Scorecard Breakdown

Before we look at the published Call Scoring Power BI app, let’s look at an example of the kind of scorecard a client may be using currently.

In this example, we can see some highlighted examples of subjective questions which if asked to a hundred different people, would give a hundred different responses.

It would be difficult to answer these questions with speech analytics as well, but we can do our best to break down subjective questions into smaller elements which can be measured objectively.

As opposed to the subjective approach, speech analytics takes the objective approach; each of the questions here is tied to a phrase library and the call either does or does not contain phrases from it.

Start Score indicates which direction scoring occurs. For example, the starting score for an agent is 0 until they identify themselves, at which point they earn 100 points for that question. Oppositely, an agent has 100 points until they use excessive filler words, at which point they lose all points for that question.

Minimum hits is the necessary number of detected phrases within a leaf-level category before the score is affected positively/negatively.

Red flag indicates whether the category is a high priority concern if detected. As seen here, when customers have negative feedback the call will be flagged for priority review.

The scorecard lists the questions which relate to the Word Bench leaf level categories; there are a total of 34 questions across four main categories.

Weights for each question are listed in the far- right column. Note the questions in the Call Scoring app are universal, not specific to any industry.

Now it’s time to open the published Call Scoring app and discover some insights!