All opinions in this column reflect the views of the author(s), not of the Council Journal
Machine learning can enhance business processes and deliver more fine-tuned and effective levels of customer service than ever before while allowing them to customize unique experiences for all prospects. The best news of all is that AI and machine learning are cost-effective solutions that are achievable through services like Google Cloud Services and Amazon Web Services.
Here are 10 ways in which machine learning can enhance customer service for businesses of all sizes and scopes:
1 – Offer superior personalisation
Remember the days when online personalisation basically meant inserting a person’s name into a field? Thanks to machine learning, it’s easier than ever to provide personalised experiences for customers and prospects.
Machine learning can be used to assess all past interactions with a prospect and use this valuable information to provide highly personalised experiences to customers, empowering better customer engagement and making them feel listened to and valued.
2 – Provide faster, more efficient assistance
If there’s one thing that customers universally hate, it’s being made to wait – especially when they need help. Old call systems would route customers to the wrong places and make them wait in long call lines which inevitably increased frustration and made things more stressful for them and the business. This is one of the biggest mistakes that you should avoid when it comes to customer service in general.
Fortunately, with the aid of machine learning capabilities customers can use their natural language and words to describe what they need assistance with. Natural language processing tools can help computers and AI understand, interpret, and manipulate human language, and the manner we communicate, which solves the issue more quickly and effectively.
3 – Know more about customer needs
Machine learning allows brands to get to know more about their customers from the first interaction. Instead of relying on a variety of tools to figure out what a customer needs support with, machine learning can work alongside programs that include a variety of features that are designed to help customer support teams organise daily support requests, answer common inquiries, fully understand a customer’s needs and provide faster solutions.
4 – Reach the right customer at the right place
As a business starts to gain more customers and gather more data, it allows machine-learning tools to analyse and offer ways to market and sell products and services that will inevitably attract more customers and create a competitive edge. For brick-and-mortar stores, it can also provide recommendations regarding shelf placement.
5 – Improve customer analytics
Machine learning pulls data from customers and uses it to predict behavioral patterns and various trends. While a customer is shopping on an eCommerce platform, machine learning tools can detect precisely when they need assistance, ensuring that they continue along the sales process without any complications. It can even help you identify and contact prospects before they contact you, which can help to improve sales and enhance the overall customer experience.
6 – Match people with products
Companies like NorthFace have been using machine learning for some time to provide personal shopping services to online customers before their competitors even caught on to the benefits that it provides. Via IBM Watson technology, which uses natural language processing, an e-commerce platform can provide fine-tuned recommendations based on things like where the customer will be going or how the weather will be.
7 – Identify fraud more easily
Fraud is a growing concern for all businesses, especially since an increase in digital dependence brought on by COVID-19. Machine learning can help guard against fraud and provide an extra layer of protection.
Implementing AI-powered online payment systems that conduct security practices through PCI (Payment Card Industry) compliance can aggregate information across thousands of transactions, detect fraudulent activity, and eliminate these payments before they happen, minimising the risk of ending up with compromised customer data.
8 – Consistently improve customer experiences
Machine learning allows programs to remember and learn from past experiences with customers. As a result, they are continuously fine-tuning their ability to provide customer service. Over time, algorithms are adjusted, and high-quality customer service is sustained. This is much easier and more cost-effective than retraining human employees.
9 – Understand customer intent
Through machine learning, you can detect why customers are contacting customer support before they even explain themselves.
For example, it can store a specific customer inquiry that came from a specific location call about a particular issue, so when another calls from the same location regarding the same product, the program will have a good clue as to why. In turn, it can offer solutions faster, making the process easier and more enjoyable for customers.
10 – Enjoy efficient data tagging
Big data presents many exciting opportunities for businesses. However, without tagging data continuously, making sense of it can be tricky. Machine learning is a cost-effective way to add data tags to unlabeled images and other files and re-gain good data quality, which is crucial in obtaining the desired end result.
Pre-trained deep learning programs can identify files and images and apply the appropriate tags quickly, have the ability to see patterns in the data that humans may not be familiar with, and deliver precise business insights.
From enhancing overall security to delivering highly personalised levels of service, machine learning is an indispensable tool for providing more efficient customer service across all levels.
Whether a business is online or based in a brick-and-mortar store, machine learning can help business owners everywhere market products and services more effectively, offer faster solutions to customer inquiries, and identify valuable prospects.
Because it continually learns and improves itself, machine learning can scale alongside businesses while easing the load on employees. Mundane and repetitive tasks can also be handled by machine learning, freeing up human employees to focus on more important jobs – a win-win situation for all.