Method and system for predicting content consumption

A method of predicting content consumption by users of user device, the method comprising:

• receiving one or more content by a user device on each user of an initial group of online users identified, by a server, from a plurality of target users based on a set of criteria provided by an advertiser;
• transmitting to the server by the user device, a plurality of initial responses from one or more users of the initial group of online users to the one or more content displayed on the lock screen;
• transmitting to the server, by the user device, a plurality of first responses from one or more users of a first group of users comprising a first set of online users and a first set of offline users, wherein the server identifies the first group of users based on the plurality of initial responses in comparison with a predetermined threshold value;
• transmitting, by the user device, a plurality of second responses from an expanded first set of offline users to predict the content consumption based on the transmitted initial responses, the first responses, and the second responses, wherein the server;
• expands the first set of offline users by a second set of offline users based on a performance of the plurality of first responses from the first set of offline users and the first set of online users;
• transmitting to the server a prediction determined by a network connectivity prediction module deployed on at least a plurality of the first group of users, a prediction of when the first set of offline users will be online, wherein the a network connectivity prediction module is configured to use data from a network connectivity log and machine learning to determine:
• (i) the online users, (ii) the offline users who are offline during a specific time period, and (iii) the users who are going to be offline after a certain time period;
• for each of the first set of offline users, when the user device of the offline user is predicted to return to an online state, waiting for a period of time for the device of the offline user to come online to receive a response from the user.

A system for predicting content consumption by users, the system comprising:

• a server comprising a processor communicatively connected to a memory and the processor configured to:
• push one or more content to a user device of each user of an initial group of online users for displaying the one or more content on a lock screen of the user device;
• receive a plurality of initial responses, from one or more users of the initial group of online users, to the one or more content displayed on the lock screen of the user device;
• identify, based on a number of the plurality of initial responses, a first group of users for pushing the one or more content to the user device of each of the first group of users, the first group of users being other than the initial group of online users and having a first set of online users and a first set of offline users;
• for at least a plurality of the first group of users, deploy a network connectivity prediction module to the user devices of the plurality of the first group of users, wherein the network connectivity prediction module is configured to use data from a network connectivity log and machine learning to determine:
• (i) the online users, (ii) the offline users who are offline during a specific time period, and (iii) the users who are going to be offline after a certain time period;
• for each of the first set of offline users having the deployed network connectivity module, predict, by the network connectivity module, when the offline user is likely to return to an online state;
• for each of the first set of offline users without the deployed network connectivity module, predict when the offline user is likely to return to an online state based on logged user offline and online activity;
• for each of the first set of offline users, when the user device of the offline user is predicted to return to an online state, wait for a period of time for the device of the offline user to come online to receive a response from the user;
• receive a plurality of first responses from one or more users of the first set of online users and the first set of offline users;
• expand the first set of offline users by a second set of offline users for pushing the one or more content, based on a performance of the plurality of first responses from the first set of offline users and the first set of online users;
• receive a plurality of second responses from one or more users of the expanded first set of offline users;
• and
• predict the content consumption based on the plurality of initial responses, the plurality of first responses, and the plurality of second responses.