WO 2006/044183 PCT/US2005/035588
Title: METHOD FOR PRICING PRODUCTS IN A RETAIL STORE
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the priority of U.S. Provisional Patent Application
Serial No. 60/618,300, filed October 13, 2004, and entitled "METHOD FOR PRICING
PRODUCTS IN A RETAIL STORE", the disclosure of which is incorporated herein by
reference.
BACKGROUND
[0002] Pricing of products is one of the most important tasks faced by companies
in the retail sector. While the goal of maximizing sales revenue is simple enough, the
price that achieves that goal is often difficult to determine. The price of a particular
product will be largely constrained by market conditions, yet it remains a formidable task
to ascertain the actual market conditions and evaluate them in a way that yields the
optimum price. For example, if the price of a product is set below the price that
consumers would be willing to pay, each sale will yield less revenue than it could
otherwise yield, thus reducing total sales revenue. If the price of a product is set too high,
a substantial number of consumers will no longer buy the product, thus decreasing sales
volume. Somewhere below this too-high price is the optimum price, which maintains
sufficient sales volume so as to maximize total sales revenue.
[0003] The market conditions relevant to product pricing include information
about consumer demand for the product and information about substitutes for the
product. There is a need for a method that enables a retailer to determine these
parameters using readily available data in order to approximate the optimum price for a
particular product.
SUMMARY
[0004] The present invention provides a method for pricing products which,
according to an exemplary embodiment, can be goods that are sold in a retail store.
Generally, the method of the present invention can be carried out using the following
five-step process:
(a) evaluating transaction data for a plurality of consumers;
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the same or similar products as the first consumer are classified, or from the product
groups of the products that the consumer has purchased.
[0007] in an alternate detailed embodiment, the product category comprises
products having common physical properties. Alternatively, the product category can
comprise products that may be used for a common purpose, products having positive
cross-elasticities of demand, or products having a common classification under the North
American Industry Classification System or Standard Industrial Classification system.
[0008] In an alternate detailed embodiment, each product in the product category
is classified into one of the plurality of product groups. In an even more detailed
embodiment, the product group into which a product is classified is determined from the
identity of consumers who have purchased that product, the price sensitivity of
consumers who have purchased that product, the distribution of consumer groups who
have purchased the product, or the consumer group into which a sufficient fraction of the
consumers who purchased the product are classified. la an alternate more detailed
embodiment, the product group into which a first product is classified is determined from
other products purchased by consumers who have purchased the first product, or from the
product group into which other products, which have been purchased by a sufficient
fraction of the consumers who purchased the first product, are classified. In an alternate
more detailed embodiment, a product group comprises products that have been purchased
by consumers, a sufficient fraction of whom are classified in a common consumer group.
[0009] In an alternate detailed embodiment, the price of a first product, which is
classified in a first product group whose products are purchased by consumers having a
lower price sensitivity, will be higher than the price of a second product, which is
classified in a second product group whose products are purchased by consumers having
a higher price sensitivity. In a more specific embodiment, products in the second product
group will be more competitively priced (versus the retail establishment's local
competitors, for example), and products in the first product group may be priced with a
lower emphasis on competition.
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(b) classifying the plurality of consumers into a plurality of
consumer groups from the transaction data;
(c) identifying a product category;
(d) classifying products in the product category into a
plurality of product groups, where the product group
classifications are determined, at least in part, based upon
the distribution of the consumer groups transacting for the
products in the product category; and
(e) setting the retail price of a product in the product
category, where the retail price is based at least in part on
the product group into which the product is classified.
[0005] In an exemplary embodiment, the transaction data includes "shopping
purchase data," which can be information regarding consumers' shopping history,
including the identity of products and quantities thereof that the consumers have
purchased. In a detailed embodiment, the shopping purchase data is collected using
frequent shopper cards (also known as loyalty cards or reward cards).
