US 20070118419 A1
Systems and methods are provided for analyzing a business's profitability. A system for analyzing customer profitability includes an interface for receiving customer, revenue and cost data from external business operating systems. Customer, revenue, and cost data are stored on a database. A data transformation module operates on the customer data, allocating revenue and costs to individual customers. A customer profitability engine calculates the profitability of customers based on the allocated revenue and cost data. A report module generates reports illustrating the profitability results and other key performance indicators. Optionally, an average customer lifetime value may be calculated based on the customer profitability results. A method for analyzing customer profitability includes identifying sources of revenue, identifying sources of costs, and establishing rules for allocating revenue and costs to individual customers. The method further includes receiving actual customer, revenue and cost data and allocating revenue and costs to individual customers according to the allocation rules. Customer profitability and KPI values are calculated for individual customers and reports are generated illustrating the profitability results and various KPIs for individual customers or groups of customers sharing a common characteristic.
1. A computer based system for analyzing profitability comprising:
a database (158);
an interface (152) for receiving customer data, revenue data and cost data from one or more business operating systems for storage in the database;
a data transformation module (154) associated with the database adapted to operate on the customer data, cost data and revenue data received from the one or more business operating systems, the data transformation module including instructions for allocating specific costs and revenue to individual customers according allocation rules, and storing the transformed data in the database;
a customer profitability module (160) adapted to operate on the transformed customer data, cost data and revenue data to calculate a customer profitability value for individual customers, based on the costs and revenue allocated to the individual customers;
a report module (164) for generating a report illustrating an key performance indicator relating to customer profitability.
2. The computer based system of
3. The computer based system of
4. The computer based system of
5. The computer based system of
6. The computer based system of
7. The computer based system of
8. A method to be implemented in a business systems environment in which a customer profitability data mart is interfaced with business operating systems including a customer billing system, a customer relationship management system, and accounting systems and in which a graphical user interface (162) is provided for accessing data in the data mart, and a report module (164) is provided for generating reports based on data stored in the data mart (158) analyzing a business's profitability on a per customer basis, the method comprising
receiving (104) customer, revenue and cost data from the business operating systems interfaced with the data mart and storing the received data in the data mart;
allocating (110) revenue and cost data to individual customers according to allocation rules;
calculating (112) customer profitability for individual customers from the revenue and cost data allocated to said individual customers;
producing (118) a report analyzing customer profitability from a per customer basis.
9. The method of
10. The method of
11. The method of
12. The method of
average profitability; costs from each identified cost source; total costs; average cost per user; revenue from each identified revenue source; total revenue; average revenue per customer.
13. The method of
14. The method of
15. The method of
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17. The method of
18. A method (100) of analyzing customer profitability comprising:
identifying sources of revenue (102);
identifying (102) sources of costs;
establishing (104) rules for allocating revenue and costs to individual customers;
receiving (112) customer, revenue and cost data;
allocating (110) revenue and costs to individual customers according to said rules;
calculating (114) a customer profitability values for individual customers;
calculating (106) a key performance indicator value derived from at least one of the cost data, the revenue data, and the customer profitability values; and
generating (118) a report displaying one of a customer profitability value and a key performance indicator value.
19. The method of
the cost associated with an identified cost source; total costs; average cost per customer; the revenue associated with an identified revenue source; total revenue; average revenue per customer; total profitability; and average profitability.
20. The method of
21. The method of
22. The method of
23. The method of
24. The method of
25. The method of
26. The method of
27. The method of
28. The method of
defining a group of customers based on a common attribute;
calculating (116) an average customer lifetime value for members of the group based on the profitability of customers in the group and an average expected duration of a relationship with a customer in the group.
29. The method of
This application claims the benefit of EPO Application No. ______, filed ______ assigned attorney docket number 10022-663 and Italian Application No. BS2005A000144, filed Nov. 21, 2005 assigned attorney docket number 10022-723, both of which are incorporated herein by reference in their entirety.
1. Technical Field
The present invention relates to systems and methods for analyzing a business's profitability on a customer-by-customer basis.
