Abstract: Systems and methods provide a cloud-based intelligent and interactive customer service platform that includes a communication manager, customer app, agent app, a virtual container (e.g. room) for communication, a natural language processor, voice processor, image processor, video processor, and an inference processor exposed by application programming interfaces; and executing an agent picker functionality within the automation infrastructure that performs operations comprising: receiving a communication from a customer; immediately analyzing the communication to determine the right agent; automatically understanding the state of the room parsing a knowledgebase for some of the conversation to the subject associated with the customer's communication; providing the state of the room to agent within a unified interface during the communication with the customer, capability to rate other party and add and drop multimedia to all containers.

Abstract: Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Abstract: Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize featureless supervised or unsupervised machine learning to generate service provider match predictions based on raw communication data. In one or more embodiments, the disclosed systems utilize a trained service provider match neural network to generate a service provider match prediction based on raw communication data associated with an incoming audio, text, or video communication. In response to the generated service provider match prediction, the disclosed systems can route the incoming communication to the matched service provider.

Abstract: Disclosed are various implementations directed to systems, processes, methods, and other implementations for cross-channel call attribution by analyzing features and aspects of the incoming call—not just the call-in phone number—to more accurately determine the advertising channel actually attributable for the consumer calling in and/or allocate attribution for a consumer call-in to one or more channels accordingly.

Abstract: A method for billboards in a data management platform (DMP) includes: receiving an indication from a user during an interaction between the user and an agent that the user would like to hear an offer; determining at least one offer to play to the customer; determining statistics regarding at least one of the characteristics, features, or aspects of the at least one offer that customers have indicated as liking or have acted on; determining measurements for KPIs regarding at least one of the interaction or the at least one offer, and other metrics; generating one or more billboards using the statistics and the measurements; and announcing the one or more billboards to one or more of clients, contact centers, or customers. The billboards comprise at least one of the characteristics, features, or aspects of the at least one offer that customers have indicated as liking or have acted on.

Abstract: A system for marketing automation includes: an intelligent database configured to extract information regarding a customer; and a marketing and ad platform configured to generate and provide real-time ads to the customer or to a contact center. The intelligent database is configured to extract the information from a text conversation or a voice conversation between the customer and an agent. The information comprises demographics of the customer. The information comprises at least one of personality type, education, race, generation, ethnicity, accent, psychographics, city, zip code, state, previous issues, marital status, number of children, or home value. The intelligent database is configured to extract the information from customer relationship management (CRM), from context, from a 3rd party, from a voice conversation, or from a chat conversation.

Abstract: A Virtual agent that is a fully automated computer software solution that can engage with real people, customers, clients and even other agents. Virtual agents have personality with animation and engage with the customer via text or voice or a combination of both as an actual person. Virtual agents are able to answer customer questions and provide information to address their issues. Virtual agents transfer calls to live agents if they cannot address customer issues.

Abstract: A Virtual agent that is a fully automated computer software solution that can engage with real people, customers, clients and even other agents. Virtual agents have personality with animation and engage with the customer via text or voice or a combination of both as an actual person. Virtual agents are able to answer customer questions and provide information to address their issues. Virtual agents transfer calls to live agents if they cannot address customer issues.

Abstract: A method for signature extraction in a data management platform (DMP) includes receiving personally identifiable information (PII) data of customers from one or more clients at the DMP; generating non-PII data using the PII data; and building a signature for each of the customers using the non-PII data. The method further comprises generating a customer DNA for each customer, using the PII data and the signatures. The method further comprises generating segments for each customer using the PII data. The method further comprises generating segments for each customer using the non-PII data. The non-PII data comprises at least one of an ID (identifier), signature, psychographics, and demographics of each customer. The DMP is further configured to generate a signature of each customer. The signature is unique for each customer and the identity of the customer is not known.

