Spotlight can help you focus on meaningful conversations by applying insight filters. These filters are in addition to the default and advanced filters described in the article Filtering conversations.
You can learn more in this article or by watching this overview video.
This article contains the following sections:
Understanding the Spotlight insight filters
You can use insight filters to find conversations that include the insight types listed below.
Spotlight insight filters are available in both the Conversation view and in Assignments.
Using the Outliers filter
Offering the highest learning potential, this filter enables you to find conversations that are critical to review at the click of a button.
This filter flags conversations where:
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the customer issue was more complicated
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the customer's problem could not be explained in one message
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the agent needed to ask for further information to understand the request
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there were more replies than average from the customer and agent
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the length of replies was longer than average.
Outliers let you get going with your conversation discovery without thinking about filtering what should be most useful to review. It is a one-click solution that selects 15% more interesting conversations and removes more regular conversations.
To turn on the Outliers filter
Add Outlier as a filter condition under Conversation.
This feature does not work for the conversations imported via browser extension (see Setting up and using the Zendesk QA browser extension).
Using other filters
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Churn risk
Identifies conversations where customers have explicitly mentioned that they are cancelling the subscription/product or have mentioned switching to a competitor. -
Escalation
Flags conversations where the customer asked to speak to a higher level representative such as a manager. It does not detect internal escalation processes happening outside the conversation. -
Follow up
Flags where a support representative has promised to undertake a future course of action. It does not detect the validity of the action, only if it was done or not. -
Extra mile
Identifies where a support representative provided exceptional service and the customer showed gratitude. -
Positive or Negative sentiment
Flags when a customer has expressed elements of delight or dissatisfaction. See Applying the Sentiment filter for setup instructions. -
Bot communication efficiency
Compares your bot’s conversation handling against average agents. Returns an efficiency percentage that indicates whether talking with the bot resulted in solving the issue faster and with fewer questions than talking with a human. Efficiency percentages under 20 percent aren’t returned. Filter values include better than agent’s and worse than agent’s. -
Bot repetition
Reports when the bot is stuck in a loop and repeating the same message to the customer. Filter values include detected and not detected.