Overview
Organizations use Verint Financial Compliance's Analytics Search capabilities to reduce the time effort required to find potential compliance issues within Conversations. This guide will describe how to:
- Search within Transcripts
- Search by Language
- Search by Sentiment
- Search by Topics
- Understand the available columns within the Conversation Search results grid
Search within transcripts
This functionality empowers the user to search within transcribed recordings.
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Search Field Name | Description |
|---|---|
| All of these phrases | Will search across transcribed conversations for transcripts that contain all of the listed phrases in one transcript. |
| Any of these phrases | Will search across transcribed conversations for transcripts that contain any of the listed phrases in one transcript. |
| None of these phrases | Will search across transcribed conversations for transcripts that contain none of the listed phrases in one transcript. |
| Info |
|---|
You cannot search within transcription summaries. |
Language search
This functionality empowers the user to search for use of a specific language within a recorded and transcribed conversation. The functionality also empowers the user to search for conversations where the recorded user, switched from one language to another.
Search Field Name | Description |
|---|---|
| Language switched during conversation | Will search across transcribed conversations where a user has switched to a second language during the conversation. |
| Language Spoken | Will search across transcribed conversations for transcripts that contain use of a recognized language. Please note, multiple instances of the language spoken search field can be added. |
Search within sentiment
This functionality empowers the user to search by sentiment within transcribed recordings.
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Search Field Name | Description |
|---|---|
| Sentiment Gradient | An additional filter is available to refine the sentiment shift. This enables the user to define a search filter (more than or less than) shift by Numeric Value, where the numeric value (-99 to +99) represents the sentiment change |
| Sentiment Gradient | Enables the user to search for conversations where the sentiment has shifted in different directions. For example:
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| TCU Instances | Enables the user to search for conversations where there has been a large volume of negative or positive TCU sentiments in a given conversation. The user is able to refine the search to focus on 'Very Negative', or 'Negative', or 'Positive', or 'Verint Positive' instances of sentiment TCU. The user can set the numeric range. |
Search within topics
This functionality empowers the user to search by Topic.
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Search Field Name | Description |
|---|---|
| Topics | Enables the user to search for conversations that contain specific Topics. |
Search results
The Conversation Search includes columns for the enriched speech analytics insights.
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Search Result Column | Description |
|---|---|
| Language Switched | Highlights if a language switch was detected during the conversation. |
| Languages | Lists the detected languages spoken during the conversation. |
| Topics | Lists key topics spoked within a conversation, providing a quick summary of the audio file content. |
| Sentiment Gradient | Provides a graphical display of the sentiment shift during the conversation. The angle and direction of the line reflects the sentiment direction and gradient. The sentiment gradient maps the changing sentiment (tone or mood) across the entirety of an interaction by calculating the change in the sentiment between the beginning and the end of the conversation for each speaker. Note that a positive sentiment gradient does not necessarily mean that the outcome of the conversation was positive, it only reflects the direction of the change in the sentiment across the call. The Verba system displays the sentiment gradient on the search result screen as follows:
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| TCU Sentiment | Lists the granular count of TCU sentiment within the conversation. The numbers with the colored background represent the number of TCUs in the respective sentiment category for the recorded conversation. |
