Hi Amber,
The Queue performance gives you the following metrics: sentiment instances, positive sentiment instances, negative sentiment instances and avg sentiment.
We also have a custom ETL solution (Slidy Data Mart) on AppFoundry that extracts the following tables and aggregate views:
Queue transcript: speech analytics metrics grouped by queue as well as per division and media type for daily, weekly, monthly and yearly aggregate containing:
- CustomerSentimentMax
- CustomerSentimentMin
- CustomerSentimentCountNegative
- CustomerSentimentCountPositive
- CustomerSentimentCount
- Avg_SentimentScore
User transcript: speech analytics metrics grouped by user as well as per division and media type for daily, weekly, monthly and yearly aggregate containing:
- CustomerSentimentMax
- CustomerSentimentMin
- CustomerSentimentCountNegative
- CustomerSentimentCountPositive
- CustomerSentimentCount
- Avg_SentimentScore
Having queue level aggregates including identified topics and sentiment scores should give you pretty much what GC has to offer today. You could also build a custom report to try to find a relationship between the sentiment score and wrap up code (if used).
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Hichem Agrebi
hichem.agrebi@cc-expertise.comCC-Expertise Ltd
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