Paying attention to the latest customer service trends ensures that an organization is prepared to meet changing customer expectations.
Customer loyalty is waning, spurred on by the COVID-19 pandemic, social influences and the ease of switching brands. More than ever, organizations must stay on top of changes in the customer service experience to improve customer satisfaction and meet increased customer needs.
A 2023 Gartner study found that 58% of leaders identified business growth as one of their most important goals. Customer service is a necessary component of this strategy. Good customer service can increase brand loyalty and bad customer service can hurt customer retention. Providing great customer experience is the best way to maintain an organization’s competitive advantage.
Seven new customer service trends that organizations must prioritize
Great customer service requires organizations to meet customer needs and expectations wherever they occur.
1. The increasing importance of omnichannel support
Customer engagement continues to occur across multiple channels. As such, customer success requires customer support teams to interact with customers across call centers, text, social media and email. Organizations must dedicate the appropriate resources to each channel as dictated by their customers’ preferences.
2. The move toward self-service
Organizations have built out their content libraries and knowledge bases, leading to more customers preferring self-service options to communicating with a support agent. While some customers want human interaction by a phone call or messaging, others prefer to solve the issue on their own if feasible.
3. The rise of artificial intelligence
New technologies will drive the future of customer service. The use of artificial intelligence (AI) has the potential to remake how every department in an organization operates, but the changes might be most powerful in customer support. For example, organizations are now infusing their chatbots (or bots) with generative AI to increase the success rate of interactions.
Organizations can also use machine learning to better analyze historical data around customer issues to create more valuable FAQs, improve call scripts and identify emerging issues that the organization can solve proactively. Machine learning helps create smarter workflows, so customer service representatives can better-utilize technology to solve customer issues more efficiently.
4. The use of simple automation
Many customer service tasks can and should be automated rather than require a customer to talk to a customer service agent. For example, a simple chatbot can often handle straightforward returns of a defective product. Or customers can fill out a form that asks a couple of questions and returns answers such as a price quote or a request for more information. These simple automations answer the customer’s needs while saving their time—they don’t have to call customer support and wait for a human representative.
5. The growth in messaging-based customer service
In the 2010s, customers flocked to social media to post their questions or issues and communicate with organizations’ customer service reps. The rise of messaging apps such as WhatsApp and SMS-based customer service is the next progression for consumers interested in asynchronous communication with organizations. While some customers will always prefer talking on the phone to a live agent on the customer service team, many more will text or message the support team as the preferred way to interact with that organization.
Most organizations will need to build an infrastructure that enables near real-time responses to texts and messages to meet customer expectations about response times. The use of messaging also enables organizations to find good opportunities to follow up with customers to ensure they remain satisfied with their products.
6. The desire for a personalized experience
Organizations can now track their customers, their habits and purchase history better than ever before through customer relationship management (CRM) tools. They’ve built up impressive stores of customer data over time. By using technology such as machine learning, which makes it easier and quicker to parse this data in real time, organizations can build more personalized experiences across the entire customer journey.
For example, a brand can email exclusive offers to customers based on their preferences or send them a free product or discount code on their birthday. Customer service representatives can also access information about a customer they’re helping and use that information to improve the customer relationship.
7. The need for proactive support
Organizations can no longer wait for customer feedback if they’re concerned about providing an excellent customer experience. Instead, they must invest in ways they can reach customers before an issue happens to ensure they’re satisfied with a product and are using it correctly. For example, organizations can email tutorials to their customer base to help them understand how to use their products.
Providing excellent customer service requires organizations to keep up to date on key trends so they meet customer expectations. As more organizations embrace advanced technologies such as generative AI and machine learning, those who fail to do the same will fall behind the competition.
It’s important to remember that customers have interactions with many different companies throughout their lifetimes and can easily differentiate between those that provide good customer service and those who undervalue or under-invest in it.
The majority of service professionals (60%) have said that customer expectations have increased since before the pandemic. Therefore, poor customer service is a major impediment to business growth and customer retention. CEOs understand this acutely, which is why they have identified customer service as the number one priority for incorporating generative AI investment, according to an IBV CEO Guide to Generative AI for Customer Service.
IBM has been helping enterprises apply trusted AI in this space for more than a decade, and generative AI has further potential to significantly transform customer and field service with the ability to understand complex inquiries and generate more human-like, conversational responses.
IBM Consulting® offers end-to-end consulting capabilities in experience design and service, data and AI transformation. By using IBM watsonx™, the enterprise-ready AI and data platform, and IBM watsonx™ Assistant, a market-leading conversational AI solution, we partner with you through the AI value creation process to enhance conversational AI, improve the agent experience and optimize call center operations and data.
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