System and method for dynamic audience mapping and promotion execution

A method for executing an advertising campaign that iteratively adjusts a promotion displayed to targets viewers the method comprising:

• generating a plurality of audience clusters from anonymized data regarding a plurality of individuals who purchase goods and/or services in the marketplace, the anonymized data including demographic information and sales data, the sales data including data regarding purchases made in response to some form of advertising and/or promotion, wherein each audience cluster is partitioned as a coherent group based on buying preferences;
• generating a first result including a personalized promotion to and a first audience cluster from the plurality of audience clusters using a matching algorithm that is refined using machine learning techniques based on sales results reported from past promotions aimed at a particular audience group to identify a type of promotion to apply to the first audience cluster;
• signaling using a digital display channel to a plurality of user interfaces for a plurality of individuals matching characteristics of the first audience cluster to display the personalized promotion;
• generating a second result including a first measurement of success of the personalized promotion with the plurality of individuals matching characteristics of the first audience cluster, the first measurement of success including one or more of margin, revenue, or market share;
• and
• repeating adjusting one or more terms of the personalized promotion based on the first measurement of the personalized promotion, signaling to a plurality of user interfaces for another plurality of individuals matching characteristics of the first audience cluster to display the personalized promotion, and generating the second result until the earliest of the first measurement of success reaching a desired measurement of success or a predetermined promotion adjustment ending point being reached.

Non-transitory computer readable media encoded with programming instructions configurable to cause a controller to perform a method for executing an advertising campaign that iteratively adjusts a promotion displayed to targets viewers, the method comprising:

• generating a plurality of audience clusters from anonymized data regarding a plurality of individuals who purchase goods and/or services in the marketplace, the anonymized data including demographic information and sales data, the sales data including data regarding purchases made in response to some form of advertising and/or promotion, wherein each audience cluster is partitioned as a coherent group based on buying preferences;
• generating a first result including a personalized promotion and a first audience cluster from the plurality of audience clusters using a matching algorithm that is refined using machine learning techniques based on sales results reported from past promotions aimed at a particular audience group to identify a type of promotion to apply to the first audience cluster;
• signaling using a digital display channel to a plurality of user interfaces for a plurality of individuals matching characteristics of the first audience cluster to display the personalized promotion;
• generating a second result including a first measurement of success of the personalized promotion with the plurality of individuals matching characteristics of the first audience cluster, the first measurement of success including one or more of margin, revenue, or market share;
• and
• repeating adjusting, one or more terms of the personalized promotion based on the first measurement of success of the personalized promotion, signaling to a plurality of user interfaces for another plurality of individuals matching characteristics of the first audience cluster to display the personalized promotion, and generating the second result until the earliest of the first measurement of success reaching a desired measurement of success or a predetermined promotion adjustment ending point being reached.