The application relates to the technical field of Internet, and provides a precise marketing method, device and equipment based on user consumption data, which comprises the following steps: dividing a
data set into a
majority class data set and a
minority class data set after normalizing the consumption data; sorting the
Mahalanobis distance of each sample in the
minority class data set and then dividing the sorted samples into several subsets to calculate the minimum
Mahalanobis distance; taking the samples in different subsets as parent samples by using the MAHAKIL
algorithm with a random parameter, iteratively generating
offspring samples, and training a
user group classifier by taking the
offspring samples with a
Mahalanobis distance greater than or equal to the minimum Mahalanobis distance from the parent samples as a new
minority class data set to perform precise marketing on different user groups; and balancing the sample quantity relationship between the minority class data set and the
majority class data set can make the classifier accurately identify the minority class users, avoid the bias towards a certain class of users caused by the quantity difference of the training data set, and improve the precision of marketing.