WO2001052126A2 - Interactive product selection system - Google Patents

Abstract

A product selection system and method is implemented in an interactive medium and compares criteria for a product selected by a consumer or business with the attributes of all known products in that field. The system identifies products which satisfy the needs of the user and provides a detailed objective comparison of products, ranked by the suitability of each product against the selection criteria. Categories of objective attributes can be removed from consideration and products are then re-ranked according to remaining categories. Once a satisfactory objective comparison has been made, the user may assess subjective elements, such as design and handling, and the products are accordingly re-ranked. Finally, a list of top ranked products, and price and availability of the top ranked product are displayed.

Description

ΓNTERACTΓVE PRODUCT SELECTION SYSTEM

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates broadly to systems for comparing and selecting products on the basis of consumer criteria. More particularly, this invention relates to interactive systems, implemented in computer software and hardware, which enables an array of products to be compared, ranked, and selected on the basis of both objective and subjective criteria.

2. State of the Art

When seeking to make a purchase, consumers are often faced with a huge choice of products with a bewildering array of specifications, features, performance and build quality, from many known or unfamiliar brands, and across a wide range of prices. For example, there are over one thousand refrigerator/freezer products, ranging in price from under $100 to over $5000, available in the United States.

In order to assist a consumer in making an educated and presumably appropriate decision as to which product is best suited to their needs, a number of product rating guides, described below, are available. However, each such guide primarily relies on a subjective analysis based on selective criteria which fail to consider the requirements of an individual consumer. In addition, most services only provide features and price listings. Therefore, a low- cost product with more features may appear superior to a higher price and higher quality product with fewer features. In reality it is impossible to determine which product is best suited for a particular individual from these guides.

Most manufacturers operate consumer led, rather than product led, marketing strategies. That is, products are designed to better satisfy a specific consumer need or set of requirements. In effect, this segments markets into groupings of like-minded consumers, and manufacturers target these consumers with specially focused products. The result is that products which are capable of more precisely meeting the needs of a segment of consumers are produced at a lower price than a ubiquitous product which attempts to meet the needs of all consumers.

As such, manufacturers differentiate their products in order to make them more desirable than the products of their competitors to a particular target market segment, and often even to sub-groups within the target segment. The products are made more desirable in that the consumer gets more of what they want, and less of what they do not require, for their money. Price itself is not usually the prime purchase motivator. Rather, it is the perceived value of the product for that price relative to other products.

This concept, referred to as "added value", is crucially important to manufacturers. It is in reality the backbone of product positioning and range strategy, which is deeply influential in the achievement of volume, margin and return on investment objectives.

Therefore, in the case of cameras, for example, consumers appear to be provided with an abundance of choice when it is realized that over 300 cameras from fifty manufacturers are available from which to choose. However, this abundance of choice is directed to various market segments all with sub-segments, each of which respond to different "added value" criteria. In satisfying consumer needs, the choice of equals usually narrows to less than a dozen, where "added value" becomes the deciding factor for purchases.

Applying "added value" is a science. Combining the optimum balance of rational or objective attributes (e.g., features, performance and build quality) with the right degree of emotional or subjective attributes (styling, touch and feel and brand values) to sell at the most appealing price point (and rarely the lowest price point), while leaving sufficient margin for retailers/distributors is a complicated equation. Adding too much "added value" can adversely affect the price point or margin, while adding too little "added value" can reduce desirabihty of the product or even erode brand values.

Over the last twenty years consumers have become increasingly more sophisticated and demanding in their purchase processes. This sophistication has been matched equally by manufacturers who have improved and enhanced their products, with an ever-increasing focus on tightly targeted "added value". Predictably this has created difficulties in the retail environments where the need for more speciahzed staff knowledge and explanatory point-of-sale has had to keep pace in making sure the benefit of each product can be adequately explained in relation to different consumer needs. The fact that retailers can typically stock only a limited range of products within any product category, which thereby edits the choice and reduces the number of directly competing products to a manageable number, has for the most part masked the inevitable shortcomings of a complicated marketplace. However, the rapid growth of product sales over the Internet has recently exposed these shortcomings. For example, while a display of fifty models of dishwasher would be exceptional for a retailer, the Internet has expanded the consumer's selection to a choice of well over three hundred dishwashers.

Both manufacturers and retailers are fully aware that the Internet will widen a consumer's choice to conceivably every model available and to many sales outlets. This concerns the manufacturers and retailers enormously because, without a proper means of comparing products, consumers are unable to determine value (quality versus price), let alone recognize the "added value" which is important to a particular consumer; i.e., "the right product for me". Without detailed "like-for-like" comparative data a consumer cannot distinguish the difference between a high quality product and a cheap look-a-like. While televisions, power drills, stereos, etc. can all look very similar from the outside, their list of features can indicate differences. Nevertheless, determining the real differences important to a particular consumer requires more than a skin deep or cursory appraisal, as products suited to one product segment will be a poor value to a person requiring a product in another product segment.

While the consumer understands his or her needs, the consumer does not necessarily know how to articulate the needs in a way that creates usable selection criteria. While the consumer may read up on one or more products, the consumer rarely reaches a proper understanding of details. Therefore, most consumers seek a shortcut to make a purchase decision easier, surer and more enjoyable.

Various types of product selection guides including product comparisons are published in print or online to help consumers choose products. Such guides, which are all described in detail below, include: (1) editorial advice from magazines, newspapers, or television; (2) test reports, ratings, and "best buy" recommendations from independent rating and testing organizations, such as Consumer Reports®, Consumer Digest®, and Consumers Association™; (3) features and price listings from specialist magazines, and online shopping sites such as the MSN eShop™ and NetMarket.com™; (4) structured analysis provided by Personalogic™; and (5) consumer opinion poles, as provided by J.D. Power® or online sites such as deja.com™. However, none of these guides provides truly objective and quantified product comparisons that show a buyer which products best suit their individual needs.

Editorial advice is personal and anecdotal opinion. The function of the editorial advice is not to suggest which product is the right product for a particular consumer, but rather to provide advice for a broad audience which rarely matches the needs of a particular consumer.

Independent testing organizations having several shortcomings. First, they typically restrict products tested to 10-20% of the products in any sector, so that the information provided to a consumer is incomplete. Second, the organizations test products that have been purchased, rather than test the manufacturers' specification, thereby invalidating the statistical accuracy of the test. That is, testing an individual product model is not a statistically valid representation of all products of that model. Third, the consumer does not know how the reported data relates to their specific needs. The typical five choice scale (excellent, very good, good, fair and poor) for selected criteria is far too broad and superficial to compare similar products within a sector. Fourth, the overall scores are so general as to be meaningless. For example, in Consumers Association™ products are given an overall score within a range of 1-10, yet with most scoring 7-9. This three point scale in difference (7-9) is not particularly helpful when trying to choose between sixty products, as it is likely that approximately twenty products will have a score of 7, twenty products will have a score of 8, and twenty products will have a score of 9. This compression of scores fails to provide sufficient information for an educated choice by the consumer. With a greater number of products, the capability to distinguish products further dissolves. Fifth, each product is scored individually without using any common measurement. Such scores are not relative or comparable and are unable to highlight superiority of one product relative another.

By way of example, Consumer Reports® evaluated only 10 compact cameras available in a restricted price range of $120 to $265. However the compact camera market sector in the United States includes 407 cameras, ranging in price from $26 to $2495, with 120 priced in the limited range of $120 to $265 chosen by Consumer Reports®. Therefore, on the basis of these ratings a consumer cannot choose with any degree of confidence which, of all available compact cameras, is best for the consumer, or even best overall. In another example, a Consumers Association™ report evaluated 12 cameras out of sector of 68 available cameras. In the report, Minolta had both the most expensive, with the lowest score (7/10), and the least expensive, with the highest overall score (9/10). Clearly, in this context, the Consumers Association™ rating is misleading.

The consumer reporting models do attempt to rate products. However, because their ratings are mostly subjective and mix tangibles (measurable) with intangibles (immeasurable), their shortcomings dilute the validity of their results to just being better formed opinions.

