Artificial Intelligence Is Vital To Customer Service
Ask any business leader and they'll explain why an outstanding customer service (CX) is the top priority for any business in any field. While the process of attracting new customers is vital, customer retention occupies a more prominent position in any area, be it online retail, software or technology, or travel and tourism.
The Journeys Customer Service tool does not just revolutionize customer service, but also boosts customer loyalty and brand reputation. Businesses in the B2C sector are more likely to adopt automated customer support thanks to tools such as AI-powered bots that can help in providing customer service. What is automated customer service and what's the role of AI in improving customer service? This topic will be explored along with examples from industry in the sections that follow.
Obtaining Feedback from customers via AI
What can you do to get customer feedback using AI-powered tools in a business? Here are some use cases which make use of AI techniques:
Sentiment analysis
Customer feedback that is analyzed for sentiment is a proven technique to assess what customers think about your business and its brand. Text analytics using AI can analyze and categorize feedback as positive negative, neutral, or positive. NLP methods can be used to classify all words (in a comment) together and extract the relevant information.
Additionally, CX metrics like Net Promoter Score (NPS) or Customer Effort Score (CES) are effective indicators of the general customer's perception and sentiment of the business.
Here's an example of NLP-based analysis of customers' sentiments:
Text analysis
The analysis of customer text feedback is a type of qualitative analysis which allows you to evaluate the moods and opinions of your clients in a more detailed manner. AI-powered text analytics tools analyse customer comments on online feedback forms. They can determine the sentiment by using some keywords.
Here are a few examples of words that are often employed in the finance and banking sector.
To provide insights into a company Text analysis can be utilized to study a collection of words. For example, if a customer comment uses a combination of the words (costs, expenses, and monthly) It could be determined that most customers are finding the monthly charges of your service too expensive.
Analytics to improve customer service
Customer service (or CS) analytics is an effective mode of evaluating all CS-related activities and determine the best way to improve their quality and decrease costs. A good illustration of CS analytics using customer service automation analytics, which is an excellent source of customer interactions and can be used to determine various metrics, including customer retention rate, user satisfaction and goal completion rates. Advanced call analysis and customer reviews analytics are two additional types of CS analysis that can enhance customer satisfaction as well as efficiency in operations.
Categorization of customer feedback with machine learning
Machine learning algorithms are among of the most widely used methods to use machine learning to classify customer feedback by common feedback points like:
The quality and price of the product
Customer service quality
Delivery of products
Online availability
Businesses can make use of categorization in order to understand how your customers feel about the products and services you offer. It can also help find common issues that must be addressed. Automatic categorization can be implemented by using pre-defined tags, making it easier to manage large amounts of customer feedback.
Customer reviews
Machine learning tools in customer reviews can be used to analyse reviews about products and categorizing them as either positive, negative, or neutral. Analysis of reviews on products made using machine learning could be used to identify:
Find out what customers like and dislike about your product.
Review your product's reviews against your competitors' reviews.
Gain 24/7 real-time insights about your latest products.
Learn the general comments and opinions about your newly launched product quickly.
Conclusion
Listening to customers is key to retaining customers and building loyalty in a competitive business. The company has expanded to collect and analyze customer feedback to get more relevant and practical insights.