2. Background Information
Profit is the fundamental measure of a business's success. Improving profits is the key to improving business performance. Most businesses monitor profits based on the products or services they sell. Under this model profits are calculated by subtracting the costs associated with producing and distributing a product, or providing a service, from the revenue generated by the sale of the product or service. Underperforming products or services are easily identified by their low profitability. Once under performing products or services are identified, steps may be taken to improve their performance. For example, the price of a product or service may be raised in order to increase revenue, or production or delivery processes may be improved to maximize efficiencies and reduce costs. Alternatively, poorly performing products and services may simply be discontinued, leaving the business to concentrate its efforts on more profitable ventures.
Analyzing the profits generated by individual products and services, however, only provides a portion of the overall profitability picture. Products and services are consumed by customers. For numerous and varied reasons some customers may be more profitable than others. For example, a company in the business of providing telecommunications services may have several different types of customers. Some may be business customers and some may be residential customers, some may be heavy talkers who use their telephones often, while others rarely use their phones at all. Still others may be moderate chatters falling somewhere inbetween. Furthermore, different customers may subscribe to different service plans. Some may pay for large blocks of minutes each month, while others may purchase smaller blocks of access time but are required to pay additional fees if they go over their allotted time. Some customers may purchase pre-paid phone cards, while others are billed for their usage at the end of each month. All of these factors and more may contribute to the overall profitability of individual customers such that some customers are more profitable than others.
Due to the large number of variables involved, it is not easy to predict or determine which customers will be the most profitable. Often the answer is not intuitive. For example, heavy talkers may pay higher monthly fees for more minutes of access each month than do moderate chatters. Thus, one might be led to believe that heavy talkers would be more profitable than moderate chatters. However, heavy talkers may initiate many more calls to parties outside the service provider's network, incurring termination fees that must be paid to other telecommunications service providers. These additional fees are costs that reduce profits to the point where heavy talkers may be less profitable than moderate chatters. This is useful information for the telecommunications service provider to know. Steps taken to increase usage by customers who rarely use their phones may have a more significant impact on overall profitability than efforts to increase the usage of moderate chatterers. Such business intelligence provides a clear direction for future marketing campaigns.
Analyzing the profitability of individual customers and groups of customers can provide valuable business intelligence to a telecommunications service provider or operators of other types of businesses. Knowing who a business's most profitable customers are, and who are the least profitable allows an organization to allocate marketing, sales, product development and customer service efforts and resources according to the potential value provided by individual customers or classes of customers.
Heretofore the complexities of allocating heterogeneous costs and revenues to individual customers have prevented businesses from determining the profitability and value of individual customers within the business's customer base. The lack of such systems has prevented businesses from organizing their customer relationship efforts on an individual customer value basis. When data identifying customers who are the most profitable and those who not are available, almost every aspect of the customer relationship can be refocused. Businesses can identify which customers must be given the highest priority in order to retain high profit customers. Likewise, businesses can determine which customers are the least profitable and who are not worth extensive customer service efforts to keep satisfied. When combined with various customer attribute data such as service plans, type of customer, market segment, and the like, the insights into the sources of profitability can be enlightening and profound.
The present invention provides systems and methods for analyzing customer profitability on a customer-by-customer bases. According the invention the sources of a business's costs and revenues are defined. Rules are established for allocating the revenue and costs to the business's individual customers. Customer, cost and revenue data are received from the business's operating systems and profitability is analyzed based on the profitability of individual customers. First, the revenue and cost data are allocated to individual customers based on the established allocation rules. Once the revenue and costs have been allocated, the profitability for individual customers is calculated by subtracting the costs allocated to a customer from the revenue allocated to the customer. Additional key performance indicators (KPIs) may be defined and calculated based on the revenue and cost data as well as the profitability results. Finally, reports are generated for displaying the profitability results. The results may be presented in multiple different ways. Reports may compare and contrast the profitability results and KPIs for different customer segments, market segments, profitability tiers, geographical regions, different products or service packages, different sales channels and so forth.