[0006] The consumer groups are established based upon the concept that
consumers may base their respective transaction decisions upon different factors such as
demographic factors (age, income, or geographic location) and/or other personality
factors (price sensitivity or negotiation tendencies, for example). Thus, in a more
detailed embodiment, the plurality of consumer groups may indicate different degrees of
price sensitivity. In an even more detailed embodiment, the consumers in each of the
plurality of consumer groups have a similar degree of price sensitivity. In an even more
detailed embodiment, each of the plurality of consumers is assigned to one of the
plurality of consumer groups based on the consumer's degree of price sensitivity. In an
even more detailed embodiment, each consumer's degree of price sensitivity is
determined from the products that the consumer has purchased, the product groups of the
products that the consumer has purchased, and/or from the degree of price sensitivity of
other consumers who have purchased the same products as the first consumer. In an even
more detailed embodiment, the consumer group into which a first consumer is classified
is determined from the consumer group into which other consumers who have purchased
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[0010] Again, while exemplary embodiments discussed herein classify consumers
into consumer groups based upon relative price sensitivity of the consumers and, in turn,
classify products into product groups based upon the distribution of the price sensitivity-
based consumer groups that have purchased the products, it is within the scope of the
invention to classify consumers into consumer groups based upon any demographic or
personality-based factor (or any combination thereof) that may have an effect on the
consumer's decisions with respect to a transaction.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIG. 1 is a flow chart diagram of a method according to an exemplary
embodiment of the present invention.
[0012] FIG.2 shows an exemplary embodiment of the step of classifying a
plurality of consumers into a plurality of consumer groups.
[0013] FIGS .3 through 6 are graphs depicting selection criteria for four exemplary
consumer groups.
[0014] FIG.7 is a chart depicting selection criteria for four exemplary consumer
groups.
[0015] FIGS. 8 through 11 are graphs depicting selection criteria for four
exemplary product groups.
DETAILED DESCRIPTION
[0016] FIG. 1 shows a flow chart diagram of an exemplary method 10 of the
present invention. The method 10 begins with the first step 12, evaluating transaction
data for a plurality of consumers. 'Transaction data" refers to data relating to any
transaction or interaction between a consumer and a business. In an exemplary
embodiment, transaction data includes "shopping purchase data," which can be
information regarding a consumer's shopping history, including the identity of products
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and quantities thereof that the consumer has purchased. As used herein, the term
"products" includes not only consumer products that can be purchased in a retail store,
but also any other product, service, or thing of value that can be furnished by a business
to a consumer. This step 12 can include the act of collecting the shopping purchase data,
or it can evaluate previously-collected data. The shopping purchase data can be collected
using a unique identification tag or card, commonly known as a "frequent shopper card"
or "loyalty card," carried by each consumer. Such cards or tags contain a unique
identification code stored by a bar code, magnetic media, or other data storage device and
can be read by an electronic device in various manners that are well known to persons
skilled in the art.
[0017] When a consumer goes through the checkout process at a store and the
products being purchased are scanned, the unique identification code of the consumer's
frequent shopper card can also be read by electronic device. The store's computer system
can then compile a record of the products being purchased during this particular sale and
associate that list with the unique identification code of the consumer. By repeating this
process each time the consumer visits the store and makes purchases, the store can build a
cumulative record of a particular consumer's shopping history, including the identity of
products and quantities thereof that the consumer has purchased. The compiled record of
a consumer's shopping history can be stored in a database and analyzed to develop a
profile regarding the consumer's product preferences, as discussed in the next step. The
"consumer" whose shopping history is profiled can be an individual person or a
household, for example, consisting of a group of persons residing at the same address or
using the same credit card account, or even a business or governmental entity.
[0018] In an alternative embodiment, a consumer's shopping purchase data can be
associated with the consumer using other consumer identification information (such as a
telephone number, store credit card, bank credit card, or checking account number)
instead of codes from frequent shopper cards. In this manner, the details of a particular
transaction can be matched to the consumer's previous transactions, thus facilitating the
continuing addition of transactional information to each consumer's record in the
database.
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[0019] Each consumer's record in the database can comprise a plurality of
transaction entries or records, one for each transaction by that consumer. For each of
these transaction records, there is provided, in the exemplary embodiment: a code
identifying the SKU/product(s) purchased by the customer for the transaction; a code
identifying the particular transaction or 'basket'; a code identifying the customer or
household for the which the transaction is attributed; a code identifying the store in which
the transaction occurred; data concerning the quantity of products purchased and the
amount spent; data concerning the date, time, etc. of the purchase; and any other data or
codes, such as a code indicating a geographical region for the purchase, as could be
useful to generate reports based upon such transactional data.
