Background
UK wide contact centre handling thousands of calls a day. They had adequate staff levels but needed to accurately allocate and plan resources based upon call data. There was also a significant number of customers calling incorrect numbers and routed to the wrong department.

The Challenge
Customer Service resource levels driven by call volumes. Requirement for insights about patterns in demand created by time of day, channel, type of enquiry, prevailing sentiment expressed, length of call, and the need for further assistance from elsewhere in the business.

The Solution

• Call characteristics were created and call patterns analysed to enable correct identification of the client’s request. Identification of true call demand across the business. Enabling accurate Customer Services Agent resourcing and a review of the current client communication.
• Historical transactions and call volumes dimensioned by features such as channel, time of day, proximity to events such as product updates, created accurate data feeds to the Workforce management system.
• A prediction algorithm was created using historical patterns by category and features, to help predict the number of Customer Service Agents required and the skills and experience they need to possess. 
• Enhanced data source enabled instant multi-dimensional ‘slice and dice’ analysis.