System and method for determining client-based user behavioral analytics

A computing device comprising:

• a processor;
• a memory device electrically coupled to the processor, the memory device including therein a plurality of instructions that, when executed by the processor, result in the processor:
• monitoring for a predetermined behavioral event initiated by a user on the computing device;
• updating, in response to an occurrence of the predetermined behavioral event, a frequency of occurrences of the predetermined behavioral event, the frequency of occurrences being indicative of the number of occurrences during a first time period;
• determining an affinity metric for the predetermined behavioral event based on the frequency of occurrences, wherein determining the affinity metric comprises (i) determining a frequency of occurrence of the predetermined behavioral event for each of a plurality of first time periods, (ii) comparing the determined frequencies of occurrence of the predetermined behavioral event, and (iii) determining a historical trend of the frequency of occurrence of the predetermined behavioral event over a second time period equal to the sum of the plurality of first time periods based on the comparison of the determined frequencies, wherein the second time period being a multiple of the first time period;
• determining an avidity metric for the predetermined event based on the frequency of occurrences, the avidity metric being indicative of a ranking of a total number of occurrences of the predetermined behavioral event within the second time period relative to a predetermined range of total occurrences;
• and
• determining a behavior analytic index for the user based on the affinity metric and the avidity metric.

A non-transitory, machine readable medium comprising a plurality of instructions that, in response to being executed, result in a client computer:

• determining an affinity metric for the predetermined behavioral event in response to an occurrence of a predetermined behavioral event initiated by a user on the client computer, wherein determining the affinity metric comprises (i) determining a frequency of occurrence of the predetermined behavioral event for each of a plurality of first time periods, (ii) comparing the determined frequencies of occurrence of the predetermined behavioral event, and (iii) determining a historical trend of the frequency of occurrence of the predetermined behavioral event over a second time period equal to the sum of the plurality of first time periods based on the comparison of the determined frequencies;
• determining an avidity metric for the predetermined event in response to the occurrence of the predetermined behavioral event, wherein the avidity metric is indicative of a ranking of the frequency of occurrences relative to a predetermined criteria;
• determining a behavioral index for the user based on the affinity metric and the avidity metric;
• transmitting the behavioral index to a content provider server in response to receiving a request from the content provider server for the behavior index request;
• and
• receiving content from the content provider server in response to transmitting the behavior index, the content being selected based on the transmitted behavioral index.