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How Machine Learning Can Help Elevate Your Customer Service

Artificial intelligence (AI) used to be the stuff of science fiction, as writers and filmmakers alike tried to imagine how such advancements might change our world. Today, AI is not only largely...

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Artificial intelligence (AI) used to be the stuff of science fiction, as writers and filmmakers alike tried to imagine how such advancements might change our world. Today, AI is not only largely responsible for how we live, work, and play in our daily lives but also for how businesses conduct their operations. Algorithms address issues in everything from production to distribution to sales and customer service. When correctly deployed, they can automate functions that previously required considerable manhours to perform, freeing up time for employees to focus on other endeavors and improving a given company’s efficiency by a considerable amount. Similarly, AI tools can analyze trends and habits, providing not only a more accurate picture of a given business’s market, but a road map to take advantage of opportunities and address shortcomings before they become a problem. 

Customer service, in particular, is being revolutionized by the advent of AI. It’s a necessary component of every business, and yet it can often be quite time-consuming. Proper customer service is a very old problem, felt most keenly by industries that rely heavily on it to succeed. That includes things like eCommerce, which needs to carefully track countless pieces of information in order to function. Healthcare, too, relies on good customer service to ensure that patients and customers alike receive the information they receive. Other industries such as hospitality, use customer service as such an integral part of their business that separating the two becomes impossible. 

AI can provide an excellent solution to all manner of customer service issues, and yet despite the many positive benefits, many companies are still reluctant to upgrade their processes to include AI. Technology is here to stay, and indeed is advancing in leaps and bounds. Companies that adopt it will have an advantage over those that don’t want to utilize what AI can offer. The more you understand what it is and how it works, the clearer its advantages become.

AI and Machine Learning in Customer Service 

Every company needs a healthy customer service division, to ensure that customers are happy and that the business is responding to their needs. Good customer service builds loyalty, which improves the business’s reputation as well as ensures a reliable financial base. Poor customer service, on the other hand, can prove disastrous. Accordingly, many companies adopt a customer-first culture—prioritizing customer service—in order to reap the benefits. AI and machine learning are invaluable tools for that. Indeed, a recent survey by HubSpot showed that 79% of customer service professionals say AI/automation tools are important to their overall strategy. 

In order to better understand how AI works in the context of customer service, it’s important to differentiate between machine learning and deep learning. Both concepts are a key part of making AI work for you, but each one plays a distinctive part in the process. 

Machine learning is defined as the ability of a given system to streamline and improve without additional programming. Previously, such improvements would require new coding to be written to accommodate the new parameters. By analyzing data and trends, an AI can be programmed to make corrections automatically, without the additional human effort required. 

Deep learning is a subset of machine learning, which applies to the “fuzzy” logic that human brains often use. That allows the AI tool to make reasonable assumptions in logic that other types of machine learning wouldn’t. For example, a voice recognition program on an automated customer service line could infer the numbers that the caller is saying even if their voice isn’t clear, by inferring connections between similar sounds. Deep learning requires more raw data than other kinds of machine learning, and has a longer learning curve in most cases, but tends to be much more accurate and effective in return. 

When it comes to AI customer service, machine learning often means deep learning, which is able to better address issues like the example above. The two can be often conflated, and for the purposes of this article typically mean the same thing, but it’s important to note the distinction. 

Leveraging Machine Learning 

Regardless of the precise type of machine learning, the key question for businesses is how they can leverage it to make their operations more efficient. This is particularly true for customer service, for which it is well-suited, but requires a certain finesse to properly implement. The more a given company understands how it works, the more the benefits become apparent. 

In the most general terms, proper leverage of machine learning entails streamlining processes: allowing your workers to accomplish given tasks in less time and with greater accuracy. More specifically, it can address the following issues: 

Automation

Anything that a machine can accomplish instead of a human being will save that human being time to use on other things. For instance, a program that automatically alerts customers to sales or discounts via text or email prevents a human from having to send those notices out individually. Automation has been used for decades in production and shipping, but when it comes to customer service, it can enhance the process considerably. Customers are routed to the place they need to be more quickly and spend much less time waiting on the phone: improving customer satisfaction accordingly. Automation also makes client authentication and security easier as well, allowing customers to make purchases and get the information they need without delay. 

Scalability 

As businesses succeed, they expand their operations, which in turn creates a greater demand for customer service and an enhanced need to make it as smooth and effective as possible. Machine learning algorithms are scalable, meaning they can be adjusted to take on more expansive duties very easily. It also means it can work for smaller businesses as well as larger ones, which can be a boon to smaller companies where employees must sometimes take on multiple jobs. Implementing a customer service AI will give them more time to focus on those matters while expanding to match your company’s needs moving forward. 

