Abstract: The invention is a system 3-00 and method for presenting off-platform incentive information 14C during shopping sessions conducted on a merchant platform by a consumer. The system 3-00 comprises: (a) a merchant server 31 in data communication with a network 15 during each shopping session; (b) one or more computing devices, each computing device including a display window, a user interface, and a page viewer; (c) one or more payment servers 30A; (d) one or more affiliate servers 30B; and (e) an extension module integrated with the page viewer. The extension module captures merchant platform product pricing and merchant coupon incentives details during the shopping session. The extension also stores or accesses the off-platform incentive information 14C of payment service programs and affiliate programs. The price impact from all the available incentives are presented on at least one modified checkout page 14 for consumer viewing and approval of the transaction.

Abstract: The present disclosure relates to systems and methods for managing a fleet of ridesharing vehicles. In one implementation, the system may include a communications interface configured to receive requests for shared rides from a plurality of users; a memory configured to store indications of passenger-capacity for specific ridesharing vehicles in the fleet; and at least one processor configured to receive information from the communications interface and access the memory The at least one processor may be further configured to assign, to ridesharing vehicles already transporting users, additional users for simultaneous transportation in the ridesharing vehicles; track a current utilized capacity of each specific ridesharing vehicle; and implement a threshold block that prevents assignment of additional users to a ridesharing vehicle when the ridesharing vehicle's current utilized capacity is above a threshold being less than the ridesharing vehicle's passenger-capacity.

Abstract: A processor may receive user interaction data of a user for a plurality of electronically-presented offers. The processor may generate a plurality of labels, the generating comprising generating a label for each respective offer according to a comparison of the quality of the user interactions of the respective offer to the frequency of the user interactions of the respective offer. Each label may be a positive label or a negative label. The processor may determine whether the generating produced both positive and negative labels. The processor may select one of a plurality of available ML models, wherein a two-class ML model is chosen in response to determining that the generating produced both positive and negative labels and a one-class ML model is chosen in response to determining that the generating did not produce both positive and negative labels. The selected ML model may be trained and/or may be used to process user profile data and provide recommendations.

Abstract: In one aspect, a system receives a request to cluster a set of log records. Responsive to receiving the request, the system identifies at least one dictionary that defines a set of tokens and corresponding token weights and generates, based at least in part on the set of tokens and corresponding token weights, a set of clusters such that each cluster in the set of clusters represents a unique combination of two or more tokens from the dictionary and groups a subset of log records mapped to the unique combination of two or more tokens. The system may then perform one or more automated actions based on at least one cluster in the set of clusters.

Abstract: Most current systems decompose sales volume of a product into base volume and additional volumes associated to each sales driver. Here base volume refers to sales quantity that is derived from non-promoted sales period. It leads base volume of a product with partial price effect. In addition, base volume includes volume contributed by store location, space allocated to product category and assortment etc. In the present disclosure a system and method for sales decomposition is described by computing reference base volume and sales contribution by each sales driver. Here reference base volume is the volume derived by excluding the effect of sales drivers namely, retailer price, competitor price, demographics, weather conditions, space occupied by the category to which the product belongs, number of available substitute products in assortment. Retail strategies are recommended in real time based on sales contribution of the sales driver for the product.

Abstract: 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.

Abstract: Described is a system and method for collecting item and user information and utilizing that information to determine materials handling facility patterns, item trends and inventory location trends. User monitoring data for users located in a materials handling facility may include information identifying inventory locations approached by users, gaze directions of users, user dwell times, an identification of items picked by users, an identification of items placed by users, and/or in-transit times for items. This information may be aggregated and processed to determine materials handling facility patterns, item trends and/or inventory location trends.

Abstract: The present disclosure includes a haptic guidance and navigation system for a vehicle that includes two Blutooth modules configured as beacons (using, for example, Bluetooth®, Low-Energy (BLE) modules) disposed on the front-center end and back-center end of a vehicle. The system may include an application operative on a mobile device that is also configured for BLE. The BLE modules onboard the vehicle may be uniquely associated with the vehicle with a unique identification (ID), and used to determine relative distances and angles between the BLEs and the mobile device. The haptic guidance and navigation system may generate haptic and other feedback using the mobile device and haptic output devices onboard the vehicle, to guide a user to a determined point of entry for the vehicle.

