This article discusses various artificial intelligence (AI) technologies that are helping the customer service team improve their performances and businesses. The customer service team is required to keep customers happy and delightful.
You must have come across the joke, “If the customer is always right, then why isn’t everything free?” Well, everything cannot be free in business, but one thing is for sure that every business setup needs to listen to customers carefully, including their requirements and problems. ‘Customer is King’ is an age-old proverb and philosophy but still relevant to every business in the modern world.
The customer service team is required to keep customers happy and delightful. This team is an integral part of all businesses. By automating different customer service activities with artificial intelligence (AI) tools, companies can provide faster and better responses to customers’ queries and smart customer experiences.
Let us look into various AI technologies that are helping the customer service teams improve their performances and businesses. But before delving into the AI technology, let’s find out why customer service is important in every business.
Why customer service?
As per the definition on Wikipedia, customer service is the provision of service to customers before, during, and after a purchase. Quality customer service is about making sure that your customers are valued, treated fairly, and appreciated. Prioritising customer service support helps attract as well as retain loyal customers. This will have a big impact on the growth and success of your company. So, customer service plays an important role in every business and industry. The advantages include preventing business failures, retaining customers, helping your brand, and providing an element of trust and value to your business.
Prevents business failure
When a business does not have good customer service associates, customers can become frustrated over small problems that are not addressed properly. There is a high chance that customers may stop doing business with your brand and go for your competitors or brands offering similar solutions. To prevent such problems, the customer service team can follow up and promptly address the issues. Customer service is the backbone of your business, and without a backbone, your business could collapse.
Retains customers
The customer service team can retain customers. In most cases, satisfied customers become devoted buyers when you provide good customer services along with your trustworthy business records. When you’re offering the same products as your competitors, one of the things that you can do to differentiate yourself from your competitors is to build a good customer service team.
Promotes your brand
Aligning your brand and customer service is a good way forward to survive in the market. When a brand focuses on customer service and support, it has great growth potential.
As per the report from Customer Experience Impact, 82 per cent of consumers in the US said that they’ve stopped doing business with a company due to poor customer service experience. Of these, 73 per cent cited rude staff as the primary reason, and 55 per cent was due to the company’s failure to resolve their problems in a timely manner. Another report says that 66 per cent of B2B and 52 per cent of B2C customers stopped buying from a brand after a bad customer service interaction.
Provides element of trust
When your business has good customer service in place, customers trust you more. Trust could make all the difference in the world of business. When customers trust you more, they are likely to remain loyal to your brand and product.
Provides value
The customer service team provides value to your business by treating customers well, answering questions, and building strong relationships. Customers understand that they are the source of revenue for your business, and they want to feel appreciated.
Is AI a big deal for customer service?
AI is revolutionising the future of customer service in many ways. It is not just limited to chatbot or auto-answering; it is much beyond, as described in the next section. AI supports and works alongside humans, enables a business to grow in a cost-effective way, and promotes the best possible customer experience. By assigning simple and repetitive tasks to AI machines and allowing humans to focus on customers that require complex issues or assistance, companies are able to improve customer services leading to improved customer experiences, enhanced brand reputation, and well-informed actions.
Some of the advantages of AI include auto-answering, 24-hour service, faster decisions, handling voluminous data, and boosting efficiency.
Auto-answering
Auto-attendant is a common feature in office telephone systems. It is an important part of your business. It is typically the first point of contact with your customers. Similarly, AI-based voice bots and chatbots are used in modern communication devices.
24-hour service
One of the key benefits of an AI chatbot is that it never sleeps. It is there to help customers resolve their issues at any time. This is important for companies operating globally and looking to provide better customer service and support. Humans can get tired and demotivated after answering the same repetitive questions. AI is perfectly suited for repetitive and menial tasks like tagging tickets. Most of the time, the bot is able to resolve the query, but in situations where it cannot, it is passed on to the humans.
Handling data
Companies are collecting more data than ever about their customers. But it’s difficult for humans to accurately analyse the vast amount of unstructured data. AI and machine learning can derive quantitative data and respond to customers much faster than humans.
Faster decisions
When customer service is available round the clock with a vast amount of data, AI platforms can find answers quickly and respond to queries faster.
Boosting efficiency
Even if your brand has an experienced customer service team, AI can still lend a hand behind the scenes. Using natural language processing, AI can read a ticket and direct it to the right team much faster than a human triage system can.
