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Communications, Media, and Energy (CME)
Communications, Media and Energy industry-specific analytics dashboards and pages are shown in Table 27.
Table 27. Communications, Media and Energy Dashboards and Page Tabs Dashboard Page Function Loyalty Management Customer Lifetime Value Segments customers based upon defined ranges of scores predicting customer lifetime value. Churn Propensity Segments customers based on defined ranges of scores estimating churn propensity. Selling Propensity Segments customers based on defined ranges of scores valuing the potential of up-sell and cross-sell opportunities. Financial Risk Segments customers based on defined ranges of scores predicting financial risk. Actual Churn Shows trending of actual customer churn, and actual customer acquisition, over time. Revenue Management Revenue Trends Charts trends of order revenue and order volume over time, and identifies top products based on order revenue and volume. Service Activations Charts trends of service activations over time, and indicates top service activations based on order revenue and volume. Service Modifications Charts trends of service modifications over time, and indicates top service modifications based on order revenue and volume. Service Disconnections Charts trends of service disconnections over time, and identifies services with the highest disconnection volume. Account Management Sales Portal Identifies top accounts, and related top products, based upon order revenue and order volume. Service Activations Charts trends of account service activations, and indicates top accounts based on service activation performance metrics. Service Modifications Charts trends of account service modifications, and indicates top accounts based on service modification performance metrics. Service Disconnections Charts trends of account service disconnections, and identifies accounts with the highest volume of disconnections. Trouble Tickets Provides trouble ticket trending charts, and performance indicators, for particular accounts, and for accounts with selected common characteristics. Customer Satisfaction Provides customer satisfaction trending charts, and performance indicators, for particular accounts, and for accounts with selected common characteristics.
To support these industry-specific dashboards, Communications, Media and Energy (CME) Analytics contains corresponding industry-specific metadata. In the Siebel Analytics Administration Tool, industry-specific metadata is flagged with an icon picturing a telephone. Although this icon is visible in the Administration Tool, it is neither visible nor included within Siebel Answers. End-users employ Siebel Answers to access metadata for building queries and reports. For users of Siebel Answers to view and access CME metadata columns, they must login to Siebel using one of the CME responsibilities listed in Table 10. These responsibilities also determine what subject areas the user may access.
The data requirements for each of the Communications, Media and Energy dashboards are detailed in Table 28.
Table 28. Data Requirements for Communications, Media and Energy Dashboards Dashboard Function Loyalty Management This dashboard uses customer scores generated from any 3rd party predictive modeling application offering the following predictive models: Customer Lifetime Value, Churn Propensity, Up-Sell Propensity, Cross-Sell Propensity, and Financial Risk Propensity. Scores must be generated for each Siebel Account, integrated into the Siebel Transaction Database, and then written to the Siebel Data Warehouse. This dashboard uses the Siebel Analytics Customers subject area. See Predictive Analytics Metadata for more information. Revenue Management This dashboard uses data generated by Siebel Communications, Media and Energy order management and interactive selling functionality. No specific data requirements are required beyond the data generated from these Siebel modules. This dashboard uses the Siebel Analytics Orders and Products subject areas. Account Management This dashboard uses data generated by Siebel Communications, Media and Energy order management, interactive selling, and service functionality. No specific data requirements are required beyond the data generated from these Siebel modules. This dashboard uses the Siebel Analytics Orders, Products, Service Request and Customer Satisfaction subject areas.
Predictive Analytics Metadata
The Loyalty Management Dashboard and several Siebel Analytics subject areas use customer scores generated from a third-party predictive modeling application. A predictive modeling application uses mathematical models to predict customer behavior. For customer scoring to be made available for analysis in Siebel Analytics, CME metadata is provided which maps these customer scores to dashboards and subject areas. Relevant predictive scores available include:
To facilitate customer segmentation in Siebel Analytics, the following metadata fields group these scores into score ranges:
- Churn Score Range
- Customer Value Score Range
- Upsell Score Range
- Cross-Sell Score Range
- Financial Risk Score Range
While the majority of predictive analytics metadata resides in the Customers subject area, some of it resides in other subject areas as well.
