Method for personalizing customer interaction experiences by routing to customer interaction channels

Abstract

A computer-implemented method and an apparatus for personalizing customer interaction experiences receives an input corresponding to at least one of a business objective and a customer interaction channel. A customer classification framework is selected based on the input. The customer classification framework is associated with a plurality of persona types, where each persona type is associated with a set of behavioral traits. A persona type for a customer is predicted from among the plurality of persona types during an interaction on the customer interaction channel. A propensity of the customer to perform at least one action is predicted based on the persona type. A provisioning of personalized interaction experience to the customer is facilitated based on the predicted propensity of the customer to perform the at least one action.

1 . A computer-implemented method for personalizing customer interaction experiences to improve the performance of a network by provisioning a personalized interaction in a language that is suitable for a customer, where personalization is for that customer being in another language, comprising:
 receiving an input corresponding to at least one of a business objective and a customer interaction channel;   selecting a customer classification framework from among a plurality of customer classification frameworks based on the input, the customer classification framework associated with a plurality of persona types, wherein each persona type from among the plurality of persona types is associated with a set of behavioral traits, wherein the persona type is predicted from among the plurality of persona types based on behavioral traits of the customer, and, wherein the behavioral traits are exhibited or mentioned by the customer during the interaction or are inferred during the interaction;   predicting a persona type for a customer during an interaction on the customer interaction channel, the persona type predicted from among the plurality of persona types;   predicting a propensity of the customer to perform at least one action based on the persona type;   determining a confidence level associated with the prediction of the persona type of the customer;   facilitating a provisioning of personalized interaction experience to the customer based on the predicted propensity of the customer to perform the at least one action;   adapting a degree of personalization related to the personalized interaction experience to be provided to the customer based on the determination of the confidence level;   generating and maintaining a personalization model for customer interactions associated with a first language, the personalization model generated and maintained based on provisioning of personalized interaction experiences to a plurality of customers based on prediction of persona types for the plurality of customers; and   provisioning personalized interaction experiences to one or more customers interacting in a second language based on the personalization model, wherein provisioning personalized interaction experiences comprises presenting a computer interface of a web channel or an automated voice response in the second language.   
     
     
         2 . The method of  claim 1 , wherein the persona type is predicted from among the plurality of persona types based on past interaction history associated with the customer, the past interaction history indicative of behavioral traits corresponding to the customer. 
     
     
         3 . The method of  claim 1 , wherein an action from among the at least one action corresponds to one of purchasing a product, interacting with an agent over one or more customer interaction channels, and socializing at least one of a product, a purchase, a good sentiment, a bad sentiment, a brand, an experience and a feeling. 
     
     
         4 . The method of  claim 1 , further comprising:
 associating one or more value traits with the persona type, wherein each value trait from among the one or more value traits corresponds to an attribute characterizing a nature of the interaction, the attribute deemed to be of value to the persona type.   
     
     
         5 . The method of  claim 1 , further comprising:
 generating one or more recommendations based on the predicted propensity to perform the at least one action for facilitating a provisioning of the personalized interaction experience to the customer, and, wherein the one or more recommendations are generated to achieve at least one of an accomplishment of the business objective during the interaction and a satisfaction of the one or more value traits associated with the persona type.   
     
     
         6 . The method of  claim 1 , further comprising:
 identifying an affinity of the persona type to one or more customer interaction channels from among a plurality of customer interaction channels;   determining if the customer interaction channel associated with the interaction is one among the one or more customer interaction channels; and   routing the interaction to the one or more customer interaction channels if the customer interaction channel associated with the interaction is determined to be not among the one or more customer interaction channels, wherein the routing of the interaction to the one or more customer interaction channels is performed to provision the personalized interaction experience to the customer.   
     
     
         7 . The method of  claim 1 , further comprising:
 generating and maintaining a multi-lingual personalization model for personalizing customer interactions across a plurality of languages, the multi-lingual personalization model generated and maintained based on provisioning of personalized interaction experiences to a plurality of customers based on prediction of persona types for the plurality of customers.   
     
     
         8 . An apparatus for personalizing customer interaction experiences to improve the performance of a network by provisioning a personalized interaction in a language that is suitable for a customer, where personalization for that customer is in another language, the apparatus comprising:
 at least one processor; and   a memory having stored therein machine executable instructions, that when executed by the at least one processor, cause the apparatus to:
 receive an input corresponding to at least one of a business objective and a customer interaction channel; 
 select a customer classification framework from among a plurality of customer classification frameworks based on the input, the customer classification framework associated with a plurality of persona types, wherein each persona type from among the plurality of persona types is associated with a set of behavioral traits, wherein the persona type is predicted from among the plurality of persona types based on behavioral traits of the customer, and, wherein the behavioral traits are exhibited or mentioned by the customer during the interaction or are inferred during the interaction; 
 predict a persona type for a customer during an interaction on the customer interaction channel, the persona type predicted from among the plurality of persona types; 
 predict a propensity of the customer to perform at least one action based on the persona type; 
 determine a confidence level associated with the prediction of the persona type of the customer; 
 facilitate a provisioning of personalized interaction experience to the customer based on the predicted propensity of the customer to perform the at least one action; 
 adapt a degree of personalization related to the personalized interaction experience to be provided to the customer based on the determination of the confidence level; 
 generate and maintaining a personalization model for customer interactions associated with a first language, the personalization model generated and maintained based on provisioning of personalized interaction experiences to a plurality of customers based on prediction of persona types for the plurality of customers; and 
 provision personalized interaction experiences to one or more customers interacting in a second language based on the personalization model, wherein provisioning personalized interaction experiences comprises presenting a computer interface of a web channel or an automated voice response in the second language. 
   
