The Customer is king, and this remains true today. Today customers have the power to express themselves freely regarding the product and services and a factor for any business’s success is to take customer reviews or feedback positively.
There is a wise saying that reminds us not to judge someone until we’ve walked miles in his shoes or until we have experienced what they have experienced. Whenever customers are satisfied and happy with the offerings of the company, they express praise. On the other hand, if dissatisfied they also want to shed frustration and let the company know regarding their poor services.
In such a scenario, what can companies do to analyze the tone of customers?
Sentiment analysis is a crucial tool for understanding the tone and the hidden sentiment of customers. It gives great insights to companies as to what customers are thinking about their product or service and helps them to improve the services and plan a better strategic move.
Companies can analyze the customer’s sentiments through NLP (Natural Language Processing), a machine learning algorithm that can analyze human text.
This brings us to the question, what exactly is NLP?
NLP is a technology that is used to analyze the emotional intent of the text, whether it is negative, positive, or neutral. It uses Computer Science to understand and interpret the human language.
For instance, Apple’s Siri and Amazon’s Alexa to understand human questions and to answer them better, utilize NLP. Additionally, search engines such as Google and Bing use NLP to improve their search engine results.
As far as text analytics is concerned, companies usually adopt this technology to understand the mindset of customers regarding their product, through customer reviews and feedback.
Let’s witness how NLP can significantly improve the marketing strategies of businesses-
Customized Marketing Notifications
Analyzing the tone of the customers offers a better chance for businesses to personalize notifications as per the emotional intent. It is one of the best ways to drive customer attention toward the brand and help companies customize their marketing efforts. It will ultimately help in prospecting and generating sales revenue.
Saves Cost Through Targeted Advertising
Analyzing the sentiments and emotions of customers helps companies tailor their advertising campaigns as they can segment the customers based on their emotional responses. Targeted ads lead to better optimization of the budget and avoid spending on customers who are not at all interested in the services.
Improving Services by Examining Customers’ Pain Points
NLP through sentiment analysis can detect the emotion behind any feedback mentioned by the customer. If the feedback depicts customer dissatisfaction, it gives enough opportunity for businesses to identify the pain points, address them, and improve their marketing strategies.
Utilizes Emotion Quotient to Segment Customers for Marketing Strategies
Different customers perceive products or services differently based on their satisfaction level and the sentiments associated with them. NLP facilitates the segmentation of the customer based on their emotional responses. Thus, recognizing the emotions of different customers helps companies in crafting marketing strategies as per different segments identified.
Aids in Evaluating Campaign Effectiveness
Through NLP analyses, companies can assess how customers perceive their products. It will help companies evaluate the effectiveness of their marketing campaigns and optimize future campaigns to make sure that campaigns align well with customer’s expectations and emotions.
Final Words
Computers can now understand unstructured and complex textual human data, all thanks to Natural language processing (NLP). By unlocking the power of NLP, businesses can get valuable insights, automate the whole process through chatbots, and help companies make data-driven decisions.
We at Canopus Infosystems, through data analyses, can help you improve your products or services and understand human sentiments through their feedback by leveraging NLP.
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