Patent Publication Number: US-2005131770-A1

Title: Method and system for aiding product configuration, positioning and/or pricing

Description:
FIELD OF THE INVENTION  
      The present invention relates to configuration, positioning and/or pricing of new products and reconfiguration, repositioning and/or repricing of existing products.  
     BACKGROUND  
      In an increasingly competitive world, businesses or merchants wishing to enter a market segment or maintain a position in a market segment constantly need to introduce new products and reposition existing products. Existing products that might have historically helped gain market share frequently face declining revenues as a result of increased competition, new technologies, and changes in customer preferences.  
      Merchants or businesses seeking to introduce new products typically generate product configurations manually and then test the configurations out using market research. The market research is frequently outsourced to agencies, which determine a product&#39;s positioning based on heuristic judgment and/or inputs from advertising professionals.  
      The various stages of a new product development process include generating and screening ideas, developing and testing alternate product concepts, developing a marketing strategy (including segmenting the market and determining the target market segment, positioning the product, determining product pricing, distribution, etc.), testing the marketing mix, conducting a technical feasibility and costing study, going into limited production, and finally, going into full production.  
      One technique used in the idea generation phase is that of Attribute Listing, in which the values of major attributes of a product are listed and subsequently modified in search of a better product. A large number of combinations may be generated, which may be subsequently pared down, frequently based on heuristic judgment. Such judgment typically factors in competitive offerings. Market research may then be conducted to elicit customer opinion and techniques such as conjoint analysis and multi-dimensional scaling may be used for drawing conclusions. A large number of responses from each respondent are necessary for the results to be meaningful. Additional information relating to the techniques referred to above may be found in a book by Green, P., Tull, D., and Albaum, G., entitled “Research for Marketing Decisions”, 5 th  Edition, Prentice Hall, 1988.  
      Product pricing and positioning are typically based on a multiplicity of factors, including pricing and positioning of competitors&#39; products. However, tracking of the offerings of a large number of competitors is difficult and requires substantial resources. Moreover, even when the positioning of competitive products is known, subjective judgment is usually relied upon to determine product positioning.  
      A further potential problem for merchants or businesses is that existing product pricing and/or positioning might cease to be appropriate as the market evolves, thus resulting in declining revenues. Businesses and merchants are generally unable to detect such a situation, particularly at an early stage, unless costly market research is continually conducted in relation to each potentially competitive product.  
      U.S. Patent Application No. 20020055832 A1, entitled “Structured System for the Planning, Integration, Analysis and Management of New Product Development on a Real-time, Enterprise-wide Basis”, was filed in the names of Donelan A. T., Brown R. G., and Moore R. S. on Jun. 22, 2001 and published on May. 9, 2002. The specification relates to a structured system for managing production tasks involved in the development of a new product.  
      International Publication No. WO 02/03225 A2, entitled “Method and System for Product Lifecycle Management” was filed on Jun. 15, 2001 in the names of Davies J., Chabot P., and Rubin M and published on Jan. 10, 2002. The specification relates to a network-enabled software engine that assists users to coordinate and keep track of the progress and status of activities relating to new product development and product lifecycle management in an enterprise.  
      U.S. Patent Application No. 20010010041A1, entitled “Method for New Product Development and Market Introduction”, was filed in the name of Harshaw B. F. on Dec. 19, 2000 and published on Jul. 26, 2001. The specification relates to a method for management of a pool of new product concepts and ideas by a third party manager, including development and licensing of a new product selected from the pool.  
      Japanese Patent Application No. JP2001243340 A2, entitled “Product Definition in Customer Service Processing System”, was filed in the name of International Business Machines (IBM) Corporation on Feb. 28, 2000 and published on Sep. 7, 2001. The specification addresses the problem of reducing costs by reducing the time taken to introduce new products or modify existing products. None of the above references appear to aid pricing and/or positioning of new or existing products.  
      A need exists for a method, a system, and a computer program product to assist businesses and merchants in relation to configuration, positioning and/or pricing of new and existing products.  
     SUMMARY  
      Aspects of the present invention provide automated methods for aiding new product introduction and for identifying a need for reconfiguring, repositioning and/or repricing existing products.  
      For the case of new product introduction, data relating to a proposed new product is obtained from a merchant, data relating to products similar to the proposed new product is obtained from competitors&#39; websites and processed, product attributes and positioning attributes are identified based on the processed data, and at least one marketing mix for the proposed new product is identified based on the identified attributes. Alternatively, online market research is conducted based on the identified attributes and the at least one proposed new product is identified based on a result of the online market research.  
