When it comes to customer support, the entire process is built on a simple idea: when someone communicates a problem, the representative dealing with the case uses their dashboard to review, work, resolve, and close a ticket. This ticket then remains open until the issue is closed, along the way acting as a repository for information about that particular request or problem.
There are plenty of reasons why you want to keep you customers happy: Happy customers make great “brand ambassadors.” The cost of attracting a new customer is higher than retaining an existing one. Today’s social media makes it possible for an unhappy customer to do harm in the marketplace. Etc.
In a world in which anyone can order any product at any time with just the click of a mouse, the once dominant differentiators of price and product are quickly disappearing. In fact, it’s predicted that in just two years, customer experience will become the key competitive advantage for any organization, no matter the product or service.
With customer support & service at the forefront of the brand battle, it's no wonder that companies are turning to artificial intelligence (AI) for help. The customer churn caused by poor customer service is $62 billion problem, so finding ways to speed response time is no small matter.
Most customers don’t like calling customer support. It takes too long to get the answers they want, and they walk away feeling exasperated. Many organizations find themselves frustrated with their customer support experience as well. They know they need to provide a better, seamless experience for their customers, but they are challenged with information silos, an incomplete view of the customer, and a support team that has to hunt and peck to find the right information.
In earlier blogs about the value of cognitive search for life sciences companies, we’ve focused on the role it can play in accelerating drug discovery and finding new therapeutic uses for drugs that have received FDA approval. The search technologies that help achieve those goals can also make life sciences sales and marketing smarter and more effective.