Leveraging Business Growth Using NLP(Natural Language Processing)
Business leaders are adopting AI strategies due to its unique capabilities of making sense of unstructured data and obtaining valuable market insights from the same. One of the AI functionalities that are gaining increasing traction these days is Natural Language Processing (NLP). This article will take you through the concept of NLP and its various use cases that help businesses thrive while standing apart from their market competition. Here’s why:
The amount of data analyzed by NLP powered cognitive systems will reach 1.4 ZB by 2025
The global market size of NLP is predicted to grow a CAGR of 18.6% between 2020-2026
By 2026, the NLP market CAGR is estimated to reach USD 27.6 Billion
NLP is predicted to have a huge impact on healthcare. The Journal of Medical Internet Research used NLP to sift through 204,597 Instagram posts and 6,029,323 tweets to find questionable sales of Covid-19 products.
What is Natural Language Processing?
Natural language processing assists programs to understand and interpret human language, thereby bridging the gap between human communication and machine (computer) understanding. NLP tools can gather and analyze huge amounts of unstructured data- linguistic, jargon, slang, and numerical- and help organizations obtain data-driven results. NLP brings great potential to accelerate and automate tasks in your business to streamline workflows and processes.
A popular example of NLP in action is Amazon’s Alexa, a device that can identify speech patterns and derive meaning from the same to complete a task and assist the user. Another great example of NLP is in the Human Resources field. HR professionals can considerably speed up candidate shortlisting by filtering out relevant resumes using semantic analysis to find relevant synonyms used within the resume and detect candidates that meet the job requirements.
How does NLP function?
The basic NLP model functions in 3 stages:
#1 Data Analysis
In this phase, the model captures a huge amount of data from various sources. This data is often in a raw and unstructured format. Therefore, the NLP model cleans and structures the data according to some predefined rules.
#2 Data Classification
Data is classified into various pools using syntax and semantics that are recognized by the model. Words, phrases, and tone of voice can be studied by the model to take the right action and perform the pre-defined task.
#3 Data Summarization
After the data is segregated into categories, the model can extract important information from this data which can be helpfully applied in medical, academic, research, or healthcare domains. This data can be studied by business leaders to make informed decisions.
How can NLP be Leveraged in Business Operations?
Here are the top 3 NPL-powered business applications that have helped businesses reach new milestones in terms of customer engagement, customer satisfaction, and overall business growth.
#1 Smart Virtual Assistants and Chatbots
Chatbots and Virtual Assistants(VA’s) are influencing customer buying patterns, customer engagement, customer service, and taking a load of human employees when it comes to performing repetitive tasks of assisting humans in commonly asked queries.
Think of an assistant that is available 24*7/ 365 and who can converse in any language to promptly attend to customer queries and direct them towards the right department or action to be taken. This not only makes the customer feel attended to but also increases brand awareness.
NLP powered chatbots can even interpret the emotion behind customer feedback, thereby providing valuable insights to the business with regards to its products and processes. AI-powered VA’s can study customer buying patterns and recommend products and ongoing discounts for a holistic customer experience. They can convert leads to potential customers, schedule appointments, and handle a “PR Crisis” in time by just analyzing and understanding the customer’s language and directing angry customers to the correct team member. A popular example of a VA is Siri and Alexa — these virtual smart assistants use NLP to understand user sentiment and tone and complete user-requested tasks.
#2 Analytics in Tone and Semantics
Human languages are complex and multifaceted. Any communication contains layers of meaning, intermixed with emotion and feelings. Language can be interpreted with multiple assumptions, contexts, and cultural backgrounds- leaving room for misinterpretation. NLP can analyze such text sources obtained from emails, social media posts, customer reviews, news events and more, to help companies derive actionable insights.
Sentiment and tone analysis helps adjust sales and marketing strategy according to what customers feel about your brand. By assigning a value to the text/tone (either negative, positive, or neutral), businesses can make informed decisions across various verticals- right from product rollout to discontinuation to better sales and marketing strategies.
#3 Predictive text
NLP makes applications like autocorrect and auto-complete possible. The tool can also understand a user’s personal language habits and make suggestions based on their behavioral patterns. Whether that be suggestions given during sending a message or even during simple documentation- predictive text makes it faster for individuals to get things done.
Take an example of the popular grammar and writing tool- “Grammarly”. With 30 million active users, this tool uses NLP to correct grammatical errors in text, improve sentence and paragraph clarity by suggesting, adjusting writing tone and so much more!
Final Thoughts
NLP tools and software powered by AI/ML are creating major impacts on countless business decisions across numerous domains. These technologies are heavily involved in assisting companies with optimizing processes and gaining new insights from data.
To know how NLP can help improve your business operations, send us an email at contact@fargowiz.com or request the below quotation form.
