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Sentiment analysis, a powerful tool for retail customer care

12 April 2021

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SUMMARY

Today it is increasingly important to use sentiment analysis to better understand the needs of its customers, to improve brand reputation.

Users increasingly rely on online reviews and opinions for their choices: shopping, restaurants, hotels and vacation spots Every aspect of our life is subject to evaluation by other consumers.

While this proves to be an excellent way to avoid unpleasant experiences on the one hand, it is also a double-edged sword for companies, brands and professionals.

This is why it becomes important to know how to analyze and use the data that comes to us from this type of opinion and “traces” left on the web, through the so-called sentiment analysis.

What is sentiment analysis

The simplest definition of sentiment analysis in Italian is sentiment analysis. It is basically a field of Natural Language Processing, whose intent is to analyze a text, with the aim of understanding and classifying the information contained therein.

Also called Opinion Mining, sentiment analysis allows you to obtain a lot of information on the opinions and experiences of customers and consumers of a given brand.

Through textual analysis of the exchanges of reviews, comments and opinions of users and their interactions on social media, through machine learning algorithms, it becomes possible to open an illuminating window on the brand reputation of a company and on the customer journey of its average customer, called in this case Opinion holder.

The strategic importance of sentiment analysis

The first major practical application of sentiment analysis began with the concept of Web 2.0: over time, internet users have transformed from mere consumers to content creators who communicate, evaluate and discuss the services they receive.

Initially, the first approaches to opinion mining were aimed at selecting and dividing the orientations of the opinions expressed, evaluating them as positive, negative or neutral. With the progress of systems, the use of AIand the specialization of analysis algorithms, research has gradually become more widespread, deepening the motivations behind a given sentiment.

The customer is unhappy, but why? In what part of the buying process did something go wrong? Understanding the needs and opinions of your catchment area is finding a solution to the problem.

The benefits of sentiment analysis

Unlike a complex process such as a market survey on a product, sentiment analysis allows you to get to know your target of consumers better in a short time and to acquire changes in opinions with a much greater frequency.

Understanding how a new product is received, checking the quality of its customer services, staying up to date on comments and reviews in order to intervene to improve the brand reputation, if necessary. All this is possible thanks to the monitoring carried out through sentiment analysis.

Another aspect of opinion mining that should not be underestimated is its scalability: social media are an invaluable source of information, but verifying every data, without the right tool, turns out to be an impossible process to manage. With sentiment analysis, on the other hand, everything is done directly, in real time and efficiently.

Use the obtained data

But how to best use this tool, how to channel all the information acquired in order to derive a real usefulness?

Monitoring the sentiment of your customers over time, allows you to segment their habits and verify their customer journey within a purchase process, for example. Understanding which customers are unhappy, and the reason for their negative experience, is an indispensable source of improvement in customer service, or even in the marketing management of the brand, in terms of content, costs or products themselves.

Choosing to take advantage of sentiment analysis also allows you to manage situations of “communicative emergency” with timing and the right strategy. Detecting customer consent or dissent, understanding the reasons, becomes an invaluable brand reputation management tool.

Customer care retail and applied sentiment analysis

It is therefore important to understand how to apply this method of analyzing information relating to customers in practice.

How is it useful, for example in an area like retail, to have a sentiment analysis management tool? Why does retail need to analyze the collected data?

Brand perception and customer satisfaction

Today social media and the web spread opinions and reactions like wildfire in a short time, creating or destroying the fortune of a product or a brand in the blink of an eye. Timeliness of reaction is therefore necessary in a digital age.

By applying sentiment analysis with effective algorithms, using AI and machine learning, response times (a response designed ad hoc according to the situation) become fast and effective. For example, let’s think of a thank you message with a free discount made by the company to a user who, after a purchase, positively reviews his experience: this leads the brand perception and reputation to increase exponentially.
The same is true in a case of negative consumer experience. Sentiment analysis will make it possible toreact in such a way as to stem the situation, and hopefully transform it from a negative to a positive sentiment through actions aimed at customer satisfaction.

XCALLY and sentiment analysis tools

The complexity of human language is not always easy to interpret. This is why specific tools are needed to analyze and “train” algorithms to better understand a customer’s sentiment.

XCALLY, through the Transcript and Sentiment Analysis tools included in the Call Recordings section of the software, allows you to have the quality of your contact center under control, and to analyze the data collected in depth thanks to Artificial Intelligence.

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