Problems Solved with AI And Machine Learning in Customer Service

There are a lot of benefits of using AI technology to solve customer service problems.

11 Min Read
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The marketing profession has been fundamentally changed due to advances in artificial intelligence and big data. The market size for AI in marketing is expected to grow over 31% a year through 2028. It is growing at an even faster pace as more companies discover new benefits.

Unfortunately, there are a number of AI-driven marketing mistakes companies continue to make. One of the biggest issues is focusing entirely on outreach at the expense of customer service.

AI technology is helping solve customer service problems. However, it is only useful for companies that utilize it properly.

In order to appreciate the benefits of AI in customer service, you must recognize the most common customer service problems. When customers have a bad customer service encounter:

  • 91% of customers leave without a warning
  • 47% of customers switch brands
  • 40% of customers recommend against the business

It is obvious from the statistics that each customer, facing a bad customer service experience, does more than one step to hurt the business. Think about your bad service experience with a brand and the actions you took after that. It is easily palpable that you would be reluctant to recommend the service to your friends and family. AI technology can help address these issues.

Customer Service in a Services Business

One broad way businesses can be categorized is as product business and services business. The marketing mix for product businesses includes the product, price, promotion, and place. But for services business, additional elements in the marketing mix are people, process, and physical evidence. These three elements are prominent in delivering customer satisfaction.

All the elements of a services business are accentuated in the customer service. It is where the people and process of a business are translated to physical evidence. Thus, customer service becomes the one area that has the maximum friction between business and its consumers.

All kinds of financial businesses are services businesses. It could be a fintech business, fund management, or brokerage. All of them are services business and the maximum friction between customers and financial businesses occur in the customer service process.

Why is Customer Service Important?

A customer has to do business with a services business for a long period to recover the acquisition cost incurred. This is determined by calculating the Customer Lifetime Value (CLV) for each individual customer. This is essentially the profit the business can generate from one customer. In most modern businesses customer acquisition is a costly affair. The CLV of a customer increases the longer he conducts business with the firm.

When a customer has a bad experience, there is a very high chance that he will ditch the service. This decreases the CLV and it is possible to lose the acquisition cost that went into acquiring the customer. There is also a possibility of wider backlash from the public. With modern social media outlets, customers can share their bad experiences with customer service and garner significant attention.

On the other hand, excellent customer service delights consumers and he will not even consider alternatives. This ensures that he stays longer as a customer increasing the CLV. Also, a customer with a positive experience is also more likely to recommend the financial service to friends or family. This decreases the acquisition cost for new customers. In short, how the customer service of a firm functions can dramatically impact the profitability of the firm, either positively or negatively.

AI & ML: Problem Solver in Customer Service

Artificial intelligence and machine learning tools have advanced over the years. They can accomplish much more complex functionalities than simple computer algorithms are capable of. It is a constantly evolving area and more improvements are made possible each passing day. For example, deep learning can be used to understand speech and also respond with speech.

AI and ML can be used in customer service to tackle various problems that need a large scale. It also works as customer service functions deal with a lot of complexity. The following sections discuss some of the most common challenges and how AI can help solve the challenge.

1. Information Gap

A major challenge in customer service is the information gap of the customer service executive. This leads to inaccurate problem identification and incomplete resolution. As one can imagine one executive cannot be knowledgeable of all the systems and processes of a company. The information gap of customer service executives leaves customers dissatisfied.

A common way of bridging the information gap without AI solutions is with user forums. Take the example of 17-years-old MQL5.community, created by MetaQuotes, the developing company of MetaTrader 5. Here, the community themselves identifies the root cause of problems and figures out the solution. Such instances require very little external support from the company. But it is not applicable to all kinds of financial services companies and AI solutions will be more appropriate in most instances.

The AI Solution

Implementing AI with the knowledge base of the firm can transform the information gap experienced by the executive to information abundance. AI tools can identify the right solution from the knowledge base without the executive requiring to search through the database. Search tools with Natural Language Processing (NLP) can bring the right solution with very little query effort. AI tools can also search the knowledge database to find similar queries experienced in the past and how it was resolved.

2. Disjointed Customer Experience

There are plenty of touchpoints between customers and a financial services firm. This can range from various physical locations to a multitude of online touchpoints. Customers feel a disjointed experience when traversing the different touchpoints. It also makes the job of customer service executives as she is not aware of the customer journey of the particular customer in front of her. This makes problem resolution difficult and hence degradation in customer experience.

The AI solution

Applying AI to the various systems of the firm and stitch together the relevant information related to a customer. This helps to weave together the information of a customer across different touchpoints. With this, the complete customer journey of every customer is available to the customer service executive at the touch of a button. AI tools can also help highlight the parts of the customer journey relevant to the query at hand. This unified information leads to faster resolution and in turn better customer experience.

3. Personalization

Customer service centers and other touchpoints have standardized procedures and processes to make things simpler. This is done for maximum efficiency. But the most efficient processes are not customer-friendly. Each customer is different in some way or the other. Standardized processes and procedures cannot deliver tailored resolutions to different customers. Due to this customer delight is elusive in most customer service interactions with financial services firms.

The AI solution

AI tools have a very large scale and they can accommodate various types of processes and procedures. It has the ability to deliver a tailored experience to each customer. The advantage of AI tools is that tailored experiences can be delivered without sacrificing efficiency. This AI is able to deliver the trifecta of scale, personalization, and efficiency at a very low cost.

4. Customer Service Volume

When a large number of customers have to be serviced, the infrastructure and the human resources required to serve them increase proportionally. Adding more physical locations and more customer service representatives is a cost-prohibitive. The firm faces a challenge between two choices. Increase the infrastructure at a higher cost or use existing infrastructure delivering poor customer service.

The AI solution

AI tools are easily scalable to a large number of users without needing additional infrastructure. A lot of customer service functions can also be automate with AI. More users can be served just by spinning up more cloud computing servers. This incurs a very minimal cost of operations compared to adding physical infrastructure and customer service executives. This helps to deliver the same level of service without huge capital expenditure. Another advantage is that scaling down operations is also much easier. The unwanted server capacity needs to be shut down to scale down. There is no problem faced with reducing physical infrastructure or downsizing employees.

Final Thoughts

Customer service is a key factor in retaining customers which in turn is needed for a higher return on invested capital for firms. But delivering a great customer service experience is quite difficult with physical infrastructure and customer service executives. There are limitations to what can be achieved by customer care executives. AI tools have the ability to transcend the customer service of businesses. They are capable of delivering scale, personalization, quality, unified experience, and information abundance. AI is capable of delivering all these resulting in customer delight at a significantly lower cost.

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