Abstract: A market planning system and associated methods are disclosed for dynamically generating an at least one local trade area and/or market planning area for an at least one business location. In at least one embodiment, a central computing system identifies a plurality of block groups proximal to the at least one business location. For each of the identified block groups, the computing system identifies at least one trade anchor located within said block group. The computing system defines a plurality of local trade areas based on the identified block groups and associated trade anchors, and subsequently defines an at least one market planning area based on the local trade areas.

Abstract: Methods, systems, and devices are described that support extensible data mapping. A data mapping server may receive an indication of a source schema for a data source and may receive a user input indicating creation of a custom data object to handle the source schema. The server may create the custom data object based on the user input. The data mapping server may automatically map one or more data fields for a source data object (e.g., based on the source schema) to one or more custom data fields for the custom data object (e.g., based on a custom schema). The server may import a set of data records stored at the data source and may store the data records in a database system according to the custom schema based on the data mapping. The stored custom data objects may be used for segmentation, activation, analysis, or some combination thereof.

Abstract: 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.

Abstract: A system and methods are disclosed for scoring audience responsiveness or exposure to viewing of paid content or advertising via connected television devices (“CTV”) and/or over-the-top (“OTT”) delivery mechanisms. The scoring system and method determines relevant data and creates and records the relevant data in an “Ad Exposure File” and an “Advertiser Outcome File” and at regular intervals compares them to identify matches via overlapping combinations of IP Address/DID, Timestamp (for confirmation of appropriate recency) and recording a conversion event to the “Exposed Household Record.” of the appropriate household on the Ad Exposure File.

Abstract: Devices and techniques are generally described for determining a recalibration frequency of a state space model. In various examples, a first hyperparameter for a first dataset may be determined. A residual value between a first data point of the first dataset and a machine learning model fitted to the first dataset may be determined. A plurality of second datasets may be generated based on the residual value. Second hyperparameters may be determined for the plurality of second datasets. A variability of the second hyperparameters may be determined. A third hyperparameter may be determined for a subset of the first dataset. A recalibration frequency may be determined for the machine learning model by comparing the third hyperparameter to the variability of the second hyperparameters.

Abstract: A benefit-provision system is operated by an administrator to provide a benefit from a source, which may be an administrator, to a benefit-eligible recipient who is part of or associated with a sponsored applicant group for which access to the benefit-provision system is being sponsored by a sponsor. A method thereof provides a benefit by an administrator from a source to a benefit-eligible recipient who is part of or associated with a sponsored applicant group for which access to a benefit-provision system is being sponsored by a sponsor.

Abstract: Embodiments discussed herein are directed to systems and methods for processing audio feedback on a business, product or service offered and providing the feedback to an associated company in a way that enables the appropriate actors within the company's organizational hierarchy to analyze and take action with respect to the feedback. Customers or employees can interact with a virtual assistant platform or other voice recognition platform to access a feedback service that enables customers or employees to provide feedback to or have a conversation with any business about their product or service. The feedback service can be accessed at any time using a mobile phone or internet connected speaker device using a digital assistant platform.

Abstract: A computing system includes one or more processors and one or more computer-readable storage media communicatively connected to the one or more processors. The one or more computer-readable storage media have instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to receive a request from a user device to process an electronic transaction, identify an anomaly, transmit data corresponding to the anomaly to an interactive dashboard, receive a first response from the interactive dashboard, transmit an indication of one or more rule violations and instructions, receive a second response from the interactive dashboard, update the profile of a user.

Abstract: Systems and methods are described for predicting a future topic of a current conversation and providing content associated with the predicted topic. A topic may be predicted based on a first part of a current conversation between a first user and a second user and information about the first user and the second user. Content associated with the predicted topic may be identified, and information about the identified content may be provided to a device associated with the first user or the second user.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of storing, for each respective customer of one or more customers, respective customer information in a customer database; predicting, using a machine learning lifetime value (LTV) update model, a respective LTV for each respective customer of the one or more customers; determining an online advertisement for each respective customer of the one or more customers using the respective LTV, as predicted, for each respective customer of the one or more customers; and coordinating displaying the online advertisement for at least a portion of the one or more customers. Other embodiments are disclosed herein.