According to an embodiment of the invention a computer based system for analyzing profitability is provided. The system includes a database adapted to receive and store various data including customer data, revenue data and cost data. An interface is provided for receiving the customer data, revenue data and cost data from one or more external business operating systems for storage in the database. A data transformation module associated with the database is adapted to operate on the customer data, cost data and revenue data received from the one or more business operating systems. The data transformation module includes instructions for allocating costs and revenue to individual customers according predefined allocation rules. The transformed data are again stored in the database. A customer profitability module is provided and is adapted to operate on the transformed customer data, cost data and revenue data. The customer profitability engine calculates the customer profitability of individual customers, based on the costs and revenue allocated to the customers, and calculates KPIs derived from the customer, cost and revenue data. Finally, a report module is provided for generating reports illustrating the customer profitability and the various KPIs. Multiple different KPIs and customer attributes may be selected in order to display data from many different vantage points, offering a flexible, insightful view of customer profitability.
According to another aspect of the invention a method of analyzing profitability is provided. The method is intended to be implemented in a business systems environment in which a customer profitability data mart is interfaced with business operating systems including a customer billing system, a customer relationship management system, and accounting systems. The systems environment further includes a graphical user interface for accessing data in the data mart and defining KPIs. A report module is provided for generating reports based on data stored in the data mart. The predefined reports analyze the business's profitability from a customer-by-customer perspective. The method involves receiving customer, revenue and cost data from the business operating systems interfaced with the data mart and storing the received data in the data mart. The received revenue and cost data are allocated to individual customers according to predefined allocation rules. Customer profitability and KPIs are calculated for individual customers from the revenue and cost data allocated to the individual customers. The profitability results and KPIs are then used to populate reports that are produced for purposes of analyzing customer profitability results. Optionally, an average customer lifetime value may be calculated for statistically significant customer populations. The customer lifetime value calculations may be run again and again with different input parameters in order to test how various changes in operating conditions or profitability performance may impact customer value and long term profitability.
Finally, according to another aspect of the invention, a method of analyzing customer profitability involves identifying sources of revenue, identifying sources of costs, and establishing rules for allocating the revenue and costs to individual customers. The method further involves receiving customer, revenue and cost data. Typically these data will be collected from external business operating systems. Next, the received revenue and cost data are allocated to individual customers according to the established allocation rules. Customer profitability and key performance indicators are calculated for individual customers. The customer profitability is calculated based on the revenue and cost data allocated to each customer. The KPIs are derived from various combinations of the revenue and cost data. Finally, one or more reports are generated displaying various combinations of profitability results and KPIs.
The present invention relates to customer focused systems and methods for analyzing a business's profits. The systems and methods of the invention glean business intelligence from operating data that may be used to improve a business's profit performance. The systems and methods allow a business to identify its most profitable customers and identify characteristics of both profitable and non-profitable customers alike. Such analysis can assist the business with strategic decision making and resource allocation in order to improve overall profitability. Business goals supported by such a customer-centric profitability analysis include optimizing profits from existing customers, retaining profitable customers, and increasing the ranks of a business's most profitable customers.
Analyzing profitability from a customer-centric point of view poses a number of significant technical challenges. In order to perform the most wide ranging and thorough analysis possible, it is necessary gather copious amounts of data from widely disparate sources. Furthermore, the data must be manipulated and stored in a manner such the data may be substantially instantly aggregated or individualized or segmented as necessary according to the requirements of a user, and the substantially instantly aggregated, individualized or segmented data must be presented to a user in a coherent form. This requires interfaces, data structures, and processing modules which, until the present invention, were unavailable to those of ordinary skill in the art who would build and use such a business intelligence system. Furthermore, such a system must implement and execute sophisticated revenue and cost allocation rules previously unknown in the industry. Only when the necessary data are collected and stored in an appropriate manner can the revenue and cost data, and thus the profitability data associated with individual customers, be thoroughly and efficiently analyzed for a substantial customer base. Similarly, only when the appropriate data are properly analyzed and stored may they be effectively accessed to meet the online analytical processing requirements of a user seeking to probe the profitability data from multiple perspectives. For this, a novel reporting module capable of identifying and retrieving the necessary data and displaying the data in various report formats “on-the-fly” is required. Combining these elements in the unique manner of the present invention provides a complete end-to-end business intelligence system for analyzing customer profitability.