      For the case of existing products, data relating to one or more of a merchant&#39;s products is obtained, data relating to products similar to the merchant&#39;s products is periodically obtained from competitors&#39; websites and processed, product attributes and positioning attributes are identified based on the processed data, a change in the identified product and positioning attributes relating to the at least one similar product is identified, and one or more of the merchant&#39;s products that require repositioning and/or repricing are identified based on the detected change.  
      Other aspects of the present invention provide systems and computer program products for practising the methods disclosed herein. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
      Embodiments are described hereinafter, by way of example only, with reference to the accompanying drawings in which:  
       FIG. 1  is a flow diagram of a method for aiding new product introduction;  
       FIG. 2  is a more detailed flow diagram of a method for aiding new product introduction;  
       FIG. 3  is a flow diagram of a method for identifying a need for reconfiguring, repositioning and/or repricing a product;  
       FIG. 4  is a more detailed flow diagram for identifying a need for reconfiguring, repositioning and/or repricing a product and aiding a merchant to reconfigure, reposition and/or reprice the product;  
       FIG. 5  is a schematic block diagram of a system for practicing embodiments of the present invention; and  
       FIG. 6  is a schematic representation of a computer system suitable for practicing embodiments of the present invention. 
    
    
     DETAILED DESCRIPTION  
      Embodiments of methods, systems and computer program products are described hereinafter for aiding product configuration, positioning and/or pricing. More specifically, embodiments described hereinafter aid new product introduction and reconfiguration, repricing and/or repositioning of existing products.  
      The term “product”, as used in the present specification, is intended to comprise both products and services offered by a merchant or business. A product possesses one or more attributes (‘product attributes’). For example, attributes of a mobile phone comprise size, weight, battery life, technology standards supported (e.g., GSM), number of ring-tones, presence or absence of built-in camera, etc.  
      The terms “configuration” and “reconfiguration”, as used in the present specification, are intended to refer to the identification or determination of product attribute values.  
      Merchants and businesses strive to “position” their products, which essentially entails creating a real or perceived difference in a customer&#39;s mind between the merchant or business&#39;s products and competing products. Either product attributes or key benefits are focussed on to achieve this. These dimensions which a company may use to position their products may be called positioning attributes. Examples of positioning attributes comprise: 
          Weight: e.g., “the lightest cellphone”.     Price: e.g., “Dress for less (Ross Stores)”    Flavor: e.g., Lightly flavored v/s highly flavored yoghurt, with each positioning targeted to different groups     Looks: e.g. Sporty-looking v/s conservative-looking sports car, with each positioning targeted to different groups.        

      Competitors comprise parties that offer similar products. Similar products not only comprise products of obvious similarity (e.g., two mobile phones from Nokia and Ericsson), but may also comprise products that offer a similar service (e.g., a video cassette player and a DVD player).  
      Embodiments disclosed hereinafter may require the formulation and performance of explicit and/or implicit Online Market Research (OMR) experiments to assist in gathering data by asking for or observing respondents&#39; preferences. Techniques for conducting OMR are disclosed in co-pending U.S. patent application Ser. No. 10/321017, entitled “Method and System for Conducting Online Marketing Research in a Controlled Manner”, which is incorporated herein by reference.  
      Certain embodiments disclosed hereinafter are automated in that steps of methods, sub-systems, and program code are performed or operate without human intervention apart from input by the merchant.  
       FIG. 1  shows an automated method for aiding new product introduction. Data relating to a proposed new product is obtained at step  110 . At step  120 , data relating to products similar to the proposed new product is obtained from competitors&#39; websites. The data relating to the similar products is processed at step  130  and key attributes are identified based on the processed data at step  140 . Online market research based on the key attributes is optionally conducted at step  150  and at least one marketing mix for the proposed new product is identified at step  160 . The at least one marketing mix may be identified based on the key attributes identified in step  140  or the results of the online market research conducted at step  150 , if online market research is conducted, and is representative of customer or market preferences or the ideal market position. A marketing mix may comprise one or more of a product configuration, a product price and a product position.  
       FIG. 2  shows a more detailed flow diagram of a method for aiding new product introduction. At step  210 , merchant input relating to the product is obtained. Attributes of the product, along with attribute value ranges of interest to the merchant may also be specified. The merchant may further specify an objective such as maximization of revenue, profit, unit sales, etc.  
