Multi-service business platform system having custom object systems and methods
The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems, the creation, development, maintenance, and use of a set of custom objects (and core objects) for use in a wide range of activities, including sales activities, marketing activities, service activities, content development activities, and others, as well as improved methods and systems for sales, marketing and services that make use of such entity resolution systems and methods as well as custom objects.
1. A computer-implemented method comprising:
receiving a user request comprising custom object information for creating a custom object defining an action that is performed by an individual, represented by the customer object, and a business represented by an object;
interpreting the custom object information to create custom object metadata using business logic;
converting the custom object metadata into language-independent data, having a language-independent data form, that is inserted into a relational-type database as the custom object;
providing the custom object, comprising the language-independent data in the language-independent data form, from the relational-type database to a service of a multi-service platform;
generating, by the service, an insight for the custom object by performing predictive machine learning utilizing a machine learning model, wherein the generating the insight comprises:
retrieving, by the service, data from instances of the action, defined by the custom object, being performed by individuals with respect to the business; and
generating, by the machine learning model using the data as input, the insight as to a future instance of the action being performed based upon an association directed from the custom object to the object and an inverse association directed from the object to the custom object, wherein the association specifies a first action performed by the individual in relation to the business and the inverse association specifies a second action performed by the business in relation to the individual; and
utilizing the insight to perform a computer implemented customer interaction.
2. The computer-implemented method of claim 1 , wherein the custom object information includes a custom object name, an object type, and a property of the custom object.
3. The computer-implemented method of claim 1 , wherein the custom object information includes a second association of the custom object with a second object.
4. The computer-implemented method of claim 1 , wherein the interpreting of the custom object information further comprises executing sensible default to interpret the custom object information.
5. The computer-implemented method of claim 1 , further comprising generating the insight as data is received from occurrences of actions related to the custom object being performed.
6. The computer-implemented method of claim 1 , wherein the computer implemented customer interaction is a marketing activity executed by a marketing process of the multi-service platform using the custom object.
7. The computer-implemented method of claim 1 , further comprising applying and using the service of the multi-service platform to process the language-independent data of the custom object.
8. The computer-implemented method of claim 7 , wherein the service includes workflow automation.
9. The computer-implemented method of claim 1 , wherein the service includes a customer service process.
10. The computer-implemented method of claim 1 , wherein creation of the custom object includes updating definitions, properties, values, instances, and associations for objects within a multi-tenant data store.
11. The computer-implemented method of claim 1 , wherein the custom object includes a custom identification label, or a property of the custom object.
12. The computer-implemented method of claim 1 , further comprising creating second association for the custom object with a second object based on the custom object information, wherein the association includes an association identification, an association type, a first object identification, a second object identification, and a timestamp, wherein the custom object is directed to the first object identification based on a defined relationship between the custom object and the second object.
13. The computer-implemented method of claim 1 , wherein the computer implemented customer interaction is a sales activity executed by a sales process of the multi-service platform using the custom object.
14. A computing system including memory storing instructions and including a processor that executes the instructions to perform operations comprising:
receiving a user request comprising custom object information for creating a custom object defining an action that is performed by an individual, represented by the customer object, and a business represented by an object;
interpreting the custom object information to create custom object metadata using business logic;
converting the custom object metadata into language-independent data, having a language-independent data form, that is inserted into a relational-type database as the custom object;
providing the custom object, comprising the language-independent data in the language-independent data form, from the relational-type database to a service of a multi-service platform;
generating, by the service, an insight for the custom object by performing predictive machine learning utilizing a machine learning model, wherein the generating the insight comprises:
retrieving, by the service, data from instances of the action, defined by the custom object, being performed by individuals with respect to the business; and
generating, by the machine learning model using the data as input, the insight as to a future instance of the action being performed based upon an association directed from the custom object to the object and an inverse association directed from the object to the custom object, wherein the association specifies a first action performed by the individual in relation to the business and the inverse association specifies a second action performed by the business in relation to the individual; and
utilizing the insight to perform a computer implemented customer interaction.
15. The computing system of claim 14 , further comprising a multi-tenant data store including properties that are changed as part of creating the custom object.
16. The computing system of claim 14 , further comprising an ontology including the custom object, other custom objects, and core objects, wherein the ontology further includes associations between the custom object, the other custom objects, and the core objects.
17. The computing system of claim 14 , further comprising an instance knowledge structure including an instance of the custom object, other custom object instances, and core object instances, wherein the instance knowledge structure further includes association instances between the instance of the custom object instance, the other custom object instances, and the core object instances.
18. The computing system of claim 14 , wherein the computer implemented customer interaction is a customer service activity executed by a customer service process of the multi-service platform using the custom object.
19. The computing system of claim 14 , further comprising an object schema service for providing an object definition application programming interface (API) for receiving the custom object information from a user device.
20. The computing system of claim 14 , wherein the computer implemented customer interaction is a marketing activity executed by a marketing process of the multi-service platform using the custom object.
21. The computing system of claim 14 , further comprising common data format conversion service to assist with synchronization and integration of the custom object within the multi-service platform for use by the process.
22. A non-transitory computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:
receiving a user request comprising custom object information for creating a custom object defining an action that is performed by an individual, represented by the customer object, and a business represented by an object;
interpreting the custom object information to create custom object metadata using business logic;
converting the custom object metadata into language-independent data, having a language-independent data form, that is inserted into a relational-type database as the custom object;
providing the custom object, comprising the language-independent data in the language-independent data form, from the relational-type database to a service of a multi-service platform;
generating, by the service, an insight for the custom object by performing predictive machine learning utilizing a machine learning model, wherein the generating the insight comprises:
retrieving, by the service, data from instances of the action, defined by the custom object, being performed by individuals with respect to the business; and
generating, by the machine learning model using the data as input, the insight as to a future instance of the action being performed based upon an association directed from the custom object to the object and an inverse association directed from the object to the custom object, wherein the association specifies a first action performed by the individual in relation to the business and the inverse association specifies a second action performed by the business in relation to the individual; and
utilizing the insight to perform a computer implemented customer interaction.
23. The non-transitory computer readable storage medium of claim 22 , wherein creation of the custom object includes updating definitions, properties, values, instances, and associations for objects within a multi-tenant data store.