70 results about "Demographics" patented technology

Conversations in an online content universe are monitored. A conversation index is generated in social media. An individual conversation is defined by user-selectable input terms. Publishers that influence a conversation are identified. The system generates an influence ranking of site's that influence a particular conversation. The system permits ads to be placed on sites based on the sites influence on the conversation. The system can be updated to permit ads to be targeted based on current influence rankings. The influence ranking is used to perform online advertising targeting and placement. Additional marketing filters, such as demographics, historical performance, and return on investment, may be used to adjust an initial influence ranking based. The ad placement may also be expanded to include related conversations, inlinking sites, and/or outlinking sites.

A healthcare mass customization infrastructure individualizes plan designs by incorporating demographics, income, drug history, medical history, lab values, and future genomic information for appropriate and affordable access to medications. The mass customization infrastructure results in quality outcomes for the patients, improved care and productivity for the providers, and lower medical costs for the payers.

The present invention is a system and framework for augmenting any retail transaction system with information about the involved customers. This invention provides a method to combine the transaction data records and a customer or a group of customers with the automatically extracted demographic features (e.g., gender, age, and ethnicity), shopping group information, and behavioral information using computer vision algorithms. First, the system detects faces from face view, tracks them individually, and estimates poses of each of the tracked faces to normalize. These facial images are processed by the demographics classification module to determine and record the demographics feature vector. The system detects and tracks customers to analyze the dynamic behavior of the tracked customers so that their shopping group membership and checkout behavior can be recognized. Then the instances of faces and the instances of bodies can be matched and combined. Finally, the transaction data from the transaction data and the demographics, group, and checkout behavior data that belong to the same person or the same group of people are combined.

Audience commonality metrics for characterizing the relationship between networked media channels based on audience overlap of identified visitor entities and their related media consumption histories. Audience commonality metrics may be scalars or multi-dimensional metrics and may take into account and/or be used in conjunction with data related to on- or off-network media channels, on- or off-network activities, sociographics and/or demographics. The current invention may be used in the design of networked advertising campaigns, identification of new or unusual market segments and/or valuation of media buys. A system according to the current invention comprises access to a configuration, an input for receiving audience commonality data, an audience commonality metrics engine and an output for providing calculated audience commonality metrics. Data related to identified visitor entities may be received, determined and/or inferred from resources such as a cookie, log file, sniffer, firewall, proxy server, client agent, tracking pixel and/or tool

A data processing system generates recommendations for on-line shopping by scoring recommendations matching the customer's cart contents using by assessing and ranking each candidate recommendation by the expected incremental margin associated with the recommendation being issued (as compared to the expected margin associated with the recommendation not being issued) by taking into consideration historical associations, knowledge of the layout of the site, the complexity of the product being sold, the user's session behavior, the quality of the selling point messages, product life cycle, substitutability, demographics and/or other considerations relating to the customer purchase environment. In an illustrative implementation, scoring inputs for each candidate recommendation (such as relevance, exposure, clarity and/or pitch strength) are included in a probabilistic framework (such as a Bayesian network) to score the effectiveness of the candidate recommendation and/or associated selling point messages by comparing a recommendation outcome (e.g., purchase likelihood or expected margin resulting from a given recommendation) against a non-recommendation outcome (e.g., the purchase likelihood or expected margin if no recommendation is issued). In addition, a probabilistic framework may also be used to select a selling point message for inclusion with a selected candidate recommendation by assessing the relative strength of the selling point messages by factoring in a user profile match factor (e.g., the relative likelihood that the customer matches the various user case profiles).

In a video delivery context, collection and analysis of viewing data can provide insight into viewer interaction with video and the Internet. The viewing data can be transmitted in a controlled manner to a data repository. The system can selectively target specific viewers/households to obtain viewing data, which can be combined with demographics, anonymized, and encrypted. Embodiments enable precision selection of media opportunities, by determining detailed characteristics associated with broadcasts including movement of audiences and specific viewer behavior, such as visits to websites on the Internet. The effective yield of broadcasts, including promotional spots and advertisements, can be determined and predicted based on concrete data at a level of detail down to individual viewers. Accordingly, embodiments enable improvement of the effectiveness and return on investment for programming, promotional spots, and advertisements.

Disclosed is an Internet-based address book that enables individuals (“users”) or (“members”) to use people (“contacts”) from their address book for event planning, purchasing gifts, marketing, and anything else anyone dreams up. The system includes the following modules: an address book whose information can be utilized by any client for any purpose, a full-fledged event planner suitable for planning formal events such as weddings, a marketing module that allows people to refer products and information to people who would be interested, and a recipient transaction module that makes recipient-based transactions such as gifts and money transfer assessable and convenient. Features of the event planner include automatic generation and reprinting of invitations, placement cards, and thank-you cards with proper etiquette. Features of the marketing module includes the ability (a) to restrict the contacts that can be marketed to based on demographics, negative feedback, missing requisite information, or other reasons, (b) to reward users that market merchandise to their contacts with a discount on the merchandise itself, and (c) to bundle all the marketing sent by all users to one contact and deliver it as a single consolidated information package. Features of the recipient transactions module include the ability to (a) send one person a gift through postal mail or email, (b) send many people a gift, and (c) allow many people to purchase a single gift together.

A method and system for analyzing product strength or brand strength by determining shopper decision behavior during a shopping trip. Specifically, shopper behavior can be analyzed to determine whether a shopper's decision to purchase an item occurred at-shelf or pre-shelf. Aggregating decision data across many shoppers over time can then be used to generate analytics regarding the strength of a product or brand. The analysis can then be used to make recommendations to manufacturers or retailers about how to strengthen the product or brand. A deployment of cameras and mobile signal sensors can be utilized to recognize shoppers and track their behavior. Demographics information can also be estimated about the tracked shoppers. The visual and mobile signal trajectories can be fused to form a single shopper trajectory, then associated with Point of Sale (PoS) data. This results in a dataset describing the shopping trip for each tracked shopper.

