SYSTEM AND METHOD FOR CLIENT APPLICATION USER ACQUISITION

1 . A method, comprising:

providing a client application to a group of users;

obtaining data related to interactions between the client application and each user in the group of users;

providing the data to a predictive model configured to receive the data as input and provide as output a predicted value of each user in the group of users, the predicted value comprising a predicted measure of how valuable the user will be to the client application;

identifying a subset of users in the group of users for whom the predicted value exceeds a predetermined threshold;

for each user in the subset of users, providing an identification of the user to a new user finder; and

providing the client application to a new group of users,

wherein the new group of users was acquired through the new user finder based on the provided identification of the subset of users.

2 . The method of claim 1 , wherein the client application comprises an online game.

3 . The method of claim 1 , wherein the data describes at least one of user characteristics, client device characteristics, or a history of user activity.

4 . The method of claim 1 , wherein the predicted value for each user in the group of users comprises a predicted likelihood that the user will be a payer in the client application.

5 . The method of claim 1 , wherein the predicted value for each user in the group of users comprises a predicted level of engagement with the client application.

6 . The method of claim 1 , wherein the identification comprises the predicted value and a respective client device identifier.

7 . The method of claim 1 , wherein the new user finder is configured to identify prospective new users for the client application based on the provided identification of the subset of users.

8 . The method of claim 7 , wherein the new user finder is further configured to provide the prospective new users with offers to install the client application.

9 . The method of claim 1 , further comprising:

adjusting the predetermined threshold to achieve a desired frequency at which the identifications are provided to the new user finder.

10 . The method of claim 1 , further comprising:

identifying a second subset of users in the group of users for whom the predicted value does not exceed the predetermined threshold; and

providing an identification to the new user finder of one or more users in the second subset of users based on random number generation.

11 . A system, comprising:

one or more computer processors programmed to perform operations comprising:

providing a client application to a group of users;

obtaining data related to interactions between the client application and each user in the group of users;

providing the data to a predictive model configured to receive the data as input and provide as output a predicted value of each user in the group of users, the predicted value comprising a predicted measure of how valuable the user will be to the client application;

identifying a subset of users in the group of users for whom the predicted value exceeds a predetermined threshold;

for each user in the subset of users, providing an identification of the user to a new user finder; and

providing the client application to a new group of users,

wherein the new group of users was acquired through the new user finder based on the provided identification of the subset of users.

12 . The system of claim 11 , wherein the client application comprises an online game.

13 . The system of claim 11 , wherein the predicted value for each user in the group of users comprises a predicted likelihood that the user will be a payer in the client application.

14 . The system of claim 11 , wherein the predicted value for each user in the group of users comprises a predicted level of engagement with the client application.

15 . The system of claim 11 , wherein the identification comprises the predicted value and a respective client device identifier.

16 . The system of claim 11 , wherein the new user finder is configured to identify prospective new users for the client application based on the provided identification of the subset of users.

17 . The system of claim 16 , wherein the new user finder is further configured to provide the prospective new users with offers to install the client application.

18 . The system of claim 11 , wherein the operations further comprise:

adjusting the predetermined threshold to achieve a desired frequency at which the identifications are provided to the new user finder.

19 . The system of claim 11 , wherein the operations further comprise:

identifying a second subset of users in the group of users for whom the predicted value does not exceed the predetermined threshold; and

providing an identification to the new user finder of one or more users in the second subset of users based on random number generation.

20 . An article, comprising:

a non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more computer processors, cause the one or more computer processors to perform operations comprising:

providing a client application to a group of users;

obtaining data related to interactions between the client application and each user in the group of users;

providing the data to a predictive model configured to receive the data as input and provide as output a predicted value of each user in the group of users, the predicted value comprising a predicted measure of how valuable the user will be to the client application;

identifying a subset of users in the group of users for whom the predicted value exceeds a predetermined threshold;

for each user in the subset of users, providing an identification of the user to a new user finder; and

providing the client application to a new group of users,

wherein the new group of users was acquired through the new user finder based on the provided identification of the subset of users.