Revenue and cost data are collected at 108. Once the revenue and cost data are collected they are allocated to individual customers at 110. The allocation of the revenue and costs is conducted in accordance with the allocation rules established at 104. The profitability values and KPIs are then calculated at 114. Optionally a customer lifetime value (CLV) may be calculated at 116. The CLV provides an estimate of the net present value of the profits that will be generated from a relationship with a customer over the expected life of the relationship. The CLV uses statistical modeling and past results to predict the behavior of customers in the future. Accordingly, a statistically significant customer sample must be defined prior to the CLV calculation. Customer attribute data are received at 112. Customer segments and sub-segments may be defined based on customers having common attributes. The CLV calculations may be performed for customers in various customer segments. Sequentially, the timing of the customer data collection is unimportant. The only requirement is that the data must be collected before the various customer segments can be defined and the CLV calculated.
In any case, whether the CLV is calculated at 116 or not, the results of the profitability analysis are compiled into reports at 118. Many of the most useful and enlightening reports will display the customer profitability and other KPIs against one another for various customer segments. The various criteria for dissecting the customer population may be obtained from the customer data received at 112. Finally, the reports are displayed for a business intelligence consumer at 120.
Data are received by the Data Mart 158 via a data feeding module 152. The data feeding module operates as an interface to the business's various external operating systems, such as the accounting systems, billing/invoice systems, marketing systems, customer relationship management systems, and other operating systems in which customer, cost and revenue data are generated. The data feeding module 152 defines the data to be extracted from the external systems and forces the external systems to supply the data in a format consistent with storage and indexing requirements of the data mart 158. The raw data received from the data feeding module 152 include all customer data, revenue data, and cost data necessary to perform the customer profitability analysis and generate the desired reports.
A data transformation module 154 implements the revenue and cost allocation rules. The data transformation module 154 accesses the customer, revenue, and cost data stored in the data mart 158 and processes the received data, assigning costs and revenue to individual customers on a customer-by-customer basis. The transformed data are also stored in the data mart 158.
A customer profitability engine 160 operates on the transformed data and calculates the profitability of customers individually and calculates the KPIs. Again the data output from the customer profitability engine 160 are stored in the data mart 158.
A graphical user interface (GUI) 162 provides user access to the data mart 158. The GUI 162 allows a user to create, modify, and delete KPI records, and selectively view profitability and KPI values stored in the data mart 158. Through the User Interface, the profitability data mart may be explored by predefined KPI, customer ID, customer segment and time (by month). The GUI provides online active processing (OLAP) that allows a user to “drill down” through the data to gain valuable insight into the sources of profitability and the areas that need improvement.
A customer relationship management system (CRM) 156 is also shown as part of the customer profitability analysis system 150. The CRM 156 is not actually involved in the calculation or analysis of the customer profitability analysis, but may be a consumer of the customer profitability results. The CRM 156 pulls customer profitability data from the profitability data mart 158. The CRM may use such data for numerous purposes, such as determining the effectiveness and value of its customer relations efforts, or tailoring its relationship management efforts to individual customers' profitability. For example, customer relations management efforts may be designed such that the most profitable customers receive the most attention, while less profitable customers are given lower priority. Other operating systems in the enterprise can also consume the customer profitability information.
A reporting module 164 is provided to generate a plurality of predefined reports 166. The reports are created to display the customer profitability data in an organized insightful manner that allows a business intelligence consumer to quickly absorb the data and comprehend its import. The reports will typically contrast two or more KPIs dimensioned by some customer attribute. For example, a report may show customer profitability by customer profitability tier over a number of years in order to highlight profitability trends among various segments of the customer population. The reporting module 164 pulls the customer profitability data necessary to populate the various reports from the data mart 158 and generates the reports. The module may be a standard software package customized for interfacing with the profitability data mart and generating the reports. The reports 166 may be published as printed documents or as electronic pages accessible via the GUI 162 or some other interface module.
The system shown in
The CLV module 174 may be considered a web services client.
