Computer systems and methods for efficient query resolution by customer representatives
First Claim
1. A computerized method of representing customer interactions with an organization, the computerized method comprising:
- receiving, by a computing device, customer web interaction data segments and customer conversation data segments including at least one of chat data or phone call transcripts;
pre-processing, by the computing device, the customer conversation data segments to remove specified types of information, thereby generating pre-processed customer conversation data segments, each data segment having a timestamp and a customer identifier;
scoring, by the computing device, each of the pre-processed customer conversation data segments using a pre-trained transaction module;
pre-processing, by the computing device, the customer web data interaction segments, thereby generating pre-processed customer web data interaction segments, each data segment having a timestamp and a customer identifier;
extracting, by the computing device, from the pre-processed customer web interaction data segments, one or more tokens;
combining, by the computing device, the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set;
parsing, by the computing device, the customer data set into one or more windows using the timestamps and the customer identifiers, each window including one or more tokens;
assigning, by the computing device, for each window, pre-trained weights to each of the one or more tokens in each window;
assigning, by the computing device, a transaction theme to each window based on the on one or more tokens in each window using an association model; and
generating, by the computing device, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments.
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Abstract
A computerized method of representing customer interactions with an organization includes: receiving, by a computing device, customer web interaction data segments and customer conversation data segments; pre-processing the customer conversation data segments to remove specified types of information; scoring each of the pre-processed customer conversation data segments; pre-processing the customer web data interaction segments; extracting from the pre-processed customer web interaction data segments tokens; combining the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set; parsing the customer data set into one or more windows; assigning, for each window, pre-trained weights to each of the tokens in each window; assigning a transaction theme to each window based on the tokens in each window; and generating, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments.
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Citations
15 Claims
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1. A computerized method of representing customer interactions with an organization, the computerized method comprising:
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receiving, by a computing device, customer web interaction data segments and customer conversation data segments including at least one of chat data or phone call transcripts; pre-processing, by the computing device, the customer conversation data segments to remove specified types of information, thereby generating pre-processed customer conversation data segments, each data segment having a timestamp and a customer identifier; scoring, by the computing device, each of the pre-processed customer conversation data segments using a pre-trained transaction module; pre-processing, by the computing device, the customer web data interaction segments, thereby generating pre-processed customer web data interaction segments, each data segment having a timestamp and a customer identifier; extracting, by the computing device, from the pre-processed customer web interaction data segments, one or more tokens; combining, by the computing device, the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set; parsing, by the computing device, the customer data set into one or more windows using the timestamps and the customer identifiers, each window including one or more tokens; assigning, by the computing device, for each window, pre-trained weights to each of the one or more tokens in each window; assigning, by the computing device, a transaction theme to each window based on the on one or more tokens in each window using an association model; and generating, by the computing device, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computerized system including:
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a computing device including a context engine for representing customer interactions with an organization and a query engine for generating a question-answer set for use by a customer service representative of an organization and mining answers to questions, the computing device configured to; receive customer web interaction data segments and customer conversation data segments including at least one of chat data or phone call transcripts; pre-process the customer conversation data segments to remove specified types of information, thereby generating pre-processed customer conversation data segments, each data segment having a timestamp and a customer identifier; score each of the pre-processed customer conversation data segments using a pre-trained transaction module; pre-process the customer web data interaction segments, thereby generating pre-processed customer web data interaction segments, each data segment having a timestamp and a customer identifier; extract, from the pre-processed customer web interaction data segments, one or more tokens; combine the pre-processed customer conversation data segments and the pre-processed customer web interaction data segments into a customer data set; parse the customer data set into one or more windows using the timestamps and the customer identifiers, each window including one or more tokens; assign, for each window, pre-trained weights to each of the one or more tokens in each window; assign a transaction theme to each window based on the on one or more tokens in each window using an association model; and generate, based on the transaction themes, a ranked list of topic keywords reflecting the customer web interaction data segments and customer conversation data segments; one or more databases in electronic communication with the computing device, the one or more databases storing customer web interaction data and customer conversation data including at least one of chat data or phone call transcripts; and a virtual agent computing device in electronic communication with the computing device. - View Dependent Claims (15)
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Specification