Systems and methods for predicting user tasks across digital and communication channels using multimodal customer interaction sequences

A system for predicting tasks that a user performs across one or more interaction channels, the system comprising a computing device with a memory for storing computer-executable instructions and one or more processors that execute the computer-executable instructions to:

• train a machine learning model, at a first stage, based on historical customer interaction data corresponding to each of one or more users who have previously interacted with a website or one or more additional interaction channels, wherein the historical customer interaction data includes one or more customer interaction sequences, each customer interaction sequence being a sequence of multimodal event records associated with a user session or user journey, wherein each multimodal event record corresponds to a customer interaction and includes an event identifier, a timestamp, a channel identifier, and one or more modality-specific features, and wherein, during the first stage, each multimodal event record in a customer interaction sequence is interpreted as a lexical token and the machine learning model is trained to generate an event embedding for each lexical token based upon model learning derived from past customer interaction sequences;
• train the machine learning model, at a second stage, based on customer interaction data, user attribute data, and user task data, wherein the second stage comprises fine-tuning the machine learning model to predict a task associated with a training customer interaction sequence using only a partial sequence of multimodal event records from the training customer interaction sequence;
• determine, by the machine learning model, during an ongoing user session and prior to completion of a task, one or more predicted tasks after a predetermined number of customer interactions have occurred in the ongoing user session, wherein the one or more predicted tasks are determined based on at least one of the predetermined number of customer interactions and the user attribute data;
• and
• generate one or more recommended content items based on the one or more predicted tasks, wherein the one or more recommended content items are displayed to the user on a page or interface that is currently being accessed by the user and wherein the one or more recommended content items are generated independently of an explicit user approval to create a task record.