Personalized customer service, and a personalized customer experience, means that a business 1) knows its customers and their needs, and 2) is willing and able to provide them as efficiently as possible. This is sometimes called personalization at scale: where software solutions help provide the context necessary for assisting customers in need or pointing them efficiently to what they want.
Landing new customers is a hell of a lot of work for B2B (business-to-business) software companies. Even the easy deals require extensive brand awareness efforts, targeted marketing, testimonials, sales conversations, proposals, and so much more. If there’s so much effort put in to acquiring a customer, then why do so many businesses stop caring once the deal is signed?
Machine learning in customer service is used to provide a higher level of convenience for customers and efficiency for support agents. Support-focused tools enabled with machine learning are growing in popularity thanks to their increasing ease-of-use and successful applications across a variety of industries. Gartner predicts that by 2021, 15 percent of customer service interactions will be handled completely by artificial intelligence.
An active user community within a help center is a great way for users to connect with one another, share ideas, and get answers to questions. Communities like these are helpful for companies scaling their support operations, because they allow users to get help from the people who most deeply understand their needs—their peers. Here’s how the Zendesk Community works and why it’s valuable in improving and enhancing the customer experience.
Consider all the different ways humans have come to rely on machines to expand their abilities. From calculators to cell phones, industrialization to robotics, humans have been able to achieve more than they ever have before, due to adopting machines. Machine learning is the next frontier in using machines to work more efficiently. And it’s particularly helpful in optimizing customer support. What is machine learning?
Social media is growing in popularity as a support channel. Customers love it because it allows them to get help right where they’re already spending time, and all companies should love it because it’s an excellent way to gain insights about your customers and cultivate brand loyalty. Paying attention to your customers on social media, also known as “social listening”, allows you to do a few key things that can help build lasting relationships with your customers.
Most customer service systems keep customer data siloed within each channel, i.e., in chat, phone, or email. A customer’s information and history with your company could be locked up in their chat history, but now that same customer is trying to solve their problem over the phone.
Change management might be needed for all sorts of reasons, such as an implementation of a new technology, transition to a new strategy, or an organizational change. Without a change management process to ensure success, all kinds of disruptions can occur, slowing down productivity and eating away at resources. Change management refers to the process, tools, and techniques used to manage the human side of change to achieve the required or desired business outcome.
What if there was one customer support channel that helped cut down the number of support tickets and delivered faster customer service, without relying on customer support staff? It exists — and it’s entirely powered by a network of users who volunteer their time and knowledge to help other users, building what’s known as a customer community.
Creating a solid business case for customer service initiatives has been difficult in the past. There’s still a mindset in the workplace that customer service is a “necessary cost” and that’s it. You need customers to have a business, and they require customer service to stick around. That’s the way the relationship has been viewed for decades. But, over the last ten years, the dynamic has changed. Why?
