Patent Application
20110022470
The present invention relates to ad targeting in general, and more particularly, ad targeting when content is being watched. Still more particularly, the present invention is related to a system and method for real-time ad selection and scheduling for targeting purposes so as to enhance viewers' attention on the displayed ads.
Ad targeting in general and TV ad targeting in particular involves delivering specific ads to specific audience. Ad customization deals with diverse consumer segments and hundreds of variations of an ad are generated, say based on context-based business rules, to help in targeting. This further helps in making the ads more effective at the same time reducing the ad wear-out. It has been observed that many TV viewers cite having already seen a commercial, possibly several times, as one of the major reasons for their intent to skip the TV commercials. In order to help retain the interests of the users on the ads, it is required to “beat the expectations” of the viewers. This needs to be achieved while a user is viewing content on a television, personal computer, or mobile phone. Note that “user,” “viewer,” and “subscriber” are used interchangeably. Specifically, the ads compete with content in being able to draw the attention of the viewers. Further, the viewers are mentally tuned to watch the content and hence, the ads are treated an unwanted interruptions. On the other hand, the return of investment on ads is related to the attention factor: the fraction of time the user's attention is on the ads being shown. As a consequence, any solution that addresses the issues related to ad monotonicity, that is, the bombarding of the viewers with the same and most importantly predictable ads, would go a long way in improving the return on investment for the ad sponsors.
U.S. Pat. No. 7,228,555 to Schlack; John A. (Southampton, Pa.) for “System and method for delivering targeted advertisements using multiple presentation streams” (issued on Jun. 5, 2007 and assigned to Prime Research Alliance E., Inc. (Tortola, VG)) describes a system and method for delivering channels of presentation streams carrying targeted advertisements in a television service network environment that includes a generator for generating a set of presentation streams for each of programming channels, each of the presentation streams in each set having same programming data but different ads directed to advertiser-specific market segments of different advertisers.
U.S. Pat. No. 7,203,684 to Carobus; Alexander Paul (Mountain View, Calif.), Roetter; Alex (Palo Alto, Calif.), Davenport; Ben (Mountainview, Calif.) for “Serving content-targeted ADS in e-mail, such as e-mail newsletters” (issued on Apr. 10, 2007 and assigned to Google, Inc (Mountainview, Calif.)) describes an approach for serving content-targeted ads with emails such as email newsletters by including a unique content identifier in the content and using of the same to fetch content-relevant ads from an ad server.
U.S. Pat. No. 7,185,353 to Schlack; John A. (Southampton, Pa.) for “System and method for delivering statistically scheduled advertisements” (issued on Feb. 27, 2007 and assigned to Prime Research Alliance E., Inc. (Tortolla, VG)) describes a system and method for scheduling advertisements in a television network based on such information as channel change statistical information and avail information.
U.S. Pat. No. 6,463,585 to Hendricks; John S. (Potomac, Md.), Bonner; Alfred E. (Bethesda, Md.), McCoskey; John S. (Derwood, Md.), Asmussen; Michael L. (Herndon, Va.) for “Targeted advertisement using television delivery systems” (issued on Oct. 8, 2002 and assigned to Discovery Communications, Inc. (Bethesda, Md.)) describes a novel multiple channel architecture that is designed to allow targeted advertising directed to television terminals connected to an operations center or a cable headend by providing additional feeder channels to early alternate advertising that may be better suited for certain viewing audiences.
U.S. Pat. No. 6,144,944 to Kurtzman, II; Stephen J. (San Jose, Calif.), Nawathe; Sandeep A. (Sunnyvale, Calif.) for “Computer system for efficiently selecting and providing information” (issued on Nov. 7, 2000 and assigned to Imgis, Inc. (Cupertino, Calif.)) describes a system for selecting advertisements in response to a request from a web page server based on such information as demographic information, page sponsor information, and keyword sponsor information.
“Auctioning Ad Space in Video on Demand (VoD) Assets” by Hood; Bill, Sinha; Nishith, and Barker; Reed (document available in the URL; http://www.experts-iptv.com/database/forums2007/advertizing_methods_vodassets.pdf) describes a competitive selection of advertising for Video on Demand based on real-time and near real-time “ad auctioning” that provides a mechanism for dynamically selecting advertisements that need to be placed in conjunction with a specific viewing of a movie.
“Event Driven Semantics Based Ad Selection” by Thawani; Amit, Gopalan; Srividya, and Varadarajan; Sridhar (appeared in the Proceedings of the 2004 IEEE International Conference on Multimedia and Expo (ICME '2004), The Grand Hotel, Taipei, Taiwan, Jun. 27-30, 2004) describes a system for the selection, filtering, and presentation of advertisements based on detected program events and profiles contained in the Home Information System.
