Abstract: Techniques are described in which a service store is provided that allows consumers to shop for services online. The service store system architecture includes a service store which interacts over a network with service consumers, service providers, a social single sign-on aggregated identity engine, and various external partners. Through the online service store, complex and customized ordering and fulfillment processes are achieved using the service store environment.

Abstract: Store intelligence—in-store analytics (“in-store analytics”) techniques are provided that, by combining analytics with experience, improve the shopping, managing, monitoring, etc., experience of an end user. In-store analytics can be integrated with workflow for optimizing and assisting prioritizing operations.

Abstract: Store intelligence—in-store analytics (“in-store analytics”) techniques are provided that, by combining analytics with experience, improve the shopping, managing, monitoring, etc., experience of an end user. In-store analytics can be integrated with workflow for optimizing and assisting prioritizing operations.

Abstract: Techniques are described in which for a user to obtain access to or entitlement to objects or locations, such as for example a web application or entry into an accounting office, the system derives a unified risk score associated with the user. The computer compares the unified risk score against a set of rules to determine whether the unified risk score is greater than a particular threshold. Based on such determination, the computer can cause denial of access or entitlement for example by denying entry to the web application or transmitting a denied message to a system that controls the physical lock on the door to the accounting office. In generating the unified risk score, the computer retrieves the most up-to-date identity information about the user by signing on to an aggregator system using any supported login identity provider username and password or other authenticating credentials associated with the user.

Abstract: Store intelligence—in-store analytics (“in-store analytics”) techniques are provided that, by combining analytics with experience, improve the shopping, managing, monitoring, etc., experience of an end user. In-store analytics can be integrated with workflow for optimizing and assisting prioritizing operations.

Abstract: Techniques are described in which to access a user's web applications, the user registers and signs on to an aggregator system using any supported login identity provider username and password. When the user registers for the first time, the system collects additional information to verify the user for a subsequent access to the system. The system also automatically creates a system secret username and secret, highly securely generated password, both of which are unknown and inaccessible to the user. The secret username and password are stored in an lightweight directory access protocol (LDAP) server or database or in a distributed cloud database system. The system also maps the login identity provider user name to the secret user name and password for subsequent usage.

Abstract: Techniques are described in which for a user to obtain access to or entitlement to objects or locations, such as for example a web application or entry into an accounting office, the system derives a unified risk score associated with the user. The computer compares the unified risk score against a set of rules to determine whether the unified risk score is greater than a particular threshold. Based on such determination, the computer can cause denial of access or entitlement for example by denying entry to the web application or transmitting a denied message to a system that controls the physical lock on the door to the accounting office. In generating the unified risk score, the computer retrieves the most up-to-date identity information about the user by signing on to an aggregator system using any supported login identity provider username and password or other authenticating credentials associated with the user.

Abstract: Techniques are described in which a service store is provided that allows consumers to shop for services online. The service store system architecture includes a service store which interacts over a network with service consumers, service providers, a social single sign-on aggregated identity engine, and various external partners. Through the online service store, complex and customized ordering and fulfillment processes are achieved using the service store environment.

Abstract: Techniques are described in which to access a user's web applications, the user registers and signs on to an aggregator system using any supported login identity provider username and password. When the user registers for the first time, the system collects additional information to verify the user for a subsequent access to the system. The system also automatically creates a system secret username and secret, highly securely generated password, both of which are unknown and inaccessible to the user. The secret username and password are stored in an lightweight directory access protocol (LDAP) server or database or in a distributed cloud database system. The system also maps the login identity provider user name to the secret user name and password for subsequent usage.

Abstract: Techniques are described in which to access a user's web applications, the user registers and signs on to an aggregator system using any supported login identity provider username and password. When the user registers for the first time, the system collects additional information to verify the user for a subsequent access to the system. The system also automatically creates a system secret username and secret, highly securely generated password, both of which are unknown and inaccessible to the user. The secret username and password are stored in an lightweight directory access protocol (LDAP) server or database or in a distributed cloud database system. The system also maps the login identity provider user name to the secret user name and password for subsequent usage.

Abstract: Techniques are described in which to access a user's web applications, the user registers and signs on to an aggregator system using any supported login identity provider username and password. When the user registers for the first time, the system collects additional information to verify the user for a subsequent access to the system. The system also automatically creates a system secret username and secret, highly securely generated password, both of which are unknown and inaccessible to the user. The secret username and password are stored in an lightweight directory access protocol (LDAP) server or database or in a distributed cloud database system. The system also maps the login identity provider user name to the secret user name and password for subsequent usage.

Abstract: Store intelligence—in-store analytics (“in-store analytics”) techniques are provided that, by combining analytics with experience, improve the shopping, managing, monitoring, etc., experience of an end user. In-store analytics can be integrated with workflow for optimizing and assisting prioritizing operations.