Profitability Analytics brings together cost, revenue and margin analytics to understand the profitability of subscribers, services, devices, rate plans and other entities measured from a revenue perspective. It is targeted aimed at finance professionals or other departments with profit-and-loss (P&L) responsibilities for areas such as roaming, interconnect access, or data services. Further, it is of value to market segment owners (prepaid, consumer, enterprise), product owners (data services, IPTV) or even device portfolio managers (iPhones, Blackberry) who need to measure the financial performance beyond the typical ARPU metrics, to incorporate cost and determine true business performance.
This analysis is performed at the transactional level (subject to the granularity of cost components) to determine the business impact of each customer interaction. Because all events are considered, these metrics go beyond averages and aggregates to allow analysis down to an individual session, subscriber, service, device, or any combination thereof.
By integrating with other Customer Analytic modules, it is possible to incorporate behavioral attributes (from the Profitability Analytics module) or quality metrics (from the Quality of Experience Analytics module) or to derive a more holistic financial view. For example, a highly popular service may in fact be incurring significant 3rd party costs, and should be trimmed back rather than expanded, or may warrant the development of an in-house equivalent.
- Ability to assign fixed and variable cost and revenue elements to the session level in order to determine true margins.
- 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
- Profitability analysis is extensible with behavioral and quality of experience attributes.
- Analytic environment for deeper investigation into individual customers, or group of customers with similar financial attributes.
- Subscriber Analytics: tracks usage, cost, revenue, and margin metrics at the subscriber level to understand the business contribution of each customer. This information provides a business metric to guide personalized corrective or retentive campaign.
- Device Analytics: tracks usage, cost, revenue, and margin metrics to understand the business contribution of each device, whether it is a handset, broadband data card, tablet, e-reader or any other device. By analyzing the various characteristics and form-factors of devices to identify and predict usage of particular services, generation of additional revenue (or costs), and helpw determine corrective actions for forecasting, cooperating and negotiating strategies with device manufacturers.
- Service Analytics: deliver analytics focused on service or content. By performing cost, revenue and margin analytics at the service level, it is possible to create new bundles or implement new services and partnerships to take advantage of customer preferences.