In addition, "best buy" recommendations tend to be unreliable unless they define the criteria against which the chosen products are a best buy. Typical criteria include "best value" (most benefit for the money), "best budget-priced" (most benefit for a low price), "best mid- priced" (most benefit for a mid-price), and "best top-end" (most benefit for a top price) models, against which the provided recommendations are merely unsubstantiated opinions. However, a product considered as providing the most "benefit" for a product reviewer may not provide the most benefit for a particular person. Different people have different needs and the product providing the best value for one person will not be that which provides the best value for another person with different needs. Specialist magazines and online shopping sites such as MSN eSHOP™ which provide features and price listings are ineffective for accurate comparisons, as products cannot be accurately compared based on features and price alone. Moreover, the consumer is left to work out what is critical, useful or optional for their needs. In addition, differences between products having similar features, which often have significant and unexplained price differences are not illuminated. The result is that differently priced products having similar features appear equal when most often they are not. This type of guide provides no guidance in determining which is better value: a more expensive known brand or a cheaper product from an unfamihar brand. Without any comparison of quality, it is impossible to compare value.

In structured analysis, such as provided by a system like Personalogic™, the consumer is required to self-complete a "selection decisions" questionnaire from which the suitability of products is ranked. However, such structured analysis only works if the consumer knows exactly what are his or her needs, wants, and decisions. Any uncertainty negates the validity of the result. In addition, most questions require answers ranging from "feel strongly" to "don't mind"; this broad characterization inevitably skews most results towards an uninformed guess. The rating system fails to compare variables of product quality and performance relative to consumer needs. Moreover, once ranked, the Personalogic™ system provides only a chart listing features and price, similar to MSN eShop™ and NetMarket.com™. However, as discussed above, the consumer cannot make an informed and appropriate choice solely on the basis of features and price.

Consumer poles, such as J.D. Power® are quantitative studies of the post-purchase opinions of selected users. They are not a rating system to evaluate like-for-like comparison and suitability for a particular consumer.

Therefore, given the number of guides available to a consumer, determining what products should be on their short list of products to evaluate, the examination of the pros and cons of those products, the evaluation of the performance of those products, and the balancing of priorities and trade-offs is a very complex, and for most buyers, laborious process.

SUMMARY OF THE INVENTION

It is therefore an object of the invention to provide a interactive product selection system which selects the appropriate products for a consumer based upon the consumer's particular usage and needs requirements for the product. It is another object of the invention to provide a product selection system which distinguishes between objective criteria and subjective criteria.

It is a further object of the invention to provide a product selection system which given the needs of a consumer, performs all of the objective comparison and analysis.

It is an additional object of the invention to provide a product selection system which, where no standard exists, establishes objective criteria and scales for measurement of objective criteria and fairly evaluates products.

It is also an object of the invention to provide a product selection system in which manufacturers are assured that their products are considered by any consumer using the system whose selection criteria matches the attributes of the product.

In accord with these objects, which will be discussed in detail below, a consumer product selection system is provided which includes a rating system which compares and ranks products The system is implemented in an interactive medium, for example, over the Internet, an in-store kiosk, portable digital media, e.g., CD-ROMs and DVDs, or via interactive television or telephone.

The product selection system compares an individual consumer's selected criteria for a product with the attributes of all known, and preferably available, products in that field. The system identifies products which satisfy the consumer's needs and provides to the consumer a detailed objective comparison of products, ranked by the suitabihty of each product against that individual's selection criteria. Categories of objective attributes can be removed from consideration and products are then re-ranked according to remaining categories. Once a satisfactory objective comparison has been made, the system enables a consumer to assess subjective elements, such as design and handling, and then re-ranks the products. Finally, the system preferably displays a final list of products, and price and availability of the top ranked product.

The product selection system operates through a back end and a front end. The back ent identifies objective and subjective criteria (attributes), produces the comparative objective data, scores the objective data in terms of product performance, functionality and build quality. According to one preferred aspect of the invention, independent and authoritative research, e.g., consumer research, is used to determine both objective (quantitative and qualitative) and subjective categories, and products are rated within an objective category by manufacturer specifications and/or independent scientific tests to provide the comparative objective data. The front end to the system assesses a consumer's needs, identifies the products having the attributes that satisfy those needs, requests that the consumer enter a price range, and then displays comparative data on those products satisfying the needs within the price range. According to a preferred aspect of the invention, products are ranked, and the overall rank of a product is determined by consumer-provided selection criteria grading the consumer's usage and needs for a product. According to yet another preferred aspect of the invention, products may be re-rankec based on subjective determinations by a consumer with respect to ranked products. In order to assist the consumer in making subjective determinations, subjective features or aspects of several products may be viewed side-by-side.

Additional objects and advantages of the invention will become apparent to those skilled in the art upon reference to the detailed description taken in conjunction with the provided figures.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a block diagram of the interactive consumer product selection system of the invention;

Fig.2 is a flow chart of the back end portion of the interactive consumer product selection system according to the invention;

Fig. 3 is a flow chart of the front end portion of the interactive consumer product selection system according to the invention; and

Figs.4-15 are exemplar screen displays which illustrate the front end implementation of the interactive consumer product selection system of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring to Fig. 1, a consumer product selection system 10 is provided which, in general, objectively compares the requirements an individual consumer (user) has for a product with the attributes of all known, and preferably available, products in the relevant market segment. The system then identifies which products satisfy the consumer's needs and provides a detailed and ranked objective comparison of each product relative to the selection criteria of the user and overall product suitability ranking for the particular consumer. Once an objective comparison has been made, the system enables a consumer to assess subjective attributes of a product, such as design and handling. Finally, the system preferably displays product price and availability.

More particularly, the system 10 generally includes a database 12, a data entry computer 13 used in entering data into the database, and an inquiry computer 14 (e.g., a server) coupled to the database for manipulating the data within the database. The data provided by the data entry computer is preferably obtained from a collection operation 15 which is described in more detail with respect to Fig. 2. The system also includes one or more user interfaces 16, 18, 20 (e.g., remote computer terminals with video monitor and computer mouse attached thereto) coupled to the inquiry computer 14. As such, the system is implemented in an interactive medium: for example, on a web site on the Internet, on an in-store kiosk, in portable digital media (e.g., CD- ROMs and DVDs) operable with a computer, or on an interactive television channel. Preferably more than one user may interface with the system at the same time.

The product selection system 10 operates through a back end 100 (shown in Figs. 1 and 2 and described in detail below) and a front end 200 (shown in Figs. 1 and 3 and described in detail below). The back end 100 identifies subjective and objective criteria which may affect a purchase by a consumer, produces the comparative objective data, and utilizes algorithms to score (grade) the objective criterion attributes. The objective attributes are further categorized as either a "features" (functionality) related attribute, a "performance" related attribute, or a "build quality" related attribute. In addition, "feature"-related attributes are further categorized as pertaining to a particular "level of interest", and "performance"-related attributes are categorized as pertaining to a particular "results wanted", which will be described in more detail below. With respect to subjective attributes (e.g., the "look and feel" of a product), the back end collects information to enable a consumer to subjectively rate such attributes. The front end 200 of the system assesses a consumer's needs, identifies the products having the attributes that satisfy those needs, requests that the consumer enter a price range, and then ranks and displays comparative data on those products satisfying the needs within the price range.

