Methods and systems for improving engagement with a recommendation engine that recommends items, peers, and services

A computerized system for improving engagement with a recommendation engine that recommends items, peers, and services, comprising:

• a recommendation engine comprising a software application residing on an application server for recommending at least one of recommended items, peers, and services in response to a user inquiry;
• a digital communications network connecting the recommendation engine to a plurality of user devices of a plurality of users;
• a remote server for accessing the user devices over the digital communications network;
• a data analyzer software application resident on the remote server for:
• remotely electronically accessing, via the digital communications network, data stored on the user devices;
• automatically analyzing the stored data to obtain information pertaining to the stored data;
• a mapping tool associated with the data analyzer for automatically creating a respective passive profile for each of the users by mapping the information obtained from the analyzing of the stored data into newly determined keywords associated with the stored data;
• a database associated with the recommendation engine for storing the respective passive profiles for use by the recommendation engine;
• and
• wherein:
• the recommendation engine automatically provides the recommendations for the at least one of the recommended items, peers, and services to the respective users based on at least the respective passive profiles of the users,
• the stored data comprises at least software applications, computer hardware data, and electronic device data resident on the user devices,
• the stored data is obtained from two or more user devices of each of the users;
• the users' interactions with the stored data and changes made to the stored data are tracked;
• the respective passive profiles for the users are periodically automatically updated based on the tracking;
• alerts are provided to the recommendation engine when changes to the passive profiles are detected based on the updating;
• a query is automatically constructed for the respective user with keywords based on the detected changes;
• the recommendation engine provides additional recommendations comprising at least one of additional recommended items, peers, and services returned by the query to the respective user;
• and
• the passive profiles are automatically created and updated without user input once access to the user devices is provided.