Global software company enlists Kalles Group to reverse downward customer service satisfaction trends
The cloud computing operation of a global software company began receiving puzzling customer complaints about their customer service. As company leaders began diving into how to solve the problem, they realized that they had no way to accurately anticipate upcoming customer service demand, which was impacting how their customer service team was able to perform. Kalles Group tackled the problem head on, developing a data-based planning process to accurately allocate customer service resources. After implementation, customer service demands were successfully met within 5% accuracy.
Noticing a troubling downward trend in customer service satisfaction, the client realized that they couldn’t improve their performance without data about how much (and what type) of customer service would be needed before it was needed. The negative customer satisfaction scores were more than just a frustrating shift—they were creating a negative reputation for the client and putting the entire brand at stake. The client sought expertise from Kalles Group to determine a way to accurately plan and distribute customer service resources and reverse the negative customer satisfaction trend.
First, Kalles Group researched the current system of customer service resource allocation. It seemed that users of the client’s cloud computing software would create new features, but only provide the customer services team a limited amount of funding to support the new features. The client lacked quantification to determine the amount of funding that would be sufficient to support these new features and releases.
Historically, product teams had provided sufficient budget for resourcing customer service. But over time, as those budgets began to dwindle, no connection had been drawn between the reduction in budgets and the decline in customer service satisfaction. Kalles Group brought this to the attention of the client and began developing a way to quantify the resources needed for successful feature launches.
Presenting concrete, data-based forecasting and allocation planning, Kalles Group provided the client with a clear picture of the customer service resources required to improve customer satisfaction.
Kalles Group first analyzed data to determine optimal customer service resourcing, assessing patterns around the number of licenses and users in the system compared to the number of tickets, as well as historical comparisons of customer service performance for previous feature releases. With this data, Kalles Group developed a forecast model of the customer service resources needed for fully supported, successful launches.
Presenting concrete, data-based forecasting and allocation planning, Kalles Group provided the client with a clear picture of the customer service resources required to improve customer satisfaction. The client increased headcount by 500 people, and Q1 customer service performance reflected that the additional headcount was utilized within 5% accuracy. The client was once again successfully meeting customer service needs, and the client’s reputation began to rapidly rebound.