Referring now to Fig. 2, the back end 100 of the system is directed by one or more research planners. For each product segment, a research planner creates a report identifying which types of consumers are buying which products and hypothesizes as to why such purchases are made by the consumer groups. Based upon the report, a researcher specializing in qualitative and quantitative research assembles at least one consumer research group reflecting the target audiences for a product segment and conducts consumer research at 110. The consumer research groups preferably include at least one focus group, e.g., eight to ten people, each of which are each prompted to provide open-ended responses and thereby provide qualitative data, and at least one larger group, e.g., hundreds, in which the consumers are requested to provide multiple choice or true/false responses and thereby provide quantitative data. The researcher prompts the research group with questions to independently and authoritatively construct statistically sound research which determines consumer selection criteria for a product segment. The methodolody of inquiry for a focus group preferably follows the order of (1) inquiries designed to elicit spontaneous answers, (2) probe and unprompted inquiries, and then (3) prompted inquiries. An exemplar series of inquiries according to this methodolody for SLR (single lens reflex) cameras, would be (1) "What's important in a camera?", (2) "What else can you think of?", and (3) "Is ease of use important?" Another exemplar series would be (1) "What makes a camera easy to use?", (2) "Can you think of anything else?", and (3) "Do you think autofocus makes a camera easier to use?". The questions and their respective responses are directed at determining (1) the usage and needs of consumers ('level of interest' and 'results wanted'), (2) the determination of and relative importance of all relevant product attributes, and (3) the degree of significance for individual attributes. With respect to the relative importance of attributes, attributes are weighted in relative importance (given a priority ranking) by determining which features a consumer expects products within a market segment to have and which valuably distinguish one product from another. The degree of significance determines what level of performance difference is noticeable or valuable to a consumer. For example, in rating computer monitors, 640 x 480, 800 x 600, and 1024 x 768 are all discemable differences in image resolution. However, a monitor having a resolution of 820 x 615 likely would not provide significant or discemable difference to a consumer relative to a monitor having an 800 x 600 resolution. Moreover, while for monitors 640 x 480, 800 x 600, and 1024 x 768 have become defacto standards with respect to significant differences in image resolution, where no standards exist for discerning degrees of significance with respect to a product attribute, the consumer research, through appropriate inquiry by the researcher, determines the degrees of significance. For example, with SLR cameras, the difference between "happy snaps", amateur, and professional quality can be defined through the consumer research. These responses provide a detailed analysis of which features and other factors affect a consumer's purchase decision for a type of product. As such, the consumer research completely defines market segments for each of the products serviced by the system.

The market segments may additionally be defined using approved common standards, technical standards, and manufacturer product specifications. Approved common standards are typically industry or government definitions of performance and quality, e.g., fuel consumption, washing cleanliness, etc. Technical standards are generally industry standards for grading individual product components and performance, e.g., processor speed. Manufacturer product specifications are provided by product manuals or questionnaires completed by the manufacturers. Based upon the above, the research planner can determine how consumer usage and needs segment a market. For example, with respect to single lens reflex (SLR) cameras, based on the consumer research, the research planner may determine that consumers use cameras for four purposes: (1) for easy to use point and shoot photography, (2) for learning the basics of photography, (3) for creative control of various aspects of photography, and (4) for professional use. The research planner in conjunction with a professional in the field of the products assigns every objective attribute to satisfying one or more purposes. For example, there may be one hundred fifty cameras attributes (e.g., manual focus, autofocus, predictive focus, eye controlled focus, center weighted metering, spot metering, selective metering, matrix metering, aperture control, shutter control, etc.) and each is designated as to whether it satisfies one or more of the purposes. "Autofocus" may be a useful feature for each of point and shoot photography, learning the basics, and creative control, while "aperture and shutter control" may be assigned as useful for creative control and professional photography. In addition, performance attributes are likewise assigned as to whether they meet the needs of consumers: (1) candid snapshots, (2) excellent amateur photographs, (3) professional quality photographs, or (4) suitable for slide reproduction. As a result, in the front end 200 as described below, when a consumer desires a camera that will provide professional quality results, cameras having the feature attributes of aperture and shutter control, as well as all other professional attributes are selected. Likewise, if a consumer wants a camera for travel, cameras having build quality attributes associated with a rugged construction are selected.

Once the consumer market research and other market defining research is concluded, the research planner defines, at 112, selection criteria based on the research results. The selection criteria are preferably multiple choice-type inquiries for objective attributes (which is utilized in the front end for the user to input the user's usage and needs of a product within a product segment), and identify the correct product segment for each user of the system. That is, the selection criteria are inquiries which allow the system to determine the importance of various features, performance, and build quality for an individual. For example, for SLR cameras, now that the market segments are known, selection criteria preferably includes an inquiry which defines the purpose for which the consumer is purchasing the camera: (1) "point and shoot", (2) "learning basics", (3) "creative control", and (4) "professional". Another inquiry is . preferably directed to the results the consumer is trying to achieve with the camera: (1) "happy snaps"; i.e., candid snapshots, (2) "excellent pictures", (3) "professional standards", or (4) "slide reproduction". The selection criteria inquiries also preferably determine a consumer's weighting of importance for selected features of a camera. The selected features are preferably features which have been identified through the consumer research as being so important to consumers that consumers prefer to provide input particularly with respect thereto. For example with respect to the important features of light metering, autoexposure and/or flash capability, an inquiry may be made as to what value the user places on that feature: (1) essential, (2) desirable, (3) unimportant, (4) no value, and (5) don't want. With respect to the scoring of the features, as described in more detail below, the value the user of the system places on a particular feature affects the scoring of that feature as a weighting factor. For example, if a feature is "essential", the feature, in the preferred embodiment of the invention, is not weighted up or down, but only cameras having that feature will be selected in the operation of the front end. In the preferred embodiment of the invention, if a feature is "desirable", it is weighted one hundred fifty percent, if "unimportant" weighted fifty percent, and if of "no value" given a zero weighting. If the feature is not wanted, the result will be that no camera having the feature is selected for the user of the system.

Once the selection criteria have been determined, the objective attributes are categorized under either Features, Performance, or Build Standard. The Features category include attributes related to the functionality of a product. The Performance category assesses the technical performance of the attributes, and covers any aspect of performance relevant to the criteria selected. The Build Standard assesses the build quality of a product, and preferably is a measure of all tangible aspects of quality in terms of materials, components, and production finish are assessed. For example, SLR for cameras, the Build Quality score may include a measure of the durability of the housing (e.g., plastic or metal), the surface finish quality (e.g., whether or not rubber-reinforced), the quality of the viewfϊnder housing (plastic or metal), the construction of the viewfinder lens (plastic or glass), the construction of the shutter curtain (plastic or metal), the affixation of the lens mount (e.g., four screws or six screws) the quality of the electronic circuitry (based on accepted industry standards as to circuit quality), and the abrasion and corrosion resistance of contacts (e.g., whether or not gold plated), among other measures. In addition, an Accessory Range category may be included as a category to permit an assessment o: the optional features and accessories available for a product. The use of categories enables the front end of the system to identify areas of product strength important to a user without inundating the user of the system with too much information. That is, in the front end, for each product a score is given for each of Features, Performance, and Build Standard, and each such score is a sum (preferably indexed out of 100) of the scores of selected attributes in that product which are in the same category. In particular, the Features score will provide an overall score of all attributes relevant to a user's level of interest, typically affected by the features which may be weighted by the user. The Performance score is an overall score of all attributes relevant to the user's results wanted. The Build Standard score is an overall measure of quality, regardless of selected criteria. This is because a poor quality component with respect to a non-relevant attribute may affect the quality of a relevant attribute. Therefore, the system preferably assumes the user wants a product which is well built. In order to calculate scores, each objective attribute is rated by the system in the back end 100, as described below, while the subjective attributes are presented to the user for rating by the user in the front end 200. More particularly, each objective attribute within the categories is assigned by the planner at 114 a Rule by which it may be rated. Rules are a scaled scoring system by which product attributes can be compared. The Rules create a level playing field which facilitate distinguishing "added value" in relation to an individual consumer's particular needs. The Rules divide the product into factually comparable attributes, features, and components which are at a level sufficient to differentiate the "added value".