[0020] The code in the transaction record identifying the SKU/product can be
used to retrieve details pertaining to that product from a separate database containing a
plurality of "product records," one for each product. For each "product record" in the
product database, there is provided, in the exemplary embodiment: product grouping or
categorization data or codes; product UPC data; manufacturer or supplier data or codes;
and any other data or codes, such as suggested retail price data, as could be useful to
generate reports based upon a combination of transaction data and product data.
[0021] The code in the transaction record identifying the customer or household
for the transaction can be used to retrieve details pertaining to that household from a
separate database containing a plurality of "household records," one for each household.
For each "household record," there may be provided, in the exemplary embodiment: data
and/or codes pertaining to the customer's demographics, shopping history, shopping
preferences, and any other data or codes as could be useful to generate reports based upon
a combination of transaction data and customer/household data.
[0022] The code in the transaction record identifying the store in which the
transaction occurred can be used to retrieve details pertaining to that store from a separate
database containing a plurality of "store records," one for each store. For each "store
record," there is provided, in the exemplary embodiment: store name data; store location
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data or codes; and any other data or codes as could be useful to generate reports based
upon a combination of transaction data and store data.
[0023] As will be appreciated by those of ordinary skill, the above-described
database record structures are only exemplary in nature and that unlimited combinations
of database records and hierarchies are available to cross-reference transaction
information, product information, customer/household information, store information,
location, information; timing information, and any other appropriate information with one
another. Additionally, one of ordinary skill will appreciate that the invention is not
limited for use with retail store transactions and that the invention can be used with most
(if not all) types of transactions (such as financial/banking transactions, insurance
transactions, service transactions, etc.), where the database structures and hierarchies will
be adapted for generating reports on such alternate transaction data.
[0024] In the second step 14 of the method 10, the consumers are classified into a
plurality of consumer groups. As shown diagrammatically in HG.2, the database 40
contains a plurality of consumer records 42, one for each consumer for whom shopping
purchase data has been compiled. Each consumer in the database 40 can be classified
into one of the consumer groups 44. in the exemplary embodiment, the consumer group
into which a particular consumer is placed will be determined from characteristics about
that consumer that can be ascertained from the consumer's shopping history. Because a
consumer's shopping history, including the identity of products and quantities thereof
that the consumer has purchased, provides valuable insight into the consumer's lifestyle,
financial means, and other important characteristics, it allows consumers to be divided
into groups according to various selection criteria. The consumer group into which a
particular consumer is placed may also be based upon demographic data and/or
personality data, which may or may not be ascertained from the consumer's transaction
history. Demographic data may include, but is certainly not limited to, age data, income
data, geographic data, and education-level data. Personality data (also referred to as the
consumer's "transaction personality") may include, but is certainly not limited to, price
sensitivity, negotiation tendencies, coupon usage, attention to promotions, loyalty,
attention to product locations or configurations, and the like. Those of ordinary skill in
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the art will appreciate the numerous sources for such demographic and/or personality-
data.
[0025] In the exemplary embodiment shown in FIG.2, there are four consumer
groups 44 into which consumers may be placed. These exemplary consumer groups
classify consumers according to their price sensitivity. Price sensitivity is a desirable
way in which to classify consumers because it is a strong indicator of which particular
products the consumer is likely to purchase. For example, most product categories (e.g.,
pet food, ice cream, canned goods, wine, etc.) contain several product offerings by
multiple manufacturers, and the several product offerings usually differ in price. Within
a given product category, the consumer usually can choose between low-end products
that are relatively inexpensive, high-end products that have higher prices, and other
products having prices somewhere in between the low-end and the high-end for that
product category. Because very price sensitive consumers will tend to purchase less
expensive products and high-end consumers will tend to purchase more expensive
products, we can ascertain a particular consumer's price sensitivity by analyzing the
products that the consumer buys. Each consumer can be classified into the appropriate
consumer group depending on the price sensitivity indicated by list of products in the
consumer's shopping history.