Abstract: The subject technology receives code corresponding to a neural network (NN) model and a set of weights for the NN model. The subject technology determines a set of layers that are mutable in the NN model. The subject technology determines information for mapping a second set of weights to the set of weights for the NN model. The subject technology generates metadata corresponding to the set of layers that are mutable, and the information for mapping the second set of weights to the set of weights for the NN model, wherein the generated metadata enables updating the set of layers that are mutable during execution of the NN model.

Abstract: Provided is an upgrade evaluation device for calculating cost in relation to the introduction effects of an upgrade menu. The present invention has: a performance data acquisition step for acquiring the performance data of an apparatus; and an effect calculation step for calculating, on the basis of the performance data, introduction effects based on a difference in performance when an improvement function for improving the performance of the apparatus is introduced and when the improvement function is not introduced; the introduction effects being calculated for each of a plurality of points in time in a prescribed period in the effect calculation step. There may also be calculated a cost exchanged between an improvement-function-supply side and the supplied side, the cost being based on the introduction effects calculated in the effect calculation step.

Abstract: The present application provides systems and methods for a mobile storefront having direct customer access to inventory and pricing from a mobile storefront. In particular, systems and methods provide an application usable by customers to purchase goods or services from a mobile storefront through an electronic communication device. This includes reserving and purchasing products in inventory of the mobile storefront or pooled inventory from multiple mobile storefronts in an area, reserving and purchasing services and/or support, and for communicating directly with an electronic communication device of the mobile storefront.

Abstract: A method and system for allocating displays to a plurality of stores grouped into a plurality of store configurations is presented. It includes receiving a plurality of counts, that specifies spaces available in the store configuration for one of a plurality of types of displays, a ranking of a plurality of displays, wherein the ranking is based on a benefit of each of the plurality of displays for the store configuration, and when the plurality of displays are to be allocated to the plurality of stores; determining a subset of the plurality of displays that meet one or more conditions related to at least one of a forecasted sell through or forecasted margin of the plurality of displays for the store, allocating at least some of the displays based on the ranking of the displays, and generating an indication of the allocated displays for output to a user.

Abstract: Systems and methods can include a computing system configured to receive transaction information corresponding to a transaction between a merchant and a customer. The computing system can be configured to receive one or more images captured via a camera during the transaction. The computing system can be configured to analyze the one or more images captured by the camera to detect one or more features relating to the transaction in the one or more images. The computing system can be configured to generate a designation for the transaction based on the one or more features detected in the one or more images. The designation can comprise at least one of verified or unverified. The computing system can be configured to store the transaction information and the one or more images with the designation for the transaction in an account associated with the customer maintained in an accounts database.

Abstract: A method includes generating a model for a content taxonomy using one or more machine learning (ML) techniques. The model comprises a plurality of metadata tags for electronic content. In the method, a plurality of electronic content items are received from a plurality of content management systems, and are analyzed using the one or more ML techniques. The method also includes assigning one or more of the plurality of metadata tags to each of the plurality of electronic content items based on the analysis, and transmitting to the plurality of content management systems via one or more application programming interfaces, a plurality of recommendations comprising which of the plurality metadata tags to apply to the plurality of electronic content items.

Abstract: A computer-implemented method and system for streamlining interactions between a customer and a customer service representative of a company. An interaction is commenced between the customer and the customer service representative during which historical data is accessed related to the customer stored in a company controlled computer system responsive to the interaction. The historical data preferably relates to at least one product or service provided by the company to the customer. At least a part of the historical information is displayed to the customer service representative. On the display, a first tab is generated related to the historical data as is a second tab relating to a quote for a new product or service for offering to the customer. The customer service representative is thereafter enabled to switch between displaying the historical data and the quote by selecting the first or second tab, respectively, without having to save the quote.

