Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1998-03-11
2001-09-04
Alam, Hosain T. (Department: 2771)
Data processing: database and file management or data structures
Database design
Data structure types
C705S007380, C725S009000, C455S002010
Reexamination Certificate
active
06286005
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to the field of computer-assisted data manipulation and analysis. More particularly, the present invention relates to methods and techniques for quickly and efficiently accessing and sorting large quantities of demographic data and media access information for various decision-making purposes, especially advertising.
2. Description of Related Art
The business of supplying information and/or entertainment mingled with paid advertising to audiences has become an important part of the world economy. Many large corporations have as their primary business to inform or entertain their customers through media. In addition, most businesses depend on advertising to reach potential customers with product or service information. Television viewing, for example, is one of the most popular activities in homes around the world. Large numbers of people both in the United States and abroad use the television as a primary source for news, education, entertainment, and various social activities. This large population of television viewers is also a very desirable group of consumers, sought after for their purchasing power. Most businesses and companies recognize the potent power of the television when it comes to attracting and retaining consumers for their various products and services. Television has the capability to transmit virtually any message to millions of people in an instant. Because of this enormous potential, television advertising is believed to be one of the most important advertising vehicles available for reaching a desired consumer population.
Because television has an enormous potential to reach and influence many consumers, many businesses spend large amounts of money on television advertising, thereby making advertising revenue a major source of income for both the networks which create and commission television programs and the television stations which broadcast them. Broadcast television advertising revenue is estimated to be in excess of $30 billion per year, which explains why advertisers care so much about television viewing. The most important part of the equation is to try and get the advertising message in front of the right group of television-viewing consumers, i.e., matching the product with the desired target market.
Since the value of target marketing is well known, the focus of most businesses is to try and place their advertisements in commercial slots on television shows that effectively attract and retain the targeted consumer groups. For example, many major sporting events are heavily subsidized by advertising campaigns and commercials promoting beer. On the other hand, most weekly home and garden programs don't present any advertising or commercial promotions for alcoholic beverages. Obviously, the businesses that advertise and market alcoholic beverages such as beer have determined that the consumers who purchase beer are more likely to be watching Monday Night Football than Martha Stewart's Living. By focusing beer-related advertising efforts on those programs that the target audience is most likely to watch, the advertising campaign will, in theory, attract more consumers and pay greater dividends.
To effectively determine which shows are most favored by the desired target market, advertising agencies and businesses have utilized the services of various different research and consulting firms. These firms purportedly have the ability to accurately identify which segment of the consumer population is most likely to be viewing which television program at any given time. In addition, these research firms try to predict which viewers will be most receptive to various advertising campaigns, based on the demographic make-up of the viewing population. Based upon the weekly viewing information prepared and presented by the television viewing-related research firms/agencies, advertising campaigns are born and terminated. Above all, however, these advertising campaigns are most often the result of educated estimates, well-thought out probabilities, and other experience-based decision-making processes. It is most desirable to create an optimal campaign which effectively utilizes a finite combination of resources to communicate to the target audience. While this goal is easy to quantify, it is not so easy to achieve and many advertising campaigns are simply ineffective.
The reason why some advertising campaigns are successful and some are not is really very simple. Although the practice of identifying target markets and developing advertising campaigns attract those targeted consumers is a fairly developed practice, the ability to accurately and efficiently measure which advertising campaigns are most successful and what changes should be made in an advertising campaign to increase the overall effectiveness of the advertising campaign is a far-less developed area of industry. There is no way to effectively gather feedback for an advertising campaign and to accurately measure or evaluate the performance of the advertising effort.
One of the main problems with the currently used models and techniques for identifying and implementing the most optimal advertising campaign for a given product using a given advertising medium is the lack of effective tools for scoring, evaluating, and comparing alternative advertising strategies. There is no well known, acceptable technique or method for evaluating, scoring, and comparing one advertising plan or schedule and strategy with another. As further described below, this deficiency reduces the advertising optimization process to a series of estimates and educated guesses when determining which campaign, from among a group of similar campaigns, will be most successful in accomplishing the desired goals.
Another problem with developing effective media advertising campaigns is directly related to the technology limitations of presently implemented systems. Using the currently-available systems and methods to manipulate and analyze the huge amounts of data that are available to decision-makers can take days or even weeks to accomplish. Frequently, the various systems in use today will provide data that are no longer relevant by the time the data are generated. In addition, the lack of sophisticated advertising optimization tools impose artificial limits on advertising agencies and media planners that are actively involved in the decision-making process.
This is particularly true when trying to create and/or customize a campaign to reach the target market in the most cost-effective manner for a given advertiser. There are, at present, no broad-ranging interactive methods or tools available to the media planner for optimizing an advertising campaign in real time. Many media planners have the data available to make strategic decisions regarding advertising, but the available planning tools do not allow rapid and easy access to the data in an intuitive, interactive environment. Specifically, known systems focus only on “effective reach” and do not allow rapid week-to-week analysis of a unified sample.
In addition, present tools rely heavily on estimates and averages as a means of evaluating the impact of a given advertising plan or schedule. While good estimates may yield reliable results, good estimates are more of an exception than a rule. This means that the planning process is more an art than a science, and many years of trial-and-error experience are required to effectively determine or even estimate the probable effectiveness of a given advertising strategy. Because of these factors, many media planners are relatively ineffective in preparing valuable advertising strategies until they have several years of experience.
Another significant drawback of the systems and methods presently used to analyze television audience viewing data is limited access. Many analysis and decision support systems available today are large, expensive computer systems that many smaller companies cannot afford to purchase. Given limited access to necessary re
Alam Hosain T.
Cannon Holdings, L.L.C.
Fleurantin Jean Bolte
Schmeiser Olsen & Watts
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