The process of developing and deploying these predictive scores is as follows:
- Generate these scores using any third-party predictive modeling application. This is performed outside of the Siebel operational application.
- Integrate the scores into the Siebel transactional database. Once this is completed, scores may be viewed in the Siebel operational application by accessing the Accounts > Profiles > Loyalty Profile view.
- Load the integrated scores into the Siebel Data Warehouse during the extraction, transformation, and loading (ETL) process.
- Once these scores are loaded into the Siebel Data Warehouse, they are mapped to the following Siebel Analytics metadata fields:
- Churn Score
- Customer Lifetime Value Score
- Upsell Score
- Cross-Sell Score
- Financial Risk Score
In conjunction with other associated metadata, these fields are primarily used to populate the Loyalty Management dashboard.
Other CME Metadata
Other metadata unique to CME are:
- Account Class
- Revenue Type
- Service Type
- Product Type
- Price Type
- Action Type (for Quote and Order line items)
- CME Order # of Occurrences
- CME Quote # of Occurrences
Order Management Analytics Considerations
Siebel Communications, Media and Energy (CME) makes use of order management functionality configured for CME. For Siebel CME Analytics to fully reflect the information collected by CME order management functionality, some extensions to the Siebel CME Analytics application may be required. This section explains these potential extensions.
NOTE: For more information, see release notes documentation for Siebel Communication, Media and Energy Analytics, and Siebel Interactive Selling Suite Analytics.
Siebel Sales Orders include complex products and simple products.
Complex products are comprised of a series of products, related by a product hierarchy. The highest product in the hierarchy is the root product, and the lower level products are the child products. In complex products, revenue figures are summed and roll-up to the root product using the ROLLUP_NET_PRI field. For a complex product, Siebel Analytics examines only the root product when computing revenue. Child products are disregarded because their revenue is already reflected in the root.
Simple products by nature include only a root product. Siebel Analytics examines this root product when computing revenue, and nothing more.
Siebel Communications, Media and Energy order management functionality supports products which have recurring charges over time (for example, $20 per month for 12 months), one-time charges (for example, one-time purchase price of equipment), and usage charges (for example, 15 cents per minute).
The revenue attributed to a product with recurring charges is valued by taking the product's net price and multiplying it by the number of months that product is anticipated to be active, as represented by the Number of Revenue Occurrences field. This field, contained in Quote Item and Order Item records, is contained in the Siebel Data Warehouse by the following fields:
In Siebel CME Analytics, revenue metrics do not automatically account for all recurring charges, and do not consider the NUM_OCCURRENCE fields. Instead, Siebel CME Analytics revenue metrics incorporate one-time charges, one-month's worth of recurring charges, and no usage charges. To incorporate the anticipated value of all recurring charges, the W_QUOTEITEM_F.NUM_OCCURRENCE and W_ORDERITEM_F.NUM_OCCURRENCE fields may need to be incorporated into revenue calculations made during the Extraction, Transformation and Load (ETL) process for order item and line item records.
Alternatively, these fields in the Siebel transactional database, representing the aggregated recurring and one-time product charges, may be used and incorporated into the ETL processes:
Each CME Order line item and Quote line item contains an Action Type of Add, Update, or Delete. Because Siebel Analytics only looks at root product line items, only the Action Types associated with the root product will be considered during analysis. Therefore, while all line items for a complex product may collectively include a combination of various Action Types, only the Action Type for the root product will be considered during analysis. This is of special importance if a filter or query criteria in analysis is based on the Action Type field, which it is for most Account Management and Revenue Management dashboard reports.
Similarly, each CME Order line item and Quote line item is associated with a product of a particular Price Type. Because Siebel Analytics considers root products only, only the Price Type associated with the root product is considered during analysis. Again, this is important if a filter or query criteria is based on Price Type. Such filter criteria apply to most Account Management and Revenue Management dashboard reports.
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Siebel Analytics Installation and Configuration Guide, Version 7.5, Rev. C
Published: 18 April 2003