Abstract: A work instruction system includes: a production progress management device including a communication unit configured to communicate with a work instruction device, a product signal storage unit that stores a product signal including position information of a product, a product in-progress process estimation unit configured to estimate an in-progress process of the product using the position information, and a production progress estimation and update unit configured to estimate production progress of the product in accordance with a change in the position information and update production progress information; and the work instruction device including a communication unit configured to communicate with the production progress management device, a production progress storage unit that stores the production progress information, a data collection unit configured to obtain progress management information updated from the production progress management device, a recommended work generation unit configured to gen

Abstract: Personnel evaluation based on crowdsourcing concepts. An approach to personnel evaluation is described that uses crowd-sourced data and an iterative approach. Individual personnel evaluators are themselves evaluated and assigned weighting factors based on their acumen and accuracy with regard to personnel evaluation. Personnel evaluations are provided by each personnel evaluator, who collectively form a crowdsourcing crowd, and weighted according to each evaluator's assigned weighting factor. The crowd-sourced weighted-averages from all evaluators are combined and used periodically and iteratively to evaluate the individual crowdsourcing participants and to re-calculate their individual weighting factors. The approach provides more accurate and more directed personnel evaluations as compared to simple arithmetic averaging of crowd-sourced data, and is improved with each iteration over time.

Abstract: A method for facilitating allocation of network resources to at least one slice in a communication network includes obtaining information identifying a mapping between network resource allocations and a respective quality of experience (QoE) associated with a user and obtaining information relating to a quality of service (QoS) tolerance for a particular QoE. The method includes providing to a controller for allocating at least a portion of the network resources to the at least one slice: i) the information identifying a mapping between network resource allocations and a QoE; ii) the information relating to the QoS tolerance; and iii) information identifying a current QoE and a target QoE associated with at least one user.

Abstract: A computer-assisted method for providing re-quotations for insurance coverage may include receiving a list of insurance leads corresponding to individuals who received a previous quotation for insurance coverage but did not purchase the insurance coverage and identifying a difference between the previous quotation and a new quotation. This difference may include an increase in offered insurance coverage and/or a reduction in cost. A computing device may calculate a probability for each of the individuals on the list using a regression model based, at least in part, on the identified difference. In some cases, the regression model may be associated with individual states. In other cases, the regression model may correspond to a plurality of states. The regression model may output a probability that a resident of a particular state will purchase insurance in response to a re-quotation for insurance coverage, where individuals may then be ranked based on the probability.

Abstract: An example apparatus includes an advertisement determiner to identify a first plurality of respondents that received an addressable advertisement and a second plurality of respondents that received a linear advertisement based on combined program tuning data and reference advertisement data; a calculator to calculate a first average commercial minute rating for the addressable advertisement based on first duration weighted impressions associated with the first plurality of respondents and a second average commercial minute rating for the linear advertisement based on second duration weighted impressions associated with the second plurality of respondents; and a communication interface to transmit the first average commercial minute rating and the second average commercial minute rating for crediting the addressable advertisement and the linear advertisement with audience viewership metrics.

Abstract: Systems, methods, and other embodiments associated with a machine learning system that monitors and detects health and safety risks in electronic correspondence related to a target field are described. In one embodiment, a method includes monitoring email communications over a network to identify an email associated with a target field. A machine learning classifier is initiated that is configured to classify text from the email with a risk as being related to a safety risk or a non-risk. The machine learning classifier generates a probability risk value that the email is related to a safety risk and labels the email as safety risk or non-risk based at least in part on the probability risk value indicating that the email is a safety risk. An electronic notice is generated and transmitted to a remote device in response to the email being labeled as being safety risk to provide an alert.

Abstract: Technologies are shown for storing a data object in a distributed application architecture. Critical data in the data object is stored in an object data block on a blockchain. Noncritical data elements in the data object are stored in data block files at an address on a distributed file system, where the addresses are stored in the data block. The object data block is retrieved from the blockchain. The noncritical elements are retrieved from the file system using the address in the data block. The critical and noncritical elements are combined into a reassembled data object. The critical and noncritical data elements can be differentiated in a data definition for the data object or algorithmically analyzing data in the data object. Metadata for the data object can be stored in the object data block and utilized to combine the critical and noncritical elements into the reassembled data object.

Abstract: The present disclosure relates to systems, devices, and methods for annotating or classifying regional sports into new sports categories and generating webpages for the regional sports. The methods and systems may create new tabs or icons on the browser sports webpages with the regional sports allowing the user to select the regional sports and access a dedicated webpage for the regional sport with information for the regional sport.

