AI & Customer Service - how to create real value for the customer ?

AI & Machine Learning

According to research conducted by the analytical and consulting company Gartner, by 2020, 85% of contacts between the consumer and the enterprise will be carried out on machines, without the need to interact with a physical adviser to the client. What's more, according to analyzes carried out by the same company, between 2017 and 2021, customer service performed solely by mechanisms based on artificial intelligence (AI) will increase fivefold.

One thing is certain - artificial intelligence opens up huge opportunities for entrepreneurs, and the revolution in the interaction between the company and the consumer happens before our very eyes. So how do entrepreneurs exploit its potential and translate into real profit?

Resolve the problem before it appear.

It is known for a long time that in customer relations it is better to prevent problems than to solve them afterwards. It is not surprising then that many companies already use technologies based on artificial intelligence to guarantee maximum consumer satisfaction. According to a report developed by the Forrester analytical center, in the coming years, companies will intensively explore the possibilities of using smart agents and add conversational interfaces to static self-service content. They will anticipate needs based on context, preferences and previous queries, and will provide proactive alerts, relevant offers and content.

Already today many companies use machine learning mechanisms to create real value for the client. An example of such an action are systems with built-in artificial intelligence that can monitor almost infinite number of websites and activity in applications in order to find potential threats. What does it really mean? First of all, it gives powerful opportunities to entrepreneurs. Companies can quickly and effectively identify customers who experience shopping problems. What's more, they can quickly find out the nature of these problems. Above all - thanks to machine learning algorithms - the intelligent system can in real-time help clients solve their problem by offering support through frequently asked questions or using digital agents available on platforms and mobile devices.

Giving solutions to consumer problems before their actually appear has huge business potential. Predictive actions in customer service can significantly reduce consumer discouragement rates, while reducing the number of complaints and improving general consumer experience, making it easier for companies to establish long-term (and at the same time profitable) relationships with clients.

A value of chatbot.

The number of virtual customer advisers is constantly growing. Currently, about 30% of companies offering their services on the Internet, have independent "bots" that can answer simple questions and solve simple problems. Still, the possibilities of implemented elements of artificial intelligence are significantly narrower than the skills of a physical advisor. Nevertheless, for many companies, virtual consultants generate millions of dollars in profits.

The China Merchants Bank is a good example of benefiting from such virtual agents. This Chinese commercial bank uses bots in popular WeChat application to handle between 1.5 and 2 million queries a day. In order to cope with this amount of work without using AI systems, the same bank would have to hire over 7,000 employees. Another example is the hotel and casinos group Caesars offering Ivy - a virtual concierge that automatically responds to guest inquiries. Thanks to it, the number of connections with the hotel's service office (traditionally managed) has decreased by 30%.

Another spectacular example is the use of artificial intelligence mechanisms by one of the Australian banks. Currently, it is experimenting with an independent, intelligent virtual assistant whose main task is to listen to talks of sales department employees. If a bank employee forgets something or makes a mistake, the bot automatically engages in the conversation.

Some companies use chatbots to improve the efficiency of employees. A good example is the use of systems suggesting responses to incoming customer queries that an employee may approve or adjust before sending. Over the past year, this kind of system has allowed Dutch KLM airlines to double the number of customer queries served - up to 120,000 per week - while increasing the number of employees by just 6%.

Let's talk about emotions.

The biggest business benefit of artificial intelligence lies in the increasing of our productivity and relieving us of repetitive, tedious tasks. In order to achieve this, technologies based on AI mechanisms must better understand the functioning of people and, above all, human emotions.

There is no scientific consensus on the definition of what emotions actually are, but most experts agree that they affect our thinking, decision making, actions and social interactions. Unfortunately research also indicates that digital communication disturbs our ability to correctly send and receive emotional signals. Undoubtedly intelligent systems with the ability to adequately capture emotions will be more and more desired by various types of enterprises.

Customer service for obvious reasons is one of those aspects of the business in which accurate expressing emotions is very important. In addition, entrepreneurs are increasingly focusing on making good customer experiences when interacting with the company (and thus generating positive emotions) become their competitive advantage and distinguishing feature on the market. More and more companies are also discovering that the customer's experience is not only based on its objective assessment of the service, but also (and perhaps above all) on the emotional relationship with the given brand.

The Tractica research center estimates that revenues from software for analyzing moods and emotions will increase from USD 86.1 million in 2016 to USD 3.8 billion in 2025, in which the algorithms used in customer service will have the main share. Already, many companies are developing similar systems, including potentates such as Google, Amazon and Apple.

Several other companies have also started offering services that are supported by AI technology. One of the startups, Cogito, in which customer portfolio we find insurance companies such as Humana and MetLife, offers intelligent systems that listen to the insurance agents phone calls, assess their performance and send them real-time suggestions. Cogito’s system is also taught to recognize the so-called "Compassion fatugue". It’s analyzing how quickly agents talk, what words they use, and what words the client uses. Based on these informations the algorithm detects and assesses the emotions that arise in the conversation. If a problem is diagnosed, the system automatically encourages agents to be more empathetic.

Such a tool can help large companies monitor their employees' performance and improve their efficiency. Joshua Feast, Cogito's CEO, points out that it is the lack of proper feedback and targeting that is the main reason for call centers financial looses. Applications analyzing moods and emotions can effectively change this.

Tailor-made offer.

From the thousands of gigabytes of data that each of us generates over our lives, it is estimated that about 33% is really valuable and only if they are properly analyzed. For this purpose, artificial intelligence may serve the best.

Companies collecting customer data can combine large data sets, machine learning and other artificial intelligence mechanisms to provide customers an unprecedented level of personalization of the offer addressed to them. These can be both simple product recommendations based on previous purchases, as well as customizing the offer by redesigning the websites in real time so that they are best suited to the level of the reader and his habits. Personalization can significantly improve consumer interaction with customer service, increase customer satisfaction, speed up purchases or improve shopping conversion.

Many companies such as Google, Facebook and Amazon have been experimenting with developing the tools of recommendations based on artificial intelligence for years. However, similar practices are disseminated in industries that are not generally associated with digital activities. An example is one of the largest US banks - Goldman Sachs. Employees of the investment department of this investment bank accepting orders for buyout of corporate bonds can now immediately view proposals for bonds with similar risk profiles and offer them to the client without delay. The aforementioned consierge system at Caesars uses artificial intelligence to determine the potential daily expenses of hotel clients and select those who will receive private calls with individually tailored offers. There are only a few of hundreds of similar examples on the market.

This is just the beginning.

Although artificial intelligence has not yet become the answer to all of our customer service challenges, technologies based on the machine learning in this sector are developing at a dizzying pace. It may take some time, but artificial intelligence will undoubtedly transform the relationship between business and consumer.

What's more, customer service built on artificial intelligence technologies provides a level of reliability that a person will never be able to achieve. Chatbots (appropriately programmed) are free from prejudices that may adversely affect customer relationships. They are not late for work, they do not get upset during difficult conversations and do not argue with the client. All this means that artificial intelligence measurably improves the relations between the consumer and the company, and this translates into the real financial profit of the company. This is confirmed by research conducted by Zendesk. According to the company's last report, 42% of B2C customers after satisfactory help from the customer service department bought more products of a given brand, and 52% stopped buying products of a given company recognizing customer service of poor quality. It is a matter of time when systems based on artificial intelligence become a rule in customer service, not an interesting exception.