Customer Service Case Priority (Value & Matrix Scoring)

Problem

Customer service representatives have a case queue of questions and complaints from current customers and potential prospects. These cases can be logged from customers emailing in, or messages through live chat. The customer service reps want to prioritize their cases based on the severity of the issue encountered, and so paying customers are responded to before prospects.

Solution Option 1: Value Scoring

The customer service manager creates conditions for Value Scoring, focusing on three criteria: If the account is a current customer, if it’s been multiple days since their last reply, and if a case is urgent or not. They want customers to get faster responses than prospects, so this criteria has the largest point value. They also want to give more priority to cases that have had longer wait times, in this case three days. Finally, if a case is not urgent, then it will lose points so it goes lower in the queue.

For this example, the customer service specialists opt not to include label value ranges as they want to be as precise with their rankings as possible. They are aware the highest score possible is 15 (10 + 5), so the closer a number is to 15, the more urgent it is.

They decide to name their Field Name “Case Score.”

Solution Option 2: Matrix Scoring

The customer service manager builds a matrix, setting the Object they are prioritizing to Case, the Criteria is Case Priority, and the Alternatives are the Persona Types (User or Buyer). They then rank the criteria and input values for each cell. Buyers have more priority than users, and higher priority cases get more weight.

In this case, the customer service reps opt not to include label value ranges as they want to be as precise with their rankings as possible. They are aware the highest score possible is 14 (7 * 2), so the closer a number is to 14, the more urgent it is.

They decide to name their Field Name “Case Score.”