     
     
         9 . The apparatus of  claim 8 , wherein the persona type is predicted from among the plurality of persona types based on past interaction history associated with the customer, the past interaction history indicative of behavioral traits corresponding to the customer. 
     
     
         10 . The apparatus of  claim 8 , wherein an action from among the at least one action corresponds to one of purchasing a product, interacting with an agent over one or more customer interaction channels, and socializing at least one of a product, a purchase, a good sentiment, a bad sentiment, a brand, an experience and a feeling. 
     
     
         11 . The apparatus of  claim 8 , wherein the apparatus is further configured to:
 associate one or more value traits with the persona type, wherein each value trait from among the one or more value traits corresponds to an attribute characterizing a nature of the interaction, the attribute deemed to be of value to the persona type.   
     
     
         12 . The apparatus of  claim 8 , wherein the apparatus is further configured to:
 generate one or more recommendations based on the predicted propensity to perform the at least one action for facilitating a provisioning of the personalized interaction experience to the customer, and, wherein the one or more recommendations are generated to achieve at least one of an accomplishment of the business objective during the interaction and a satisfaction of the one or more value traits associated with the persona type.   
     
     
         13 . The apparatus of  claim 8 , wherein the apparatus is further configured to:
 identify an affinity of the persona type to one or more customer interaction channels from among a plurality of customer interaction channels;   determine if the customer interaction channel associated with the interaction is one among the one or more customer interaction channels; and   route the interaction to the one or more customer interaction channels if the customer interaction channel associated with the interaction is determined to be not among the one or more customer interaction channels, wherein the routing of the interaction to the one or more customer interaction channels is performed to provision the personalized interaction experience to the customer.   
     
     
         14 . The apparatus of  claim 8 , wherein the apparatus is further configured to:
 generate and maintain a multi-lingual personalization model for personalizing customer interactions across a plurality of languages, the multi-lingual personalization model generated and maintained based on provisioning of personalized interaction experiences to a plurality of customers based on prediction of persona types for the plurality of customers.   
     
     
         15 . A non-transitory computer-readable medium storing a set of instructions that when executed cause a computer to perform a method for personalizing customer interaction experiences to improve the performance of a network by provisioning a personalized interaction in a language that is suitable for a customer despite personalization for that customer being in another language, method comprising:
 receiving an input corresponding to at least one of a business objective and a customer interaction channel;   selecting a customer classification framework from among a plurality of customer classification frameworks based on the input, the customer classification framework associated with a plurality of persona types, wherein each persona type from among the plurality of persona types is associated with a set of behavioral traits, wherein the persona type is predicted from among the plurality of persona types based on behavioral traits of the customer, and, wherein the behavioral traits are exhibited or mentioned by the customer during the interaction or are inferred during the interaction;   predicting a persona type for a customer during an interaction on the customer interaction channel, the persona type predicted from among the plurality of persona types;   predicting a propensity of the customer to perform at least one action based on the persona type;   determining a confidence level associated with the prediction of the persona type of the customer;   facilitating a provisioning of personalized interaction experience to the customer based on the predicted propensity of the customer to perform the at least one action;   adapting a degree of personalization related to the personalized interaction experience to be provided to the customer based on the determination of the confidence level; and   generating and maintaining a language-agnostic personalization model for customer interactions across a plurality of languages, the language-agnostic personalization model generated and maintained based on provisioning of personalized interaction experiences to a plurality of customers based on prediction of persona types for the plurality of customers.   
     
     
         16 . The computer-readable medium of  claim 15 , wherein the persona type is predicted from among the plurality of persona types based on past interaction history associated with the customer, the past interaction history indicative of behavioral traits corresponding to the customer. 
     
     
         17 . The computer-readable medium of  claim 15 , wherein an action from among the at least one action corresponds to one of purchasing a product, interacting with an agent over one or more customer interaction channels, and socializing at least one of a product, a purchase, a good sentiment, a bad sentiment, a brand, an experience and a feeling. 
     
     
         18 . The computer-readable medium of  claim 15 , wherein the method further comprises:
 associating one or more value traits with the persona type, wherein each value trait from among the one or more value traits corresponds to an attribute characterizing a nature of the interaction, the attribute deemed to be of value to the persona type.   
     
     
         19 . The computer-readable medium of  claim 18 , wherein the method further comprises:
 generating one or more recommendations based on the predicted propensity to perform the at least one action for facilitating a provisioning of the personalized interaction experience to the customer, and, wherein the one or more recommendations are generated to achieve at least one of an accomplishment of the business objective during the interaction and a satisfaction of the one or more value traits associated with the persona type.   
     
     
         20 . The computer-readable medium of  claim 15 , wherein the method further comprises:
 identifying an affinity of the persona type to one or more customer interaction channels from among a plurality of customer interaction channels;   determining if the customer interaction channel associated with the interaction is one among the one or more customer interaction channels; and   routing the interaction to the one or more customer interaction channels if the customer interaction channel associated with the interaction is determined to be not among the one or more customer interaction channels, wherein the routing of the interaction to the one or more customer interaction channels is performed to provision the personalized interaction experience to the customer.