Enterprise data aggregation and collective insights generation

A system comprising:

• one or more hardware processors;
• one or more non-transitory computer-readable media;
• and
• program instructions stored on the one or more non-transitory computer-readable media which, when executed by the one or more hardware processors, cause the system to perform operations comprising:
• sanitizing, by a first enterprise-specific customer relationship management system (CRM), a first set of enterprise-specific CRM data at least by performing one or more of attribute stripping, attribute anonymization, or content masking;
• enriching, by the first enterprise-specific CRM, the first set of enterprise-specific CRM data with a first enterprise-specific unique identifier;
• transmitting, by the first enterprise-specific CRM, the first set of enterprise-specific CRM data from a first outbound data interface of the first enterprise-specific CRM to an inbound data interface of a shared insight service accessible to a plurality of enterprise-specific CRMs;
• wherein the first outbound data interface enforces cross-enterprise data privacy, at least in part, by enforcing a first set of one or more sanitization requirements before transmitting the first enterprise-specific CRM data;
• and
• wherein the inbound data interface enforces cross-enterprise data privacy, at least in part, by defining an expected dimensionality for inbound transmissions;
• responsive to receiving the first set of enterprise-specific CRM data:
• accessing, by the shared insight service based at least in part on the first enterprise-specific unique identifier in the first set of enterprise-specific CRM data, a first mapping from (a) a first data format used by the first enterprise-specific CRM to (b) a normalized data format used by the shared insight service;
• mapping, by the shared insight service, the first set of enterprise-specific CRM data to a first set of normalized CRM data according to the first mapping;
• and
• storing, by the shared insight service, the first set of normalized CRM data in collective CRM data shared by at least the first enterprise-specific CRM and a second enterprise-specific CRM in the plurality of enterprise-specific CRMs;
• sanitizing, by the second enterprise-specific CRM, a second set of enterprise-specific CRM data at least by performing one or more of attribute stripping, attribute anonymization, or content masking;
• enriching, by the second enterprise-specific CRM, the second set of enterprise-specific CRM data with a second enterprise-specific unique identifier;
• transmitting, by the second enterprise-specific CRM, the second set of enterprise-specific CRM data from a second outbound data interface of the second enterprise-specific CRM to the inbound data interface of the shared insight service;
• wherein the second outbound data interface enforces cross-enterprise data privacy, at least in part, by enforcing a second set of one or more sanitization requirements before transmitting the second enterprise-specific CRM data;
• responsive to receiving the second set of enterprise-specific CRM data:
• mapping, by the shared insight service, the second set of enterprise-specific CRM data to a second set of normalized CRM data;
• storing, by the shared insight service, the second set of normalized CRM data in the collective CRM data;
• receiving, by the shared insight service, a request to generate a collective insight that is applicable to a particular subset of the collective CRM data, the particular subset of the collective CRM data comprising at least part of the first set of normalized CRM data and at least part of the second set of normalized CRM data;
• responsive to the request, selecting a particular machine learning model from a plurality of machine learning models, wherein each machine learning model in the plurality of machine learning models is configured to generate collective insights for a respective subset of the collective CRM data;
• generating the collective insight that is applicable to the particular subset of the collective CRM data, using the particular machine learning model.

A method comprising:

• sanitizing, by a first enterprise-specific customer relationship management system (CRM), a first set of enterprise-specific CRM data at least by performing one or more of attribute stripping, attribute anonymization, or content masking;
• enriching, by the first enterprise-specific CRM, the first set of enterprise-specific CRM data with a first enterprise-specific unique identifier;
• transmitting, by the first enterprise-specific CRM, the first set of enterprise-specific CRM data from a first outbound data interface of the first enterprise-specific CRM to an inbound data interface of a shared insight service accessible to a plurality of enterprise-specific CRMs;
• wherein the first outbound data interface enforces cross-enterprise data privacy, at least in part, by enforcing a first set of one or more sanitization requirements before transmitting the first enterprise-specific CRM data;
• and
• wherein the inbound data interface enforces cross-enterprise data privacy, at least in part, by defining an expected dimensionality for inbound transmissions;
• responsive to receiving the first set of enterprise-specific CRM data:
• accessing, by the shared insight service based at least in part on the first enterprise-specific unique identifier in the first set of enterprise-specific CRM data, a first mapping from (a) a first data format used by the first enterprise-specific CRM to (b) a normalized data format used by the shared insight service;
• mapping, by the shared insight service, the first set of enterprise-specific CRM data to a first set of normalized CRM data according to the first mapping;
• and
• storing, by the shared insight service, the first set of normalized CRM data in collective CRM data shared by at least the first enterprise-specific CRM and a second enterprise-specific CRM in the plurality of enterprise-specific CRMs;
• sanitizing, by the second enterprise-specific CRM, a second set of enterprise-specific CRM data at least by performing one or more of attribute stripping, attribute anonymization, or content masking;
• enriching, by the second enterprise-specific CRM, the second set of enterprise-specific CRM data with a second enterprise-specific unique identifier;
• transmitting, by the second enterprise-specific CRM, the second set of enterprise-specific CRM data from a second outbound data interface of the second enterprise-specific CRM to the inbound data interface of the shared insight service;
• wherein the second outbound data interface enforces cross-enterprise data privacy, at least in part, by enforcing a second set of one or more sanitization requirements before transmitting the second enterprise-specific CRM data;
• responsive to receiving the second set of enterprise-specific CRM data:
• mapping, by the shared insight service, the second set of enterprise-specific CRM data to a second set of normalized CRM data;
• storing, by the shared insight service, the second set of normalized CRM data in the collective CRM data;
• receiving, by the shared insight service, a request to generate a collective insight that is applicable to a particular subset of the collective CRM data, the particular subset of the collective CRM data comprising at least part of the first set of normalized CRM data and at least part of the second set of normalized CRM data;
• responsive to the request, selecting a particular machine learning model from a plurality of machine learning models, wherein each machine learning model in the plurality of machine learning models is configured to generate collective insights for a respective subset of the collective CRM data;
• generating the collective insight that is applicable to the particular subset of the collective CRM data, using the particular machine learning model;
• wherein the method is performed by at least device comprising one or more hardware processors.