Provided are computer-implemented systems and methods for providing explainable predictions, including receiving a prediction objective from a user; providing at least one data set from at least one data source; determining, at a processor, at least one activity from the at least one data set, the at least one activity comprising a feature of the corresponding data set; generating, at the processor, at least one attribution model from the at least one feature, the at least one attribution model operative to provide a prediction and an associated explanation; generating an explainable prediction comprising a prediction rationale based on the prediction objective received from the user and the at least one attribution model.

Examples are described that enable a sales notification application executing on the mobile device to provide an indication of a better price for a product. In the examples, product information may be obtained from product purchase receipts uploaded by mobile devices executing an instance of a sales notification application. Similarities may be determined between the product information received from each product purchase of the plurality of product purchases. The product information from each of the uploaded receipts may be aggregated based on the determined similarity between the product information. A selected product and a location at which the selected product has been purchased previously may be received for comparison to the aggregated information in a product purchase database. A comparison result may be output to the sales notification application. A payment card may be enabled to purchase the selected product.

Systems and methods are disclosed for assisting users in assessing costs of transactions. For instance, method may include: determining a cost value of at least one transaction associated with a user; classifying the user into a category, based on consumer interest characteristics of the user and consumer interest characteristics associated with the category; determining a relatable product based on the consumer interest characteristics associated with the category, the relatable product being a product purchased by a plurality of persons classified in the category; determining a relatable cost value, the relatable cost value being a representation of the cost value of the at least one transaction using a quantity of the respective relatable product; and presenting the relatable cost value to the user.

An adaptive mapping (AM) computing device having at least one processor in communication with at least one memory device is provided. The AM computing device may be configured to retrieve a plurality of tasks associated with a user, and retrieve geographic mapping data. The AM computing device may also generate a route model based upon the retrieved plurality of tasks and the retrieved geographic mapping data. The AM computing device may execute the route model to determine an optimal route, and transmit, to the user, an optimized travel plan based upon the optimal route.

An interactive digital logistics system is disclosed that receives real-time, on-demand data with immediate and same-day availability information from businesses, then displays the information for consumers to view, select, connect, and reserve the available services or products within a specified radius of their current geographical location. Businesses can accept or decline each consumer request and the interactive digital logistics system tracks the consumer's progress to the business's location. The interactive digital logistics system also tracks the progress of each request until completion and prompts both the consumer and business to rate their experience with the other party. The interactive digital logistics system then calculates an average rating for each party which is displayed in their respective profiles.

A method for obtaining credit card pricing for a merchant includes obtaining a merchant category classification (MCC) code. A sales volume, a number of credit card transactions, an average dollar amount of the credit card transactions and a percentage of credit card transactions that are keyed are obtained. The MCC code, the average dollar amount of the of credit card transactions processed and the percentage of credit card transactions that are keyed are compared with corresponding data from a database of merchant credit card transactions. A matched merchant is identified whose transaction profile closely matches a combination of the MCC code, the average dollar amount of the credit card transactions processed and the percentage of credit card transactions that are keyed. Credit card processing pricing information for the matched merchant is obtained from the database. The credit card processing pricing information is used to calculate credit card processing pricing for the matched merchant.

Computer-implemented methods and computer systems are disclosed herein as implemented by one or more local or remote processors, transceivers, servers, and/or sensors. The methods and systems include the one or more processors (i) determining an electric vehicle has a state of charge (SOC) below a predetermined threshold; (ii) if the SOC is determined to be below the predetermined threshold, determining homes capable of charging electric vehicles within a vicinity of, or a predetermined distance of, the low SOC vehicle's GPS location; (iii) from among the homes within the predetermined distance of the low SOC vehicle, ranking the homes based upon various factors; and/or (iv) scheduling a rendezvous or appointment for the low SOC vehicle with the highest ranked home for recharging the low SOC vehicle, the highest ranked home being equipped to recharge the low SOC vehicle and is available to charge the low SOC vehicle.

Quantitative evaluations of friction within a customer experience may be provided to reduce abandonment and improve conversion of transactions. One or more transactions may be identified. One or more personas corresponding to the one or more transactions may be identified. One or more customer friction factor (CFF) scores corresponding to the one or more transactions may be determined. A given CFF score may be a quantification of an aspect of a given transaction that has a negative impact on a customer experience associated with the given transaction. The one or more CFF scores may be compared with one or more valid comparisons relating to the same industry and the same transaction type. One or more friction points may be identified based on the comparison of the one or more CFF scores. Addressing a friction point may reduce abandonment and improves conversion associated with transactions.

Systems and methods are described for generating efficient iterative electronic recommendation structures. In various aspects, one or more processors aggregate a plurality of ratings vectors, where each ratings vector is associated with a vector type and contains one or more content ranking metrics associated with one or more users. The one or more processors generate similarity pairing values from the plurality of ratings vectors, where each similarity pairing value is based on a similarity mapping between a first ratings vector and a second ratings vector. The one or more processors further generate an electronic recommendation structure based on the similarity pairing values, where the electronic recommendation structure includes a bi-directional look-up interface that is configured to return a bi-directional recommendation value after receiving a lookup request for either the vector type of the first ratings vector or the vector type of the second ratings vector.

A system for electronic lead generation including a semantic graph database including a knowledge graph and a dynamic profiling module comprising automated computing machinery configured to identify a near-term surge in product interest for a number of companies of a particular size in a particular industry in a particular region of the world in dependence upon the knowledge graph and create a company profile in dependence upon the size of the identified companies, the industry of the identified companies, and the region of the world of the identified companies associated with the near-term surge. Embodiments also include a lead purchase module comprising automated computing machinery configured to generate an electronic lead purchase order in dependence upon the company profile; transmit the lead purchase order to a lead generation engine; and receive, from the lead generation engine, a plurality of leads in dependence upon the lead purchase order.