According to an embodiment of the invention, the CLV module 174 may be a spreadsheet document created using a commercial spreadsheet program such as Microsoft Excel. In this case the spread sheet includes a plurality of calculation macros for projecting historical profitability into the future. For example, the CLV spreadsheet may pull all of the aggregate historical profitability data for a statistically significant segment and/or sub-segment of the customer population, these data will include all elements of customer profitability, including all revenue and cost components. The macros in the CLV spreadsheet may calculate future trends from the historical data and apply such trends toward calculating future profitability. Alternatively, trend data may be altered by a business intelligence consumer in order to determine how steps taken to alter current trends may impact future profitability.
A simple example is best to illustrate the operation and power of the CLV module. Assume the CLV analysis is to be performed on a segment of the customer population comprising moderate chatters acquired in 2003, further assume that moderate chatters have historically had an average customer lifetime of 5 years. Since they have already been customers for two years in 2005, this group of customers can be expected to remain customers for 3 more years until 2008. Suppose the average current profitability of members of this market segment is
The CLV module 174 allows a business intelligence consumer to alter data and trends in order to determine the effects various changes will have on future profitability. For example a business intelligence consumer may wish to explore the potential effects of a prospective marketing campaign to a group of customers. The average cost of the campaign may be for example
The client-server architecture of the web services module 172 is shown in
An embodiment of the invention is specially adapted for analyzing the customer profitability of a telecommunications service provider. According to this embodiment, the initial step of identifying revenue and cost sources 102 from the flow chart 100 in
A second source of revenue for telecommunications service providers is interconnection fees. Calls are often made between parties who subscribe to different telecommunications service providers. When a first party using a first telecommunications service provider places a call to a second party who uses a second telecommunications service provider, the first telecommunications service provider must pay a fee to the second telecommunications service provider for providing the service of terminating the call with the second party. A result of these interconnection fees is that a customer who receives many calls from outside his or her service provider's network, but places few calls to parties outside the network, could be more profitable than a customer who receives few calls from outside the network but places many calls to parties outside the network. The fees associated with terminating calls originating outside a telecommunications service provider's network can constitute a significant source of revenue that affects profitability. The data relating to interconnection and termination fees (both the revenue associated with terminating calls made from outside the network and costs associated with calls to parties outside the network that must be terminated by others) may be received directly from the telecommunications service provider's network operating systems. The data must include the customer and the fee either received (revenue) or paid (cost) for terminating out of network calls.
On the opposite side of the ledger, many sources of costs have been identified relating to providing telecommunications services to customers. The various sources of costs which affect profitability may be grouped into related families of costs. Thus, there are costs associated with acquiring new customers (Subscriber Acquisition Costs or SAC); retaining existing customers (Subscriber Retention Costs or SRC); servicing customers' needs (Customer Care Costs); billing and accounting (Bureau Services Costs); and costs associated with termination fees paid to other telecommunications service providers for calls made outside the telecommunications service provider's network (Usage Costs).
Service Acquisitions Costs may include commissions paid to retailers and agents for signing new customers to various service plans and subsidies paid for purchasing or offsetting the cost of a customer's handset. There may me many different types of commissions and handset subsidies, resulting in different acquisition costs depending on the type of customer, the type of plan the customer subscribes to, and so forth. Factors that may influence the type and amount of a particular commission may include the service plan, the type of access, or the type of commission. The cost of various handset subsidies may be determined by the cost of handset, the type of access, and the particular service plan the customer subscribes to.
Customer retention costs may include the costs of marketing campaigns for contacting existing customers for the purpose of stimulating greater and more profitable usage, and loyalty programs aimed at enticing customers to stay with the telecommunications service provider when their contracts expire rather than defecting to competitors. The cost of marketing campaigns is governed by the cost of contacting individual customers over the desired communication channel, multiplied by the number of customers contacted. The cost of loyalty programs may be based on the costs of the awards given to customers when they elect to stay with the service provider.
