How to Predict and Prevent Customer Cancellations
Service organizations are constantly refining everything from process, to tools, to routing to make their technicians more efficient and productive. Of all the factors in a busy field service professional’s day that a business can control, the customer is not one of them.
Last-minute cancellations and no-shows are costly and frustrating, but they’re often an understandable response to overly broad appointment windows or general lack of communication and visibility from the service supplier side. The good news is that this problem has a solution. With the right technology and historical customer data, missed appointments can be predicted—and prevented before they happen.
What happens when a customer cancels?
Though a field service tech’s day is scheduled before the day of service, it doesn’t usually stay that way due to emergencies and cancellations. It’s best if the tech knows about the schedule changes sooner rather than later, so they can adapt accordingly.
But sometimes customer cancellations happen last minute. A customer might cancel as the tech is on route to the job site, or prove a no-show when the tech knocks on their door. Not only is this a waste of fuel and time, but it could impact the tech’s next service visit. If the tech hadn’t gone to the no-show, he or she could have taken a more efficient route to the next customer’s house. What would have been a short ride from home base to the customer’s house might now be miles out of the way, and the tech could be late.
Problems on the service provider’s end
Cancellations are bound to happen—things come up unexpectedly, plans change, and sometimes the customer forgets about the appointment. But oftentimes the service provider could have avoided the no-show with better preparation. Let’s dig deeper into common reasons for no-shows.
Long appointment windows
Most people don’t like waiting, especially when it they have a problem that needs to be fixed. Your customers may have taken off work, or cancelled plans so they could be home when the tech arrives. They might have errands to run, but feel glued to their homes for the length of the appointment window.
When you give long appointment windows, and no indication of when the tech will arrive, customers might get tired of waiting around. They might find that they have too much to do and can’t afford wasting so much time waiting, so they cancel.
Lack of communication and visibility
Sometimes the tech runs late because of heavy traffic or leaving the previous job site later than expected. If the customer doesn’t know this, and the appointment window has already passed, they’re likely to cancel. The tech could be just five or ten minutes away, but if the customer doesn’t know, they might assume he or she is not coming. If they had some visibility into the tech’s location, or the ability to communicate with them, they might not be so quick to cancel.
How to predict and prevent no-shows
While customer cancellations will occasionally happen, there are ways to minimize them. With the right technology and data, it’s possible to predict no-shows or prepare for them in case they pop up.
By collecting data about your customer’s service history and demographics, it’s possible to predict the likelihood of a no-show. You can use the data to determine who’s more likely to cancel and then prioritize jobs with lower cancellation rates. It helps if you have artificial intelligence on your side to automate scheduling based on this data. It can determine much more accurately than a human who’s more likely to cancel and adjust the schedule accordingly.
Take a page out of Uber and Amazon’s books and allow your customers to map the tech’s progress. The tech can report when he or she is on route and your customers can track their location via a map on their mobile device. You could also send a voice or text notification to customers when their tech is on the way. This allows customers flexibility to do other things as they anticipate the tech’s arrival. They’ll know exactly where the tech is and when to expect them.
The tech and customer should be able to easily communicate with one another, no matter where the tech is. They should be able to easily call, text, or use a mobile app to communicate with each other at all times. If the tech’s running late, he or she could let the customer know, and the customer could ask the tech about the ETA.
You could also send reminder notifications throughout the service appointment to avoid last minute cancellations. For instance, you could send a reminder the night before, and give them an option to cancel straight from their phones if they need to.
Field service can seem unpredictable at times, but that doesn’t mean there’s nothing you can do about it. By collecting the right data and using the right technology, you can create an efficient schedule with limited cancellations. By taking these precautions to optimize your output, you’re showing your customers you value their time just as much as your own.
Categories:Artificial Intelligence, Big Data & Analytics, Customer Satisfaction, Scheduling & Dispatch Management, Workforce Management Trends