[0026] The consumer group into which a particular consumer is classified can be
determined by analyzing the product group classification of the products in the
consumer's shopping history. For example, referring again to the four consumer groups
of FIG.2, a consumer who purchases primarily low-end products can be classified in
Consumer Group #4. Specific numerical thresholds can be set for making these
determinations. For example, a consumer whose purchases consist of at least 80% low-
end products can be classified in Consumer Group #4 (as shown in FIG.3). Similarly, a
consumer whose purchases consist of at least 40% high-end products can be classified in
Consumer Group #1 (as shown in FIG.4) (the different percentages in these examples are
logically appropriate because affluent consumers tend to buy low-end products more
often than price sensitive consumers buy high-end products.) As an additional example,
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a consumer whose purchases consist of between 50% and 80% low-end products can be
classified in Consumer Group #3 (as shown in MG.4), and a consumer whose purchases
consist of between 30% and 50% low-end products and less than 20% high-end products
can be classified in Consumer Group #2 (as shown in FIG.4). The specific cutoff
percentages and selection criteria for each consumer group can vary depending on the
ranges observed for each product group's share of consumers' purchases, as well as the
distribution of the consumers along this range. These factors, among others, can be used
in. the analysis that determines the qualifications for classification into each of the
consumer groups.
[0027] In an alternate embodiment, consumers can be classified into consumer
groups based on their perceived "loyalty" to the store or to a particular product. A
consumer who spends more money at a store or shops more frequently will be perceived
as more loyal by the store. Similarly, a consumer who spends more money on a
particular product or buys the product more frequently will be perceived as a more loyal
buyer of that product. FTG.7 is a chart illustrating how consumers may be classified into
consumer groups based on their perceived loyalty to a store. In this example, there are
four consumer groups: Loyalty Group 1 through 4. Each consumer is placed into one of
these consumer groups based on how much the consumer spends at the store and how
often the consumer shops at the store, as indicated by the chart.
[0028] In an alternate embodiment, consumers can be classified into consumer
groups based on their response to promotions or other incentives. A consumer's
shopping history can include data indicating whether each product in the shopping history
was the subject of a promotion at the time it was purchased, and this information can then
be analyzed to determine how strongly each consumer responds to promotions. The
analysis can also determine and what types of promotions (e.g., coupons, rebates, volume
discounts) and what promoted products each consumer responds to.
[0029] As discussed above, it is certainly within the scope of the invention to
classify consumers into consumer groups based upon demographic and/or personality
factors or upon multiple combinations of such.
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[0030] Once the database of consumers has been classified into consumer groups,
as described above, the remainder of the exemplary method (steps three through five) is
concerned with pricing products. The first step in this endeavor (the third step 16 in the
overall method 10) is identification of a product category. Generally speaking, a product
category defines a line of competing products that are functionally interchangeable, in
other words, if two products are used for the same purpose by the consumer, then they
can be said to belong to the same product category. Examples of product categories are
pet food, ice cream, canned goods, and wine.
[0031] One of the most useful ways to define product category is by the
economists' notion of cross-elasticity of demand. The cross-elasticity of demand
measures how the demand for one product changes in response to a change in another
product's price. If demand for product A rises when the price of product B rises, and
vice versa, then product A and product B are viewed by consumers as substitutes — when
the price of one product rises, some consumers will buy the other product instead, thus
increasing its demand. Thus, if two products have positive cross-elasticities of demand,
meaning that the demand for each rises when the price of the other rises, they are
economic substitutes. It makes sense to classify such products in a common product
category because they are viewed as functionally interchangeable by consumers. A good
example of such products is Pennzoil® motor oil and Valvoline® motor oil; if the price
of one rises, some consumers will buy the other instead because it performs the same
function and is now comparatively less expensive. Two unrelated products will have
cross-elasticities of demand equaling zero because they have no functional relation and
thus are not substitutes for each other. A good example of such products is a
Remington® 12-gauge shotgun and Land O'Lakes® butter; because these goods are
completely unrelated, a rise in the price of one will have no effect on the demand for the
other.
[0032] la addition to cross-elasticities of demand, other ways can be used to
determine which products should be classified together in a common product category,
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such as the U.S. Department of Commerce's North American Industry Classification
System or Standard Industrial Classification system. Nevertheless, it is within the scope
of the present invention to use alternative ways of classifying products in a product
category, which may include subjective or even arbitrary decisions.
