System and method for selective transmission of multimedia based on subscriber behavioral model

• US 20030208754A1
• Filed: 05/01/2002
• Published: 11/06/2003
• Est. Priority Date: 05/01/2002
• Status: Active Grant

• Current Assignee: Satyam Computer Services Limited of Mayfair Centre
• Original Assignee: Satyam Computer Services Limited of Mayfair Centre
• Inventors: Rao, K. Kaliana, Sridhar, V., Sridhar, G.
• Granted Patent: US 8,099,325 B2
• Time in Patent Office: Days
• US Class Current: 725/34
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: H04N 21/25833 involving client hardware characteristics, e.g. manufacturer, processing or storage capabilities allocation of resources considering hardware capabilities in multiprogramming arrangements G06F9/5044; allocation of resources considering software capabilities in multiprogramming arrangements G06F9/5055
• CPC Class Codes: H04N 21/25841 involving the geographical location of the client retrieval from the Internet by querying based on geographical locations G06F16/9537; arrangements for identifying locations of receiving stations in broadcast systems H04H60/51; location of the user terminal in data switching networks H04L67/52; services making use of the location of users or terminals in wireless networks H04W4/02; locating users or terminals in wireless networks H04W64/00
• CPC Class Codes: H04N 21/25883 being end-user demographical data, e.g. age, family status or address arrangements for identifying locations of users in broadcast systems H04H60/52
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063
• CPC Class Codes: H04N 21/41407 embedded in a portable device, e.g. video client on a mobile phone, PDA, laptop constructional details of equipment or arrangements specially adapted for portable computer application G06F1/1626; arrangements specially adapted for mobile receivers in broadcast systems H04H20/57
• CPC Class Codes: H04N 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4663 involving probabilistic networks, e.g. Bayesian networks
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

An advertisement system that provides subscribers with the most relevant advertisements based on their individual purchase prediction of the various products and contextual information such as location, ongoing public events, festivals and personal events. The system customizes the advertisements to suit the audiovisual, language, and textual caption preferences of the subscribers. System provides for tracking of various promotional offers made to the subscribers from the time the offer is made to the time it is redeemed by the subscriber. System consists of methods to learn (a) purchase predictions (b) preferred streaming schedule and (c) the subscriber'"'"'s preferences in terms of audiovisual aspects of the advertisements. Purchase prediction for individual subscriber is derived from historical purchase data by time series analysis and the influence of events such as co-purchases of other products and organized events such as sales exhibitions and festivals is derived based on Bayesian network models.

Claims

1. A system for selecting, customizing and streaming promotional advertisements of products and services to 3G capable terminals of specific individuals who are subscribers to the system and are prospective buyers of a product or service featured in the advertisements, wherein the said system, at the initiation of the subscription, provides the subscriber an option to choose one or more of the plurality of the service levels comprising of Purchase counseling, Scheduled streaming, Promotional alerts, and Streaming to virtual communities, and the said system further comprises of subsystems:

(a) for learning a model for predicting purchase of a product by an individual subscriber from historical purchase transaction data, wherein the said system for learning purchase prediction model comprises means to derive the said prediction model by applying time series analysis to the historical purchase transaction data of the individual subscriber; and

further comprising means to derive the influences of ongoing events and co-purchases on the purchase prediction of a product by application of Bayesian analysis to purchase transaction data along with the event and co-purchase data;

(b) for selecting an advertisement featuring a product which is most relevant to an individual subscriber'"'"'s viewing through a 3G terminal device based on a set of pre-defined criteria to identify the suitability of the advertisement to the subscriber, the said criteria comprises of relevance of the product to the subscriber, relevance of the current location of the subscriber to the advertisement, and relevance of the ongoing events in the vicinity of the subscriber;

(c) for learning the schedule preferences of the subscriber for accepting the advertisements based on the demographic classification and streaming acceptance behavior of the subscriber;

(d) for deriving a weekly plan for streaming advertisements to each individual subscriber based on the sponsor requirements and the subscriber'"'"'s schedule preferences;

(e) for customizing the advertisement to suit the audiovisual preferences of the subscriber, the said system for customization comprises of means to manipulate appropriate objects in the multimedia representation of the advertisement to achieve the modification of audio visual aspects of the advertisement to suit the preferences of the subscriber;

(f) for learning the audiovisual preferences of the subscriber based on the responses of the subscriber to specific learning sessions; and

(g) for providing interactivity between the subscriber and the said system through voice, text and touch sensitive screens, the said interactivity comprises of provisioning for providing responses to the subscriber'"'"'s queries through sponsor maintained call centers.

