4 Ways NLP-Powered Customer Service Can Make A Happy Customer Even Happier
According to an article by Forbes, more than 75% of customers choose to contact companies in order to make various inquiries and get customer support via text messaging. Even more, nowadays, with the required social distancing and Covid-19 restrictions, consumers need to interact with businesses online more than at any other point in human history.
Consequently, businesses now receive hundreds and even thousands of customer queries daily. Let’s suppose that each human customer service representative could handle approximately 45 calls per day, tripling the estimation from this HubSpot report; it would need ten customer representatives to handle about 450 incoming customer queries. On the contrary, a shortage of workforce suggests prolonged customer waiting time. According to a customer behavior study by Forrester, two out of three clients don’t want to wait for more than two minutes to get customer service assistance.
Companies began to search for intelligent solutions to automate customer engagements to deal with the growing volume of customer interactions. One viable solution to this problem is to use artificial intelligence in order to augment human representatives and help answer repetitive questions, such as “What’s your company’s refund policy” or “Where can I download your mobile application”? This is happening through the evolution of natural language processing as it makes the way customers are spoken to appear more human, and helps companies solve their inquiries without human input.
Think of natural language processing-powered solutions as knowledgeable virtual agents. With the help of your NLP-powered customer service efforts, your clients can utilize them to obtain quick answers without actually speaking to an agent on the other end. In this blog post, we’ll cover how NLP-powered customer service can make your happy customers even happier and the benefits it can deliver to customer service teams.
Top Reasons Why Customer Happiness Should Be The No.1 Priority For Businesses
While searching for affordable merchant accounts and product development need to be steady pillars for any growing business, customer happiness and providing exceptional customer experiences should be the absolute no.1 priority for organizations that strive to remain competitive in the future. Nevertheless, why is it so crucial that your clients are content with your company's customer service and the overall experience with your business? Below, we'll showcase the top three reasons why having a happy customer should mean the world to you as an aspiring business owner or executive.
Each Happy Customer Helps Company Growth
For example, without your happy clients, there will be no urge to look for card processing companies capable of managing the volume of credit card transactions that your business has. This is because there will be no funds flowing into your company accounts, whether it would've been by cash, debit card, or credit card. Additionally, when clients aren't happy, they are doubtful to become repeat customers, ceasing your company's growth.
Customer Referrals Are Good For Your Business
Genuine customer referrals are perhaps the best way to grow your business because people want to know that those who recommend a particular business have spent money on its products and services. When people think about doing business with your company, having a positive review from personal contact with who that person trusts carries a lot of weight.
Your Reputation Will Precede Your Business
Suppose your business happens to have a high satisfaction rate. In that case, it’s a stat that you can put on your official website to entice visitors to fill out a form and leave their personal information to learn more about what products and services you offer and eventually make a purchase. When most clients are happy with your offerings and customer service efforts, prospective customers may also feel as if they have a good chance at being content with the overall service they’ll receive once they get into business with your company.
Treating your customers well and having terrific customer service by your side are the two things that any prosperous organization should go out of its way to do. When clients feel good about working with a prospective company, the odds that they’ll use anyone else are practically slim to none. For that reason, you need to reconsider if your company is treating its customers well and always look for ways to improve your customer service activities. Enter natural language processing-powered models for customer service.
Natural Language Processing For Customer Service
Nowadays, businesses receive thousands of customer support queries from different channels. This may include support tickets, emails, tweets, chat conversations with support agents, chatbot dialogues, and more.
All this is a lot of data that businesses deal with, and most of it is scattered in nature and unstructured, making it much harder to manage and utilize. But all this data can be used to improve the speed while answering customer service queries and eventually decrease the volume of incoming customer support tickets. And as customers foresee that their customer support inquiries will be resolved in a couple of minutes, the harsh reality is that the average response time to customer service queries is 12 hours and 10 minutes! So, how do you reduce response times while also staying effective in maintaining your customer happiness with your business?
The best way to address this issue is through automating and streamlining particular customer service processes by utilizing natural language processing and machine learning, both subfields within artificial intelligence.
Natural language processing, or NLP, is a form of AI that permits computer programs to process and analyze unstructured data, primarily free-form text data. Natural language processing combined with machine learning could be a powerful tool to transform messy, unstructured data into something more structured. They can also help your customer service representatives find patterns in your collected data and provide natural language communication with clients when implemented within chatbots or virtual assistants. However, suppose you decide on skipping these automation approaches. In that case, your customer service department will be left to perform a lot of tedious, manual, repetitive work or use a set of complicated rules to achieve some basic level of automation to have happy customers.
Y Meadows solution is 100% dedicated to empowering customer service representatives, increasing support agents' productivity, and improving the overall customer experience. Our software uses advanced AI, natural language processing, and machine learning technology to better handle customer queries and empowers the people in your customer support teams. This software solution can help organize and triage incoming support tickets, reduce response time by eliminating the need for human representatives to gather data from multiple systems, and successfully analyze each customer request to respond with relevant information and attachments instantly.