[0033] Once a product category has been identified, the next step 18 of the
exemplary method 10 is to classify products in the product category into a plurality of
product groups. The goal of placing products into product groups is to implement a
classification system that will aid in determining an appropriate price for each product.
Accordingly, one of the most useful ways to group products is by the type of consumer
that typically buys the product.
[0034] In an exemplary embodiment, there are four product groups into which
products can be placed, ranging from Product Group #1 (the high-end products that are
typically purchased by affluent consumers who are relatively insensitive to price) to
Product Group #4 (the low-end products that are typically purchased by consumers who
are sensitive to price). In order to determine the product group into which a particular
product should be classified, we look to the distribution of consumer groups represented
in the list of consumers who have purchased the product. This list can be compiled from
the same shopping purchase data from consumers as described above. From the database
that tracks what products each consumer has purchased, we can construct a list
identifying the consumers who have purchased each product. Using the consumer group
classification assigned to each consumer hi the second step 14 of the method 10
(described above), we can determine what kind of consumer (based on degree of price
sensitivity in an exemplary embodiment) tends to buy each product. Using this
information, we can construct a chart similar to those depicted in FIGS.8 through 11 for
each product, showing the distribution of consumer groups purchasing the product.
[0035] For example, if affluent or upscale (Consumer Group #1) consumers
account for 60% of a product's sales, as seen in FIG.8, that product can be classified in
Product Group #1. If Consumer Group #2 consumers account for 60% of a product's
sales, as seen in FIG.9, that product can be classified in Product Group #2. If Consumer
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Group #3 and Consumer Group #4 consumers jointly account for over half of a product's
sales, as seen in FIG.10, that product can be classified in Product Group #3. If no
particular consumer group dominates a product's sales, as seen in FIG. 11, that product
can be classified in Product Group #4. For example, we could employ a selection
criterion providing that, if the fraction of a product's sales to no pair of two consumer
groups differs by more than 10%, then the product will be classified in Product Group #4.
[0036] Once the products have been classified into product groups, one remaining
step 20 of the method 10 is to set the prices of the products in the product groups. Most
product categories (e.g., pet food, ice cream, canned goods, and wine) have a range of
prices, with some premium products in the category selling at the high end of the range,
some lesser products in the category selling at the low end of the range, and other
products in the category selling at prices near the middle of the range.
[0037] The classification of products into product groups (as performed in the
fourth step 18, described above) greatly assists the pricing of the products because a
product's classification indicates where along that spectrum the product should be priced.
For example, if the price for a half gallon of ice cream ranges from $2.29 on the low end
to $6.99 on the high end, then a particular brand of ice cream that is classified in Product
Group #1 should be priced at the upper end of this range. Similarly, a particular brand of
ice cream that is classified in Product Group #2 should be priced near the middle of this
range. By pricing products in this manner, sellers can more closely approximate the
optimum price for each product, that is, the price at which total sales revenue is
maximized. A product that is purchased primarily by affluent consumers (i.e.; a Product
Group #1 product) can be priced higher without sacrificing sales volume. By contrast, a
Product Group #3 or a Product Group #4 product, which depends on a large number of
price sensitive consumers for its sales, will experience a significant reduction in sales
volume if it is priced too high.
[0038] In an exemplary embodiment, the Product Group #3 products and Product
Group #4 products in a product category are priced to compete directly with regional
competitors because consumers who are price sensitive will be comparing prices of such
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products between regional competitors, while Product Group #1 products are priced to
provide a strong margin because the less price sensitive consumers buying such products
will typically not compare prices with the store's regional competitors.
[0039] In an alternative embodiment, a substitute for the fifth step 20 of the
exemplary method 10 can include a step of determining rebates and discounts to be
offered on particular products. Alternatively, the method can include the step of
determining other promotional details, such as store display configuration, for particular
products. In these alternative embodiments, a product's classification hi a particular
product group can be analyzed to determine what action, such as offering a rebate or
using a more visible store display, should be taken with respect to that particular product.