Customer Care Costs are those costs associated with servicing the customer's needs beyond providing the basic telecommunications services called for in the customer's service plan. Specific cost sources within the Customer Care family of costs include call center operations, technical support, and processing service inquiries. Call center costs may be allocated based on the market segment a customer belongs to, the reason for a customer's call to the call center, and the number of calls made by the customer to the call center. Technical support costs may be based and the type of trouble ticket generated when a customer calls for technical support, or the trouble ticket area. The cost of service inquiries may be related to the particular service that is the subject of an inquiry.
Bureau Services costs include the costs of producing invoices and delivering them to customers. Bureau's services costs also include the cost of credit for late receipt of customer payments.
Finally, usage costs include the costs of termination services provided by other telecommunications service providers as well as the costs associated with using the telecommunications service provider's network. Typically service margins are expressed as a percentage of revenue. To determine the cost of a call the revenue from the call is multiplied by the service margin. The remainder is allocated to costs.
The embodiment adapted for analyzing the customer profitability of a telecommunications provider further includes predefined rules for allocating revenue and costs to individual customers. Again, these allocation rules have been developed based on common practices within the telecommunications industry. According to this embodiment, allocating revenue is relatively straightforward. Each customer's invoice charges may be allocated directly as revenue derived from the customer. Additional revenue based on the interconnection fees received for terminating calls received by the customer from outside the telecommunications service provider's network are also allocated to customers on a customer-by-customer basis.
The present embodiment employs activity based costing for allocating heterogeneous costs to individual customers. Under this procedure all activities that incur cost are identified and grouped together by activity type. Each activity within an activity type is defined by its own set of cost drivers. For example, customers may call a call center for many different reasons. Each call to the call center may be considered an activity within the same activity type. Nonetheless, the reason for a call to the call center may have a significant impact on the actual cost of handling the call. A customer call reporting a lost handset may be less expensive to process than a customer calling to dispute charges on his or her last billing statement. In other words, the reasons for the calls drive the cost. Thus, while all calls to a all center may be considered to be of the same activity type, each call is a separate activity based on the reason for the call. Each pre-defined reason for a call center call may have its own set of costs associated with it. For example, in the scenario just described, a lower cost will be allocated to a customer calling a call center to report a lost phone and a higher cost allocated to a customer calling to dispute billing charges. Similar cost allocation provisions may be made for other activities and activity types as well. For example, paying commissions may be an activity type. Multiple different commissions may be paid depending on the circumstances surrounding the acquisition of a new subscriber. Payment of each different commission comprises a separate activity having a distinct cost associated with it. One or more costing activities are defined for each cost source described above. Each time an activity is performed in relation to a customer, the cost associated with the activity is allocated to the customer.
With regard to step 106 of the flowchart 100 of
Referring now to the system 150 shown in the block diagram of
The data feeding module may likewise interface directly with the telecommunications service provider's other external systems to collect cost data. Preferably the data feeding module 154 collects the cost data directly from the systems in which the data are created. For example, the data feeding module 154 may interface directly with the telecommunications service provider's ERP system in order to collect subscriber acquisition costs. Subscriber retention costs may be received from Campaign Management systems. Call center, technical service and service inquiries data may be received from Customer Relations Management systems 156. The Bureau Services costs may be received from ERP systems. Finally, usage cost data may be received from Billing, Interconnection or other specialized systems. In all cases the interfaces between the various systems supplying the information and the data feeding module are such that all data necessary to identify and allocate the revenue and cost data are provided in a manner consistent with the requirements of the system and for storage in the profitability data mart 158.
In addition to cost and revenue data, customer attribute data may also be stored in the profitability data mart 158. Like the cost and revenue data, the customer attribute data may be collected directly from the systems that create the data, or wherever the customer attribute data are typically stored. For Example, customer attribute data may be received from customer intake systems that are invoked when a new customer is acquired, or from CRM systems which store customer data. Additional attributes may be derived from the customer profitability analysis itself. Alternatively, customer attribute data may be received from a data warehouse or other application. A robust set of customer attributes allows customer profitability to be analyzed from multiple vantage points, such as across different market segments, different subscriber types, geographical regions, profitability tiers, age groups, and the like. The reporting module 164 uses the attribute data to filter the profitability KPIs to create meaningful reports that show the differences between different classes of customers.