Below, we'll display how you can make your happy customers even happier with your business if you decide on integrating Y Meadows' solution.
4 Ways NLP-Powered Customer Service Can Make A Happy Customer Even Happier
Y Meadows’ Software Can Recommend Answers
Usually, customer service agents spend a lot of precious time researching answers to customer queries. When the customer service agent tries to answer a customer question, they may be overwhelmed with determining the best solution from the pool of possible responses when they only need one or two answers to address each question. Some enterprises have an exhaustive list of problems and corresponding solutions that service agents must search through manually. This can be an energy-draining and painfully slow process if they need to perform a manual search every time there’s a customer question in line to be answered.
Natural language processing and machine learning can be advantageous in recommending the top answers given a support question. Even more, the best thing about utilizing Y Meadows NLP-powered model is our Fury Index function, which exploits natural language processing and machine learning to measure the level of frustration that each customer experiences to prioritize the customers who are least happy and solve their queries first. With this function, your customer service agents will have useful problem-solving information pushed to them automatically, preventing a break in their workflow.
Besides, by not wasting additional time searching for answers to common queries, response times can be dramatically improved, which also means that your agents will be able to handle a more significant volume of support issues while improving customer happiness at the same time.
NLP Can Help You Group Similar Questions
As far as we are all aware, context switching can be challenging. For example, shifting from resolving queries related to billing to signups and then back to billing can be a productivity killer. However, by grouping similar support issues, service agents can address similar problems in chunks, where the knowledge bank that they’ll have to tap into and potential answers are related.
With the help of artificial intelligence and its subfield natural language processing, you can automatically group these questions. The most significant advantage of doing this is that it maintains the same train of thought in resolving different problems. In many cases, the solutions may be identical, while in others, your service agents will know what steps to take in order to resolve a problem while everything is still fresh in memory. By limiting context switching, you can expect to see a reduction in response times, leading to shorter resolution times and, of course, happy customers.
The Software May Suggest Historical Threads
While some queries and questions can be quickly answered with recommended best possible answers, others can be complicated, requiring a more extended search from the representative. One way for customer service departments to solve complex problems is by searching for related historical threads and acknowledging how those issues were resolved previously. This way, your agents will form a complete answer and better resolve the issue thanks to previous successfully resolved problems.
With NLP-powered software like our solution, you can automate this process by recommending related historical threads for any given support issue. This will save your service agents from conducting extensive searches, contacting peers and managers for help on a problem. Furthermore, this approach can again help improve response times and improve your first contact resolution as the service agents will be better equipped to handle issues. As a result, you'll be able to reduce your follow-up support requests and solve your customers' queries in a faster and more efficient manner.
Y Meadows’ Model Can Help You Auto-Prioritize Service Tickets
While some organizations support customer support issues in the “first in, first out” order, meaning the oldest support tickets get addressed first, while others manually assign the level of priority based on the severity of the problem. Nevertheless, it would be best if you never forgot that not all clients are equal and not all issues deserve the same level of attention as some of your clients are “high-value” clients who’ve been using your products or services for an extended period.
By clubbing them as one and addressing their threads in the “first in, first out” order, you might miss out on the opportunity to retain your highest-valued customers. And if you’re spending your efforts on resolving low-priority issues for low-value clients before serving your most valuable ones—it’s time to rethink the process.
Although you can manually go through your customers and serve the high-value ones first, with NLP-based automation and AI, you can combine different factors and customize your issue prioritization. For instance, you can develop a tailor-made model in our fully integrative solution that will consider the customer lifetime value, severity of support threads, tenure, purchase value, and auto-prioritize new support questions. This will ensure that your biggest customers with high-priority issues get served as soon as possible and by your best support agents.
Artificial intelligence and its subfields are undoubtedly revolutionizing the future of customer service for the better. By delegating simple tasks to machines, organizations can supercharge their customer service efforts, which leads to enhanced brand reputation, taking well-informed actions, improved customer experiences, and happy clients.
Bottom line, there are enormous benefits that come with implementing AI-based solutions within your customer service teams that directly hinder your customers’ happiness with your brand and business. Without the successful implementation of such models, businesses risk becoming stagnant. They won’t be able to compete with AI-led companies, whose agents deliver highly personalized customer experiences and valuable insights.
The time to transform the way you engage with your customers is now! If you’re interested in getting started with Y Meadows software and see how we can help you boost your customer happiness, please request a demo from our team and take your team’s performance to the next level.
Vous pourriez aussi aimer
In the customer service domain, ticketing system providers have had to update their products in order to serve their customers better. Read more to learn about the top new trends that we are seeing in customer service ticketing systems.Lire la suite →
In order to meet customers’ demands for fast resolution times, companies need to incorporate a sound ticketing system for customer service to drive fast, consistent, excellent service. Such a system can help your business fast-track customer support issue-resolution.Lire la suite →