Customer Service
Using AI Sentiment Analysis to Personalize CX
Imagine you own a resort, and you wish to find out whether customers staying at your property liked the experience. You turn to the reviews written by them. Customer reviews of both products and services generally have two aspects. First, each review has an overall sentiment expressed by the reviewer. Second, reviews often highlight specific features of the product or service, which may be discussed independently of the overall sentiment. For example, a customer might have liked the property overall but have had issues with the air conditioning for his room. So, the review will give both positive and negative/constructive feedback. Extracting such inputs from reviews is very important. If you have large volumes of customer reviews to deal with, sentiment analysis becomes invaluable as a technology that helps in automatically analyzing and categorizing the tone of the reviews.
What is sentiment analysis?
Sentiment analysis involves analyzing customers’ verbal or written feedback to understand their sentiments towards the product or service offered by the company. Is the customer happy or unhappy with the brand and its offerings? The sentiments that are gathered are categorized as positive, negative or neutral. Analysis of these sentiments can help the organization decide whether the customer is satisfied with the offerings. If not satisfied, then changes and improvements could be made to improve the customers’ satisfaction levels. Sentiment analysis helps in saving time and provides insights for improvement in customer experiences.
The Role of AI in Sentiment Analysis
One of the best ways to monitor how customers feel about your brand is by analyzing customer feedback on social media and the interactions that customers have with the customer support team.
Needless to say, when there is a large amount of data or feedback received from customers, it can get tedious and overwhelming for a person to perform sentiment analysis manually. This is where Artificial Intelligence (AI) helps as it uses techniques such as NLP (Natural language processing) to automatically analyze customer interactions across various feedback sources and understand customer perspectives.
So, how are companies leveraging sentiment analysis to improve customer experience and enhance brand loyalty?
Using sentiment analysis for improving customer experience involves collecting customer feedback, analyzing it and making improvements based on the feedback received and going through the cycle again to monitor if customer satisfaction levels have improved.
Sentiment analysis should be performed by gathering feedback across a variety of channels. This is because the type of feedback received on specific channels differs. For instance, the kind of feedback received at a help desk skews towards the negative. This is of course due to the fact that customers reach out or call customer support, if they are facing problems. On the other hand, feedback received on social media could be positive or negative. By responding effectively to customer inputs and feedback, brands can help build loyalty and trust.
Benefits of Sentiment Analysis
The sentiment analysis of customer chats during interactions highlights issues mentioned by the customer and these can be addressed proactively without waiting for the situation to go downhill.
Proactive resolution of issues
When issues that customers are facing are seen time and again on platforms where they give feedback, the company can take proactive steps to rectify the issues and ensure that the customer is satisfied and thus, in turn, reduce customer churn. AI-based sentiment analysis software has the ability to alert the company if sentiments trend negatively. This can most often be done by setting up alerts on the software that will be triggered when a large proportion of the said customers are unsatisfied with the product or service received.
Personalization of products/services
Sentiment analysis provides improved customer insights and enables companies to understand the emotions of their customers, thus ensuring better customer alignment. Depending upon the feedback received from clients, companies can give personalized offerings to particular clients and have relevant interactions with them. If the feedback is positive, it could be an opportunity to upsell to such customers and enroll them into loyalty programs by running optimized marketing campaigns. On the other hand, if the feedback provided by another section of customers is negative, interactions could be more empathetic and precise and proactive retention efforts could be undertaken.
Monitoring of competitor weaknesses
Sentiment analysis can even be performed on competitors' products or offerings. This helps in understanding weaknesses of competitors, and market gaps, if any and ensures that the product or service offered does not have the same issues or limitations. The product’s strengths to build on can also be identified.
Ability to observe brand reputation
Analyzing large volumes of reviews, surveys and comments manually is time-consuming. However, sentiment analysis lets you do just that by automating the process and tracking public sentiment over a period of time. This helps businesses to consider their brand reputation among customers and ensure that issues are addressed before they escalate.
What the future says
American business magnate Jeff Bezos once said,
“If you make customers unhappy in the physical world, they might each tell six friends. If you make customers unhappy on the Internet, they can each tell 6,000.’
It is clear that sentiment analysis will remain crucial in the days and years to come. The future of sentiment analysis will depend on understanding customers' emotions with better accuracy and contextual understanding. Advances in NLP and ML will, no doubt, drive this progress and revolutionize how businesses meet customer needs.
How can Infosys BPM help?
The customer service industry is constantly changing with increasing demand for support across diverse channels. It is crucial for businesses to manage customer interactions seamlessly across the entire lifecycle. Infosys BPM’s customer service outsourcing services unit understands clients’ unique expectations and delivers tailored, sustainable, and comprehensive solutions.