      At step  215 , competitors&#39; websites are crawled to identify products similar to the specified product. For each match found, a variety of data is gathered, including product attribute name-value pairs, pricing (including list price, discounts, credit terms, etc.), and positioning attribute name-value pairs. The products identified based on merchant-specified criteria and/or other criteria based on domain knowledge preconfigured into the subsystem are filtered to produce a shortlist of products at step  220 . Attribute value ranges specified in step  210  may be used as filtering criteria. Other criteria used for filtering may comprise criteria such as the main geographical areas the merchant operates in, the top 10 products by revenue, etc. The merchant may optionally be shown the entire list or a filtered list of products for shortlisting or ratification.  
      At step  225 , the product and positioning attributes are filtered to produce a shortlist of attributes based on one or more of the following: merchant-specified criteria, frequency of occurrence of the actual attributes in the list, other predefined criteria, or on explicit selection by the merchant.  
      The shortlisted products are mapped onto the shortlisted attributes, with separate maps being created for product attributes and positioning attributes, at step  230 . ‘Holes’, which are points on the product attribute map where there are no existing products, are identified. Such may be due to unattractive attribute combinations or potential opportunities overlooked by competitors. The maps and any holes identified may be disclosed to the merchant either graphically or otherwise to enable the merchant to ratify or modify the holes, and also to classify the holes as unattractive or attractive. Clusters of products with similar attributes may be formed using clustering techniques. The attributes for clustering may be drawn from both the product and positioning attributes and the distance ‘metric’ used in clustering may factor in merchant-specified objectives (e.g., revenue, market share, etc.) in a case where the merchant wishes to guide the clustering process. Common product and positioning attributes of successful and unsuccessful products may be drawn from the clusters. These attributes represent successful and unsuccessful combinations that the merchant may wish to replicate or avoid, respectively, when the new product is introduced.  
      Conjoint and other data analysis techniques may be applied to the cluster data to analyze which attribute values contribute to a product&#39;s success. However, as the data available is frequently inadequate, one or more explicit and/or implicit Online Market Research (OMR) experiments are formulated and conducted, at step  235 , to assist in gathering the missing data by asking for or observing respondents&#39; preferences. OMR experiments are also formulated to analyze respondents&#39; perceptions of the shortlisted product offerings of competitors based on the shortlisted positioning attributes. Optionally, the formulated experiments are disclosed to the merchant for validation or modification, either explicitly or implicitly by specification of a budget, number of respondents, etc. The additional experiments are offered to respondents visiting the merchant&#39; website or other collaborating websites, and responses thereto are collected.  
      The data gathered in the OMR is analyzed, at step  240 , along with the shortlisted set of attributes to create a perceptual map and find ideal product configurations using conjoint analysis, an unfolding model, other multi-dimensional scaling techniques, or any other appropriate techniques. The OMR data may further be used to classify the unclassified ‘holes’ as attractive or unattractive and to combine with attributes of clusters of successful and unsuccessful products.  
      Alternative marketing mixes, typically comprising product configurations, positioning and/or pricing, are suggested to the merchant, at step  245 . Characteristics of the mixes may be derived from the product-positioning attribute map and the perceptual map. At step  250 , one or more marketing mixes are selected for further testing. Such may be selected by the merchant.  
      Further OMR experiments are formulated and conducted at step  255  to test the marketing mixes selected in step  250 .  
      The responses to the OMR experiments conducted in step  255  are analyzed at step  260 . The alternative marketing mixes may be ranked in terms of their acceptance by customers or respondents to the OMR and displayed to the merchant for final selection. If the performance of all the marketing mixes in the OMR is unacceptable to the merchant, new marketing mixes may be suggested and tested with subsequent OMR experiments. Such suggestions may be obtained from the merchant. The cycle of selecting and testing marketing mixes may continue until an acceptable mix is obtained or the process is aborted by the merchant.  
       FIG. 3  shows a method for identifying a need for reconfiguring, repositioning and/or repricing a product. Data relating to one or more of a merchant&#39;s products is obtained at step  310 . Data relating to products similar to the merchant&#39;s product is periodically obtained from competitor&#39;s websites, at step  320 . The data relating to the similar products is processed at step  330 . Such processing may comprise filtering, mapping and clustering of product and position attributes, as described in other embodiments herein. At step  340 , product and positioning attributes are identified. Market positions of competitors&#39; products, including pricing, are thus periodically monitored. At step  350 , any change in positioning, attributes or pricing of a competitor&#39;s product is detected. At step  360 , at least one new potential market position for the merchant&#39;s product that requires repositioning and/or repricing is identified based on the change detected in step  350 .  
       FIG. 4  shows a more detailed flow diagram of a method for aiding product reconfiguration, repositioning and/or repricing. This embodiment alerts a merchant about the need for changing positioning and/or pricing of a product and assists with achieving the repositioning and/or repricing.  