Preferably there are at least seven types of Rules, though other types of Rules may be added. Rule 1 permits only a YES or NO to be provided and assigns a score of any number (e.g., 1 or 2) or zero. Rule 1 is a useful measure as to whether a product includes a feature. Rule 2 permits the assignment of scores within a number range. Scores in Rule 2 are assigned to increments distributed throughout the range. Rule 3 permits scores to be within a range continuum where values within and outside the range are confined to particular values within the range. By way of example, for the product segment of SLR cameras, the Rule for camera motordrive speed may assign all motordrive speeds to a value of 1, 2, 3, 4, or 5. If a particular camera has a motordrive speed of 3.2 frames per second, it may be assigned a value of 3, whereas if another camera has a motordrive speed in excess of 6 frames per second, it may be assigned the maximum value of 5. Scores in Rule 3 represent levels of performance, rather than an actual measured value. Rule 4 permits multiple choice responses. Scores within Rule 4 are graded as levels of quality. Rule 5 permits the use of industry grading standards, and scores within Rule 5 reflect industry grades. Rule 6 permits the use of an options list, and scores are graded as levels of achievement. An increased number of selected options may indicate either a greater or lower score depending on how and for what purpose Rule 6 is applied. Rule 7 is a combination score and score are provided by the summation of multiple other rules. This is because certain attributes require multiple measurements across a number of different points. For example, Rule 7 is useful for measuring sound quality at a plurality of different frequencies. The Rules provide unbiased consistency and permit automated scaled scoring of raw data.

Once it is determined which Rule will be applied to each attribute within a category, a determination is made, also at 114, as to what type of data is required from the manufacturer of each product within a product segment, as well as the format of the required data, such that the Rules may be implemented. In addition, with respect to each subjective attribute, the data required to permit a user to personally rate the subjective attribute is determined. This determination permits such data, e.g., product images, dimensions, weight, etc., to be later gathered from the manufacturers. The Rules are then individually applied to the objective attributes at 116. Thus, each objective attribute is provided with a system by which it can be scored, as well as a maximum score. Each objective attribute is also assigned a maximum individual score which represents its relative importance in the decision making process, as determined by consumer research at 110. For example, for each important attribute which is key to the decision making process, a maximum score of 10 points may be assigned to the attribute. For each major attribute which represents significant added value, a maximum score of 5 points may be assigned. For each useful extra attribute which adds some value, a maximum score of 2 points may be assigned. While for a common or standard feature, a maximum score of 1 point may be assigned. Relating back to the categories (Features, Performance, and Build Standard), for each product, the score for the category includes the sum of the relevant scores of each of the attributes, indexed out of 100.

Once the Rules have been applied to attributes, data description tags are preferably created at 118 for the organization, storage, and selection of data for all products in the system. Data description tags enable the selection criteria for one market segment (e.g., cameras) to be utilized with software code which can universally process data for different types of products in other market segments (e.g., washing machines). That is, data description tags are a means by which selection criteria and product data are put into a common language for storage, display anc processing by the system.

For example, data description tags for cameras may include:

process nameancluded forms

"cameras":"use", "importance", "fit", etc. form nameancluded questions "importance":"built in flash" "autofocus" feature name:feature type:weighting

"built in flash":yesno:5,0 "autofocus" importance scale: 10,6,4,2,0

With respect to the above, "process name" refers to the collection of product data for a product category being referenced, and the standard forms ("use, "importance", "fit", etc.) required to permit a user to select a product from that product category. The forms are templates which are customized based upon the data description tags. Each form includes inquiries with respect to various attributes of the products, and the inquiries are set out by referencing a feature name, feature type, and weighting. "Feature name" refers to a particular product feature, e.g., built in flash or autofocus. "Feature type" refers to the type of response required from a question asked with respect to the features, e.g., as a yes/no response ("yesno"), or as a weighted rating along a scale. Weighting refers to the scores associated with a provided answer.

Once the data tags are created, the system references the tags and the following pseudocode could be used with data description tags from any product category. Therefore, the following pseudocode is capable of being processed with respect to any product category.

With respect to any "feature name", if <feature type> = "yesno" process_yesno using <reply>, <feature weighting> else if <feature type> = "importance scale" process_importance_scale using <reply>, <feature weighting" else if . . ..

The pseudocode would be processed as follows. The first feature name for cameras is "built in flash". "Built in flash" requires a "yesno"-type response; i.e., Rule 1 is assigned to "built in flash". If a "no" reply is received, zero points are assigned. If a "yes" reply is received, five points are assigned. The second feature name is "autofocus", and is scored on an importance scale; i.e., Rule 4 is assigned to autofocus. The reply is scored as 10, 6, 4, 2, or 0.

Based on the above, it should be clear that code processing is the same for other products. For example, data tags for washing machines may include the following:

feature name:feature type:weighting

"economy mode":yesno:7,0

"integrated tumble dryer":importance scale:8,4,2,l,0

The data is processed in the same manner as with camera data. A yes/no response is required of a question regarding whether or not a washing machine has economy mode, with a "yes" response being assigned seven points and a "no" response being assigned zero points. Next ar inquiry with respect to the importance a washing machine having a tumble dryer integrated therewith is provided, with the reply being assigned a scaled score of 8, 4, 2, 1, or 0.

An interface is then created at 120 to facilitate the collection of data at 15 from manufacturers, in either written or electronic form. Referring to Table 1, in order to prompt manufacturers to provide the required data, a data interface (the first three columns of Table 1), which may be in written or electronic form, is preferably created which sets forth what data is required, as well as what format for the data is required, for each attribute in both objective and subjective classifications. Where manufacturer data is unavailable or cannot otherwise be used, similar interfaces are created and used by independent research groups and other data providers.

The manufacturers provide data at 122 to the interface as shown in the fourth column of Table 1. Referring then to the last two columns of Table 1, the Rules convert the data into ratings at 124, and are then provided as data in the form of the description tags for storage in the database 12 of the system 10. It will be appreciated that database maintenance will be on a continuing basis at 126 as manufacturers constantly release new products, and the manufacturers or others must provide new data via the interface for entry into description tags in the database of the system.

Once the data is entered in the form of description tags, the product selection process by which the appropriate product for a consumer is selected may be performed. Turning now to Fig. 3, the operation of the front end of the system, i.e., the system interface with the consumer (user), is illustrated with respect to an exemplar search for an appropriate single lens reflex (SLR) camera. It will be appreciated that the operation of the front end will be substantially the same with other products, with the exception of different product segment appropriate selection criteria (feature lists) being presented for selection by the user.

A user preferably first logs into the system at 210 by inputting a login name (user name) and password. If the user is not akeady registered in the system, the user is preferably prompted to provide personal data (e.g., name, postal address, email address, gender, age, and reason for use of the system) as well as to choose at 212 a product category (i.e., product segment) from a list of product categories, e.g., SLR cameras. Referring to Figs. 3 and 4, the system then selects and displays at 214 objective product usage and needs inquiries (selection criteria inquiries) assigned to that product category in the form of data description tags in the back end system 100 and stored in database 12. For example, for SLR cameras, inquiries preferably include the 'Level Of Interest' 310 of the user (e.g., 'point and shoot', 'learning basics', 'creative control', and 'professional') from which more than one may be selected by the user via check boxes 312; 'Results Wanted' 314 (e.g., 'happy snaps', 'excellent pictures', 'professional standards', 'slide reproduction') from which preferably one result is selected via a radio button 316; and a plurality of 'Features' attributes 318 (e.g., autofocus, auto exposure modes, motor drive, shutter and aperture priority, spot metering, dioptic adjustment, built-in flash). The user indicates at 216, preferably with radio buttons 320, the value to the user of each attribute in the Features (i.e., essential, desirable, unimportant, no value, don't want). As discussed above, the value provided by the user affects the importance of that feature, by requiring all selected products to include the feature (essential), by weighting the score of the feature up by fifty percent (desirable), by weighting the score of the feature down by fifty percent (unimportant), by giving the attribute a zero score (no value), or by requiring all selected products not to include the feature (don't want). However, while certain features are selected for weighting according to user input, such features may only contribute a small percentage of the overall Features score for the product. Indeed, numerous other features not available for weighting may dominate the Features score.

