How to Improve Customer Experience in Field Service with Predictive Analytics

Any downtime in business-critical systems or devices can cost an organization dearly. Customers nowadays are far more demanding in terms of both purchases and after-sales care and with highly competitive markets in every sector they now have the luxury to be selective in terms of who they do business with.

Having these challenges in mind, field service companies should be more forward-looking. Predicting trends, forecasting business performance, resource demands or even future failures may help to improve clients' satisfaction and after-sales service, and to persuade customers of partner's reliability. Predictive field service analytics features can address these issues and upgrade customer experience. How exactly?

#1 Forecasting resource demands in advance

With trend analysis, service companies are able to prepare an organization for the future with predictive field service analytics. The systems provide insightful forecasts of resources needed in particular service regions. This allows field service companies to plan staff recruitments, trainings, and to respond to the demand for services in the long term. This feature also provides the ability to improve clients' satisfaction. Predicting which personnel with given skills will be in a particular region allows businesses to avoid resource gaps that influence the customer experience.

#2 Sending technicians into the field properly prepared

Whether the first customer contact is by telephone, email or web form, predictive analytics available through field service management systems can instantly access data about a client’s service history, equipment monitoring records and other issues that may be relevant to their service or devices, and deliver it to the engineer in real time. Thanks to predictive analytics, field service personnel can arrive on site with a good idea of what the problem is, how to resolve it, and, with stock control management, the parts they need to do the job. In this way, a repair may be carried out even during the first visit – something that your clients should definitely appreciate. Thus, your engineers will be able to ensure very positive customer experience.

#3 Pro-active issue resolution

The Internet of Things (IoT) has brought to our world a high level of connectivity and a major advance in the ability to provide after-service that truly excels. By using smart devices, you can monitor the performance of your clients’ equipment constantly, and provide a solution that takes pre-emptive action in the event that an issue seems likely to arise. Device-mounted sensors that monitor weather, temperature and dust data mean that you can predict and prevent many failures and cut the costs of repairs. For your client, this means boosting the level of customer satisfaction and confidence in your company.

If you are still in any doubt about the benefits of employing predictive field service analytics, just consider these findings from a recent Aberdeen Group report. According to the report organizations that do use analytics in this way increased their profits by 18% and customer loyalty by 42%.

Those numbers are serious enough to raise the question not of whether your organization can afford to invest in predictive analytics with an FSM system, but whether you can afford not to.