Some use cases of AI in customer service
Voicebot
It is based on AI and is a more advanced version of an auto-attendant system. It is great for handling automated tasks that involve numbers and simple yes/no answers. Voicebot with natural language understanding (NLU)-based voice channel for communication works by converting audio to text format. For example, Dialogflow CX, recently launched by Google, is used for building text and voice-based AI agents for mobile apps, websites, and Google Assistant actions. A user can speak to the virtual agent naturally, and it will process the information and respond appropriately. Another example is the AI-powered voice bot ‘TIA’ launched by Tata Capital on WhatsApp.
AI chatbot
The AI-based human-like bot that pops up on the website to start an online chat is becoming a common feature on most business websites. The chatbot can be integrated on websites, messaging applications, mobile apps, and kiosks. These bots play a vital role in the simplification of human interactions with the computers and customer interactions with the business, providing engaged self-service.
As per some reports, sixty per cent of online customers do not like to wait for more than sixty seconds for a response to their query. The use of chatbots drastically reduces customers’ waiting time and provides a quicker solution to their queries, thus improving customer experiences. Chatbots with Natural Language Processing or NLP capabilities are used to handle customer complaints through faster responses, thus elevating customer satisfaction.
For example, the AI-based COTA (customer obsessed ticket assistant) system built by Uber helps customer support representatives improve their speed and accuracy, resulting in improved customer experience. It is found that with the AI system, ticket routing efficiency is increased by ten percent. Big companies like Google, Microsoft, Facebook, and others are all actively engaged in the race to build chatbots that can respond to customer queries.
Customer identifications
These include biometrics and face and voice recognition. Biometrics refers to body measurements, authentication, identification, and access control. Facial recognition identifies and verifies an individual by comparing facial features from a digital image or video to a database.
Voice recognition biometrics digitises words and encodes them with data such as pitch, cadence, and tone, and then forms a unique voiceprint related to an individual.
AI-based biometrics help customer service agents to recognise customers and greet them in a personal manner. The customer support team can use biometrics to quickly authenticate customers while minimising the risk of fraud.
For example, tools like ScopeAI work with customer support teams to analyse the voice of customer (VOC) data across multiple channels.
Predictive personalisation
Most companies now have access to huge amounts of data about their customers. When a customer clicks, views and purchases a product from a website, these data are translated into predictions that deliver value-added personalisation and recommendations to targeted consumers. That is, AI-based predictive technology can identify patterns that indicate a customer’s intent based on web activity or text and route the call or chat to the appropriate agent.
AI has been used in the e-commerce industry to improve product recommendations based on personal customer needs, buying behaviour, and user profile. For example, Netflix’s AI-powered customer service algorithm uses data such as demographics, viewing history, and personal preferences to predict what the user would like to watch next.
Predictive maintenance
This technology is used to predict technical and maintenance issues before major problems occur. AI predictive maintenance is in use at United Parcel Service and Cisco. It is reported that United Parcel Service has saved millions of dollars by implementing an AI predictive maintenance solution that reduces delivery truck breakdowns. At Cisco, AI predictive maintenance is used to optimise network performance and troubleshoot issues faster.
Motivation and productivity
Research shows that disengaged employees in the US cost billions of dollars a year. With advanced AI technologies, customer service agents can work faster and more efficiently. AI tools used in customer service include:
- Call prioritisation
- Customer identification
- Recommendation engines
- Smart agent monitoring and training
AI-powered tools and solutions help extend the abilities of customer support teams, enabling them to master complex processes. It is an effective way to improve job satisfaction and reduce attrition. When employees are empowered with top-notch solutions, they are motivated to work better. You can get many AI-based tools from different vendors such as Zendesk, HappyFox, Freshdesk, and Accenture.
CLV optimisation
In marketing, customer lifetime value (CLV) is a metric that tracks how valuable a customer is to a company throughout the relationship. It is a prediction of the net profit attributed to the entire future relationship with a customer. Studies have shown that the likelihood of selling to a first-time customer is five to twenty per cent as opposed to an existing customer with the probability of sixty to seventy per cent.
There are many customer service software tools for companies to continuously improve or pinpoint areas of excellence. Using AI-driven data analysis to track customer lifecycles and target customers with loyalty promotions help optimise CLV. Apart from using AI to calculate and improve CLV, marketers are using it as a primary key performance indicator (KPI) metric.
As per the Pareto principle, better known as the 80/20 rule, eighty per cent of the profits come from twenty per cent of your customers. The actual customer distribution may vary depending on the industry and other factors. However, at the most basic level, the distribution might look like the CLV graph, as shown in Fig. 1. The goal of CLV is to identify the segments that are practical and help you make better marketing decisions. Some key parameters while calculating CLV include average order value (AOV), purchase frequency (F), gross margin (GM), and churn rate (CR).
AI-based CLV optimisation tools are available from different vendors such as XLSTAT, Pega, Qualtrics, Optimove, and others.