The personal data and the user's input with respect to the Level Of Interest, Results Wanted, and Features inquiries are stored in a second database 24 coupled to the inquiry computer.

Once the user has provided his or her selection criteria input at 216, the inquiry computer 14, based upon the user's input sorts through the data description tags, weighs the Features according to the user designated importance or necessity of the features in the database 12, and selects at 218 the products which match the selection criteria. The system accounts for the overlap which may be present in the Results Wanted category; that is, there is no clear line between wanting 'excellent pictures' and 'professional standards'. Therefore, as the purpose of the system is to match the needs of the user, and not redefine and educate users, there is preferably built-in overlap between the different levels of Results Wanted. For example, cameras having performance scores 0-80 relate to candid snapshots, performance scores of 75-95 relate to excellent pictures, performance scores of 90-100 relate to professional quality and performance scores 90-100 and having features necessary for quality slide reproduction (e.g., fractional stops) relate to slide reproduction.

Referring to Figs. 3 and 5, based on results of the search, the number of products ("11") meeting the user's selection criteria is displayed at 322, as is the price range 324 ("$400 to $1060") which the products span. If the user desires, the user may select a new price range at 220, 326 and the system then updates the number of cameras which meet the user's selection criteria. Regardless, the user may select at 328 to view which cameras meet the user's selection criteria, or may select at 330 to update the selection criteria. If the user enters a new price range at 222, 326, cameras outside the new price range will be removed at 224 from consideration, and the display will be updated with a like screen indicating the number of cameras which now meet the user's selection criteria. The user is then again able to adjust the price range until a suitable number of cameras within a desirable price range is provided by the system. Once the desired number of cameras meeting the user's selection criteria and within the desired price range is indicated at 322, the user selects to view a list of the cameras at 328.

Referring to Figs. 3 and 6, the system provides to the user at 228 a tabulated ranked list of products which meet the user's criteria. The list is provided with column headings which - preferably include 'Drop' 330, 'Brand' 332, 'Model' 334, 'Price' 336, Overall Score' 338, 'Features' 340, 'Build Standard' 342, 'Performance' 344, and 'Accessory Range' 346. The headings Overall Score' 338, 'Features' 340, 'Build Standard' 342, 'Performance' 344, arid 'Accessory Range' 346 are all score values of the respective category based upon the user's criteria. That is, while one product may have a Features score of 80 for one user, the same product may have a Features score of, e.g., 70, for a different user having different selection criteria (which were selected as shown in Fig.4). Therefore, each such category score is an individually weighted objective rating of the attributes within the relevant category. The Overall Score is preferably a rounded average of the Features, Build Standard, Performance, and Accessory Range scores. Each row includes a product (i.e., brand/model) and its scores under the appropriate heading. The listed products are preferably initially ranked by Overall Score; however, the list can be sorted by any of Brand, Price, Overall Score, Features scores, Build Standard score, Performance score, or Accessory Range score.

In accord with a preferred aspect of the invention and as discussed above, attributes which are not relevant to selected criteria preferably are not included in product assessment and ranking. With Features and Performance, the scores assigned to each category reflect user responses to selection criteria inquiries; individual Features and Performance attributes which are not relevant to the selected criteria preferably are not included in product assessment. With Build Standards, tangible aspects of quality in terms of materials, components, and production finish are assessed, and preferably all aspects of quality, regardless of selected criteria, are factored. When the Accessory Range category is included, the Performance and Build Standards of those features will also be assessed above.

Each row including a product is provided with a 'D' 348 or other 'drop' selector under the Drop heading. The Features, Build Standard, Performance, and Accessory Range columns are also provided with a 'D' 350 or other 'drop' selector. According to a preferred aspect of the invention, the 'drop' feature permits selected products or entire columns to be removed, i.e., by selecting the 'D' in the appropriate column or row. Therefore, products from manufacturers undesirable to the user can be removed from the list. In addition, by selecting the 'D' 350 in one of the Features, Build Standard, Performance, and Accessory Range columns, that criterion is removed from both the selection process and the ranking calculation. Therefore, upon remova of a category column, the Overall Score is recalculated as an average of the remaining categories, and products are re-ranked based upon the user's selection criteria with respect to the remaining categories.

The system affords the user several other options. The last action may be undone at 352 For example, a dropped column may be re-added. When a column is re-added, the Overall Score is recalculated as an average of all included categories. The user may return at 354 to the criteria selection screen. Referring to Fig.7, the information provided in the table may also be displayed as a graphic by selecting 355. For example, the information may be plotted at 356 on two axes in which each axis provides a different category or criteria, e.g., Overall Score, Price, Performance, Build Quality, or Accessory Range, which is selectable by the user at 357. Once the user is satisfied with the scores of the objective categories of the cameras selected, the user may at 358 cause the system to display a 'short list' of cameras; that is a few, e.g. six, top ranked products with respect to the objective selection criteria. All data manipulation selected by the user, e.g., dropping categories and particular products, headings by which the displayed data is sorted, etc., is also stored in the second database 24. The collective data stored in the second database 24 from multiple users of the system may be used for subsequent data mining.

Once the user elects to view the short list, the system provides an interface by which the user can subjectively rate various subjective visual attributes of the products. The subjective visual attributes, which according to the invention are preferably identified by focus groups, as discussed above, are then rated personally by the user. Based upon the user's personal feeling about "subjective" visual aspects of the products, the user may have the system re-rank products or drop products entirely. In order to facilitate the subjective comparison, it is preferable that the side-by-side images of several, and preferably all, important subjective visual aspects of the products be viewable with the system, and further preferable that enlargements (close-ups) of individual images be made available to the user.

For example, referring to Fig. 8, with respect to SLR cameras, the subjective visual attributes may include the overall visual appeal 360, the viewfinder 362, the LCD display 364, the control layout 366. With respect to each of the visual attributes, the system permits the user to rate whether the user likes the particular attribute ('Like'), at 370, finds the attribute acceptable ('OK') or is noncommittal with respect to the particular attribute ('Not Sure'), at 372. If the user is clear in his/her dislike of a visual attribute, the user can 'drop' the camera from the short Ust at 374. According to a preferred subjective rating system, each visual attribute is assigned 10 points, providing a default overall visual score of 40 points (with four visual attributes). As each attribute is reviewed, the user potentially alters the score based upon the user's rating. A 'Like' rating increases the score assigned to 25 points, an 'OK' rating keeps the score at 10 points, and a 'Not Sure' rating decreases the score to 5 points. Therefore, with four visual attributes, any product in which the user rates all the attributes as 'Like' will be provided with a visual score of 100 points. The individual visual attribute scores are held in memory.

In Fig. 8, the user rates the overall visual appeal of the cameras with side-by-side views of the 'short list' cameras. The cameras may be shown from any view (e.g., front view, top view) or may be rotated through a three dimensional image using known imaging software. Where appropriate, selecting an image on the display prompts the system to provide more detail information with respect to that visual attribute. By selecting 366 (control layout) in Fig. 8, the display of Fig. 9 is provided, and a side-by-side comparison of the control layouts of the cameras can be made. Moreover, by selecting the Pentax MZ5 (e.g., by selecting its image), the system provides an enlarged, more detailed, and annotated view of the control layout of this camera, as shown in Fig. 10. Likewise, by selecting 362 (viewfinder) in Fig. 8, side-by-side images of the viewfinder of the cameras are displayed. Selecting the viewfinder image 376 of the Pentax MZ5 in Fig. 11, causes the system to display an enlarged and more complete viewfinder image 378, as shown in Fig. 12, as well as annotated information 380 with respect to various aspects of the viewfinder. Other visual attributes may be similarly viewed to facilitate rating by the user.

Dimensional attributes, such as 'weight' (see Fig. 8, 368), can also be displayed, as shown in Fig. 13. A user can remove any product that is unacceptable from further consideration by selecting 'drop'. Preferably the system does not permit the user to otherwise rate the attribute.

