A health care provider (HCP) engagement engine is disclosed. The HCP engagement engine facilitates effective communication between pharmaceutical sales representatives (medical reps) and HCPs by generating, using machine learning algorithms, messages for the medical reps to send to HCPs. The recommended messages may be sent over a network and may include email messages, text messages, or online chat messages. The recommended messages may be drafted entirely by the engagement engine or may be drafted as addenda to messages already used by the medical reps. The HCP engagement engine uses historical data on actions performed by the HCPs and medical reps, as well as data collected from historical message recommendation events, in order to produce message recommendations.

An advertisement budget optimization device (1) includes an estimation unit (13) that estimates a cost per click of an advertisement for each predetermined unit period (specifically, one day) included in a delivery period of an advertisement campaign as a delivery target, and a determination unit (14) that determines an advertisement budget for each unit period so that a total number of clicks of the advertisement is maximized, based on the cost per click in each unit period estimated by the estimation unit (13) and a total budget for the advertisement campaign in the delivery period.

Systems and methods for the efficient generation and testing of promotions within a load to card environment are provided. A load-to-card abstraction layer collects store, user and offer data. The test promotions are then generated to span a design space of an offer. The user base is segmented and the test promotions are applied. The promotions include an offer, and the ability to load the offer for later redemption (load-to-card). Redemption and load rates are measured, and can be used individually, or in combination, to gauge consumer engagement with the promotion. Promotions with low consumer engagement may be discontinued, until only optimally performing promotions are remaining.

Methods and apparatus for generating intelligent offers with base prices are provided. In one embodiment, a promotion generator receives a current product base price, and also receives or calculates a remaining promotional program budget, a remaining promotional program duration, and a minimum discounted price for the product using the current product base price and any available previous base price data for the promoted product, creating or updating a predictive model of future product base prices.

A method for finding a solution to a problem is provided. The method includes storing candidate individuals in a candidate pool and evolving the candidate individuals by performing steps including (i) testing each of the candidate individuals to obtain test results, (ii) assigning a performance measure to the tested candidate individuals, (iii) discarding candidate individuals from the candidate pool in dependence upon their assigned performance measure, and (iv) adding, to the candidate pool, a new candidate individual procreated from candidate individuals remaining in the candidate pool. The method further includes selecting, as the winning candidate individual, a candidate individual having a best neighborhood performance measure, where the neighborhood performance measure of a particular candidate individual is given by the performance measures of (i) the particular candidate individual and (ii) K neighborhood candidate individuals which are nearest in the candidate pool to the particular candidate individual, and where K>0.

This disclosure describes techniques for generating curated In-Real Life (IRL) media data for distribution via third-party multimedia platform(s), and further providing an engagement entity (i.e., producer, merchant, or curator) with a recommendation to solicit an interaction with another engagement entity. Particularly, an IRL-Media Platform Analytics (IRL-MPA) system is described that can create curated IRL-media data by refining a presentation of raw IRL-media data, and further embedding product-service offerings and engagement requests. The IRL-MPA system may configure the curated IRL-media data for playback on one or more third-party platforms, such that a viewing audience member may respond to an engagement request embedded within the curated IRL-media data. The IRL-MPA system may also initiate establishing a communication channel between the audience member and a selected engagement entity on the engagement platform, monitoring an ensuing interaction, and further provide the engagement entity with a recommendation, based on an analysis of the interaction.

In some examples a payment processing system processes transactions between a merchant and customers during a time period, and may determine financing terms including a redemption amount to offset discounts given by the merchant for the transactions during the time period. The payment processing system may identify an amount of the discount given by the merchant to respective customers for the transactions and payment amounts received from the respective customers. In addition, the payment processing system may deposit an amount in an account associated with the merchant. For instance, the amount may be based at least on the redemption amount determined based on the discounts given by the merchant for the transactions during the time period.

Techniques described herein are directed to centralized brand asset management. In an example, a first computing device associated with a first point-of-sale (POS) service can receive an instruction to update a web page of a merchant, wherein the instruction to update the web page of the merchant changes a brand asset of the merchant. The first computing device can send a request to update the brand asset of the merchant to a centralized data storage storing one or more brand assets of one or more merchants. The centralized data storage can update the brand asset to an updated brand asset, which can be available to at least a second computing device associated with a second POS service. The second POS service can update a respective POS service feature based on the updated brand asset.

Methods, systems and computer program products for automating the association of messages. Data points associated with at least one client device associated with an identifier are logged into an activity database. Labels corresponding to message records are retrieved. Message-signal values representing behavior associated with at least a subset of the message records are also retrieved. The labels are merged with the message-signal values to generate a signal-label collection. A signal-label model is trained based on the signal-label collection, thereby generating a trained signal-label model. A mapping of the one or more activity data points and the plurality of labels are then generated. The embedding that is generated can then be used to find custom audiences.

A method and apparatus for managing and integrating lead sources for a marketing/advertisement campaign on a platform that allocates and optimizes lead source budgets and provides a customer service and payment processing function. The present technology as disclosed and claimed herein provides a platform that is a customer retention and customer management system that is automated to provide lead estimations and optimizations to allocate and optimize lead source budgets where the system has a learning function that improves over time.