Abstract: A method of streamlined selection and application of a makeup look involving personalized makeup look recommendations with respective step-by-step makeup routine instructions for executing a selected makeup look. A predictive model identifies one or more makeup look recommendations from a database of makeup looks to present to a user. Recommendations are generated from a combination of user demographic data, user-input preferences, social networking analytics (e.g., frequently used makeup looks among users such as “trending” makeup looks), and user behavioral history data obtained from a smart device application and a smart cosmetic device system. Each respective makeup look can be executed from a respective detailed tutorial guide comprising step-by-step instructions on how to apply cosmetic substances to achieve the respective makeup look.

Abstract: A system for the recommendation of a makeup look to a user in response to data corresponding to a smart cosmetic device, wherein the recommended makeup look is presented to a user for application using the smart cosmetic device. The smart cosmetic device collects user behavioral history such as cosmetic substance usage (e.g., color and formula of a particular cosmetic substance), design configuration (e.g., spray canister, pen, and so on), and usage pattern (e.g., frequency of use for a particular cosmetic substance at a particular time of the day, a particular day of the week, or a particular event). Data associated with user behavioral history is processed by the system to generate at least one user-personalized makeup look recommendation for presentation to the user.

Abstract: A system for the processing of one or more makeup look recommendations for the recommendation of a respective output makeup look recommendation, wherein the respective output makeup look recommendation is renderable in a particular rendering environment (e.g., physical world, augmented reality world, or a metaverse virtual reality world). The system allows for iterative generation of makeup look recommendations within a single rendering environment (e.g., generating new physical world makeup look recommendations from previously user-selected physical world makeup look recommendations) or interreality feedback loop generation of makeup look recommendations within a plurality of rendering environments (e.g., generating a new physical world makeup look recommendation from previously user-selected augmented reality makeup look recommendations.

Abstract: In accordance with embodiments disclosed herein, there is provided systems, apparatuses, and methods for customer relationship management (CRM) with geospatial tools. A server device receives a request to display a map image via a graphical user interface (GUI). The server device accesses a data store to retrieve property data items corresponding to the map image. The server device generates and assigns, for each of the property data items, a property quadkey. The server device filters, using a first map quadkey of the map image, the property data items to obtain two or more property data items. The server device aggregates the two or more property data items into an aggregate property marker and generates an aggregate quadkey for the aggregate property marker. The server device transmits a response to cause the user device to display, via the GUI, the aggregate property marker overlaid on the map image.