Abstract: Disclosed is a system to determine a first contact probability for each of a plurality of time slots for each of a plurality of first accounts using a trained machine learning model based on a first set of account information and first contact attempt logs, determine a first prioritization for each of a plurality of first accounts based on a second set of account information, and generate a contact schedule based on the first contact probability for each of the plurality of time slots and the first prioritization. The trained machine learning model is trained based on training accounts.

Abstract: The technology disclosed relates to web analytics and, in particular, to testing user reactions to alternative browser or web application presentations. Some implementations present a selected, ordered set of images. The position and ordering of individual images can be significant to user response. Some implementations adapt a background, motif, or image set based on a requesting user's preferences, such as a color preference. The technology disclosed simplifies test implementation, so that a few lines of code can be added to a web app to invoke the test platform and obtain operational parameters that shape a user's experience.

Abstract: The technology disclosed relates to web analytics and, in particular, to testing user reactions to alternative browser or web application presentations. Some implementations present a selected, ordered set of images. The position and ordering of individual images can be significant to user response. Some implementations adapt a background, motif, or image set based on a requesting user's preferences, such as a color preference. The technology disclosed simplifies test implementation, so that a few lines of code can be added to a web app to invoke the test platform and obtain operational parameters that shape a user's experience.