Swift, Targeted, Collaborative: 4 Ways to Use Data to Elevate Customer Service
The past year has brought considerable focus on how COVID-19 contact and travel restrictions have strained industrial customer service. But as the pandemic starts to subside, manufacturers serving industrial customers are facing a number of other customer-service challenges. In this article, we look at four ways these companies can improve their customer service in the long run.
1. Examine and optimize the process
Customer service in the industry sector demands, above all, quick help in the event of a problem. The average cost of unplanned downtime across all businesses is $260,000 per hour, according to Aberdeen Research. In the auto industry, downtime costs an average of $22,000 per minute. Therefore, minimizing plant downtime and associated production losses are of paramount importance.
To ensure a quick response time, customer-service technicians must be able to use available resources efficiently and apply them in the best way possible. This requires critical examination of current processes, on a regular basis, to help determine the fastest way for service employees to get the information they need about the customer. Employees should be able to easily access guidelines around these processes, as well as a data pool with problems and the appropriate solutions.
All service cases that have already been processed as well as their solutions can be stored in the data pool, enabling service staff to search for solutions by entering short keywords without wasting time manually trying to find a similar service case. In addition, common questions can be answered with the help of a chatbot or online FAQ, relieving some of the burden on customer service so they can focus on solving more difficult cases.
2. Streamline multi-channel inquiries
Service employees receive inquiries in a multitude of ways—phone/text, email, chatbots, self-service portals and online forms. In order to categorize and provide assistance as quickly as possible, it may be helpful to bundle all the different channels into one intelligent system. With a multi-channel inquiry system that prioritizes requests through intelligent programming, service technicians can address them according to urgency, regardless of communication method. The customer relationship management system itself can sort out whether a personal response is necessary or if the customer can be helped through an automated response—and have the relevant data ready so the service department has all the information it needs to solve the problem.
3. Maximize the rapid availability of data
Data is more available than ever, and data about machine performance is no exception. Today, service technicians typically have error logs or other data about the performance of a machine at their disposal, which can immediately provide key insights into a problem.
Using data transmitted for predictive maintenance, many customer service requests can be avoided. For example, if a system reports the wear of a component at regular intervals, the service department is prepared and can react before the component fails.
Smart glasses provide an additional way to use data to extend customer service, allowing the customer to precisely show the service employees the problem and the employee to guide the customer in correcting errors and making repairs. The technician does not have to travel to the site, reducing costs, and problem-solving can start immediately.
4. Facilitate collaboration with customers
Reliable help from service technicians increases customer loyalty enormously and makes a significant difference in the purchasing decision. With trust built over time, customers will begin to see service technicians as partners in a collaborative relationship rather than mere contact people.
Once a good bond has been established, the challenge is to keep it. Many companies have not developed a method for tracking customer satisfaction and are missing opportunities to identify areas for improvement. Online surveys and feedback forms, with ample room for customer comment, can bring valuable insight. Simply collecting data is not enough; information must be analyzed in order to adapt and improve services.
Nils Arnold is co-founder and CEO of ADTANCE, an international after-sales service technology platform provider for industrial and mechanical engineering organizations as well as manufacturers in the automotive, chemical, oil and gas industries.
