Customer care leaders are in the heart of a perfect storm.
After a couple of tough years, much of which had consumers conducting their shopping online, customers are tired and frustrated, service cases are up, agents are disengaged, attrition is rampant, and employees are hard to replace.
Even more than that, customer expectations are at an all-time high, inflation is a concern, and many digital solutions aren’t delivering on their promises.
Customers have options. Brands that don’t deliver risk losing those customers quickly and without warning.
A recent study found that it’s becoming more difficult to carry a customer through the complete buying process, with 96% of respondents saying that a negative customer service experience is enough to determine whether or not they would buy from that company again.
Yet it’s not hopeless. Companies can increase brand loyalty by balancing human touch from knowledgeable agents with digital self-service for a more personalized customer journey. This balance can be achieved using real-time customer insights that will improve agent job performance, customer satisfaction, employee productivity, and increase revenues.
Brands Must Adapt to Dividing Generational Behaviors
Today, the customer “one and done” mentality is peaking, with 12% reporting they would drop a brand after only ONE negative service experience.
In retail, for example, consumers have a variety of options at their fingertips and are equally quick to choose alternatives when they tire of leaping through problem-solving hoops with a brand.
Customers will ghost your brand without notice...
Generational preferences also have an impact on consumer behavior. With the evolution of eCommerce and an overwhelming number of resources available on retailers’ websites, 40% of Gen Z customers reported that if they can’t resolve an issue on their own, then they will abandon the brand.
Gen Z data has to be taken very seriously. At nearly a quarter of the current U.S. population, the preferences of this rising consumer demographic are pulling retailer reactions in new directions. Moreover, Gen Z customers have—and exercise—the power to effectively influence other customers’ buying and loyalty through social media.
On the flip side, while this group typically prefers self-service, some other demographics still prefer live human interaction when trying to solve a problem. Research shows that more than 52% of Baby Boomers have said they will drop a brand if they can’t speak to a person or representative.
This data underscores the need to balance human and computer-based service options and, more importantly, to have them work in sync.
Meeting the needs of all requires time and attention, leading to potential overhead increase. But what about macro-environmental factors?
Economic Pressures Mean Every Dollar Counts
Today’s tough economic environment is putting increased pressure on profits, meaning every moment spent digitally has a huge impact on conversions.
Customers will ghost your brand without notice — no angry emails, poor survey responses, or negative online reviews.
In fact, 46% of customers surveyed rarely or never complain about bad experiences, an increase of 2% over last year. Research indicates that in the U.S. alone, $62 billion is lost each year due to poor customer service.
Personalization and Consistency Are Key to Customer Retention
So how can companies identify, anticipate, and respond to potential friction points for consumers?
Step One is understanding that no two people are the same. We need to start thinking about people vs personas.
Personalization is the key to accomplishing this. According to a 2020 McKinsey study, offering a personalized customer experience (CX) is one of the greatest challenges that retailers face.
That said, a CX done well can differentiate a business from its competitors and improve customer satisfaction.
Whereas before a company could stand out through promotion and pricing, that strategy can be easily duplicated by competitors.
In this vast market of retailers, top retailers like Amazon have raised the stakes, making elements like personalized shopping recommendations and responsive customer support not only a great differentiator, but a basic expectation of customers.
Across the demographics surveyed, to have the best purchasing experience, customers expect the service and support agents they interact with to be consistent, accurate, and fast. As many as 22% of customers would abandon a brand after getting conflicting information from customer service and support agents.
On the flip side, exceptional customer service builds loyalty and long-term customer value. Tools that can predict what a customer or service agent is looking for and present the item or information seamlessly are the key to creating a standout service experience.
Which brings us to Step Two of adopting artificial intelligence (AI) technology. AI has the ability to use past user behavior to identify like-minded groups and group characteristics.
Through creating a customer profile, the AI will tailor search results to best meet the expectations of new users and customers. This technology helps organizations provide personalized experiences for both customers and support for agents.
Search solutions powered by tools such as AI search and content personalization engines offer recommendations based on past interactions from other users, ensuring that customers and support agents alike will be able to find more relevant information, tied to their specific requests.
It’s important to recognize that, despite investments in call deflection, customer insights, and knowledge management, agents are still struggling to find the right information at the right moment.
According to our Service Relevance Report, 41% of the information that the average person working in customer support received at work every day is irrelevant to their job role — a 65% leap over last year’s findings.
No brand can account for every customer touchpoint 24/7 — at least not without the support of technology.
By leveraging AI-powered tools, brands don’t just better understand their customers’ needs. They can also deliver relevant content to resolve support issues quickly and efficiently, whether through self- service or contact center channels.
AI also powers machine learning. When incorporated into customer support strategies, machine learning enables customers to help themselves, significantly increasing customer success rates, as well as reducing the amount of time that customers need to take to find the answers and resources they need.
And for customers that require an agent to help them, machine learning also helps employees find what they need to provide rapid support.
Further, the information gathered through AI-search tools provides companies with the metrics necessary to keep information on the website updated, show the popularity among the website offerings, and take the guesswork out of addressing customer needs.
More than ever before, customer care is the key to increasing revenue and sustaining business. AI-driven personalization applications can help you unlock the door.