Abstract: A method and system is provided for facilitating affiliate link generation using a web browser application. A publisher enables the system by identifying a webpage on an affiliate web site. The system performs an initial assessment of the page to extract webpage information, which is compared to information stored in a database. If the extracted information matches stored information, a record of the webpage is displayed and an affiliate link is dynamically generated for immediate use. If the extracted information does not match stored information, a new record of the webpage is created. If the webpage contains product-specific data, a product-specific record is stored. If the webpage does not contain product-specific data, a non-product record is stored. An affiliate link is then dynamically created. The new record of the product and dynamically created affiliate link is added to the database for immediate use.

Abstract: In a system for delivering information to and displaying information on a networked device of a user, a microprocessor is coupled to a database and a memory device. The microprocessor runs a software application for delivering an applet application to the networked device and managing the delivery of the applet application. The applet application provides for the display of information on the networked device by an applet. The database stores a first set of information relating to the user, and the memory device includes a second set of information for comparison to the first set of information, and a third set of information for display by the applet. The microprocessor compares the first set of information to the second set of information to determine whether to transmit the third set of information to the networked device for display by the applet.

Abstract: In a system for delivering information to and displaying information on a networked device of a user, a microprocessor is coupled to a database and a memory device. The microprocessor runs a software application for delivering an applet application to the networked device and managing the delivery of the applet application. The applet application provides for the display of information on the networked device by an applet. The database stores a first set of information relating to the user, and the memory device includes a second set of information for comparison to the first set of information, and a third set of information for display by the applet. The microprocessor compares the first set of information to the second set of information to determine whether to transmit the third set of information to the networked device for display by the applet.

Abstract: A method for processing audio generated in a virtual meeting room (VMR) includes setting a quantity of mesh vertexes according to seats in the VMR, obtaining first voiceprint information of a presenter, the first voiceprint information comprising a frequency, an amplitude, and a phase difference of an audio signal, adjusting the frequency or amplitude of the first voiceprint information according to the quantity of the mesh vertexes, and obtaining second voiceprint information; and determining a seat of the presenter in the VMR according to the second voiceprint information. An apparatus and a non-transitory computer readable medium for processing audio as above are also disclosed.

Abstract: A network computer system that determines metrics related to effort and cost on the part of deliverers who deliverer items for delivery orders. The network computer system can implement operations to facilitate or mitigate features that cause deliverers to expend effort or cost when completing delivery tasks.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for redirecting a user. For instance, the method may include: determining whether a there is a presence of one or combinations of: a particular webpage of a third party website and particular DOM element(s); performing a first DOM analysis on the particular webpage to extract an entity and first data from at least one of the particular DOM element(s); determining whether an entity website is mapped based on the entity and a mapping of entities to entity websites; performing a navigation process to interact with the entity website and extract second data; and performing a comparison analysis on the first data and the second data to determine whether at least one difference is present.

Abstract: A social media impact analysis (SMIA) computer device and methods for allocating resources in response to social media conversations are provided. The SMIA device stores for a plurality of escalation levels, corresponding trigger criteria and resource allocations, where each trigger criteria includes a sales impact range and a content category. The SMIA device is configured to receive tracking signals relating to social media conversations about a product over a time period, each tracking signal including a topic of social media conversation and correlated to a predicted future sales impact; detect that a tracking signal deviates from a threshold; compare the tracking signal to the trigger criteria for the escalation levels; and allocate resources automatically in response to the social media conversations according to the resource allocation for a first of the escalation levels.

Abstract: In an aspect, an apparatus for attribute traversal is presented. An apparatus includes at least a processor and a memory communicatively connected to the at least a processor. A memory contains instructions configuring at least a processor to receive user data. At least a processor configured to identify a plurality of attributes of user data. At least a processor is configured to calculate a proficiency score. At least a processor is configured to generate a utility function. At least a processor is configured to determine an attribute enhancement datum. At least a processor is configured to present an attribute enhancement datum to a user.

Abstract: Systems and methods are provided for recommending benefit types of benefit items to offer within a membership platform.