The system can also display particular features of the 'short list' products in a table so that the user can learn which particular added value attributes are included in the respective products. Selection of 'features' at 376 in Fig. 8 provides the user with a Ust of several feature groups from which the user can choose to view a table, as shown in Fig. 14. For cameras, feature groups may include focus at 384, film transport at 386, flash at 388, shutter at 390, meter at 392, exposure at 394, or miscellaneous at 396. For example, selecting exposure at 394 provides a feature table of exposure features for each of the 'short list' cameras. Products failing to have particular features that the user desires can be removed from consideration. As also shown in Fig. 14, information relating to other factors which may affect a consumer's purchase decision with respect to a product may also be provided. Links to information available directly from the manufacturer, at 398, or from third parties, at 400, may be provided. Manufacturer information 398 may include tinks to online product brochures at 402, other advertising at 404, and press releases at 406. Third party information 400 may include links to other consumer opinions at 408, and press comments at 410.

Referring to Figs. 3 and 15, based on the objective rankings and the subjective comparisons and rankings, the system provides at 232 a ranked final Ust 412 of products which best meet the selection criteria or subjective preferences. The Ust includes the overall visual score 414, as weU as a final score 416, which is preferably a rounded average of the objective and visual scores. The final Ust 412 preferably contains three products only, such that the appropriate products are highlighted for the user, though another number of products may be presented. In addition, the system preferably indicates whether differences in final scores 416 are statistically vaUd, for example, by providing an indication of what difference in scores is statistically significant (not shown).

According to a preferred aspect of the invention, at 417 a user may request the system to determine whether, if the consumer is wilting to spend a sum certain (e.g., fifty doUars) greater than the upper value of the selected price range, a superior camera would be selected by the system. If a camera with a higher overall score with respect to the weighted objective attributes in the categories which have not been dropped is located, a display similar to Fig. 6, but including the new camera or cameras is provided, and the user may re-evaluate the cameras at 228, 230 and 232.

If the user is not wilting to increase the upper price range or if the system locates no additional cameras for the user to choose from, the system provides at 418 the user with information as to where the top ranked product from the final Ust is available, as well as the price at 420 and preferably any promotional offers available in connection with the product, e.g., rebates. If the user wishes to see the availabiUty of one of the other final Ust products, the user may select the second or third ranked products (i.e., by selecting the underhned brand of the product at 421), and the system will provide information similar to that shown with respect to the top ranked product. Preferably, where the user is interacting with the interface 14 from home, the system 10 also provides information to facilitate user purchase of the top-ranked product, e.g., store locations or mail-order telephone numbers at 422, or online Internet availabiUty 424. On the other hand, where the system interface is a kiosk in a retail store, availabiUty and price may be indicated, without indication of availability from competing outlets. The interactive product selection system of the invention provides a consumer with a selection process which is beUeved to mirror typical consumer purchase decision behavior. Thus, the system deteπnines usage and needs identification, price range, functional suitabihty, subjective preference, and value judgment, and provides the user with one or more products which best fit the usage and needs of the consumer. In addition, the system highlights when there are significant differences between the products, and clarifies when the difference is relevant to the user's needs. Once products are selected, the system provides the consumer with the current prices of the products, as well as locates where the products are available.

Moreover, unlike prior art systems, the system of the invention assures manufacturers that their products are considered by any consumer whose selection criteria matches the rated attributes of the product.

It will be appreciated that while the system has been generaUy described above with respect to an individual person making purchase decisions on his or her own behalf, it is intended that the term "consumer" mean all product purchasers, and that "consumer products" refer to aU products which may be purchased. As such, a consumer may be an individual operating in a business environment making a business-to-business purchase or, more generaUy, any real or fictional entity (e.g., a corporation) or organization (for profit or not for profit), or person within such an entity or organization, which may make purchase decisions for products (collectively a "business" in the claims). Consumer products are then anything which the consumer, as now broadly defined, may desire to purchase. As such, consumer products may be any products or even components of products.

For example, in a business-to-business context, an employee in a purchasing department of a company (the consumer) may desire to select and purchase one or more filing cabinets for the company. According to the invention, the system includes data related to filing cabinets, as well as many other business-to-business products, which have been rated both objectively and subjectively in substantially the same manner as described above with respect to the example of cameras. That is, in the back end, independent and authoritative research will have been used to determine both objective (quantitative and quaUtative) and subjective categories for filing cabinets (e.g., front loading or top loading, frequent use or long-term storage, legal or letter size, SOHO use or large capacity, strength of materials, finish of materials, weight and dimensions), and the fiUng cabinets are rated within each objective category by manufacturer specifications and/or independent scientific tests to provide the comparative objective data. The front end to the system assesses the consumer's needs, identifies the filing cabinets having the attributes that satisfy those needs, requests that the consumer enter a price range, and then displays comparative data on those filing cabinets satisfying the needs within the price range. A resulting ranked list of fiUng cabinets is provided, with the overall rank of the fiUng cabinet being determined by consumer-provided selection criteria grading the consumer's usage and needs for a fiUng cabinet. The fiting cabinets may then be re-ranked based on subjective determinations by a consumer. In order to assist the consumer in making subjective determinations, subjective features (e.g., style and finish) of several fiting cabinets may be viewed side-by-side.

In another business-to-business example, a company may desire to purchase an HVAC (heating, ventilation, and air conditioning) system. The HVAC system is used to circulate existing air, exchange existing air with fresh air, heat air and cool air. As such, the requirements for an air conditioner generaUy include the abiUty to heat air, cool air, provide fresh air, filter air coming in, and filter air going out. Features of such systems include whether free standing, window mounted, waU mounted, ceiling mounted, cavity fitted, duct mounted, availabiUty of poUution filters (e.g., to clean outgoing air of grease and odors and to clean incoming air and circulating air of pollen and smoke), number of speeds, set speed options, variable speed setting, manual setting, thermostat control, humidity control, and flow capacity. Performance categories include flow rate (volume of air moved per hour), noise levels (internal and external), coohng or heating rate, effectiveness of humidity control, effectiveness of filters, accuracy of climate control and vibration reduction, among others. These features and performance attributes are rated by manufacturer specifications and/or independent scientific tests to provide the comparative objective data. The front end to the system assesses the consumer's needs, identifies the HVAC systems having the attributes that satisfy those needs, requests that the consumer enter a price range, and then displays comparative data on those HVAC systems satisfying the needs within the price range.

Different consumers clearly have different needs and the value of the features and performance ratings will be determined based upon the usage and needs of the consumer. For example, in a restaurant kitchen that is cooking with deep fat fryers, an HVAC system wiU need to: (1) maintain an acceptable temperature in the kitchen for both staff comfort/productivity and food hygiene safety, (2) extract fumes, smells, grease, and smoke faster than they are produced, (3) duct the extracted air to above roof height for venting, (4) ensure that vented air does not smell or contaminate the exit area, (5) ensure that the ducting does not build up a residue of grease to cause a fire hazard, (6) include a fire dampener so if fire breaks out in the kitchen, it is not spread to another area, and (7) minimize the noise and vibration so as not to disturb customers in the restaurant, neighbors of the restaurant, or make the kitchen noise levels uncomfortable. An HVAC system for use in restaurant which does not heat food, e.g., a delicatessen, will need to cool the temperature in the restaurant so that its refrigerated "serve- over" cabinets (open topped cabinets containing meats and cheeses) maintain a consistent temperature regardless of outside temperature and customer traffic. If the temperature rises in the deUcatessen, the condenser units have to work harder to keep the cabinets cold. If the cabinets are free standing the condensers will need to be located inside within the cabinets and their exhaust heat will heat the room, requiring the condensers to work even harder. If too strong a fan is used to remove heat, the still (cold) air in the serve-over cabinets wiU be removed and replaced with warm room temperature air. For the gym of a health club, an HVAC system will need to: (1) maintain a consistent and conducive temperature for its clients, (2) replace foul air with fresh cool air, (3) vent foul air away, (4) provide consistent temperature, regardless of whether there is one person or thirty people exercising, and (5) be substantiaUy silent inside the gym.