[0040] Just as consumers were classified into consumer groups based upon the
distribution of product groups found in each consumer's purchase history, the products
were classified into product groups based upon the distribution of consumer groups that
purchased each product. It may be a recursive process, with the consumer classification
being determined from the product classification which, in turn, is determined from the
consumer classification. As with the determination of consumer groups, the specific
cutoff percentages and selection criteria for each product group can vary depending on
the ranges observed for each consumer group's share of various products' sales, as well
as the distribution of the products along this range. These factors, among others, can be
used in the analysis that determines the qualifications for classification into each of the
product groups.
[0041] The method according to the present invention can be implemented on a
computer system such as a personal computer, a client/server system, a local area
network, or the like. The computer system may include a display unit, a main processing
unit, and one or more input/output devices. The one or more input/output devices may
include a keyboard, a mouse, and a printer. The display unit may be any typical display
device, such as a cathode ray tube, a liquid crystal display, or the like.
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[0042] The main processing unit may further include a central processing unite
(CPU), a memory, and a persistent storage device that are interconnected together. The
CPU may control the operation of the computer and may execute one or more software
applications that implement the steps of an embodiment of the present invention. The
software applications may be stored permanently in the persistent storage device that
stores the software applications even when the power is off and then loaded into the
memory when the CPU is ready to execute the particular software application. The
persistent storage device may be a hard disk drive, an optical drive, a tape drive or the
like. The memory may include a random access memory (RAM), a read only memory
(ROM), or the like.
[0043] Having described the invention with reference to exemplary embodiments,
it is to be understood that the invention is defined by the claims and it not intended that
any limitations or elements describing the exemplary embodiment set forth herein are to
be incorporated into the meanings of the claims unless such limitations or elements are
explicitly listed in the claims. Likewise, it is to be understood that it is not necessary to
meet any or all of the identified advantages or objects of the invention disclosed herein hi
order to fall within the scope of any claims, since the invention is defined by the claims
and since inherent and/or unforeseen advantages of the present invention may exist even
though they may not have been explicitly discussed herein.
[0044] What is claimed is:
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1 .A method for establishing the retail price of a product, comprising the
steps of:
evaluating shopping purchase data for a plurality of consumers;
classifying the plurality of consumers into a plurality of consumer group
based, at least in part, upon the evaluation of shopping purchase data;
identifying a product category;
classifying products in the product category into a plurality of product
groups based, at least in. part, upon a distribution consumer groups purchasing the
products in the product category; and
setting the retail price of a product in the product category based, at least
in part, upon the product group into which the product is classified.
2. The method of claim 1, wherein the shopping purchase data includes the
identification of products that each of the plurality of consumers has purchased.
3. The method of claim 2, wherein the shopping purchase data is collected
using frequent shopper cards.
4. The method of claim 1, wherein each of the plurality of consumers is
classified into one of the plurality of consumer groups.
5. The method of claim 4, wherein the plurality of consumer groups indicate
different degrees of price sensitivity.
6. The method of claim 5, wherein each consumer's degree of price
sensitivity is determined, at least in part, from the identity of products that the consumer
has purchased.
7. The method of claim 5, wherein each consumer's degree of price
sensitivity is determined, at least in part, from the product groups of the products that the
consumer has purchased.
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8. The method of claim 5, wherein a first consumer's degree of price
sensitivity is determined from degree of price sensitivity of other consumers who have
purchased the same products as the first consumer.
9. The method of claim 4, wherein the consumer group into which a first
consumer is classified is determined, at least in part, from the consumer group into which
other consumers, who have purchased the same products as the first consumer, are
10. The method of claim 4, wherein the consumer group into which a
consumer is classified is determined, at least in part, from the product groups of the
products that the consumer has purchased,
11. The method of claim 1, wherein the product category comprises products
having common physical properties.
12. The method of claim 1, wherein the product category comprises products
that maybe used for a common purpose.
13. The method of claim 1, wherein the product category comprises products
having positive cross-elasticities of demand.
14. The method of claim 1, wherein the product category comprises products
having a common classification under the North American Industry Classification
System.
15. The method of claim 1, wherein the product category comprises products
having a common classification under the Standard Industrial Classification system.
16. The method of claim 1, wherein the product group into which a product is
classified is determined from the consumer group into which a predetermined fraction of
the consumers who purchased the product are classified.
