Interaction effectiveness measurements
A system for measuring effectiveness of a customer service platform comprises a server configured to receive a first set of data related to an interaction between a first person and an automated communication channel, receive a second set of data related to a conversation between the first person and a second person on a call, determine, from the first set of data, a third set of word(s) that describe an intent of the first person to perform a task via the customer service platform, determine, from the second set of data, a fourth set of word(s) that describes an outcome accomplished during the call, calculate a value that describes a similarity between the third set of word(s) and the fourth set of word(s), and determine an effectiveness measure of the customer service platform based at least in part on a comparison of the value with a pre-determined threshold.
1 . A method comprising:
receiving, via a digital channel of an omni-channel customer service platform, a first indication of a user to perform a task;
transferring, by the omni-channel customer service platform, the user from the digital channel to a virtual assistant channel operated by the omni-channel customer service platform to perform the task; and
in response to receiving, within a time threshold of transferring the user to the virtual assistant channel, receiving a second indication of the user via the digital channel of the omni-channel customer service platform to perform the task,
determining an effectiveness measure of the virtual assistant channel that indicates the task was not performed,
transferring the user from the digital channel to a voice-based communication channel for a voice call with a customer service representative, and
displaying the effectiveness measure on a device associated with the customer service representative.
2 . The method of claim 1 , further comprising:
calculating a value that describes a similarity between text of the digital channel and text associated with the virtual assistant channel; and
determining the effectiveness measure based on A) a comparison of the value with a pre-determined threshold and B) a length of time of the user interacting with the virtual assistant channel.
3 . The method of claim 1 , further comprising:
determining one or more words in text of the digital channel that describe an intent of the user to perform the task via the omni-channel customer service platform.
4 . The method of claim 1 , further comprising:
generating a first semantic representation associated with the digital channel based on a first set of words of the user communicated via the digital channel;
generating a second semantic representation associated with the virtual assistant channel based on a second set of words of the user communicated via the virtual assistant channel;
measuring a distance between the first semantic representation and the second semantic representation; and
determining a value that describes a similarity between the first set of words of the digital channel and the second set of words associated with the virtual assistant channel.
5 . The method of claim 1 , further comprising:
generating a summary of information from a first set of data from the digital channel and a second set of data from the virtual assistant channel.
6 . The method of claim 1 , further comprising:
calculating a value that describes a similarity between text of the virtual assistant channel and text associated with the voice-based communication channel; and
determining an updated effectiveness measure based on A) a comparison of the value with a pre-determined threshold and B) a length of time of the user interacting with the customer service representative.
7 . The method of claim 1 , wherein the digital channel is operated without human involvement.
8 . A system comprising:
one or more processors; and
one or more memories storing instructions that, when executed by the one or more processors, cause the system to perform a process comprising:
receiving, via a digital channel of an omni-channel customer service platform, a first indication of a user to perform a task;
transferring, by the omni-channel customer service platform, the user from the digital channel to a virtual assistant channel operated by the omni-channel customer service platform to perform the task; and
in response to receiving, within a time threshold of transferring the user to the virtual assistant channel, receiving a second indication of the user via the digital channel of the omni-channel customer service platform to perform the task,
determining an effectiveness measure of the virtual assistant channel that indicates the task was not performed,
transferring the user from the digital channel to a voice-based communication channel for a voice call with a customer service representative, and
displaying the effectiveness measure on a device associated with the customer service representative.
9 . The system of claim 8 , wherein the process further comprises:
calculating a value that describes a similarity between text of the digital channel and text associated with the virtual assistant channel; and
determining the effectiveness measure based on A) a comparison of the value with a pre-determined threshold and B) a length of time of the user interacting with the virtual assistant channel.
10 . The system of claim 8 , wherein the process further comprises:
determining one or more words in text of the digital channel that describe an intent of the user to perform the task via the omni-channel customer service platform.
11 . The system of claim 8 , wherein the process further comprises:
generating a first semantic representation associated with the digital channel based on a first set of words of the user communicated via the digital channel;
generating a second semantic representation associated with the virtual assistant channel based on a second set of words of the user communicated via the virtual assistant channel;
measuring a distance between the first semantic representation and the second semantic representation; and
determining a value that describes a similarity between the first set of words of the digital channel and the second set of words associated with the virtual assistant channel.
12 . The system of claim 8 , wherein the process further comprises:
generating a summary of information from a first set of data from the digital channel and a second set of data from the virtual assistant channel.
13 . The system of claim 8 , wherein the process further comprises:
calculating a value that describes a similarity between text of the virtual assistant channel and text associated with the voice-based communication channel; and
determining an updated effectiveness measure based on A) a comparison of the value with a pre-determined threshold and B) a length of time of the user interacting with the customer service representative.
14 . The system of claim 8 , wherein the digital channel is operated without human involvement.
15 . A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations comprising:
receiving, via a digital channel of an omni-channel customer service platform, a first indication of a user to perform a task;
transferring, by the omni-channel customer service platform, the user from the digital channel to a virtual assistant channel operated by the omni-channel customer service platform to perform the task; and
in response to receiving, within a time threshold of transferring the user to the virtual assistant channel, receiving a second indication of the user via the digital channel of the omni-channel customer service platform to perform the task,
determining an effectiveness measure of the virtual assistant channel that indicates the task was not performed,
transferring the user from the digital channel to a voice-based communication channel for a voice call with a customer service representative, and
displaying the effectiveness measure on a device associated with the customer service representative.
16 . The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
calculating a value that describes a similarity between text of the digital channel and text associated with the virtual assistant channel; and
determining the effectiveness measure based on A) a comparison of the value with a pre-determined threshold and B) a length of time of the user interacting with the virtual assistant channel.
17 . The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
determining one or more words in text of the digital channel that describe an intent of the user to perform the task via the omni-channel customer service platform.
18 . The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
generating a first semantic representation associated with the digital channel based on a first set of words of the user communicated via the digital channel;
generating a second semantic representation associated with the virtual assistant channel based on a second set of words of the user communicated via the virtual assistant channel;
measuring a distance between the first semantic representation and the second semantic representation; and
determining a value that describes a similarity between the first set of words of the digital channel and the second set of words associated with the virtual assistant channel.
19 . The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
generating a summary of information from a first set of data from the digital channel and a second set of data from the virtual assistant channel.
20 . The non-transitory computer-readable medium of claim 15 , wherein the operations further comprise:
calculating a value that describes a similarity between text of the virtual assistant channel and text associated with the voice-based communication channel; and
determining an updated effectiveness measure based on A) a comparison of the value with a pre-determined threshold and B) a length of time of the user interacting with the customer service representative.