System and Method for Strategizing Interactions with a Client Base

Abstract

The present disclosure describes novel systems and methods that can be utilized to evaluate and/or direct an interaction with a consumer database and/or evaluate a consumer database, where the consumer database contains information about consumers and particular products and/or services held or used by the consumers. The interactions may be, for example, determining a strategy for sales, marketing, cross-selling, and/or retaining one or more of the consumers. The evaluations may include, for example, hierarchically ranking the consumers and/or determining a clustering of the consumers.

We claim: 
     
         1 . A non-volatile computer-readable storage medium containing a set of instructions that cause a computer processor to perform the steps of:
 (a) populating a computer database with first information about plural consumers and second information about predetermined products, wherein the plural consumers include a first consumer, and wherein each of the plural consumers is associated with a current product mix comprising certain ones of the predetermined products independent of an association of another consumer with the predetermined products;   (b) individually for each one of the plural consumers:
 (i) calculating an aggregate first Residual Life Time Value (“RLTV”) estimate from the time variable products in the current product mix for said one consumer; 
 (ii) calculating an aggregate second RLTV estimate from the finite duration products in the current product mix for said one consumer; 
 (iii) calculating an aggregate third RLTV estimate from the aggregate first RLTV estimate and from the aggregate second RLTV estimate; and 
 (iv) calculating an aggregate Potential Life Time Value (“PLTV”) estimate from preselected products not in the current product mix for said one consumer; 
   (c) analyzing a distribution of the aggregate third RLTV estimates for the plural consumers;   (d) analyzing a distribution of the aggregate PLTV estimates for the plural consumers;   (e) evaluating the first consumer as a function of the distribution of the third aggregate RLTV estimates and as a function of the distribution of the aggregate PLTV estimates; and   (f) determining an interaction strategy for the first consumer based on said evaluation of the first consumer.   
     
     
         2 . The storage medium of  claim 1  wherein the database is stratified into plural segments according to a predetermined criteria, and wherein each of the plural consumers is assigned to one of the plural segments according to the predetermined criteria. 
     
     
         3 . The storage medium of  claim 1  wherein the set of instructions further includes instructions for determining a matrix of values from the distribution of the aggregate third RLTV estimates for the plural consumers and from the distribution of the aggregate PLTV estimates for the plural consumers. 
     
     
         4 . The storage medium of  claim 3  wherein the matrix comprises N number of rows encompassing a first range of quantities for the distribution of the aggregate third RLTV estimates and M number of columns encompassing a second range of quantities for the distribution of the aggregate PLTV estimates thereby creating a matrix of X cells where X=N*M. 
     
     
         5 . The storage medium of  claim 4  wherein the first consumer is assigned to one of the X cells based at least in part on the evaluation of the first consumer. 
     
     
         6 . The storage medium of  claim 5  wherein the interaction with the first consumer is determined based at least in part on the cell assignment. 
     
     
         7 . The storage medium of  claim 5  wherein the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer are calculated at a first predetermined time and wherein the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer are recalculated at a second predetermined time. 
     
     
         8 . The storage medium of  claim 7  wherein the first consumer is assigned to one of the X cells based at least in part on the recalculated aggregate third RLTV estimate and the recalculated aggregate PLTV estimate. 
     
     
         9 . The storage medium of  claim 8  wherein the interaction with the first consumer is determined based at least in part on a difference between the cell assignment of the first consumer based at least in part on the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer and the cell assignment of the first consumer based at least in part on the recalculated aggregate third RLTV estimate and the recalculated aggregate PLTV estimate. 
     
     
         10 . The storage medium of  claim 1  wherein the first consumer comprises a cluster of consumers wherein each member of the cluster meets a predetermined criteria for inclusion in the cluster. 
     
     
         11 . The storage medium of  claim 1  wherein the interaction strategy for the first consumer is selected from the group consisting of: determining a sales strategy tailored for the first consumer, determining a cross-selling opportunity for the first consumer, determining a marketing strategy tailored for the first consumer, determining a strategy for retaining the first consumer, and combinations thereof. 
     
