Systems, apparatuses, and methods are described for determining a consumer's engagement with a brand of the business by tracking the consumer's activities in multiple platforms, such as social media platforms, content platforms, gaming platforms, other retailers, streaming video providers, service providers, etc. Method are described for probabilistically granting users variations of items that are otherwise being acquired. The granting may be random, but probabilities may be boosted based on the consumer's activities in the platforms.

Systems, apparatuses, and methods are described for determining a consumer's engagement with a brand of the business by tracking the consumer's activities in multiple platforms, such as social media platforms, content platforms, gaming platforms, other retailers, streaming video providers, service providers, etc. Method are described for probabilistically granting users variations of items that are otherwise being acquired. The granting may be random, but probabilities may be boosted based on the consumer's activities in the platforms.

An e-commerce system for displaying and selling multiple products to a plurality of users is provided. The e-commerce system comprises a catalogue module configured to dynamically assemble a catalogue, wherein the catalogue comprises a plurality of products to be displayed on an e-commerce platform; wherein each product is attributed with a unique identifier and a corresponding personalised price for a specific user. The system further comprises a feature generation module configured to generate, for a specific product, an implicit score based on clickstream data; wherein the clickstream data comprises user clickstream data for a plurality of users and product clickstream data for the specific product. Further, the system comprises a vector module configured to generate an n-dimensional vector for each product based on its corresponding implicit score and a discount generation module configured to generate a personalised discount for each user; wherein the discount is computed based on the n-dimensional vector of the product.

One embodiment provides a method, including: obtaining, from an application used by users to converse with other users, a conversation corresponding to a user, wherein the conversation includes an indication of an intent to purchase a plurality of retail services; identifying at least one micro-service corresponding to each of the plurality of retail services, wherein the micro-service allows purchase from the corresponding retail service; sequencing the micro-services, thereby sequencing purchases from the plurality of retail services through the micro-services, wherein the sequencing comprises (i) determining a sequence of purchases and (ii) identifying, for each of the determined sequences, a financial benefit to the user; and providing a recommendation comprising a purchasing sequence to the user, wherein the recommendation comprises the sequence of purchases that result in the maximum financial benefit to the user.

The embodiments disclose a method, including gathering marketing data using a digital launch platform with artificial intelligence for automatically analyzing marketing data gathered and automatically creating a marketing program for launching a new product, using application programming interface systems on the digital launch platform for interfacing across multiple social media platforms for reaching consumers regardless of their user digital device type and operating system, using at least one digital launch platform user interface for consumer/end user ordering and purchasing the new product, and delivering the new product order to the end user customer using secure delivery methods and devices electronically coupled to the digital launch platform including launch platform delivery lockers with delivery package label barcode scanning activated pass code key pads, drone captured video of home and office deliveries or mobile dispensary customer GPS location deliveries or mobile dispensary customer GPS location deliveries.

A method and associated system of producing an advertising campaign of a product for an online marketplace seller including, under control of one or more processors configured with executable instructions, generating a single keyword advertising campaign of the product; collecting data on the single keyword; executing a machine learning component of an adaptive machine learning platform to generate a machine learning component output based at least in part on the data on the single keyword; generating a behavioral curve or table relating to an advertisement bid value and a cost per click value based at least in part on the machine learning component output; generating sales goal(s) of the product for the online marketplace seller on the online marketplace; generating an optimized advertisement bid value based at least in part on the sales goal(s) and the behavioral curve or table; and generating an optimized advertising campaign therefrom.

An intermediate result set is obtained from a first machine learning model whose input data set comprises values of a first set of properties associated with a session of operations. The intermediate result and a second set of properties associated with the session are provided as input to a second machine learning model. A value of at least one property of the first set is determined before a value of at least one property of the second set is determined. A particular action recommendation, based at least in part on output generated by the second machine learning model, is implemented.

A method for chat advertisement includes: monitoring a chat session between a customer and an agent of a contact center; determining an ad based on the monitoring; determining a time or an event to send the ad to the customer; and sending the ad to the customer when the time or the event occurs. A system for chat advertisement includes: a processor configured to monitor a chat session between a customer and an agent, for at least one of context, keywords, tones, emotions, demographics, psychographics, or an identifier of the customer, and to provide an ad to a device of the customer during the chat session pursuant to the monitoring; and a database for storing the ad.

A method for call advertisement includes: establishing a call between a customer and an agent of a contact center; monitoring the call; determining an ad based on the monitoring; determining a time or event to send the ad to the customer; and sending the ad to the customer when the time or event occurs. A system for call advertisement includes: a processor configured to monitor a call between a customer and an agent, for at least one of context, keywords, tones, emotions, demographics, psychographics, or an identifier of the customer, and to provide an ad to a device of the customer during the call pursuant to the monitoring; and a database for storing the ad.

Aspects of the present disclosure relate to systems and methods for increasing user engagement using incentivized user task completion. In some embodiments, the incentivized user tasks relate to game related tasks in exchange for rewards, also referred to as gamification. Such gamification techniques entice user interaction by involving introducing user specific games, rewards, and prizes into the online shopping experience. As described herein, such functionality relates to identifying user specific features, identifying a list of prized products for the user, introducing games for the user to engage with, and rewarding the user for successfully completing a game. The games and rewards may be presented to the user in an interactive visual display incorporating the game modules and rewards throughout. The gamification process may be a collaborative endeavor between the online shopping platform and online sellers to develop games and rewards which market products directly to specific users.