The GUI 162 may be for example, a web based intranet site.
The KPI section, in addition to allowing the user to add, modify and delete KPI records and corresponding items, also allows the user to view the profitability information.
A logs page 400 is shown in
Finally, an access reports page 410 is shown in
In the embodiment of the invention relating to analyzing the customer profitability of a telecommunications service provider's customer base, a number of standard reports have been defined. The standard reports incorporate customer profitability, KPIs and customer attributes that are known to be of interest to those who seek insight into the profitability of telecommunications companies.
Before describing the reports themselves it is beneficial to review the KPIs and introduce the customer attributes on which the reports are based. Among the most useful attributes for classifying telecommunications customers is their usage patterns. Accordingly, for purposes of the present embodiment telecommunications customers have been grouped into five segments, or tiers: big spenders; heavy talkers; moderate chatters; casual callers; and safety users. The segment or tier in which a particular customer falls may be determined by the actual number of minutes the customer uses each month, the average number of minutes the customer uses each month, or some other measure. Of course, if desired more or fewer segments or tiers may be defined and other divisions made amongst the various customer segments or tiers.
Another useful attribute is subscriber type. Telecommunications service providers typically offer multiple service plans. Customers may be grouped according to the type of plan that they have subscribed to. The service plans offered by different telecommunications service providers will generally vary from one service provider to another. For purposes of the present description, customers will be grouped according to generic subscriber types A, B, C, D, and E. Of course, the number of subscriber types and their actual designations will differ according to the service plan offerings of particular telecommunications service providers
Yet another customer attribute that may be used to categorize customers is the market segment to which the customer belongs. For example, customers may be identified as either business customers or residential customers. Other market segments may also be defined depending upon the needs and customer base of a particular telecommunications service provider.
Some telecommunications service providers offer discount plans to entice customers to subscribe their service offerings. In such cases, the discount is typically expressed as a percentage of the normal service rates of the particular plan for which the discount is offered. The customer discount is another attribute by which the customers may be classified for purposes of analyzing profitability. Additional attributes by which a telecommunications service provider's customer base may be broken down may include the sales channel through which a customer relationship was established, and the types of seller or agent who secured the relationship.
In addition to customer attributes, it is also desirable to analyze profitability in terms of various operational parameters. For example, it may be desirable to measure the effectiveness of marketing campaigns by measuring their effect on profitability. Similarly, it may be desirable to measure the effectiveness (and costs) of customer service efforts by taking customer profitability into account. Useful data from a marketing campaign may include the list of customers contacted during the campaign (and all the attributes associated with the customers contacted); the number of calls made during the campaign; the number of calls answered during the campaign; the number of calls in which the customer answered but hung up before listening to the promotion, and so forth. Customer service data may include the number of calls made to a call center; the identities of the customers placing the calls (and all the attributes characterizing the customers making the calls); the reasons for the calls; the duration of the calls; and the amount of time the customer waited before reaching a call center operator. For technical service requests useful data may include the number of trouble tickets initiated; the identities of the customers who have initiated trouble tickets; (and all the attributes characterizing the customers); and the technical service areas to which the trouble tickets relate.
Finally, it may be beneficial to group customers in terms of the profitability results. Various profitability thresholds may be established, and customers whose profitability exceeds various thresholds may be classified as platinum, gold, silver, and bronze, for example, in rank order of their profitability.
Additional reports may be created as desired. For example, reports may be generated showing the highest profitability customers with no traffic for the previous month, or customers with the lowest profitability, and others.
The systems and methods of the invention, allow a business such as a telecommunications service provider to analyze virtually every aspect of customer profitability, comparing and contrasting all of the elements that contribute to profitability, and identifying characteristics and trends among its customer base that may otherwise go unnoticed. Using the analysis tools of the invention, a business may identify areas of strength and areas of weakness and direct resources accordingly either to maintain the areas of high profitability or increase their efforts in areas or customer segments where profitability lags.
While various embodiments of the invention have been described, it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the invention. Accordingly, the invention is not to be restricted except in light of the attached claims and their equivalents.