Systems and methods are provided for dynamic generation of staff analytics and forecasts based on skill and service level. Dynamic forecasting allows for forecast generation in real-time and may be based on historical data regarding skills and results, as well as data science to identify patterns and make predictions. The resulting staffing forecast may therefore provide for efficient management of messaging staff costs while preserving the desired service quality. The staffing forecast may include a volume forecast that is tailored to the unique nature of asynchronous messaging, as well as the unique messaging needs of the entity so as to efficiently manage messaging operations and make data-driven staffing decisions that take service level into account. An exemplary embodiment may include dynamic analytics tools that may use specified target and/or resource numbers (e.g., desired service level) for an existing messaging operation and get a detailed per-skill staffing forecast.

Methods and systems for routing calls based on a minimum expected delay, classification, and priority of the call are provided. In some embodiments, when a call is received, the call is classified and prioritized within the classification. A minimum expected delay time is determined. Based on the minimum expected delay time, the classification, and the prioritization, the call is routed to a representative with instructions on how the call should be treated.

A system of customer tracking is provided. The system includes: a data management platform (DMP) configured to receive personally identifiable information (PII) data of a plurality of customers and generate non-PII data using the PII data; and an intelligent database to store the non-PII data. A method of customer tracking in a DMP is provided. The method includes: providing ads or songs to a customer while the customer is on hold during an interaction with an agent of a contact center; tracking data regarding selections by the customer pertaining to the ads or songs; and generating statistics based on the selections and the data.

Systems and methods forecast inbound telecommunications, and more particularly, analyze real-time and historical call center data, and apply a forecasting model to the data in order to predict inbound call volume. These systems and methods employ tools that manipulate call center data and generate visual representations of metrics pertaining to forecasting call center data via a dashboard.

A data management platform (DMP) integrates data by anonymously integrating data streams from data sources. The DMP consolidates and unifies audiences for cross channel and contextual targeting. The DMP provides analytics by providing audience insights. The DMP activates against specific segments. The DMP provides insights, such as audience intelligence and segmentation. By integrating the data sets, richer audience profiles can be created. This allows insights to enhance the web experience, fuel strategic direction, and build audience segments for targeting. Insights provide dashboard access for a client's own data, and/or comprehensive data based on multiple clients' data. An intelligent database is a database of data pertaining to agents, users, interactions, and clients. Unique data can be extracted, inferred, and/or correlated from the intelligent database. The intelligent database comprises a repository of every interaction with associated entities and features, and enables real-time analytics and data-driven business decisions.

A mobile application for a wireless handheld computing device, such as a smartphone, is disclosed in combination with a communication link establishment and management system. Systems and methods are disclosed for calling desired contacts using a smartphone that can take advantage of the power and efficiency of agent-assisted dialing provided by the communication link establishment and management system. The systems and methods automatically integrate with a customer relationship management (CRM) system connected to the communication link establishment and management system.

A customer identifier comprises a first segment and a second segment, wherein each segment is directed to at least one feature of a customer, wherein each feature is based on one or more characteristics of the customer or another customer. The one or more characteristics comprises at least one of demographics, voice signature, psychographics, behaviors, or phone number. The behaviors comprise at least one of sentiment of the customer or personality of the customer. Each segment has a weighting. The first segment and the second segment are comprised within a customer fingerprint or a customer DNA. A system for customer identifier for a data management platform (DMP) comprises an analytics and audience insight module configured to perform analytics on data, and provide insights regarding customers; and a dashboard indicating high risk customers, moderate risk customer, and low risk customers.

A customer identifier comprises a first segment and a second segment, wherein each segment is directed to at least one feature of a customer, wherein each feature is based on one or more characteristics of the customer or another customer. The one or more characteristics comprises at least one of demographics, voice signature, psychographics, behaviors, or phone number. The behaviors comprise at least one of sentiment of the customer or personality of the customer. Each segment has a weighting. The first segment and the second segment are comprised within a customer fingerprint or a customer DNA. A system for customer identifier for a data management platform (DMP) comprises an analytics and audience insight module configured to perform analytics on data, and provide insights regarding customers; and a dashboard indicating high risk customers, moderate risk customer, and low risk customers.

The disclosed technology provides a system and method for correlating events from a single application run in a cloud communications network using session identifiers uniquely identifying a communication session, and event identifiers uniquely identifying events in network elements of the cloud communication network. A data manager of the cloud communications network maps common fields and event-specific fields of network element event records to common fields and generic fields of a data warehouse based on the event type of the event to be recorded.

A method for predicting fraudulent call activity is provided. The method includes receiving one or more datasets indicating call activity corresponding to a phone number, and analyzing the one or more datasets to identify unusual call activity. The method further includes generating a fraud prediction, based at least in part on the identified unusual call activity, that the phone number will be used for fraud.