Detecting changes in customer (user) behavior using a normalization value

A method of a computing system detecting changes in customer behavior, comprising:

• a. detecting, by a merchant server, customer action data, wherein the customer action data is sensed by a plurality of computing devices of users;
• b. receiving, by a marketing platform server, the customer action data from the merchant server over a period of time;
• c. determining, by the marketing platform server, customer parameters including a mean, and a standard deviation of the customer action data;
• d. generating a normalization value based on the standard deviation when the standard deviation is detected to be less than a deviation threshold;
• e. determining, by the marketing platform server, a modified noise factor based on a value of the customer action data to make the computing system more sensitive to certain values;
• f. calculating, by the marketing platform server, a value of deviation from expectation based at least on the mean, the standard deviation, and the modified noise factor;
• g. calculating a current cumulative sum value of the customer action data based on a prior cumulative sum value and the value of the deviation from expectation;
• h. comparing the current cumulative sum value with a preselected threshold;
• i. identifying that the customer action data received from the merchant server has stopped working, thereby identifying a problem with data syncing with the customer action data between the merchant server and the marketing platform server, and generating an informative electronic communication for the merchant server alerting the merchant server of the problem, when the current cumulative sum value satisfies a compared condition with the preselected threshold;
• j. automatically stopping dependent processes adversely affected by the problem;
• and
• k. repeating steps b-j.