2. The system of claim 1, wherein each said subsystem comprises of means to collect and store one or more of the plurality of subscriber information comprising of:

subscribed service levels;

demographic information;

historical data of product purchases;

type(s) of terminal device(s);

preferred streaming schedule;

preferred presentation aspects;

3. The system of claim 2 further comprises of means to store the collection of advertisements, which are in the form of audio, video or multimedia;

and means to retrieve the audio, video data from the database as per the requirements.

4. The system of claim 3 further comprises of means to store the characteristics of the advertisements which are normally supplied by the sponsor or the producer of the advertisement;

and means for storing the said characteristics information in MPEG-7 descriptors format or where this is inappropriate, in a specific format designed for this system.

5. The system of claim 1, wherein said service levels consist of one of the plurality of levels as streaming service (Mode-1) which is aimed at offering purchase counseling to the subscriber on the product or service referred by the subscriber and the streaming is initiated in response to a specific request from the subscriber for information on a particular product or service either in the form of voice or touch input;

Upon establishing the access to the said Mode-1 service, the subscriber is prompted to type in the name of the product or service on which she would like to have the information, in response to which, the system selects all the relevant advertisements available within system and streams the same to the subscriber; and

further, in case the requested information is not available within the advertisement database of the system, system interconnects with an appropriate call center to establish an interactive session with the call center operator.

6. The system of claim 1, wherein said service levels further consist of one of the plurality of levels as streaming service (Mode-2) which is based on sponsored advertisements of products and services with each of the advertisements customized to suit subscriber'"'"'s specific preferences.

7. The system of claim 6, wherein said service level (Mode-2) further consists of alternative service modes comprising of, Scheduled streaming mode (Mode-2a), Subscriber initiated streaming mode (Mode-2b) and Promotional alerts (Mode-2c), Promotional alert (SMS-/MMS-/VMS-based) (Mode-2D) and Real time streaming (Mode-2E).

8. The system of claim 7, wherein, in the said Scheduled streaming mode (Mode-2a), the schedule for streaming is managed based on the preferred schedule specified by a subscriber at the time of subscription or modified thereafter;

wherein the as part of the said schedule information, the subscriber provides a detailed list consisting of preferred timings on each day of the week for receiving the streamed advertisements.

9. The system of claim 7, wherein said schedule for streaming is alternatively learned by learning category-wise schedule preferences and streaming acceptance behavior of the subscriber.

10. The system of claim 8, wherein in the said Scheduled streaming mode, the advertisements to be streamed are selected based on the subscriber'"'"'s purchase prediction at that point of time or relevance to events, which are public or personal to the subscriber, or based on both purchase prediction and event relevance.

11. The system of claim 7, wherein in the said Subscriber initiated streaming (Mode 2b) mode, the advertisement is streamed in response to a specific acceptance by the subscriber to receive an advertisement;

the willingness to receive an advertisement is conveyed to the system by enabling the terminal device through a client application for receiving the streaming.

12. The system of claim 7, wherein in the said Promotional alert (Mode 2c) the advertisement is streamed whenever there is a prediction for a product for which there is a promotional offer and the terminal device is enabled for receiving advertisement.

13. The system of claim 7, wherein in the said Promotional alert (SMS-/MMS-/VMS-based) (3208) (Mode-2D) consists of a service level in which the subscriber chooses to receive Promotional alerts as alert messages in one of the three forms SMS-/MMS-/VMS, which the subscriber chooses to view immediately upon the receipt of the same or stores the messages for future viewing.

14. The system of claim 7, wherein in the said service level Mode-2E, Real time streaming, comprises of streaming advertisements with video and caption, and without audio to the subscriber during a call to the terminals which have 3G capabilities and in which the device display is viewable during the conversation.

15. The System of claim 1 further comprises of client component installed in subscriber'"'"'s device, which helps the subscriber to interact with the ad system and provides the subscriber with the functionality of configuration management and viewing of subscriber specific ad information.