      At step  410 , the merchant&#39;s existing products, along with positioning, pricing, and current sales data, etc., relating to those products, are specified. These may be read from another system where they are stored or from the inputs entered during previous iterations of the repositioning exercise or when the product was originally positioned. Alternatively, a subset of the merchant&#39;s products may be specified.  
      At step  415 , competitors&#39; websites are crawled to identify products similar to the specified products. For each match found, a variety of data is gathered, including product attribute name-value pairs, pricing (including list price, discounts, credit terms, etc.), and positioning attribute name-value pairs. The products identified based on merchant-specified criteria and/or other criteria based on domain knowledge preconfigured into the subsystem are filtered to produce a shortlist of products at step  420 . Attribute value ranges specified in step  410  may be used as filtering criteria. Other criteria used for filtering may comprise criteria such as the main geographical areas the merchant operates in, the top  10  products by revenue, etc. The merchant may optionally be shown the entire list or a filtered list of products for shortlisting or ratification.  
      At step  425 , the list of product and positioning attributes is filtered to produce a shortlist of attributes based on one or more of the following: merchant-specified criteria, frequency of occurrence of the actual attributes in the list, other predefined criteria, and explicit selection by the merchant.  
      The shortlisted products are mapped onto the shortlisted attributes, with separate maps being created for product attributes and positioning attributes, at step  430 . Holes, which are points on the attribute maps where there are no existing products, are identified. Such may be due to unattractive attribute combinations or potential opportunities overlooked by competitors. The maps and any holes identified may be disclosed to the merchant either graphically or otherwise to enable the merchant to ratify or modify the holes, and also to classify the holes as unattractive or attractive. Clusters of products with similar attributes may be formed using clustering techniques. The attributes for clustering may be drawn from both the product and positioning attributes and may comprise certain merchant-specified attributes (e.g., revenue, market share, etc.) in a case where the merchant wishes to guide the clustering process. Common product and positioning attributes of successful and unsuccessful products may be drawn from the clusters. These attributes represent successful and unsuccessful combinations that the merchant may wish to replicate or avoid, respectively, when the new product is introduced.  
      Online Market Research (OMR) experiments are optionally formulated and conducted to gauge preferences and/or perceptions of customers or repondents, at optional step  435 .  
      The foregoing steps  415  to  430  (and, optionally, step  435 ) are repeated periodically and changes relating to similar products are detected and monitored at step  440 . Such changes may comprise the introduction of a competitor&#39;s new product, which may be detected by way of a change in the list of similar products since the last crawl. The effects of such changes on customer perceptions and sales of the merchant&#39;s products specified in step  410  are evaluated using data analysis techniques such as multivariate regression. Periodic repetition of steps  415  to  430  (and, optionally, step  435 ) can be performed using a scheduler, such as shown in  FIG. 5 , hereinafter.  
      At step  445 , products requiring repositioning and/or repricing are identified based on the changes detected in step  440  violating predefined thresholds and/or thresholds explicitly specified by the merchant. The products identified at step  445  are reported to the merchant with one or more suggested alternatives for repricing and/or repositioning (i.e., changes in the marketing mix).  
      One or more alternative marketing mixes are selected at step  450  and tested by OMR experiments at step  455 . The alternative mixes are typically selected by the merchant.  
      At step  460 , the marketing mix is finalized. If the performance of the marketing mix in the OMR is unacceptable to the merchant, new marketing mixes may be suggested or merchant input may be taken and tested with subsequent OMR experiments. This cycle may continue until an acceptable marketing mix is obtained or the process may be aborted.  
       FIG. 5  shows a schematic block diagram of a system for positioning and/or pricing a new product and for identifying a need for reconfiguring, repositioning and/or repricing an existing product.  
      The system comprises a merchant input specification tool  510 , a crawler  515 , a product filtering subsystem  520 , an attribute filtering subsystem  525 , a mapping and clustering subsystem  530 , an online market research (OMR) subsystem  535 , an analysis and reporting subsystem  540 , a scheduler  545  and data storage  550 .  FIG. 5  shows the foregoing components  510  to  550  practiced in a distributed manner with each component connected via a network  555 . However, as would be understood by those skilled in the art, certain or all of the components  510  to  550  may be practiced in various combinations using a number of separate computer systems (e.g,  3  or  4  computer systems such as the computer system  600  shown in  FIG. 6 ). Alternatively, all of the components  510  to  550  may be practiced using a single computer system such as the computer system  600  shown in  FIG. 6 . Certain of the components  510  to  550  may be inessential for practicing certain embodiments of the present invention. For example, the methods shown in  FIG. 1  and  FIG. 2  do not require the scheduler  545 .  