“Viewing Characteristics based Personalized Ad Streaming in an Interactive TV Environment” by Thawani; Amit, Gopalan; Srividya, and Varadarajan; Sridhar (appeared in the Proceedings of the 2004 IEEE Consumer Communications and Networking Conference, Caesar's Palace, Las Vegas, Nev., USA, Jan. 5-8, 2004 (CCNC 2004)) describes a channel surfing analysis algorithm for predicting the “user(s) in front” of a television to enable deciding about the nature of ads that are likely to have an impact.
The known systems are largely related to the selection and scheduling of ads based on sponsors' needs and in some cases accounting of relevance. And, hence, do not explicitly address the various issues related to ad monotonicity and ad wear-out. The present invention provides a system and method for the randomized selection and scheduling of ads so as to “beat the expectations” of the users thereby reducing ad monotonicity and ad wear-out.
The primary objective of the invention is to reduce ad monotonicity and ad wear-out in the context of ads shown during the watching of a content on a television, personal computer, or mobile phone.
One aspect of the invention is to exploit multiple ad models for effective display of ads.
Another aspect of the invention is to exploit multiple ads related to the multiple ad models.
Yet another aspect of the invention is to randomly select ads.
Another aspect of the invention is to randomly distribute the randomly selected ad models throughout the content timeline.
Yet another aspect of the invention is to ensure that the randomly selected ads are relevant to the content being watched.
a provides an approach for Time Allocation for Ads.
a provides an approach for Randomized Ad Scheduling (LbAC).
b provides an approach for Randomized Ad Scheduling (SbAC).
c provides an approach for Randomized Ad Scheduling (SAC).
Ads are an important component of any content delivery system. For example, consider a broadcasting scenario: in this case, the content is typically delivered onto a television sets at homes. Most of the programs aired in this manner have one or more sponsors and in return, each of the sponsors gets spots during the airing of the corresponding programs to display their ads. The major expectation on the part of sponsors is that ads, especially during prime time, lead to increased sales revenue. However, the constant bombardment of the same ads can turn out to be counterproductive: viewers may turn off television sets or may skip to another channel. It has been observed in the literature that such a behavior is partially due to the boredom of seeing the same ad again and again leading to ad wear-out. The main challenge is to make ad viewing a pleasure thereby, reducing the boredom and ad wear-out. A solution for this challenge is to identify ads, to be inserted at various time points during the delivering and displaying of a content (say, a movie), so that it is not monotonous and it “beats the expectations.”
For illustrative purposes, three classes of ad models are identified.
Some Illustrative Ad Models are as follows:
a provides an approach for Time Allocation for Ads.
Input: T—Duration of Content (say, a movie);
AMR—The expected ad movie ratio; typically, set by the providers;
W1—The weight associated with the class SAC;
W2—The weight associated with the class SbAC;
W3—The weight associated with the class LbAC;
Cads—Content specific ads related to the various classes;
Here, AMR stands for Ad to Movie Ratio. This is one of the operator/provider controlled parameters and indicates the amount of possible ad time while delivering a particular content, say a movie. Typically, it is a value between 0 and 1. Operator/provider also specifies how the ads related to the various of the classes need to be prioritized. One way to specify this information is to define a weight for each class such that the sum of the weights is unity. For example, for each of the three classes, a weight is associated as follows: W1 with SAC, W2 with SbAC, and W3 with LbAC with W1+W2+W3=1;
a provides an approach for Randomized Ad Scheduling (LbAC). Ads of the various classes are scheduled based on the allotted durations: Ta1 for SAC class, Tat for SbAC class, and Ta3 for LbAC class.
An Approach for Ad Scheduling for ads of LbAC class is as follows:
Note that the ads are randomly selected so as to create a surprise in viewer's mind. Further, all the ads in the class are given an opportunity to be selected before reconsidering an ad again for scheduling.
b provides an approach for Randomized Ad Scheduling (SbAC). Having scheduled LbAC ads, the next step is to schedule SbAC ads. In this embodiment description, while no block-wise randomized selection is described in the case of LbAC class ads, the selection of SbAC ads illustrates block-wise randomized selection.
An Approach for Ad Scheduling (Contd.):
Step 2: Process and schedule SbAC ads;
Note that SAR stands for Scene Ad Ratio which is used in conjunction with AMR, the Ad Movie Ration. SAR of a scene describes the ratio of the amount of ads that has been inserted for to be displayed during the scene break, and the scene duration.
c provides an approach for Randomized Ad Scheduling (SAC).
The final step is to schedule SAC ads.
An Approach for Ad Scheduling (Contd.):
Step 3: Process and schedule SAC ads;
Thus, a system and method for randomized ad selection and scheduling is disclosed.
Although the present invention has been described particularly with reference to the figures, it will be apparent to one of the ordinary skill in the art that the present invention may appear in any number of systems that need to overcome monotonicity and package a deliverable that “beats the expectations.” It is further contemplated that many changes and modifications may be made by one of ordinary skill in the art without departing from the spirit and scope of the present invention.