16. The System of claim 1, wherein comprises of means to implement service level agreements as agreed with a sponsor comprising of the number of targeted streaming sessions of a particular advertisement in a given time interval, and number of repeated streaming of a particular advertisement to a subscriber.

17. The system of claim 1, wherein said service level further comprises of one of the plurality of service levels as “

Streaming to virtual community”

(Mode-3), in one of the variations of the said service (Mode-3a), the advertisements are streamed to one of the plurality of the terminals, which are watched by a group of subscribers at one time, where more than one of them is a subscriber to the system; and

the advertisement selection is based on community profile derived by pooling the individual profiles of the subscribers present in the said event.

18. The system of claim 17, wherein said service level comprises of a variation (Mode-3b) in which the advertisements are streamed to groups involved in remote conferencing such as video conferencing and the said advertisements are selected based on the profile of each subscriber participating in the conference and are streamed at scheduled time slots as specified by the organizers.

19. The system of claim 1 further comprises of means to offer incentive in terms of discounts in the billing of 3G services to subscribers based on the subscribed service levels and the volume of accepted advertisement streaming.

20. The system of claim 19 comprises of method to determine the billing rules applicable to different subscribers which are based on the subscriber profile comprising of time of streaming and loyalty to the service.

21. The system of claim 1, wherein in the said selection of advertisements to be streamed is based on their matching with one or more of the plurality of criteria which includes purchase prediction made for the subscriber at that point of time, user location relevance and event related relevance;

wherein the weighted combination of these multiple relevance is used as basis for selection.

22. The system of claim 21, wherein said selection of advertisement using an alternative criterion, based on most recent and voluminous purchases, when any of the plurality of said criteria does not match with any of the advertisements.

23. The system of claim 21, wherein said criteria is learned for a subscriber based on the historical purchase data;

wherein the information of purchases made by the subscriber of different products but belonging to a particular brand or manufacture is derived from the historical data.

24. The system of claim 21, wherein the said criteria comprises of one of the plurality as the user location relevance of the advertisement at the time of streaming, said relevance can be in terms of proximity to a specific outlet, proximity to specific place of importance, or as defined by the content producer as part of characteristic data of the advertisement.

25. The system of claim 21, wherein the said criteria comprises of one of the plurality as the relevance of the advertisement to other events which are public or personal to the subscriber.

26. The system of claim 21, wherein said additional relevance to an event or location is defined by the sponsor as part of description of the advertisement which is made available to the system.

27. The system of claim 25 further comprising of means to determine the event or location relevance by matching the relevance definition of each advertisement with event information or location information which are respectively supplied by event organizers and location service providers.

28. The system of claim 1 further comprising of means to make a purchase prediction for a given subscriber;

said prediction comprises of the product which she is likely to purchase, the type of the product and the likely time of purchase.

29. The system of claim 28, wherein the said purchase prediction is based on a modeled purchase pattern of each individual subscriber.

30. The system of claim 1, wherein said means to learn the model of the purchase prediction for each individual subscriber, from historical data of the purchases made by the subscriber, comprising the step of:

learning the frequency pattern of a product purchase by time-series analysis of the historical purchase data.

31. The system of claim 30, wherein said means comprises the step of deriving hierarchical relations for different products and extend the individual product prediction to hierarchically related product groups;

and using this hierarchical relation for extending the preferences learned for a product to the related product groups.

32. The system of claim 31, wherein said means further comprises the step of learning the influence of external events, on the pattern of purchase of a product by an individual subscriber, based on Bayesian network model of events, the said events comprising of festivals, seasonal sports events, purchase of other products, and the personal events such as anniversaries.

33. The system of claim 31, wherein said means further comprises the step of:

learning the life style aspects of a subscriber which include but not limited to most preferred colors, and background for visuals.

34. The system of claim 1, wherein said week-wise plan for streaming the advertisements is derived in accordance with the purchase prediction made for the subscriber and service level agreements with the subscriber and sponsors.

35. The system of claim 1, wherein said method comprises of means for customizing the presentation of the advertisements to suit a subscriber'"'"'s preferences;

said customization is affected at various levels and one of the plurality of the levels of customization is at the level of the visual contents wherein the visual contents are modified to contain human characters or animated cartoon characters or a combination of both so as to match with the preferences of the individual subscriber;

the said matching of preferences is carried out by choosing one of the plurality of the possibilities provided by the sponsor which is hierarchically close to that preferred by the subscriber.

