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The “Advanced search” feature in the Talkdesk Interaction Analytics™ application provides the ability to uncover deeper cases, as this option allows for more complex queries to be performed. 

 

In this article, you will find information on:

• Accessing the Advanced Search feature
• Editing Queries
  • Query examples
• Filters Mapping

 

Accessing the Advanced Search feature

When accessing the “Search” page within the Interaction Analytics application, select the “Advanced search” toggle [1]

Tip: Check the query hint [2] displayed whenever the “Advanced search” toggle is enabled. This way you can double-check the Technical Name (e.g., interaction_started) of a given field, as an example of how to use it in a custom query. Note: To learn more about each filter, please check this article.

 

Editing Queries

Users will be able to edit queries by switching the “Advanced Search” toggle to the right [1], whenever required.

 

Query examples

Below, you can see several query examples that might be helpful while editing/typing a keyword or phrase in the “Query editing” search bar [1]: 

 

Logical Operators

Filter by a conjunction (AND) operator example:

• All utterances that contain both the “hi” and the “hello” keywords:

("hello" AND "hi")

 

Filter by disjunction (OR) operator examples:

• All utterances where the sentiment has been labeled as “positive” or “negative”: 

sentiment_label:("POSITIVE" OR "NEGATIVE")

• All utterances labeled with the intent “Order returns” or “Order information”:

intent_value:("Order returns" "Order Information")

Note: query intent_value:("Order returns" OR "Order Information") would produce the same result.

 

Filter by negation (NOT) operator example:

• All utterances labeled with the intent “Satisfaction” but don't contain “virtual agent” keyword

NOT message_text:(“virtual agent”) AND intent_value:("Satisfaction")

Filter by complex boolean operands' logics example:

• All utterances that either contain one of the “hi” or “hello” keywords and were matched with intent “Order Information” or were matched with the “Order returns” intent and have a positive sentiment label:

(message_text:("hi" OR "hello") AND intent_value:("Order Information")) OR (intent_value:("Order returns") AND sentiment_label:("POSITIVE"))

 

Comparison Operators

Filter by equal to operator example:

• All utterances where the sentiment has been labeled as “positive”:

sentiment_label:("POSITIVE")

• All utterances that contain the “hello” keyword:

("hello")

Filter by greater than operator example:

• All utterances that were matched with an intent with a confidence score of at least 0.5:

intent_confidence:[0.5 TO *]

Filter by less than operator example:

• All utterances that were matched against an intent with a confidence score of up to 0.8:

intent_confidence:[* TO 0.8]

Filter by between range operator examples:

• All utterances that were matched against an intent with confidence between 0.5 and 0.8:

intent_confidence:[0.5 TO 0.8]

• All utterances that were matched against an intent with a confidence between 0.5 and 0.8, not including the 0.8 value:

intent_confidence:[0.5 TO 0.8]

• All utterances that were matched against an intent with confidence between 0.5 and 0.8, not including the 0.5 value:

intent_confidence:{0.5 TO 0.8]

 

Proximity operators

Filter by one occurrence of any character example:

• All utterances with keywords that start with “tes” followed by one more character (e.g., return results like “test”):

(tes?)

Filter by any sequence of characters examples:

• All utterances with keywords that start with “tes” followed by any given number of characters (e.g., return results like “test”, “tests”, “testing”, among others): 

(tes*)

Note: Since the search is case-sensitive, you must specify lower and/or upper cases in the query search, so that the output of the record meets the desired criteria. If you need to search for keywords or phrases of a specific agent, you must include the exact username in your search. E.g. There is an agent named “John Doe”. To retrieve the correct results, you would need to type:

message_text:* AND message_agent_id:(John Doe)

• Or, if you need more than one agent named John, you can use the search for any sequence of characters.

message_text:* AND message_agent_id:(John*)

Filter by fuzziness example:

• All utterances that contain both “hello” and “today” keywords separated by up to 5 other keywords: 

("hello today"~5)

 

Dealing with different data types

Filter by dates examples:

• All utterances for interactions starting from 2021-11-08T00:00:00: 

interaction_started:[2021-11-08T00:00:00 TO *]

• All utterances for interactions started before 2021-11-09T23:59:59:

interaction_started:[* TO 2021-11-09T23:59:59]

• All utterances for interactions started between 2021-11-08T00:00:00 and 2021-11-09T23:59:59:

interaction_started:[2021-11-08T00:00:00 TO 2021-11-09T23:59:59]

Filter by number examples:

AND intent_confidence:[0.5 TO 0.7]

AND intent_confidence:[0.88 TO 0.99]

Filter by special fields examples:

interaction_started:[2022-11-02T00:00:00 TO 2022-11-04T23:59:59]

Filter by channels queries examples:

• Voice calls

AND (source_system:STT AND message_channel:VOICE)

• Autopilot Digital

AND (source_system:VA AND message_channel:WEBCHAT)

• Autopilot Voice

AND (source_system:VA AND message_channel:VOICE)

Querying with multiple filters:

• Filtering outbound voice calls and showing only utterances spoken by the agent with the intent_id 298255eb-7f64-4ab2-b0c7-5353e5af713c in the last 3 months.

message_text:* AND interaction_started:[2022-08-09T23:00:00.000Z TO 2022-11-10T23:59:59.999Z] AND ((source_system:STT AND message_channel:VOICE)) AND message_direction:("OUT") AND message_participant:("AGENT") AND intent_id:("298255eb-7f64-4ab2-b0c7-5353e5af713c") AND (source_system:STT OR source_system:VA)

• Filtering Autopilot Voice calls and showing only Negative sentiment spoken in en-US language.

message_text:* AND stt_language_code:("en-us") AND ((source_system:VA AND message_channel:VOICE)) AND sentiment_label:("NEGATIVE") AND (source_system:STT OR source_system:VA)

 

Filters Mapping

To build a query, you must use the Technical Names listed below:

Filter Name	Technical Name	Data type
“When”	interaction_started	Timestamp
“Channels”	source_system AND message_channel*	Text
“Direction”	message_direction	Text
“Ring Groups”	ring_groups	Text
“Speakers”	message_participant	Text
“Agents”	message_agent_id	Text
“Interaction ID”	interaction_id	Text
“Language”	stt_language_code	Text
“Intents”	intent_value	Text
“Intent Threshold”	intent_above_threshold	number
“Sentiment”	sentiment_label	Text