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17. The method of claim 1, wherein the product group into which a first
product is classified is determined from the product group into which other products,
which have been purchased by a predetermined fraction of the consumers who purchased
the first product, are classified.
18. The method of claim 1, wherein aproduct group comprises products that
have been purchased by consumers, a sufficient fraction of whom are classified in a
common consumer group.
19. The method of claim 1, wherein the step of setting a retail price for a
product includes the step of setting the price of a first product, which is classified in a
first product group whose products are purchased by consumers having a lower price
sensitivity, relatively higher than the price of a second product, which is classified in a
second product group whose products are purchased by consumers having a iigher price
sensitivity.
20. The method of claim 1, wherein the step of setting the retail price for a
product includes the step of setting the price of a product, which is classified in a product
group purchased more often by consumers having a higher price sensitivity, to be directly
competitive with a retail store's local competition.
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21. A method for establishing the retail price of a product, comprising the
steps of:
evaluating transaction data for a plurality of consumers;
classifying the plurality of consumers into a plurality of consumer groups
based, at least in part, upon the evaluation of transaction data;
identifying a product category;
classifying a product from the product category into one of a plurality of
product groups based, at least in part, upon a distribution of consumer groups transacting
for the product; and
setting the retail price of the product in the product category based, at least
in part, upon the product group into which the product is classified.
22. The method of claim 21, wherein each of the plurality of consumers is
classified into one of the plurality of consumer groups.
23. The method of claim 22, wherein the plurality of consumer groups
indicate different degrees of price sensitivity.
24. The method of claim 21, wherein the product category comprises products
having positive cross-elasticities of demand.
25. The method of claim 21, wherein the product category includes a plurality
of products; and
wherein each product in the product category is classified into one of the
plurality of product groups.
26. The method of claim 21, wherein a product group comprises products that
have been purchased by consumers, a predetermined fraction of whom are classified in a
common consumer group.
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27. The method of claim 21, wherein the step of setting a retail price for a
product includes the step of setting the price of a first product, which is classified in a
first product group whose products are purchased by consumers having a lower price
sensitivity, relatively higher than the price of a second product, which is classified in a
second product group whose products are purchased by consumers having a higher price
sensitivity.
28. The method of claim 21, wherein the step of setting the retail price for a
product includes the step of setting the price of a product, which is classified in a product
group purchased more often by consumers having a higher price sensitivity, to be directly
competitive with a retail store's local competition.
29. A computer system comprising software programmed to perform a
method for establishing a business transaction strategy, comprising the steps of:
classifying a plurality of consumers into a plurality of consumer groups based
upon at least one of consumer transaction history data and consumer demographic data;
identifying a product;
collecting product transaction history data for the product from the plurality of
consumers classified into the consumer groups;
categorizing the product into a product category based upon an analysis of the
product transaction history data; and
establishing a business transaction strategy for the product based upon the product
category into which the product is categorized.
30.The computer system of claim 29, wherein the step of establishing a
business transaction strategy for the product is based upon an analysis of a distribution of
the consumer groups' purchases of the product from the product transaction history data.
31.The computer system of claim 29, wherein the step of classifying a
plurality of consumers into a plurality of consumer groups includes the steps of, for each
consumer:
determining from the consumer transaction history a transaction personality; and
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classifying the consumer into one of the plurality of consumer groups based, at
least in part, upon the consumer's transaction personality.
32 The computer system of claim 31, wherein the step of establishing a
business transaction strategy for the product is based upon an analysis of a distribution of
the consumer groups' purchases of the product from the vehicle transaction history data.
33. The computer system of claim 31, wherein the transaction personality is
based upon one or more tendencies taken from a group consisting of:
a consumer's price-sensitivity;
a consumer's brand loyalty;
a consumer's product loyalty;
a consumer's attention to promotions;
a consumer's use of coupons;
a consumer's attention to product layout;
a consumer's payment method; and
a consumer's tendency to negotiate.
34. The computer system of claim 33, wherein the step of classifying the
consumer into one of the plurality of consumer groups is based upon a combination of the
consumer's transaction personality and the consumer's demographic data.