36. The system of claim 35, wherein said levels of customization further consists of a level at which the customization of an advertisement is affected in terms of the preferred kind of audio comprising of male or female voice, alternative types of background musicals available with the system;

and preferences in terms of audio message or textual message.

37. The system of claim 35, wherein said levels of customization further consists of a level at which the customization of the advertisement is affected in terms of the preferred language wherein the audio and the textual content are customized to be in the language preferred by a subscriber.

38. The system of claim 35, wherein said levels of customization further consists of a level at which the advertisement is customized in a way it is suitable for reception by any one of the plurality of terminals consisting of, but not limited to, Telephones, Mobile phones with or without video capabilities, Wireless enabled Laptop or handheld computers, Desktop computers connected to web, and TV sets.

39. The system of claim 35, wherein said levels of customization further consists of a level at which the advertisement is customized to suit the device limitation of a subscriber in terms of audio and video capabilities.

40. The system of claim 35, wherein said levels of customization further consists of a level at which the advertisement is customized to include subscriber preferences derived from the life style information of the subscriber, the said preferences comprises of color combinations, preferred background of the visuals, and favorite personalities.

41. The system of claim 35, wherein said method comprises of means to learn the subscriber'"'"'s preferences in terms of the presentation aspects comprising of audio, visual, movie with animation or movie without animation, and musical content, the said learning is based on the response by the subscriber to a specially designed questionnaire which is administered on-line or offline at the start of subscription and at regular intervals thereafter to update the changes that may occur in the subscriber'"'"'s preferences.

42. The system of claim 38, comprises of means to collect voluntary feedback from a subscriber on the streamed contents;

said voluntary feedback specifies her like or dislike of a particular advertisement and is motivated by an offer of surprise gifts to randomly selected subscribers.

43. The system of claim 1, wherein in the said interactivity is provided with the advertising system during the streaming of the advertisement, the said interactivity is provided to the subscriber by making use of interaction by voice or interaction by touch screen, wherein subscriber can ask for additional information, in response to which the system supplies the requested information either directly or through a call center.

44. The System of claim 43, wherein said interactivity further provides an option to use a mobile commerce facility through which the subscriber performs the activities such as accepting promotional offers and making online purchases of the advertised products.

45. The System of claim 43, wherein said interactivity further provides an option for the subscriber to convey the acceptance of a promotional offer by direct interaction with system and realize the actual offer through the retail outlets at a later time by presenting the specific offer ID allotted by the system to the outlet.

46. An apparatus, for selecting, customizing, and streaming promotional advertisements of products and services to 3G capable terminals of specific individuals who are subscribers and are prospective buyers of a product or service featured in the advertisements, comprising of:

(a) a computer system for performing non-real time procedures;

(b) a computer system for performing real time procedures; and

(c) a subscriber-specific mobile terminal providing 3G features comprising of means to provide time dependent location information, means for configuration management, and means for interactivity related to streamed advertisements.

47. The system of claim 46 wherein said computer system for performing non-real time procedures comprises of means for deriving purchase predictions for individual subscribers and means for selecting advertisements which are relevant to the individual subscribers.

48. The system of claim 46 wherein said computer system for performing non-real time procedures comprises of means for learning subscriber preferences.

49. The system of claim 46 wherein said computer system for performing non-real time procedures comprises of means for managing the information related events, mall and outlets, and means for deriving weekly plans for streaming advertisements to an individual subscriber in accordance with schedule preferences.

50. The system of claim 46 wherein said computer system for performing real time procedures comprises of means for stream management and managing interactivity with the subscriber.

51. An apparatus, for selecting, customizing and streaming promotional advertisements of products and services to 3G capable terminals of specific individuals who are subscribers and are prospective buyers of a product or service featured in the advertisements, coupled to a telecommunication and data-communication network for communicating plurality of information comprising of:

(a) information related to events, mall, and outlets, and associated offers;

(b) purchase transaction information from outlets;

(c) advertisement information from sponsors;

(d) schedule information, purchase predictions, and advertisement selections;

(e) configuration modifications and real time interactions from subscriber-specific 3G terminals; and

(f) dynamic location information from subscriber-specific 3G terminals.