Ability To Recognize And Understand The Actual Customer Perception Of Your Brand

The most effective method of gauging customer sentiment is through sentiment analysis powered by artificial intelligence.

Since the beginning of commerce in antiquity, the customer has always been the primary focus of attention. The likelihood that a customer will purchase your product or service is high if he is satisfied with it. Despite the fact that most businesses recognize that the "Customer is King," they have difficulty understanding their customers and their perception of the brand.

The experience that a brand provides determines the perception of a brand's customers and the likelihood that they will make a purchase in nearly 96 percent of cases. Accepting this reality and revising and modifying their customer journeys outperform their competitors and generate up to 5.7 times the revenue.

With the help of strategic changes to operational processes and the integration of advanced technologies, it is possible to gain a comprehensive understanding of customers by reimagining the customer experience. When it comes to assessing and improving customer experience, AI-powered sentiment analysis stands out as the most effective method available today.

In the business world, customer sentiment is not synonymous with emotions. Customer satisfaction data is derived from meticulously measuring how customers feel about the product or service they have purchased. Additionally, when a company uses sentiment analysis, it gains additional insights, such as the ones listed below:

• Buyers may be attracted or turned off by a particular day, a particular product, or a particular aspect of customer service.
• In what way does a current marketing campaign or other company activity affect the customer's perception?
• Customers' perceptions of a brand are shifting, and if so, is the shift pro- or anti-brand in nature?

When a company conducts sentiment analysis, it can determine which activities it should continue to invest in and which it should eliminate completely from the company's operations. This process can be used to make changes to a product or service, introduce a new offering, or make any other strategic changes that are necessary.

Customers' Feedback Mechanisms Must Be Redesigned 

You are typically asked to rate the customer service representative with whom you spoke or the chatbot that assisted you on a variety of parameters, such as product knowledge, behavior, language, and responsiveness when you contact a traditional business's customer service department. Today, almost every business organization, from the largest e-commerce portals to small local businesses, is focused on listening to customers and taking action based on their suggestions.

It is encouraging to see this level of awareness and commitment to the customer experience because recognizing a need is the first step in solving a problem. However, due to the nature of survey-based feedback, it is unable to provide anything other than point-to-point insights at this time. As an example, if a customer reports that their issue has been resolved, this may not accurately reflect their dissatisfaction with having to wait on hold for several minutes or some other problem.

It is possible for businesses to continue to lose customers despite being aware that their customers' experiences are critical and having implemented a customer feedback mechanism.

The Application of Sentiment Analysis to Improve the Customer Service Experience

Businesses require advanced artificial intelligence and data analytics-based sentiment analysis platforms in order to overcome the aforementioned challenge of struggling with customer experience (CX) even after putting in place a feedback mechanism. Due to the fact that they enable complete listening and understanding of the customer journey across multiple communication channels with the brand, such as voice, chat, or email, these solutions have the potential to revolutionize the way customer experience is measured.

These are world-class platforms that have been trained to analyze recorded conversations on a variety of parameters in order to detect clues such as anger, disappointment, irritation, and so on, as well as to determine the efficiency and accuracy of the customer service department's responses.

The standard 'Rate the call on a scale of 1 to 5' feedback option may overlook a number of important considerations. Many customers who are pleased and satisfied with the response may choose not to provide feedback, resulting in only the negative aspects of their experience being recorded on the feedback form.

But when a company is able to accurately hear and assess true, 100 percent customer sentiment, the results are frequently game-changing for everyone involved.

Would you prefer, as a business, to continue losing money while not knowing what is causing it? What about a solution that is highly available, scalable, and technologically advanced, ensuring that you can keep an eye on your customers' pulse at all times? Consider your options and take action immediately, before your customers switch to a competitor's brand!

Author:

The Head of Marketing at Mihup, a leading conversational artificial intelligence platform that was founded in 2016, is Jnanankur Ghosh. Because of his more than a decade of experience managing multiple product portfolios across multiple industries, Jnanankur adds tremendous value to Mihup's operations. He is in charge of all marketing initiatives for Mihup as a whole.

The aspirational marketing executive Jnanankur has worked for Fortune 500 companies such as Fujitsu, Subex, and Cypress Semiconductors and has a bachelor's degree in marketing from the University of California, Berkeley. His experience includes, among other things, managing product launches and go-to-market strategies, as well as partner marketing associations, digital marketing, and analyst relations, to name a few areas of specialization.

In his previous role as a global product marketing manager at Fujitsu, Jnanankur was in charge of planning and executing product launches, developing go-to-market strategies, supporting campaigns, channel and country marketing, as well as communicating with the sales team and other stakeholders. He joined Mihup in 2015. As product marketing manager at Subex Ltd, he was responsible for the development and implementation of the company's go-to-market strategy, as well as the coordination of all marketing activities for two major product portfolios. Also in 2021, he will participate as a panelist at the Product Marketing Alliance's Asia Summit in Hong Kong, China.

In computer science, Jnanankur received a Bachelor of Engineering degree from Visvesvaraya Technological University, and in marketing, he received a Master of Business Administration degree from Punjab Technical University.