Abstract: Data is received that defines a rule mining run including a scope of a search and at least one data source to be searched. In response, the at least one data source is polled to obtain rules responsive to the rule mining run. Each rule can specify one or more actions to take as part of a computer-implemented process when certain conditions are met. A list of rules (i.e., a proposed subset of the obtained rules) can then be generated using at least one machine learning model. The generated list of rule can then be displayed in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Abstract: A method including determining a zip code of a user using a website that displays items for sale. Determining the zip code of the user can include determining the zip code of the user through at least one of using tracking cookies for the user using the website or geo-sniffing a current session of the user using the website. The method also can include receiving a selection by the user to display information about an item of the items for sale. The method additionally can include determining a shipping speed to display to the user for the item based on (a) a geo-classification for the item, (b) a list of fulfillment nodes that can currently deliver to the zip code of the user within a first shipping speed, and (c) a node-level inventory for the item. The method further can include facilitating a display of the shipping speed to the user. The geo-classification for the item is a first classification at least when a sale margin for the item exceeds a first predetermined margin threshold.

Abstract: A method of analyzing biological data containing expression values of a plurality of polypeptides in the blood of a subject. The method comprises: calculating a distance between a segment of a curved line and an axis defined by a direction, the distance being calculated at a point over the curved line defined by a coordinate along the direction. The method further comprises correlating the distance to the presence of, absence of, or likelihood that the subject has, a bacterial infection. The coordinate is defined by a combination of the expression values, wherein at least 90% of the segment is between a lower bound line and an upper bound line.

Abstract: A novel approach to facilitating access to valuable actionable content from a multi-tenant database involves system generated ranking of connection content with associated data retrieval methods and systems, utilizing “connector” scores to rank responsive content. The system “learns” how to optimize retrieving and ranking high value actionable content with experience; and applies optimized scoring parameters to enhance future operations. The computer platform is greatly improved by delivering actionable content that is immediately translated into critical operations and tasks recommended by the system to support transactions for the User.

Abstract: Protected audience selection system. Media consumption histories of browsers which have converted are received at a modeling system where targeting of browsers is prohibited. A model is built by determining a frequency of each respective media consumption event among the histories and comparing each determined frequency of a respective media consumption event to a frequency of the respective media consumption event among a population of browsers without the conversion event. The model is sent to a targeting system which excludes conversion events. A description of the conversion event is received at the targeting system. A history of a targetable browser is received at the targeting system. The model is applied to the history of the targetable browser at the targeting system, where conversion events have been excluded from the history. Advertising content is sent to the targetable browser according to a result of applying the model.

Abstract: In some embodiments, a computing system identifies a current engagement stage of a user with an online platform by applying a stage prediction model based on interaction data associated with the user. The interaction data describe actions performed by the user with respect to the online platform and context data associated with each of the actions. The computing system further identifies one or more critical events for promoting the user to transition from one engagement stage to a higher engagement stage based on the interaction data associated with the user. The computing system can make the identified current engagement stage of the user or the identified critical event to be accessible by the online platform so that user interfaces presented on the online platform can be modified to improve a likelihood of the user to transit from the current stage to a higher engagement stage.

Abstract: Described are computer-based methods and apparatuses, including computer program products, for authenticating user service requests from a social networking site. Data representing a selected message and an originator of the selected message is stored. Data representing a reply to the originator of the selected message is transmitted for posting at the social networking server, the reply including data that causes transmission of a service request to the server when actuated. Data representing the service request and a sender of the service request is received. Data representing a user profile of the sender of the service request is retrieved from the social networking server. One or more attributes of the user profile of the sender are compared against one or more attributes of the stored data representing the originator of the selected message in order to verify the one or more attributes of the user profile.

Abstract: A method for a lead grading platform can include, receiving a lead from a lead vendor, wherein the lead comprises a plurality of lead attribute values, converting the plurality of lead attribute values to a plurality of benchmark values, assigning the lead to a pre-determined cluster and a pre-determined sub-cluster based on the plurality of benchmark values, determining a grade for the lead based on the pre-determined cluster and the pre-determined sub-cluster, and responding to the grade being greater than a threshold grade by: delivering the lead to a lead consumer. In this way, a conversion rate of leads delivered to a lead consumer may be greater than an overall conversion rate of an unfiltered population of leads.