Intelligent prediction of future generation of types of data objects based on past growth
Disclosed are some implementations of systems, apparatus, methods, and computer program products for facilitating the prediction of the quantity and/or qualities of new data objects of a particular data object type to be generated based upon past generation of data objects of the particular data object type. Data that is used to generate predictions is obtained and filtered according to criteria that are configurable. In some implementations, the criteria indicate an industry for which predictions are generated, a geographic region for which predictions are generated, and/or time period criteria indicating a time period for which the predictions are generated. Predictions may be generated using a computer-generated model, which may be associated with the particular data object type.
1. A system comprising:
a database system providing customer relationship management (CRM) for an organization, the database system implemented using a server system, the database system configurable to cause:
providing a graphical user interface (GUI) for display by a client device, the GUI including user-selectable options for configuring a prediction engine;
obtaining, from the client device:
a designation of a contact data record as one of a plurality of CRM object types for which prediction is to be performed, the designation of the contact data record based on first user input submitted via one or more of the user-selectable options,
designations of prediction criteria based on second user input submitted via one or more of the user-selectable options, the designations of prediction criteria including at least a specified type of industry;
determining, according to the specified industry type, a length of time for periods of time used to predict generation of contact data records;
identifying, according to the designation of the contact data record, a set of contact data records in one or more data sources;
filtering the set of contact data records based, at least in part, upon the prediction criteria to identify two or more sets of data, each of the sets of data corresponding to a different period of time having the determined length of time, each of the sets of data being a respective subset of the set of contact data records that were generated during the corresponding period of time;
determining, from a first one of the sets of data, a first quantity of contact data records generated during a corresponding first period of time;
determining, from a second one of the sets of data, a second quantity of contact data records generated during a corresponding second period of time that is subsequent to the first period of time;
predicting a third quantity of contact data records to be generated during a third period of time according to the prediction criteria based, at least in part, on the first quantity of contact data records and the second quantity of contact data records; and
providing an indication of the third quantity of contact data records predicted to be generated during the third period of time according to the prediction criteria.
2. The system of claim 1 , wherein contact data records are configurable.
3. The system of claim 1 , the database system further configurable to cause:
predicting characteristics of individuals associated with the third quantity of contact data records based, at least in part, on the first set of data, the second set of data, and user profiles of individuals identified in the first and second sets of data.
4. The system of claim 1 , wherein predicting the third quantity of contact data records according to the prediction criteria is further based, at least in part, on social data, wherein the prediction criteria indicate at least one of: a source of the social data or a type of the social data.
5. The system of claim 1 , wherein predicting the third quantity of contact data records is further based, at least in part, on information pertaining to a product or service that has been released or is scheduled to be released.
6. The system of claim 1 , wherein predicting the third quantity of contact data records according to the prediction criteria is performed using a computer-generated model based, at least in part, on a first weight associated with the first quantity of contact data records and a second weight associated with the second quantity of contact data records.
7. A computer program product for providing customer relationship management (CRM) for an organization, the computer program product comprising computer-readable program code capable of being executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code comprising instructions configurable to cause:
providing a graphical user interface (GUI) for display by a client device, the GUI including user-selectable options for configuring a prediction engine;
obtaining, from the client device:
a designation of a contact data record as one of a plurality of CRM object types for which prediction is to be performed, the designation of the contact data record based on first user input submitted via one or more of the user-selectable options,
designations of prediction criteria based on second user input submitted via one or more of the user-selectable options, the designations of prediction criteria including at least a specified type of industry;
determining, according to the specified industry type, a length of time for periods of time used to predict generation of contact data records;
identifying, according to the designation of the contact data record, a set of contact data records in one or more data sources;
filtering the set of contact data records based, at least in part, upon the prediction criteria to identify two or more sets of data, each of the sets of data corresponding to a different period of time having the determined length of time, each of the sets of data being a respective subset of the set of contact data records that were generated during the corresponding period of time;
determining, from a first one of the sets of data, a first quantity of contact data records generated during a corresponding first period of time;
determining, from a second one of the sets of data, a second quantity of contact data records generated during a corresponding second period of time that is subsequent to the first period of time;
predicting a third quantity of contact data records to be generated during a third period of time according to the prediction criteria based, at least in part, on the first quantity of contact data records and the second quantity of contact data records; and
providing an indication of the third quantity of contact data records predicted to be generated during the third period of time according to the prediction criteria.
8. The computer program product of claim 7 , wherein contact data records are configurable.
9. The computer program product of claim 7 , the program code further comprising instructions configurable to cause:
predicting characteristics of individuals associated with the third quantity of contact data records based, at least in part, on the first set of data, the second set of data, and user profiles of individuals identified in the first and second sets of data.
10. The computer program product of claim 7 , wherein predicting the third quantity of contact data records according to the prediction criteria is further based, at least in part, on social data, wherein the prediction criteria indicate at least one of: a source of the social data or a type of the social data.
11. The computer program product of claim 7 , wherein predicting the third quantity of contact data records is further based, at least in part, on information pertaining to a product or service that has been released or is scheduled to be released.
12. A method for providing customer relationship management (CRM) for an organization, the method comprising:
providing a graphical user interface (GUI) for display by a client device, the GUI including user-selectable options for configuring a prediction engine;
obtaining, from the client device:
a designation of a contact data record as one of a plurality of CRM object types for which prediction is to be performed, the designation of the contact data record based on first user input submitted via one or more of the user-selectable options,
designations of prediction criteria based on second user input submitted via one or more of the user-selectable options, the designations of prediction criteria including at least a specified type of industry;
determining, according to the specified industry type, a length of time for periods of time used to predict generation of contact data records;
identifying, according to the designation of the contact data record, a set of contact data records in one or more data sources;
filtering the set of contact data records based, at least in part, upon the prediction criteria to identify two or more sets of data, each of the sets of data corresponding to a different period of time having the determined length of time, each of the sets of data being a respective subset of the set of contact data records that were generated during the corresponding period of time;
determining, from a first one of the sets of data, a first quantity of contact data records generated during a corresponding first period of time;
determining, from a second one of the sets of data, a second quantity of contact data records generated during a corresponding second period of time that is subsequent to the first period of time;
predicting a third quantity of contact data records to be generated during a third period of time according to the prediction criteria based, at least in part, on the first quantity of contact data records and the second quantity of contact data records; and
providing an indication of the third quantity of contact data records predicted to be generated during the third period of time according to the prediction criteria.
13. The method of claim 12 , wherein contact data records are configurable.
14. The method of claim 12 , the method further comprising:
predicting characteristics of individuals associated with the third quantity of contact data records based, at least in part, on the first set of data, the second set of data, and user profiles of individuals identified in the first and second sets of data.
15. The method of claim 12 , wherein predicting the third quantity of contact data records according to the prediction criteria is further based, at least in part, on social data, wherein the prediction criteria indicate at least one of: a source of the social data or a type of the social data.
16. The method of claim 12 , wherein predicting the third quantity of contact data records is further based, at least in part, on information pertaining to a product or service that has been released or is scheduled to be released.
17. The method of claim 12 , wherein predicting the third quantity of contact data records according to the prediction criteria is performed using a computer-generated model based, at least in part, on a first weight associated with the first quantity of contact data records and a second weight associated with the second quantity of contact data records.