With trends like the Great Resignation and skyrocketing operational costs, many customer service departments are looking for ways to reduce their budgets without impacting support quality and working conditions for agents. Taking a thoughtful look at cost reduction is critical: A recent survey found that 80% of customers had poor customer experiences within the last year, representing $4.7 trillion dollars in lost global consumer spending. On the other hand, 60% of customers would buy more from a company that provided excellent service.
Fortunately, technology including artificial intelligence and self-service customer support can help stretch lean budgets and allow customer service teams to focus more on improving the customer experience. Here’s how.
Leverage digital self-service options
In 2021, Gartner predicted that digital self-service options would become a tremendous cost-saving opportunity for customer service departments. Basic self-service options such as chatbots or interactive voice response (IVR) systems can handle simple requests such as password resets, payment processing, responses to frequently asked questions (FAQs) and more. Beyond that, predictive analytics can help teams predict customer behavior and make the digital customer experience more seamless.
Many leading brands have used predictive models within their customer experience to proactively offer better prices or identify churn risks. For example, the Progressive Insurance Snapshot offering allows existing customers who are safe drivers to proactively get better rates for their coverage, without having to make contact with the customer service team. And FedEx uses an algorithm that can predict whether a customer may seek out a competitive offering with 60 to 90% accuracy. Offerings like these can alleviate contact volume for the customer service team and identify at-risk customers who need a higher level of service.
Offer customer support agents the right training
According to Forrester, many customers are becoming more aware of how companies treat their employees and contractors, and will leave if they hear about poor or unfair working conditions. A major part of employee retention in the contact center is offering the right training and career advancement opportunities, empowering agents to offer superior support. In fact, 86% of millennials said they’d be willing to stay in a job that offered training and development. While this step may seem like more of an upfront investment, the right training will pay dividends when it comes to both employee and customer satisfaction and retention.
To respond to this need with minimal disruption, technologies such as conversation intelligence can analyze speech or text in the contact center, and surface proactive opportunities for performance improvements based on conversations that are already happening. In addition, customer service managers and supervisors can identify positive patterns within agent conversations, and use those interactions to motivate employees to continue the good work. These insights can also be used to onboard and train new team members based on what’s happening in the field.
Use AI for multilingual translation
Multilingual support matters to global customers: 68% of customers will leave if they aren’t offered support options in their native language. Speaking a customer’s native language matters so much because it creates empathy between customers and brands, and makes customers feel more confident in selecting a product or service.
However, the costs of supporting multilingual customer service at scale can quickly add up. Hiring native speakers can get expensive fast. Not to mention, if an agent handling a low-volume language is out of the office, or if demand in a particular language surges, customer support volumes can grow to unacceptable levels.
Using human-refined AI translation technology can relieve the pressure to hire native speakers, allowing any available agent to handle customer support tickets or chats in multiple languages. This process can dramatically lower the TCO for customer service operations. For example, Tile leveraged multilingual machine translation technology from Unbabel across 29 different languages, saving 91% on the cost of international tickets. As a rapidly growing global company, Tile tapped into this technology to expand its customer service coverage in the Asia-Pacific and European markets, without having to invest in hiring native speakers.
By using the AI technologies and training strategies detailed above, customer service teams can achieve economies of scale and learn from what’s actually happening in the field. The results are not only greater efficiency, but a more effective and cohesive team dynamic that helps improve the overall customer experience.
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