      The merchant input specification tool  510  is used to specify the merchant&#39;s product. The crawler  515  examines or ‘crawls’ websites to locate products similar to a specified product and additionally gathers information about the positioning attributes and values relating to those products for processing by the product filtering subsystem  520  and the attribute filtering subsystem  525 . The operation of the crawler  515  has some similarities to “shopbots”, which are automated software agents that automatically gather and collate information from multiple on-line vendors about the price and quality of consumer goods and services. Information gathered by shopbots is forwarded to customers for assistance in making a final purchasing decision.  
      The product filtering subsystem  520  filters the products found by the crawler  515 . The attribute filtering subsystem  525  filters the list of product and positioning attributes obtained by the crawler  515 . The filtered data is used by the mapping and clustering subsystem  530  to identify desirable attributes. The mapping and clustering subsystem  530  may also identify “holes” in the market space (i.e., regions of low product density on the product attribute map). Such “holes” may result from unattractive attribute combinations or potential opportunities overlooked by competitors.  
      The OMR subsystem  535  formulates one or more explicit and/or implicit OMR experiments to obtain customer or market preferences and/or perceptions of the shortlisted products offered by competitors. The analysis and reporting subsystem  540  uses the results of the online market research to identify at least one potential market position for the merchant&#39;s product.  
       FIG. 6  is a schematic representation of a computer system  600  that can be used to practice the methods described herein for aiding new product introduction and for identifying a need for reconfiguration, repositioning and/or repricing existing products. The computer system  600  is provided for executing computer software that is programmed to assist in performing the described methods. The computer software typically executes under an operating system such as MSWindows XP™ or Linux™installed on the computer system  600 .  
      The computer software comprises a set of programmed logic instructions that may be interpreted by the computer system  600  for instructing the computer system  600  to perform predetermined functions specified by those instructions. The computer software may be an expression recorded in any language, code or notation, comprising a set of instructions intended to cause a compatible information processing system to perform particular functions, either directly or after conversion to another language, code or notation.  
      The computer software program comprises statements in an appropriate computer language. The computer program may be processed using a compiler into computer software that has a binary format suitable for execution by the operating system. The computer program is programmed in a manner that involves various software components, or code means, that perform particular steps in the methods described hereinbefore.  
      The components of the computer system  600  include: a computer  620 , input devices  610 ,  615  and a video display  690 . The computer  620  includes: a processing unit  640 , a memory unit  650 , an input/output (I/O) interface  660 , a communications interface  665 , a video interface  645 , and a storage device  655 . The computer  620  may comprise more than one of any of the foregoing units, interfaces, and devices.  
      The processing unit  640  may comprise one or more processors that execute the operating system and the computer software executing under the operating system. The memory unit  650  may comprise random access memory (RAM), read-only memory (ROM), flash memory, and/or any other type of memory known in the art for use under direction of the processing unit  640 .  
      The video interface  645  is connected to the video display  690  and provides video signals for display on the video display  690 . User input to operate the computer  620  is provided from input devices  610 ,  615 , comprising a keyboard and a mouse, respectively. The storage device  655  may comprise a disk drive or any other suitable non-volatile storage medium.  
      Each of the components of the computer  620  is connected to a bus  630  that comprises data, address, and control buses, to allow the components to communicate with each other via the bus  630 .  
      The computer system  600  may be connected to one or more other similar computers via the communications interface  665  using a communication channel  685  to a network  680 , represented as the Internet.  
      The computer software program may be provided as a computer program product, and recorded on a portable storage medium. In this case, the computer software program is accessed by the computer system  600  from the storage device  655 . Alternatively, the computer software can be accessed directly from the network  680  by the computer  620 . In either case, a user can interact with the computer system  600  using the keyboard  610  and mouse  615  to operate the programmed computer software executing on the computer  620 .  
      The computer system  600  has been described for illustrative purposes. Accordingly, the foregoing description relates to an example of a particular type of computer system suitable for practicing the methods and/or computer program products described hereinbefore. Other configurations or types of computer systems can equally well be used to practice the methods and/or computer program products described hereinbefore, as would readily be understood by persons skilled in the art.  
      Conclusion  
      Embodiments described hereinbefore for aiding new product introduction and for identifying a need for repositioning and/or repricing existing products advantageously reduce dependence on heuristics and the subjective judgment of a merchant.  
      The foregoing detailed description provides exemplary embodiments only, and is not intended to limit the scope, applicability or configurations of the invention. Rather, the description of the exemplary embodiments provides those skilled in the art with enabling descriptions for implementing an embodiment of the invention. Various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth in the claims hereinafter.