Abstract: A method for predictive marketing includes: receiving information that an event is expected to happen or is happening; predicting which attributes of customers will be associated with calls or chats directed to the event; predicting which customers will contact a contact center based on the predicted attributes; and taking action based on the predictions. A system for predictive marketing includes: an intelligent database for storing interaction data of customers; and a data management platform (DMP) configured to receive customer data from the intelligent database, analyze the customer data, determine which of the customers will be affected by an event, determine how the customers will be affected by the event, and take action. A predictive marketing platform includes: data sources; and a marketing and ad platform configured to receive data from the data sources, make predictions based on the data; and take action based on the predictions.

Abstract: A Virtual agent that is a fully automated computer software solution that can engage with real people, customers, clients and even other agents. Virtual agents have personality with animation and engage with the customer via text or voice or a combination of both as an actual person. Virtual agents are able to answer customer questions and provide information to address their issues. Virtual agents transfer calls to live agents if they cannot address customer issues.

Abstract: Disclosed is a contact center that stores data related to a consumer in a blockchain. More specifically, disclosed is a methodology for conducting and concluding a communication with the consumer; creating a record of the communication; encrypting the record of the communication with asymmetric cryptography; and updating the blockchain with the record of the communication.

Abstract: A method for chat advertisement includes: monitoring a chat session between a customer and an agent of a contact center; determining an ad based on the monitoring; determining a time or an event to send the ad to the customer; and sending the ad to the customer when the time or the event occurs. A system for chat advertisement includes: a processor configured to monitor a chat session between a customer and an agent, for at least one of context, keywords, tones, emotions, demographics, psychographics, or an identifier of the customer, and to provide an ad to a device of the customer during the chat session pursuant to the monitoring; and a database for storing the ad.

Abstract: A method for chat advertisement includes: monitoring a chat session between a customer and an agent of a contact center; determining an ad based on the monitoring; determining a time or an event to send the ad to the customer; and sending the ad to the customer when the time or the event occurs. A system for chat advertisement includes: a processor configured to monitor a chat session between a customer and an agent, for at least one of context, keywords, tones, emotions, demographics, psychographics, or an identifier of the customer, and to provide an ad to a device of the customer during the chat session pursuant to the monitoring; and a database for storing the ad.

Abstract: A system for marketing automation includes: an intelligent database configured to extract information regarding a customer; and a marketing and ad platform configured to generate and provide real-time ads to the customer or to a contact center. The intelligent database is configured to extract the information from a text conversation or a voice conversation between the customer and an agent. The information comprises demographics of the customer. The information comprises at least one of personality type, education, race, generation, ethnicity, accent, psychographics, city, zip code, state, previous issues, marital status, number of children, or home value. The intelligent database is configured to extract the information from customer relationship management (CRM), from context, from a 3rd party, from a voice conversation, or from a chat conversation.

Abstract: Disclosed are various implementations directed to optimizing a number pool for dynamic number insertion (DNI) used for call attribution by considering physical characteristics of the DNI number assigned to a specific channel versus characteristics of consumers within that channel to make more optimized DNI number assignments.

Abstract: A Virtual agent that is a fully automated computer software solution that can engage with real people, customers, clients and even other agents. Virtual agents have personality with animation and engage with the customer via text or voice or a combination of both as an actual person. Virtual agents are able to answer customer questions and provide information to address their issues. Virtual agents transfer calls to live agents if they cannot address customer issues.

Abstract: A Virtual agent that is a fully automated computer software solution that can engage with real people, customers, clients and even other agents. Virtual agents have personality with animation and engage with the customer via text or voice or a combination of both as an actual person. Virtual agents are able to answer customer questions and provide information to address their issues. Virtual agents transfer calls to live agents if they cannot address customer issues.

Abstract: Disclosed are various implementations directed to systems, processes, methods, and other implementations for cross-channel call attribution by analyzing features and aspects of the incoming call—not just the call-in phone number—to more accurately determine the advertising channel actually attributable for the consumer calling in and/or allocate attribution for a consumer call-in to one or more channels accordingly.