Chat/calls data are commonly trained for analytics and monitoring-based use cases to gain a detailed understanding of the processes, issues, and sentiments within a conversation.
Some examples of questions you can answer for these communication types:
- How many conversations start with a customer asking us about a topic, a complaint, etc.?
- What are the top topics customers are contacting us about?
- How long does it take to resolve a conversation about a given topic?
- What is the quality of service that agents are providing for our customers?
- What is the sentiment when a certain topic is mentioned?
A chat/call thread
|Please Note: If you have sentiment analysis enabled on your chat/calls data, the differences when labelling are the same as labelling with sentiment for other communications channels (i.e. - assigning a sentiment each time you assign a label, using neutral label names, etc.). See here for more details on labelling with sentiment analysis.
Training chat/calls data is very similar to training other verbatim types, where a user would go through the Discover, Explore, Refine phases to train their model further.
The key distinctions are:
- Thread layout - With chat/calls data, verbatims between all parties in a given conversation are automatically compiled into a single thread view, but labels are still assigned to individual verbatims (i.e. - turns in the conversation).
- Uninformative verbatims - A verbatim in a chat/call can be marked as 'uninformative' if it does not add context or value to the given conversation. By marking a verbatim as uninformative, you are teaching the model that none of the labels are applicable, and therefore the model will learn that similar verbatims should not be expected to have label predictions.
- Coverage - When assessing coverage for chat/calls data, in addition to assessing the proportion of verbatims covered by informative (i.e - meaningful) label predictions, it also incorporates the proportion of verbatims that are predicted to be uninformative. For more information on how coverage is determined, click here.
Validation factor card for coverage for a chat or calls dataset