Behavioral Analytics paints a detailed picture of preferences and habits of like-minded individuals, accounts and customer segments. It analyzes subscribers’ consumption of content or services, including who, when, where, how much, and on what device. This digital interaction is cross-referenced with customer, device, service, network, location and business data to provide a true snapshot of a subscriber and customer groups. Conversely, the information may also be used to identify candidates for marketing campaigns based on their usage levels, consumption of particular services/content, use of certain devices, and other behaviors.
Behavioral Analytics is aimed at marketing professionals, such as product managers responsible for services, devices, rate plans and 3rd party content partnerships, as well as market campaign analysts.
By integrating with other Customer Analytic modules, it is possible to incorporate quality metrics (from the Quality of Experience Analytics module) or financial metrics (from the Profitability Analytics module) to derive a more holistic view of each customer. For example, a highly popular service may in fact be incurring significant 3rd party costs, and should be trimmed back rather than expanded. Similarly, a candidate who is likely to buy a new service may be removed from a campaign list if her profitability is low, or has significant usage in locations where coverage may be incomplete.
- Consolidated subscriber-level view of all calls, messages, web sessions, purchases, downloads and other digital interaction across all services and technologies: fixed, wireless, 4G, voice, messaging, and data.
- Multi-dimensional analytics puts the customer first, but also allows analytics at the aggregate level (e.g., accounts, customer segments). Complementary analytics on device, service and network-level, as well as any combination of the various dimensions.
- Contextual drill-down from customer profile down to specific events.
- Behavioral analysis is extensible with quality of experience and profitability attributes.
- Analytic environment for deeper investigation into individual customers, or group of customers with similar demographic or behavioral attributes.
- Subscriber Analytics: tracks usage and behavior down to the subscriber level to understand service or content consumption, including when, where, how much, and on what device, to paint a detailed picture of each subscriber’s activity.
- Device Analytics: provide analytics focused on device. With the increasing importance of devices, and the diverging characteristics and form-factors, it is possible to identify what type of consumers prefer them, what content is being accessed across locations and times. Such profiles can help shape future campaigns for converting users to new handsets (e.g., upgrading feature phone users to smartphones) or identify potential candidates for other devices (e.g., tablets, e-readers, etc).
- Service Analytics: deliver analytics focused on service or content. Gain the ability to understand and predict potential issues, inefficiencies and trends for both financial, marketing and network planning/forecasting strategies.