Customer Expectations Demand a Modern Approach to Customer Service



A shift in customer expectations is changing customer service in every industry. Customers expect a great experience, whether they are researching a product or service, making a purchase, and especially when they have a question or problem.

According to best practice insight and technology company CEB, customer service interactions are nearly four times more likely to lead to disloyalty than loyalty. Business success now hinges on helping customers achieve their desired outcomes. Exceptional, personalized experiences, especially in customer service, are now a critical requirement.

But many organizations still use common service models that are based on decades-old operational models and legacy thinking that cannot evolve to meet customers' growing service expectations.

Customers prefer self-service (and you will too)

Research from the Technology Services Industry Association (TSIA) shows more customers prefer a self-service approach, with 65 percent of U.S. online adults saying web self-service is their preferred channel when seeking support for a product. In addition, 66 percent say they have used a self-service mobile phone application or FAQs on company websites to help themselves in the past 12 months.

Self-service is significantly more cost-effective than other service channels, both in cost per resolution and because it reduces the overall case load on contact centers. In fact, the TSIA reports that phone and email support are each at least 100 times more expensive per incident than web self-service.

The goal of an efficient self-service strategy is to cut repeatable calls to the contact center by reducing customer effort. This means making it easier for customers to get answers than to open a support case, ensuring they do not have to repeat their personal or contact information, and eliminating dead ends by providing an easy switch to assisted service.

While efficient self-service is critical to any company, it will not keep a business thriving.

Enabling customers to self-serve has important ramifications on traditional agent-assisted support. As customers self-serve for known issues, service agents must handle more challenging cases, and a knowledge base might not provide that one right answer they need. Instead, the agent must now become a highly proficient super-sleuth capable of quickly and efficiently researching from across multiple sources to access and deliver knowledgeable support.

Leading companies in the tech industry—which is often an early adopter of new ways of doing business—are facing these challenges head on by moving to a modern approach to customer service that meets customers' rising expectations and agent needs. It's called intelligent customer service.

Proactive insights for customers and service agents

Intelligent customer service helps companies deliver the personal and effortless experiences customers demand and the contextual knowledge agents need, automatically. Based on a combination of search, analytics, and machine-learning technologies, intelligent customer service provides proactive insights for customers and service agents to deliver seamless support experiences, while enabling business growth and significantly reducing support costs.

By way of example, a leading provider of customer experience solutions used this approach to reduce costs and improve customer satisfaction while increasing case deflection threefold. This organization has reduced the number of cases being routed to its call center by empowering customers to use search five times more often than creating/updating cases on its website.

Intelligent customer service features intelligent search technologies that maximize what Forrester Research has termed "cognitive search" and what Gartner refers to as "insight engines." These intelligent search technologies securely connect to an entire IT ecosystem, including all the systems and sources that contain case-resolving information, whether they are on premises or in the cloud. The technology understands what creates success based on desired outcomes, as well as dynamically generated customer and agent profiles and past issue resolutions. It then proactively delivers a unified view of the most personalized, relevant insights to contact center agents and customers so they can successfully complete the task at hand.

Measure outcomes for success

Moving more interactions to self-service has ramifications for the entire company. It is critical to understand how this revolution in service will affect not just self-service measurements, but also the very type of measurements that show if agents are successful or not. This is one particular area where companies will face the challenge of changing decades-old operational models and legacy thinking.

For example, rather than always trying to reduce average call handling time as customers self-solve the easy issues, call handling times will increase as new, unknown issues are now coming into agent-assisted support. Measuring an outcome in this respect might include measuring increased customer loyalty or customer satisfaction. In this new world, agents must become proficient in real time, as they work on new problems, for the initially expanded times to decrease from the new benchmark.

Build the case

According to the TSIA, a fully burdened, self-service case resolution costs $4 on average, while agent-assisted support costs around $510. Case deflection alone will more than pay for the transformation of customer service.

In addition, the real-time increases in agent proficiency and customer satisfaction on the toughest cases will also contribute to this new model. Measurements such as time to proficiency (for agents) and customer satisfaction support these savings.

Making customer service effortless takes effort and investment, even beyond technology. Like any transformative initiative, it's a journey. Traditional thinking, existing metrics, and outdated processes all need to be re-examined and reimagined. Start by having a clear vision and an actionable plan to improve self-service. The results, from significant cost savings to happier customers, agents, and even product engineers, make the journey rewarding operationally, financially and culturally.


Jennifer MacIntosh is vice president of customer success at Coveo.