1. A method for generating a human likeness score based on a Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), the method comprising: selecting a visual advertising asset; generating the CAPTCHA comprising a graphical interface, the visual advertising asset and a graphical object depicted within the graphical interface; assigning an instruction for completing the CAPTCHA; from a user, receiving an input within the graphical interface, the input comprising a solution to the CAPTCHA from the user, the solution comprising a selection of the graphical object within the graphical interface; extracting a motion pattern from the input; comparing the motion pattern to a motion model based on input patterns of previous users; and calculating the human likeness score of the user based on the comparison of the motion pattern to the motion model, the human likeness score lying within a continuum of discrete human likeness scores, wherein calculating the human likeness score comprises: generating a first confidence group according to an accuracy of the solution in fulfilling the instruction; generating a second confidence group based on the comparison of the motion pattern to the motion model; generating a third confidence group based on user data pertaining to at least one of a CAPTCHA previously attempted by the user, an Internet Protocol address of the user, and a cookie associated with the user; determining a reliability of the first confidence group, the second confidence group, and the third confidence group; compiling the first confidence group, the second confidence group, and the third confidence group, based on the determined reliability thereof, to generate the human likeness score; and selecting a number value, from the continuum of human likeness scores comprising a continuum of number values, that correlates with a calculated confidence that the user is human.