Customer service is a business mantra as old as time, but it’s relevant today more than ever. Businesses that know their customers well enough and cater to their lifestyles and needs are the ones that succeed today. Increasingly, businesses are finding ways to use artificial intelligence (AI) to learn more about their customers and provide them with the support they need.

Almost every aspect of the customer experience can be enhanced by AI when it’s applied correctly, from data collection to speech recognition to message response times. The Forbes Business Council presents 15 expert insights on how organizations can improve customer service using artificial intelligence.

Solving the most common questions of users

The most frequently asked questions by users have been answered by AI chatbots for us and for our clients. In addition to improving the user experience, we are able to reduce costs for the organization by solving over 50% of recurring questions from the outset. – Nate Nead,

Identifying customer behavior patterns

By learning patterns of customer behavior (like credit card purchases, retail spending or travel), AI can then be used to forecast the customer’s behavior. Based on the time and date of previous activities, these patterns can be used to intelligently offer the most likely service options or information to the customer when they contact the organization. – Janine Bensouda, Bensouda Consulting

Response times can be sped up by 3

I am an advisor to a SaaS company that leverages AI to speed up customer support agents’ response times. Being an AI company as well, we see a lot of value in the customer service use case. By identifying the customer’s needs through AI and displaying the right information to agents, they provide the best-in-class customer service. SF is also great. – Gaspard de Lacroix, Skypher

The use of natural language understanding

With the help of natural language understanding (NLU), organizations can utilize AI to better understand customer service calls, chats and emails. By analyzing real-time customer service calls, chats, and emails, they can gain a deeper understanding of the customer’s frustration, the need for escalation, and a faster resolution of problems. – Robin, KodeKloud.

Predicting trends, sentiments, and events

AI-enabled predictive anticipation of trends, sentiment and key events of interest is possible thanks to the huge volumes of public data produced globally every second. As a result, powerful new opportunities are unlocked for proactively mitigating malicious digital threats to your brand, customers, or business, an important but often overlooked component of customer experience. – Alejandro Romero, Constella Intelligence

Enhancing the interaction between humans

A tech company has successfully developed a cutting-edge recommendation system aimed at enhancing customer interactions by proactively suggesting agents with the next steps to take. This system leverages various data sources, including ticket and remediation history, interactions, and more, which are stored in a data lake. Additionally, multiple NLP pipelines are utilized to process the data effectively. The system also incorporates a business graph, enabling comprehensive analysis and insights. As a result of implementing this solution, the company has witnessed notable improvements in NPS ratings and a reduction in resolution times. This achievement was accomplished by Pritam Kanti Paul and his team at BRIDGEi2i Analytics Solutions.

Measurement of customer wait times

In the service industry, for example, restaurants, where wait times (or drive-thrus) have a huge impact on revenue, artificial intelligence can now be used to measure customer wait times. Poor customer service has traditionally been hard to track scalably. With computer vision AI, you can collect actionable insights on each interaction and use them to perfect your service. – Alex Popper, Hellometer

Data Capture: Capturing large amounts of data

In healthcare, human interaction is crucial to providing patient care, whereas AI is most suited to serve physicians. Organizations need to be clear about who AI serves. A common complaint is how much data is required to meet quality metrics and risk codes. AI can capture data from workflows with its mining and recognition capabilities, giving physicians more time to provide patient care. – Vijay Murugappan, First Quadrant Advisory

Agent Action Suggestions

A tech company developed a recommendation system that proactively recommends agents the next steps based on ticket and remediation history, interactions, etc., to make customer interactions more effective. The solution featured a data lake for different types of data, multiple NLP pipelines, and a business graph, which resulted in improved NPS ratings and decreased resolution times. – Pritam Kanti Paul, BRIDGEi2i Analytics Solutions

Embracing speech analytics

It’s a very hot space with major cloud players (Microsoft, Amazon, Google) investing in speech analytics. Using speech analytics, management can identify which calls are more effective, which customer service reps perform best, and what training and operational changes will result in better customer service. – Sandeep Bhargava, Pravana

Enhancing customization options

Use AI to apply personalization in communications. Organizations can integrate AI-generated content into communication with clients. Would you like support with Homer Simpson’s voice? AI can handle it in a matter of seconds. The strategy can be successful for businesses that are competing in a creative niche. One example is to personalize shopping based on the features, preferences, or likeness of customers. – Dima Shvets, Reface

Communication with customers on time

MoEngage utilizes Sherpa, its proprietary AI engine, to power its customer engagement platform. Sherpa leverages customer behavioral data to determine the optimal message variant, timing, and channel for communication. In real-time, it provides brand marketers with recommendations on which customer messages to send based on the performance of different messages. Raviteja Dodda is the individual responsible for this innovative technology at MoEngage.

Identifying the root causes of problems

Insights generated by AI can assist companies in determining the root causes of problems, which can lead to better decision-making and action, such as decreasing customer attrition. In addition to better enabling measurement programs, AI can help you understand your customers’ emotional and cognitive responses in real-time. – Sindhu Kutty, Kuroshio Consulting

Integrating CRM systems

AI can be integrated with CRM systems to automate tasks seamlessly, allowing customer support representatives to save precious minutes each time they interact with customers. By combining AI with chatbots and speech-to-text capabilities, agents have access to information they need to resolve customer queries, improving customer service and resolving voice interactions in a more timely manner. – Ashish Sukhadeve, Analytics Insight

Managing a high volume of queries

A high volume of customer inquiries can be managed effectively using bots for many organizations. In spite of the fact that setting these up effectively, testing and learning accuracy can take time, I recommend embarking on the process if your team is struggling to respond to inquiries. In the long run, bots can also result in significant cost savings. – Muraly Srinarayanathas, Computek College.