A resulting ranked Ust of HVAC systems is provided, with the overaU rank of the HVAC system being determined by consumer-provided selection criteria grading the consumer's usage and needs for an HVAC system. For a restaurant in which cooking is performed, the selected systems may include high speed, manually controlled, fans of proper extract flow capacity for the size of kitchen and number of cooking appUances, along with ducting with filters, a fire damper, and a high rise wind resistant exit flue. For a delicatessen, the selected systems may be slow ceihng extraction fans, with large blades, to take hot air out of the top of the room. The fan speed is preferably automatically adjusted based on readings from temperature sensors. For a gym, the selected systems may include automated climate control air conditioners with external cootihg unit having a flow capacity for the size of room in which it will be used.

The selected HVAC systems may then be re-ranked based on subjective determinations by a consumer. In order to assist the consumer in making subjective determinations, subjective features (e.g., style and finish particularly where the system will be in view of customers) of several HVAC systems may be viewed side-by-side.

As such, it is seen that the system and method operate substantially the same for an entity in a business-to-business context as they do for an individual person.

There have been described and inustrated herein an embodiment of an interactive product selection system and a method of implementing the system. While a particular embodiment of the invention has been described, it is not intended that the invention be timited thereto, as it is intended that the invention be as broad in scope as the art will aUow and that the specification be read likewise. Thus, while the system has been described in detail with respect to three products, SLR cameras, fiUng cabinets, and HVAC systems, the system of the invention is adaptable for use with respect to any consumer purchase product. For example, the selection of a medical device by a physician for a patient can also be faciUtated with the invention. In addition, while a single inquiry computer has been disclosed, it will be appreciated that the inquiry computer may comprise a cluster of systems each having a copy of the database or in communication with the database. In addition, while particular manners in which to identify the objective and subjective product attributes which may be important to a consumer, it will be appreciated that other ways may be utilized for such identification may utiUzed. Also, while particular ways in which to collect objective data has been disclosed, yet other or alternative data collection methods can be used. Furthermore, while several Rules have been identified to score coUected data, it wiU be understood that other Rules can be similarly used. Moreover, while a fifty-fifty weighting between objective and subjective scores is preferably utiUzed to compile a final score, it wiU be appreciated that other respective weighting can be used as weU. Also, while the inquiry and results are preferably visuaUy displayed, it wiU be appreciated that the system may be may have auditory functionaUty, permitting inquiry and response to occur, e.g., over a telephone. It will therefore be appreciated by those skilled in the art that yet other modifications could be made to the provided invention without deviating from its spirit and scope as claimed.

Claims

Claims:

1. A method of constructing a database having back-end data for a market segment for an interactive product selection system, said method comprising: a) utilizing a focus group to determine general attributes of products within the market segment: b) dividing said general attributes into a group of objective attributes and a group subjective attributes; c) for each of a plurality of said objective attributes, identifying levels of significant difference in performance; d) based on product specifications received by a plurality of manufacturers, and based on said identified levels, assigning products from said plurality of different manufacturers with ratings for said objective attributes; and e) storing said ratings for said objective attributes as back-end data in a database memory of said interactive product selection system.

2. A method according to 1, further comprising: f) determining relative importance of said plurahty of objective attributes.

3. A method according to either of claims 1 or 2, wherein: said identifying comprises utilizing said industry standards and/or said focus group to identify.

4. A method according to any previous claim, further comprising: for each of said pluraUty of said objective attributes, identifying said objective attribute as one of a feature-related attribute,' a performance-related attribute, and a build quaUty-related attribute.

5. A method of constructing a database having back-end data for a market segment for an interactive product selection system, said method comprising: a) utilizing a focus group to determine general attributes of products within the market segment; b) dividing said general attributes into a group of objective attributes and a group subjective attributes; c) for each of a pluraUty objective attributes from said group of objective attributes, categorizing said objective attribute as being feature-related, performance-related, or build quaUty-related; d) based on product specifications received from a plurality of manufacturers and based on said categorization, assigning products to a market subsegment; and e) storing said categorization of said objective attributes as back-end data in a database memory of said interactive product selection system.

6. A method according to 5, wherein: said categorizing comprises utilizing said focus group to categorize.

7. A method according to either of claims 5 or 6, further comprising: f) determining relative importance of said plurality of objective attributes; and g) storing said relative importance as back-end data in said database memory.

8. A method of constructing a database having back-end data for a market segment for an interactive product selection system, said method comprising: a) utilizing a focus group to determine the usage and needs of consumers or businesses with respect to products within said market segment; b) identifying general attributes of products within said market segment, said general attributes including a pluraUty of objective attributes; c) linking said pluraUty of objective attributes with said usage and needs of consumers or businesses; d) assigning products from a plurality of different manufacturers with ratings for said objective attributes; and e) storing said ratings for said objective attributes as back-end data in a database memory of said interactive product selection system, said objective attributes being Unked in said memory to said usage and needs.

9. A method according to claim 8, further comprising: f) dividing said general attributes into a group of objective attributes and a group of subjective attributes; g) either determining relative importance of said pluraUty of objective attributes, or for each of a pluraUty objective attributes from said group of objective attributes, categorizing said objective attribute as being feature-related, performance-related, or build quaUty-related; and h) storing said categorization and/or said relative importance as back-end data in said database memory.

10. A method according to either claim 8 or 9, wherein: said linking utilizes said focus group to tink.

11. A method according to any of claims 2, 3, 4, 7, 9 or 10 wherein: said focus group is used to determine said relative importance.

12. A method of selecting a product from a plurality of products in a market segment, comprising: a) identifying objective and subjective product attributes; b) for each objective attribute, collecting data for each of the pluraUty of products; c) rating the collected data; d) entering said rated collected data into a database; e) categorizing the objective attributes; f) providing an interactive consumer or business interface coupled to said database; g) eliciting through the interactive consumer or business interface the objective and subjective requirements of a consumer or business for a product within the market segment; and h) determining from said objective requirements which products provide more added value to the consumer or business relative to other products within the market segment.

13. A method according to claim 12, wherein: said products determined to have more added value are ranked in order of the added value which they provide to the consumer or business.

14. A method according to either of claims 12 or 13, wherein: said objective attributes are categorized into a plurality of categories, and the consumer or business can select to remove any one or more of said categories from affecting the rank of products determined to have more added value.

15. A method according to any of claims 12-14, wherein: said determining deteπnines from said objective as weU as said subjective requirements.

16. An interactive product selection system for selecting one or more products for a consumer or business from a plurality of products within a segment of a market, said system comprising: a) a computer system having a processor and a database including rated attribute data for each of said pluraUty of products within the segment of the market, said rated attribute data including a scaled rating of a pluraUty of categories, said pluraUty of categories including at least two of features, performance, and build quahty of the plurality of products; and b) an interface adapted to display a grid tisting a group of said pluraUty of products, and for each member of said group, an overall score, and a score for each of said plurality of categories, said interface further adapted to peπnit the consumer or business to delete at least one of said plurality of categories from said grid, wherein when said consumer or business deletes a category from said grid, said processor calculates a revised overall score for each member of said group.

17. A system according to 16, wherein: said products are arranged in said grid initially in order of said overall score, and said products are rearranged in said grid in order of said revised overall score.

18. A system according to either of claims 16 or 17, wherein: said grid is displayed by row and column, at least a first column displaying a brand and model number of each of said group of said plurality of products, a second column displaying overall score, and at least a third, a fourth, and a fifth column separately displaying said pluraUty of categories.

19. A system according to claim 18, wherein: at least a sixth column displays price for each member of said group.

20. A system according to claim 18, wherein: a drop indicator is provided in conjunction with each column displaying said pluraUty of categories, wherein said interface means is adapted to permit the customer to delete a category by selecting said drop indicator.

21. A system according to claim 16, wherein: each of said products has objective attributes, and each of said categories includes a pluraUty of factors related to said objective attributes only.

