Phrases/Terms
Your Turn |
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Enter “frustrated” and “confused”, they will appear in the “Search Terms” section. |
Further to the right, there is an option to select between AND / OR.
AND: Results must contain all entered search terms.
OR: Results must contain at least one of the entered terms.
This defaults to AND, so we can leave on that.
2. The Search Terms “frustrated” and “confused” are in fact located in the call as indicated by the preview of the transcript. However, the terms we used limited the search too much due to variations of these terms like “confusing” or “frustration” not being included.
You could include all the variations of the terms manually, or you could use a special character to be more inclusive.
3. Changing the terms to “frustr*” and “confus*” has expanded the results to 6 calls by making use of the wildcard special character which allows any variations of words that start with “frustr” and ”confus”.
Examples seen in the results:
Frustrated
Frustrating
Frustration
Confusing
Confusion
Your Turn |
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Next, let’s try a different approach to locating calls of interest. Select the ”X” here to clear all search terms. |
4. Let’s look for calls where the agent fails to use polite words. We would use the negative or minus “ – “ character to exclude calls where those terms were used.
5. You could further refine the search by looking specifically at calls where the AI has determined Agent Emotion to have an overall negative score.
Your Turn |
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Try entering the phrases and filters as seen on the example; take note of how many results show in this section. Once you’ve completed this, “X” out the search terms and return the Emotion filter to “All”. |
6. Because speech is complex, we may need to learn how agents speak to build phrase libraries.
7. To see how clients talk about “call back” or “calling back”, we could use the terms here with the OR option, but this is restrictive.
8. To discover other ways clients bring up this topic and to expand the search, we could use a tilde “ ~ “ to allow words in between “call” and “back”.
We also want to exclude the original phrases so we only see the different ways clients bring up the topic.
9. We want to continue adding negative terms to the ”Search Terms” list when they relate to call backs; this will allow us to continue filtering through different ways calls backs are brought up.
10. When we see terms that are not related to call backs, we do not add them to the list; these are considered “false positives.”
In this case, “call log” does not relate to call backs, so we will use remember this when we build an application in Module 5: Application Building/Management.
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