     
         12 . A non-volatile computer-readable storage medium containing a set of instructions that cause a computer processor to perform the steps of:
 (a) populating a computer database with first information about plural consumers and second information about predetermined products, wherein the plural consumers include a first consumer, and wherein each of the plural consumers is associated with a current product mix comprising certain ones of the predetermined products independent of an association of another consumer with the predetermined products;   (b) for a time variable product in the current product mix for a one of the plural consumers:
 (i) determining a baseline product survival curve; 
 (ii) determining a shift in the baseline product survival curve as a function of characteristics of said one consumer to thereby determine a consumer product survival curve; 
 (iii) calculating an area under the consumer product survival curve; 
 (iv) calculating an estimated potential residual profit from the calculated area to thereby determine a first Residual Life Time Value (“RLTV”) estimate for said time variable product for said one consumer; 
 (v) repeating steps (b)(i) through (b)(iv) for each time variable product in the current product mix for said one consumer; and 
 (vi) determining an aggregate first RLTV estimate for said one consumer from the first RLTV estimate for each said time variable product for said one consumer; 
   (c) repeating step (b) for each one of the plural consumers;   (d) for a finite duration product in the current product mix for a one of the plural consumers:
 (i) determining a remaining outstanding balance; 
 (ii) multiplying the remaining outstanding balance by a funds transfer pricing value for said finite duration product to determine an approximate residual value to thereby determine a second RLTV estimate for said finite duration product for said one consumer; 
 (iii) repeating steps (d)(i) through (d)(ii) for each finite duration product in the current product mix for said one consumer; and 
 (iv) determining an aggregate second RLTV estimate for said one consumer from the second RLTV estimate for each said finite duration product for said one consumer; 
   (e) repeating step (d) for each one of the plural consumers;   (f) individually for each of the plural consumers, determining an aggregate third RLTV estimate from that consumer's aggregate first RLTV estimate and from that consumer's aggregate second RLTV estimate;   (g) calculating the likelihood of a one of the plural consumers to acquire one or more of the predetermined products not in the current product mix for said one consumer;   (h) for a preselected product not in the current product mix of a one of the plural consumers:
 (i) determining a baseline product survival curve; 
 (ii) calculating an area under the baseline product survival curve; 
 (iii) calculating an estimated potential residual profit from the calculated area to thereby determine a Potential Life Time Value (“PLTV”) estimate for said preselected product for said one consumer; 
 (iv) repeating steps (h)(i) through (h)(iii) for each preselected product not in the current product mix for said one consumer; and 
 (v) determining an aggregate PLTV estimate for said one consumer from the PLTV estimate for each said preselected product for said one consumer; 
   (i) repeating steps (g) and (h) for each one of the plural consumers;   (j) analyzing a distribution of the aggregate third RLTV estimates for the plural consumers;   (k) analyzing a distribution of the aggregate PLTV estimates for the plural consumers;   (l) evaluating the first consumer as a function of the distribution of the third aggregate RLTV estimates and as a function of the distribution of the aggregate PLTV estimates; and   (m) determining an interaction strategy for the first consumer based on said evaluation of the first consumer.   
     
     
         13 . The storage medium of  claim 12  wherein the database is stratified into plural segments according to a predetermined criteria, and wherein each of the plural consumers is assigned to one of the plural segments according to the predetermined criteria. 
     
     
         14 . The storage medium of  claim 12  wherein determining the baseline product survival curve in step (b)(i) includes evaluating the second information about said predetermined product for ones of the plural consumers associated with said predetermined product. 
     
     
         15 . The storage medium of  claim 12  wherein the set of instructions further includes instructions for determining a matrix of values from the distribution of the aggregate third RLTV estimates for the plural consumers and from the distribution of the aggregate PLTV estimates for the plural consumers. 
     
     
         16 . The storage medium of  claim 15  wherein the matrix comprises N number of rows encompassing a first range of quantities for the distribution of the aggregate third RLTV estimates and M number of columns encompassing a second range of quantities for the distribution of the aggregate PLTV estimates thereby creating a matrix of X cells where X=N*M. 
     
     
         17 . The storage medium of  claim 16  wherein the first consumer is assigned to one of the X cells based at least in part on the evaluation of the first consumer. 
     
     
         18 . The storage medium of  claim 17  wherein the interaction with the first consumer is determined based at least in part on the cell assignment. 
     
     
         19 . The storage medium of  claim 12  wherein the first consumer comprises a cluster of consumers wherein each member of the cluster meets a predetermined criteria for inclusion in the cluster. 
     
     
         20 . The storage medium of  claim 20  wherein the interaction strategy for the first consumer is selected from the group consisting of: determining a sales strategy tailored for the first consumer, determining a cross-selling strategy for the first consumer, determining a marketing strategy tailored for the first consumer, determining a strategy for retaining the first consumer, and combinations thereof.