The Interact learning module monitors visitor's responses to offers and visitor attributes. The learning module has two general modes:
The learning module alternates between exploration and exploitation based on two properties: a confidence level you configure with the confidenceLevel property and a probability that the learning module presents a random offer you configure with the
percentRandomSelection property.
You set the confidenceLevel to a percentage which represents how sure (or confident) the learning module must be before its scores for an offer are used in arbitration. At first, when the learning module has no data to work from, the learning module relies entirely upon the marketing score. After every offer has been presented as many times as defined by the
minPresentCountThreshold, the learning module enters the exploration mode. Without a lot of data to work with, the learning module is not confident that the percentages it calculates are correct. Therefore, it stays in the exploration mode.
To ensure that the system is not biased toward the offers that perform best during early stages, Interact presents a random offer the
percentRandomSelection percent of the time. This forces the learning module to recommend offers other than the most successful to determine if other offers would be more successful if they had greater exposure. For example, if you configure
percentRandomSelection to 5, this means that 5% of the time, the learning module presents a random offer and adds the response data to its calculations.
Learning is also based on the recencyWeightingFactor property and the
recencyWeightingPeriod property. These properties enable you to add more weight to more recent data than older data. The
recencyWeightingFactor is the percentage of weight the recent data should have. The
recencyWeightingPeriod is the length of time that is recent. For example, you configure the
recencyWeightingFactor to .30 and the
recencyWeightingPeriod to 24. This means that the previous 24 hours of data are 30% of all data considered. If you have a week's worth of data, all of the data averaged across the first six days is 70% of the data, and the last day is 30% of the data.