Predicting whether a party will purchase a product

Abstract

A method for predicting whether a party will purchase a product. The method includes accessing data wherein the data is obtained from a plurality of computing environments of a plurality of parties, analyzing the data; and predicting whether one of the plurality of parties will purchase a product based on the analyzed data.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method for predicting revenue generation, the method comprising:
 accessing data associated with two or more computing environments from two or more computing devices, wherein the data is collected by an executable of a scan utility stored on temporary storage of the computing devices, and each computing environment of the two or more computing environments is associated with a party of a plurality of parties;   based on the accessed data, identifying a parameter that facilitates in prediction of revenue generation using a machine learning model;   determining a value for the parameter for each party of the plurality of parties;   clustering a subset of the plurality of parties into a cluster based on the determined values for the parameter;   identifying a difference in a status of an application between a first party of the subset and two or more remaining parties of the subset; and   predicting that the first party will purchase a product or accept an upsell offer associated with the product when the purchase or the upsell eliminates the difference in the status of the application between the first party and the two or more remaining parties.   
     
     
         22 . The method of  claim 21 , wherein:
 the product is associated with the application;   one or both of the application and the product are provided by a vendor; and   the subset of the plurality of parties are users of the product.   
     
     
         23 . The method of  claim 21 , further comprising communicating the scan utility directly to an agent of the two or more computing devices, wherein the scan utility is configured to be cached and reused on a subsequent execution. 
     
     
         24 . The method of  claim 21 , wherein each computing environment of the two or more computing environments includes one or more or a combination of:
 a set of machines;   a set of applications; and   a set of networks.   
     
     
         25 . The method of  claim 21 , wherein each party of the subset included in the cluster have a value for the parameter that is within a predefined difference to the values for the parameters of other parties in the subset. 
     
     
         26 . The method of  claim 21 , further comprising prioritizing an offer for a purchase the product or an upsell directed to the first party over other offers to other parties of the subset. 
     
     
         27 . The method of  claim 21 , wherein:
 the difference between in status between the first party and the remaining parties is a first difference in a first status; and   the method further comprises:
 identifying a second difference in a second status of the application between a second party of the subset and the two or more remaining parties of the subset; 
 predicting that the second party will purchase the product or accept an upsell offer associated with the product based on the second difference; and 
 responsive to the first difference being less than the second difference, determining that it is more likely that the first party will purchase the product or accept the upsell offer than the second party. 
   
     
     
         28 . The method of  claim 21 , wherein:
 the difference between in status between the first party and the remaining parties is a first difference in a first status; and   the method further comprises:
 identifying a second difference in a second status of the application between a second party of the subset and the two or more remaining parties of the subset; 
 predicting that the second party will purchase the product or accept an upsell offer associated with the product based on the second difference; and 
 responsive to the first difference being less than the second difference, prioritizing a first offer for a purchase the product or an upsell directed to the first party over a second offer for a purchase the product or an upsell directed to the second party. 
   
     
     
         29 . The method of  claim 21 , wherein the parameter includes:
 a number of hypervisors on a network of an environment of the two or more computing environments;   a number of virtual machines of an environment of the two or more computing environments; or   a number of users in company associated with one of the parties of the plurality of parties.   
     
     
         30 . The method of  claim 21 , further comprising automatically providing a notification of the prediction to one or both of a management team of a vendor and the first party. 
     
     
         31 . One or more non-transitory computer-readable media storing one or more programs that are configured, in response to execution by one or more processors, to cause a system to execute or control execution of operations comprising:
 accessing data associated with two or more computing environments from two or more computing devices, wherein the data is collected by an executable of a scan utility stored on temporary storage of the computing devices, and each computing environment of the two or more computing environments is associated with a party of a plurality of parties;   based on the accessed data, identifying a parameter that facilitates in prediction of revenue generation using a machine learning model;   determining a value for the parameter for each party of the plurality of parties;   clustering a subset of the plurality of parties into a cluster based on the determined values for the parameter;   identifying a difference in a status of an application between a first party of the subset and two or more remaining parties of the subset; and   predicting that the first party will purchase a product or accept an upsell offer associated with the product when the purchase or the upsell eliminates the difference in the status of the application between the first party and the two or more remaining parties.   
     
     
         32 . The one or more non-transitory computer-readable media of  claim 31 , wherein:
 the product is associated with the application;   one or both of the application and the product are provided by a vendor; and   the subset of the plurality of parties are users of the product.   
     
     
         33 . The one or more non-transitory computer-readable media of  claim 31 , wherein:
 the operations further comprise communicating the scan utility directly to an agent of the two or more computing devices; and   the scan utility is configured to be cached and reused on a subsequent execution.   
     
     
         34 . The one or more non-transitory computer-readable media of  claim 31 , wherein each computing environment of the two or more computing environments includes one or more or a combination of:
 a set of machines;   a set of applications; and   a set of networks.   
     
     
         35 . The one or more non-transitory computer-readable media of  claim 31 , wherein each party of the subset included in the cluster have a value for the parameter that is within a predefined difference to the values for the parameters of other parties in the subset. 
     
     
         36 . The one or more non-transitory computer-readable media of  claim 31 , wherein the operations further comprise prioritizing an offer for a purchase the product or an upsell directed to the first party over other offers to other parties of the subset. 
     
     
         37 . The one or more non-transitory computer-readable media of  claim 31 , wherein:
 the difference between in status between the first party and the remaining parties is a first difference in a first status; and   the operations further comprise:
 identifying a second difference in a second status of the application between a second party of the subset and the two or more remaining parties of the subset; 
 predicting that the second party will purchase the product or accept an upsell offer associated with the product based on the second difference; and 
 responsive to the first difference being less than the second difference, determining that it is more likely that the first party will purchase the product or accept the upsell offer than the second party. 
   
     
     
         38 . The one or more non-transitory computer-readable media of  claim 31 , wherein:
 the difference between in status between the first party and the remaining parties is a first difference in a first status; and   the operations further comprise:
 identifying a second difference in a second status of the application between a second party of the subset and the two or more remaining parties of the subset; 
 predicting that the second party will purchase the product or accept an upsell offer associated with the product based on the second difference; and 
 responsive to the first difference being less than the second difference, prioritizing a first offer for a purchase the product or an upsell directed to the first party over a second offer for a purchase the product or an upsell directed to the second party. 
   
     
     
         39 . The one or more non-transitory computer-readable media of  claim 31 , wherein the parameter includes:
 a number of hypervisors on a network of an environment of the two or more computing environments;   a number of virtual machines of an environment of the two or more computing environments; or   a number of users in company associated with one of the parties of the plurality of parties.   
     
     
         40 . The one or more non-transitory computer-readable media of  claim 31 , wherein the operations further comprise automatically providing a notification of the prediction to one or both of a management team of a vendor and the first party.