22. An interactive product selection system for selecting one or more products for a consumer or business from a pluraUty of products within a segment of a market, said system comprising: a) a computer system having a processor and a database including rated attribute data for each of said pluraUty of products within the segment of the market, said rated attribute data including a scaled rating of objective data, said database further including subjective data regarding each of said pluraUty of products; and b) an interface adapted to display a grid tisting a group of said plurality of products, and for each member of said group an overall score based on said scaled rating of said objective data, and further adapted to provide the consumer or business with a plurahty of side-by-side comparisons related to said subjective data, whereby the consumer or business can rate said subjective data.

23. A system according to claim 22, wherein: said subjective data includes images of subjectively ratable aspects of said plurality of products.

24. A system according to either of claims 22 or 23, wherein: said overall score is recalculated to include adjustments based on said rating of said subjective aspects by the consumer or business.

25. An interactive product selection system for selecting one or more products for a consumer oi business from a plurality of products within a segment of a market, said system comprising: a) a computer system having a processor and a database including rated attribute data for each of said plurality of products within the segment of the market, said rated attribute data including a scaled rating of objective data; b) an interface adapted to provide a plurality of inquiries requiring consumer or business response with respect to the intended usage of a product by the consumer or business, needs for the product by the consumer or business, and/or feature desirability to the consumer or business in a product within the segment of the market, wherein based on said consumer or business response, said computer system selects one or more products form said plurality of products within the market segment for the consumer or business.

26. A system according to claim 25, wherein: said selected products are provided on said interface.

27. A system according to claim 26, wherein: said selected products are provided as a tabulated grid on said interface.

28. A system according to claim 27, wherein: said tabulated grid Usts said selected products in order of a combined scaled rating of said selected products.

29. A system according to claim 28, wherein: said combined scaled rating score is modified based on said consumer or business response.

30. An interactive product selection system for selecting one or more products for a consumer or business from a plurality of products within a segment of a market, said system comprising: a) a computer system having a processor and a database including rated attribute data for objective features for each of said pluraUty of products within the segment of the market; and b) an interface adapted to provide a plurality of inquiries requiring consumer or business response which rates the desirabihty of said objective features to the consumer or business, wherein based on said consumer or business response, said computer system weights said rated attribute data for said objective features and selects one or more products form said plurality of products within the market segment for the consumer or business.

31. An interactive product selection system for selecting an appropriate product for a consumer or business from a plurality of products within a segment of a market, each of said products having objective attributes and subjective attributes, said system comprising: a) a computer system having a processor and a database including, for the segment of the market, selection criteria inquiry data which is adapted to eUcit respective added values to the consumer or business for the objective attributes of products within the segment of the market, and rated attribute data related to the objective attributes of each of the pluraUty of products, wherein said rated attribute data includes a scaled rating of one or more of the features, performance, and build quatity of the plurality of products; and b) an interface adapted to permit the consumer or business to input responses to said selection criteria inquiry data, wherein said computer system uses said input responses and said rated attribute data to identify products having objective attributes which have the most added value to the consumer or business relative to other products in the segment of the market.

32. An interactive product selection system according to claim 31, wherein: said attribute data further includes comparative subjective data for subjective attributes of said pluraUty of products, said comparative subjective data being presentable by said interface to said consumer or business to permit the consumer or business to make a subjective comparison of said subjective attributes of said products.

33. An interactive product selection system according to either of claims 31 or 32, wherein: said attribute data includes attribute data on substantiaUy every product within the segment of the market.

34. An interactive product selection system according to any of claims 31-33, wherein: said objective attributes are determined by focus groups.

35. An interactive product selection system according to any of claims 31-34 , wherein: said objective attributes are ranked in order of importance by focus groups.

36. An interactive product selection system according to any of claims 31-35, wherein: said objective attributes are weighted relative to their ranked importance.

37. An interactive product selection system according to any of claims 31-36, wherein: said ratings of said objective attributes are at least in part based on common standards, technical standards, and manufacturer product specifications.

38. An interactive product selection system according to any of claims 31-37, wherein: a scoring system is applied to the attribute data to objectively rate each said objective attribute.

39. An interactive product selection system according to claim 38, wherein: said scoring system apphes a score based on one or more of the following scoring , methods,

(i) any one whole number or zero,

(ii) any number within an infinite number range,

(in) any number within a range continuum,

(iv) any one of a multiple choice response,

(v) industry standard grading,

(vi) selection of one or more options, where a greater number of selected options indicate a higher or lower score, and

(vii) a summation of scores from any one or more of scoring methods (i) - (vi).

40. An interactive product selection system according to any of claims 31-39, wherein: wherein said computer system identifies uses said input responses and said rated attribute data to identify products having objective attributes which have the most added value to the consumer or business of all the products in the segment of the market. said computer system ranks said identified products according to the added value for the consumer or business.

41. An interactive product selection system according to any of claims 31-40, wherein: said interface includes a display, and said computer system visually displays the identified products by rank on said display.

42. An interactive product selection system according to any of claims 31-41, wherein: said database is provided on portable digital media.

43. An interactive product selection system according to any of claims 31-42, wherein: said interface is located remotely from said computer system.

44. An interactive product selection system according to any of claims 31-43, wherein: said interface is located in an outlet in which said plurality of products are sold.

45. An interactive product selection system for selecting an appropriate product for a consumer or business from a plurality of products within a segment of a market, each of said products having objective attributes and subjective attributes, comprising: a) a computer system having a processor and a database including, for the segment of the market, selection criteria inquiry data which is adapted to elicit the usage and needs of the consumer or business and rated attribute data related to objective attributes of each of the plurality of products, said rated attribute data including ratings of at least one of the features, performance, and build quality of the pluraUty of products, wherein at least one of said selection criteria data and said rated attribute data are at least in part identified by focus groups; and b) an interface adapted to permit the consumer or business to input responses to said selection criteria inquiry data, wherein said computer system uses said input responses to said selection criteria inquiry data and said rated attribute data to identify products having objective attributes which are most appropriate to the consumer or business relative to other products in the segment of the market.

46. An interactive product selection system according to claim 45, wherein: said attribute data further includes subjective inquiry data for subjective attributes of said pluraUty of products, said subjective inquiry data being presentable by said interface to the consumer or business to permit the consumer or business to make a subjective comparison of said subjective attributes of said products.

47. An interactive product selection system according to claim 46, wherein: the consumer or business inputs subjective preferences into said interface in response to said subjective inquiry data, and based on said input responses to said selection criteria inquiry data and said subjective preferences, said system ranks said products.

48. An interactive product selection system according to any of claims 45-47, wherein: said objective attributes are ranked in order of importance by focus groups.

49. An interactive product selection system according to any of claims 45-48, wherein: said objective attributes are weighted relative to their ranked importance.

50. An interactive product selection system according to any of claims 45-49, wherein: said ratings of said objective attributes are at least in part based on common standards, technical standards, and manufacturer product specifications.

51. An interactive product selection system according to any of claims 45-50, wherein: said usage and needs of the consumer or business elicited by the selection criteria inquiry data correspond to the added value of respective objective attributes of the products within the segment of the market.

52. An interactive product selection system according to any of claims 45-51, wherein: said interface is located remotely from said computer system.

53. An interactive product selection system according to any of claims 45-52, wherein: said interface is located in an outlet in which said pluraUty of products are sold.

54. An interactive product selection system for selecting an appropriate product for a consumer or business from a plurality of products within a segment of a market, each of said products having objective attributes and subjective attributes, comprising: a) a computer system having a processor and a database including, for the segment of the market, subjective attribute data related to subjective attributes of each of the plurahty of products, said subjective attributes being at least partially identified by focus groups; and b) an interface adapted to display representations of subjective attributes to the consumer or business and adapted to permit the consumer or business to input personal preferences with respect to the subjective attributes, wherein said computer system uses said input personal preferences to rank products based on the desirability of said subjective attributes to the consumer or business.

55. An interactive product selection system according to claim 54, wherein: said interface displays subjective attributes for a pluraUty of products at one time.