Natural Language Processing (NLP) has had a huge impact on how companies interact with their patrons. NLP provides a powerful means to decipher human language, allowing for infinite possibilities when used in the enterprise.
In this post, we will comprehend some of the most widespread NLP applications and their use cases. We also review how NLP can help to construct an enhanced customer experience while also amplifying operational productivity. So, let’s get started.
What is NLP?
NLP is the sister technology of Artificial Intelligence and focuses on the interaction between computers and human language. With an array of strategies, computers are enabled to comprehend, interpret, and manipulate language.
NLP has been employed for an extensive variety of applications such as natural language understanding systems, voice-activated devices, machine translation, automated customer service, language recognition, text summarization, question answering, and text classification.
NLP strategies are used in multiple realms of research, comprising
- natural language understanding,
- natural language generation,
- speech recognition and synthesis,
- text mining,
- machine translation,
- dialog systems,
- and information retrieval.
Overall, it is an incredible technology that undermines the speech data of humans and brings out insights. Businesses can leverage this technology immensely to personalize user experience. So, let’s understand the application of NLP across business settings.
Applications Of Natural Language Processing
#1. Sentiment Analysis
NLP can help business organizations to decode customer feedback and viewpoint data using sentiment analysis. This technology classifies text as positive, negative, or neutral to gauge the overall feeling associated with a particular topic.
By utilizing sentiment analysis-based AI solutions, organizations can detect customer attitudes in real-time and act upon the conclusions drawn from the results. Furthermore, sentiment analysis also enables companies to find fresh patterns in customer opinions.
The benefit of it include:
- Social media sentiment analysis
- Brand experience insight
- Multilingual insights
- Improve customer services
- Insights from customer feedback
Ultimately, sentiment analysis provides organizations with a helpful way to access meaningful insights into customer thoughts and preferences. With the aid of NLP, businesses are able to make informed decisions based on analytical data and create better customer experiences.
#2. Language Modeling
Topic modeling, a process from Natural Language Processing (NLP), is able to determine the core ideas discussed in a set of documents. It takes advantage of algorithms to detect the hidden meaning within written texts and recognize concealed topics.
Using this technique, Companies can
- Speedily and accurately analyze consumer reviews and survey answers.
- Unearth patterns in customer data that can guide business decisions.
It also has applications for search engine optimization (SEO) and content suggestion for users. Through recognizing the topics being discussed, businesses gain useful insight into their customers’ preferences and needs.
#3. Language Translation
NLP has enabled a revolution in language translation, providing immediate translations between languages with considerable precision. NLP-based language translation leverages sophisticated algorithms and machine learning models.
These models detect language patterns & consequently, convert words, phrases, and sentences from one language to another. This technology has a wide range of applications, such as
- Allowing people to communicate in various languages.
- Assisting businesses in accessing new markets.
- Enhancing operations by ensuring customer interaction in multiple languages.
In addition, NLP-based language translation enables more accurate automated customer service experiences and speeds up the feedback loop.
#4. Text Summarization
The role of natural language processing in text summarization is critical as it can reduce large amounts of text into a shorter version that still contains the key points. Summarizing text using NLP can be useful for various applications such as
- summarizing news articles,
- research papers,
- and book summaries.
Organizations can leverage it to summarize large business reports and get valuable insights from huge company data.
#5. Namely Entity Recognition
Named Entity Recognition (NER) is a technique of Natural Language Processing that extracts important information from text, such as persons, locations, organizations, and dates. It helps identify these entities within unstructured data.
Also, it allows machines to better understand the content and create knowledge out of it. This will enable businesses to automate mundane tasks, such as customer data sorting & decision-making while saving both money and time.
Moreover, you can apply these solutions easily by leveraging NLP services that specialize in enterprise AI integration. But, make sure to strategize everything clearly/
Potential Use Case of Natural Language Processing & AI
Now you have understood the application of NLP and how it can enhance data quality. Let’s understand the use cases of natural language processes across different enterprise operations.
Virtual/ Smart Assistance
Virtual and voice assistance have become part of households these days. And these devices largely depend on NLP. This technology is a major force behind this solution allowing the device to understand human speech and extract information to produce the response.
The modern customer wants these devices to give respond more specifically and allow them to automate so many tasks. Using Natural Language Processing solutions, we can make these devices more self-driven and responsive as per users’ needs.
Digital Phone Calls
Have you called on customer care and hear this: “our call may be recorded for training”. There is NLP based solution that records the calls for automating custom services.
Usually, enterprises leverage NLP systems to personalize and speed up customer care. This solution usually records customer calls and extracts the data from those queries to provide personalized customer services.
Natural language processing in these systems analyze the conversations and extract insights that help business improve CX and save both cost & time.
The use of NLP across different marketing and advertising channels can help in identifying customer response and behavior to your services. These platforms include social media, chatting platforms, and many others.
The use of NLP can identify what people are talking about your brand and alert you on significant matters. By understanding their response and needs, you can target them with personalized solutions or services.
Report Urgency Matters
There are instances across organizations and operations, where immediate attention is required. Using NLP solutions, businesses can gain swift information into critical situations. Actually, these models leverage certain enterprises to recognize certain insights.
Using AI solutions, it is easy for enterprises to prioritize customer requests and address critical issues at first. From detecting urgency in the text and helping businesses take action on the industry aspect of emergency management.
Overall, natural language processing is revolutionary AI technology with the potential to seriously affect customer experience. Moreover, it can also enable enterprises to streamline several critical processes and boost operational effectiveness.
If you want to leverage this technology to uplift your enterprise operations productivity and streamline the customer experience. You can integrate NLP in chatbots, marketing & sales systems, and many other areas where you gather huge data.
You can also leverage Data Analytics services in a combination of these technologies to get more agility in operations. So, don’t stress much if you are thinking about smart solutions to automate customer assistance, AI and NLP are right there to make it a digital reality.