A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics.

In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos.

In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.

The disclosure relates to systems and methods of predicting one or more locations to which a consumer will travel within a retail establishment during a current shopping trip based on prior shopping histories, current in-store behavior, and demographic information. The system may make the predictions based on a model of a population of consumers to determine correlations between prior shopping histories and demographic information and locations visited during previous shopping trips. A particular consumer's shopping histories, current in-store behavior, and demographics may be used to identify an appropriate model for the consumer. The system may use the model to make the predictions and provide information such as incentives based on the predictions.

Embodiments provide consumers browsing and shopping online for durable goods such as new vehicles with pricing information for user-specified vehicle configurations based at least in part on dynamic, user-centric local regions that can be any shape. A local region may initially center around or start from user-provided geo-specific information and be refined using criteria such as distance, demographics, buying behaviors, etc. The system can leverage data from the finest level of granularity available and dynamically determine multiple, potentially overlapping, local regions which can be user-specific, product-specific, or both. A pricing model may incorporate the data within a dynamic local region thus determined. The parameters of the pricing model may be weighted utilizing a weighting function that can be dynamically adapted to individual users as well as specific vehicles. The pricing model may provide for pricing information that is not limited or constrained by standard administrative or political boundaries.

An advertisement selection system is presented in which vectors describing an actual or hypothetical market for a product or desired viewing audience can be determined. An ad characterization vector is transmitted along with a consumer ID. The consumer ID is used to retrieve a consumer characterization vector which is correlated with the ad characterization vector to determine the suitability of the advertisement to the consumer. The consumer characterization vector describes statistical information regarding the demographics and product purchase preferences of a consumer, and is developed from previous purchases or viewing habits. A price for displaying the advertisement can be determined based on the results of the correlation of the ad characterization vector with the consumer characterization vector.

Systems and methods are provided for predicting visitor traffic to a network of web site pages. The systems and methods are used, as an example, to predict the inventory of total available online advertisements available within the network for a forthcoming period. The visitor traffic includes page viewing, listening or transacting on web pages within a web site, wherein the web pages are categorized by subject, interest areas or specific user queries such as word or phrase searches. For each page whose traffic is being predicted, the system takes into account annual seasonality, day-of-week, holidays, special events, short histories, user demographics, user web behavior (viewing, listening and transacting) and parent and child web page characteristics.

A method for obtaining demographic and/or preferences information for the display of targeted advertisements into applications on mobile platforms. The described method has advantages of directly connecting the collected demographic information and preferences to the application in question and allowing any type of demographic or preference information to be requested and collected.

Determining an optimal atrioventricular interval is of interest for proper delivery of cardiac resynchronization therapy. Although device optimization is gradually and more frequently being performed through a referral process with which the patient undergoes an echocardiographic optimization, the decision of whether to optimize or not is still generally reserved for the implanting physician. Recent abstracts have suggested a formulaic approach for setting A-V interval based on intrinsic electrical sensing, that may possess considerable appeal to clinicians versus a patient average nominal A-V setting of 100 ms. The present invention presents a methods of setting nominal device settings based on entering patient cardiac demographics to determine what A-V setting may be appropriate. The data is based on retrospective analysis of the MIRACLE trial to determine what major factors determined baseline A-V settings.

Trending data demographics are described. In one or more implementations, content posted on online content sources is analyzed to determine topics associated with the posted content. Analysis is then performed to ascertain which of those topics in the posted content are trending. A determination as to which of the topics are trending may be based on a number of times the posted content involves a topic. For the topics that are trending, demographic data of the users that posted about those topics is collected. In some cases, demographic data may be assigned to users that posted about the topics that are trending. Based on the collected and assigned demographic data, a prediction is made to predict segments of users that are likely to find the trending topics interesting. Targeted content may then be provided to the segments of users that are likely to find the trending topics interesting.

An apparatus of processing a digital service signals and a method thereof are disclosed. The present invention includes a receiving module configured to receive declarative contents and a first PDI (Profiles, Demographics, Interests) table including a first PDI question having a first question id for identifying the first PDI question and receive a second PDI table including a second PDI question having a second question id for identifying the second PDI question, an obtaining module configured to obtain an answer to the first PDI question, a storing module configured to store the obtained answer to the first PDI table, a fetching module configured to fetch the stored answer to the second PDI question by using the first question id and the second question id, wherein the first question id is equal to the second question id, wherein the storing module further stores the fetched answer to the second PDI table and a downloading module configured to download contents using the fetched answer, wherein the declarative contents fetches the stored answer by using an API (Application Programming Interface).

A computer solution inclusive of web-enabled client-server hardware architecture and a unique software method for soliciting, sharing and influencing opinions on social issues. The software gathers metrics from collective opinions and facilitates social-networking using these metrics to guide members in forming informed opinions. Specifically, users are given feedback on their personal opinion selections, others' opinion selections, % in agreement, and other statistics or demographics. Each user is given the ability to “Change Opinion” base on this feedback.

A cable television distribution system in which the head end substitutes different channels for a plurality of separated geographic zones. The head end creates a plurality of channel spectrums and transmits the spectrums on distribution trunks such that a different spectrum may be present on each distribution trunk. The spectrums on the distribution trunks are connected to zones of the viewer community which have been selected for market research purposes on the basis of demographics. Product sales collection units are provided at stores throughout the community served by the cable television distribution to collect consumer purchase data for market research purposes.