments are derived from various responses, feedbacks, and reviews given by the customers on multiple social media channels, web pages and sites. NLP captures the data from several sites and analyses the human emotions and helps companies to improve customer experience.
NLP, as a technology works wonders as it has the ability to understand data and categorize it into different data sets. Example: the data extraction includes – entity extraction (names, demographic, certain keywords), categorization of text (emotions, different categories, by context), data clustering (according to topics new and old), facts (validated and structured information for better analysis), relationship extraction, (helps in establishing real-world relationships through texts). All the different components of data can be collected and put into a structured format for further use in designing marketing campaigns and for business analytics.
Businesses use email marketing as a great tool in reaching out the target audiences. Use of NLP can be greatly seen in email filters. NLP helps in filtering the spam messages from the servers and separates them before it even reaches the mailboxes.
By making use of NLP and AI technology, companies can create voice interfaces and Chatbots that can talk with customers anytime and every time. These voice interfaces have the ability to understand customers’ voice, recognize the words and sentiments and reply to their queries with appropriate solutions. NLP can convert voice/speech into text helping machines to understand the human language easily.
Customer service is one of the key areas of a successful business. Companies that take efforts to improve customer service and offer more personalized services to their customer flourish more in the market. Voice recordings, text messages and online responses can be collected through the systems and analyzed for deeper insights, further providing ways to offer tailor-made services to the customers.
It is crucial that a brands advertisement should reach the right audience at the right time through the right channel. Thus, NLP identifies consumer preferences through browsing history, keyword searches, social media pages, online responses, emails, and behaviors. After identifying the data, it categorizes it into different buyer personas and allows marketers to create ad campaigns specific to the personas. This way, companies can target customers in a better way and reach them with the right message. It simply does keyword matching in the most accessible format.
NLP helps companies to stay updated with industry trends by offering market intelligence that includes information relating to competitors, stakeholders, governments and other regulatory bodies. NLP helps in tracking these market reports especially useful for financial organizations that have an eye on changing numbers, profit and loss, market status, openings and closings.
With ever increasing competition in the market, companies need to know where they stand and what their reputation in the market is. To do so, companies need to monitor brand reputation regularly. It is said that 90% of customers read online reviews and check for feedbacks before they buy a product. Thus, brand reputation plays a key role in deciding a brand’s place in the market. NLP combines human text, i.e. responses, feedbacks and reviews with the market statistics and analyses and does opinion mining or sentiment analysis to know an opinion at large. Hence, through all the analysis, it finds out if the product or brand is doing well in the market or not and decides the brand reputation.
Other use cases of NLP include Resume segregation that makes HR’s life easier, determining spams, regulatory compliance, biometrics, robotics etc. NLP is gaining importance in the business activities slowly, and companies are investing majorly into the technology. Although there is more research work required and the technology is still evolving but, NLP is undoubtedly helping businesses to stay ahead in the competition proving to be future of every business.