Problem-Solving 

One of the key features of machine learning is the algorithms designed to analyze data and make adjustments based on certain factors. Not only does that permit it to learn and adapt to new conditions, but it can be an excellent source of problem-solving in and of itself. Not only can it point out potential issues to your customer service department, but it can also often make adjustments to correct them automatically: sparing your workforce the trouble. Best of all, when properly implemented, such problem-solving can become an ongoing affair: helping your team anticipate and resolve issues well into the future. 

Personalization 

Few things are more important to successful customer service than personalization: the ability to meet an individual customer’s needs regardless of what they are. Personalization demonstrates the company’s concern for the customer and their business, as well as ensuring that any problems they may have are dealt with swiftly. It also allows the AI to analyze customers’ past interactions and respond accordingly. As a result, it can guide customers to new products they might like, respond more

swiftly to their requests, and reach them in the right way to keep them engaged. That, in turn, helps customers feel heard and can increase both sales and overall loyalty as a result. 

Applications of Machine Learning 

With the leverage that machine learning can provide, the question becomes how best to apply them. One of the big benefits of machine learning is that it has numerous practical applications, which you can use to suit the specific needs of your customer service department. Integrating them with your particular process will create a marked uptick in efficiency. That can include, but is not limited to, the following: 

Chatbots and Virtual Assistants 

Virtual assistants such as Alexa and Cortana have become an accepted part of mainstream consumer culture. Customer service departments often make use of similar programs such as chatbots, which answer questions for customers in lieu of a real person. Chatbots are useful because they allow people to get answers to commonly asked questions without causing a strain on your employees’ work hours.

But they can also be a source of frustration when they provide incorrect information or don’t appear to be responding to the customers’ needs. AI machine learning can improve the effectiveness of chatbots and other virtual assistants: ensuring that customers get the details they need and freeing up time for human customer service agents. 

Email Verification Tools 

Email verification is a way of ensuring that your customer contact info is up to date and that invalid or outdated email addresses are purged from the system. The benefits are considerable. Spam and undelivered email can build up, reducing the data storage capacity of your system and even opening the door for malware. Verified email also ensures that your messages are getting to actual customers— either real or potential—instead of an empty hard drive somewhere. The time cost of performing such duties manually is considerable, but properly implemented machine learning can make it a snap. 

Behavioral Analysis Tools 

Behavior analysis tools are used to get an improved understanding of customers’ thought processes. That allows the customer service department to better anticipate customer needs, as well as determine things like which products they’re looking at the most and how much time they spend on a given web page. That makes them invaluable ways to pinpoint what works and what doesn’t in your operation, as well as predict sales trends and point out areas that could use improvement. Best of all, they can be tailored to match the specific needs of your business, ensuring that they work as you require them to. 

Human-Agent Support 

In one way or another, every form of machine learning is intended to provide human agent support. Every task it can perform frees up time for a customer service agent or another employee to perform a different task. But proper human agent support goes beyond that by ensuring that flesh-and-blood humans stay in the loop. That allows them to better “train” chatbots and other tools to respond more effectively, as well as moderate content and make adjustments for those times when an AI tool isn’t performing as it should. The best tools facilitate this kind of oversight, which ensures that you and your team can control the output as needed and keep the system doing what you need it to no matter what.

How AI Is Improving CX in 2024 — Comprehensive Stats

How AI will improve the Customer Experience in 2024

Improve Overall Operational Performance with AI and Machine Learning 

The overall intent of AI and machine learning is to streamline your business’s operations: saving time by handling various tasks without an attendant loss in efficiency. In fact, the potential to improve overall operational efficiency in any business, regardless of circumstances, is rapidly transforming the way business itself is done. And the effect goes far beyond customer service. The flexibility and effectiveness provided by AI tools can give businesses a leg up on their competition. Conversely, companies that don’t upgrade to machine learning run a significant risk of being left behind, as their competitors are able to respond to customer needs more swiftly and shift to meet new challenges more readily. 

Helpware provides AI outsourcing services to help transform your business. Our services include: 

  • Data gathering, digitization, and tagging services: helping you identify the information you need to understand your business’s status. 
  • Image processing to enhance object identification, facial recognition, and text analysis. 
  • Video annotation, lets you categorize videos and images according to your specific needs. 
  • Natural language processing enhances the AI’s understanding of natural language to better facilitate customer service. That in turn drives outcome-based learning, helping your AI tools adjust and improve to better meet your company’s needs. 

Our products and services allow you to take full advantage of machine learning’s potential, improving your bottom line and streamlining your entire operation in the process. With it, you and your business will be ready to meet whatever challenges the future may hold. Contact our team to set up a consultation and let us demonstrate what Helpware can do for you!

contact us today!

 

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