35. The computer system of claim 29, wherein the step of establishing a
business transaction strategy for the product includes one or more steps taken from a
group consisting of the steps of:
setting a price for the product;
establishing a product promotion for the product;
modifying a product promotion for the product;
modifying a product position for the product within a retail establishment;
modifying a product display for the product within a retail establishment;
modifying a coupon strategy for the product;
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setting a price for another product having a predetermined relationship with the
product;
establishing a product promotion for another product having a predetermined
relationship with the product;
modifying a product promotion for another product having a predetermined
relationship with the product;
modifying a product position for another product having a predetermined
relationship with the product within a retail establishment;
modifying a product display for another product having a predetermined
relationship with the product within a retail establishment; and
modifying a coupon strategy for another product having a predetermined
relationship with the product.
36. The computer system of claim 35, wherein the step of classifying a
plurality of consumers into a plurality of consumer groups includes the steps of, for each
consumer:
determining from the consumer transaction history a transaction personality; and
classifying the consumer into one of the plurality of consumer groups based, at
least in part, upon the consumer's transaction personality.
37. The computer system of claim 36, wherein the transaction personality is
based upon one or more tendencies taken from a group consisting of:
a consumer's price-sensitivity;
a consumer's brand loyalty;
a consumer's product loyalty;
a consumer's attention to promotions;
a consumer's use of coupons;
a consumer's attention to product layout;
a consumer's payment method; and
a consumer's tendency to negotiate.
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38. The computer system of claim 29, wherein the method further comprises
the step of identifying a product category, wherein the categorizing and establishing steps
are performed for a plurality of products in the product category.
39. The computer system of claim 29, wherein the consumer transaction
history data and the product transaction history data are taken from one or more databases
of transaction history data.
40. The computer system of claim 39, wherein the one or more databases of
transaction history data include data collected from the use of frequent shopper cards.
41. The computer system of claim 39, wherein the one or more databases of
transaction history data include data collected from the use of credit cards.
42. The computer system of claim 29, wherein the step of classifying a
plurality of consumers into a plurality of consumer groups includes the steps of, for each
consumer:
determining from the consumer transaction history a price sensitivity, and
classifying the consumer into one of the plurality of consumer groups based, at
least in part, upon the consumer's price sensitivity, wherein each of the consumer groups
respectively correspond to different predetermined levels of consumer price sensitivity.
43. The computer system of claim 42, wherein the step of establishing a
business transaction strategy for the product includes the steps of setting a price for the
product
44. The computer system of claim 43, wherein the step of categorizing the
product into a product category is based upon an analysis of a distribution of the
consumer groups' purchases of the product from the product transaction history data,
wherein each of the product categories respectively correspond to different predetermined
levels of importance as to whether products falling within the product categories should
be competitively priced or not.
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45. A computer system comprising software programmed to perform a
method for establishing a business transaction strategy, comprising the steps of:
classifying a plurality of consumers into a plurality of consumer groups based
upon at least one of consumer transaction history data and consumer demographic data;
identifying a transaction vehicle;
collecting vehicle transaction history data for the transaction vehicle from the
plurality of consumers classified into the consumer groups;
analyzing of the vehicle transaction history data; and
establishing a business transaction strategy for the transaction vehicle based upon
the analysis of the vehicle transaction history data.
46. The computer system of claim 45, wherein the step of establishing a
business transaction strategy for the transaction vehicle is based upon an analysis of a
distribution of the consumer groups utilization of the transaction vehicle from the vehicle
transaction history data.
47. The computer system of claim 45, wherein the step of classifying a
plurality of consumers into a plurality of consumer groups includes the steps of, for each
consumer:
determining from the consumer transaction history a transaction personality; and
classifying the consumer into one of the plurality of consumer groups based, at
least in part, upon the consumer's transaction personality.
48. The computer system of claim 47, wherein the step of establishing a
business transaction strategy for the transaction vehicle is based upon an analysis of a
distribution of the consumer groups utilization of the transaction vehicle from the vehicle
transaction history data.
49. The computer system of claim 47, wherein the transaction personality is
based upon one or more tendencies taken from a group consisting of:
a consumer's price-sensitivity;
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a consumer's brand loyalty;
a consumer's product loyalty;
a consumer's attention to promotions;
a consumer's use of coupons;
a consumer's attention to product layout;
a consumer's payment method; and
a consumer's tendency to negotiate.
50. The computer system of claim 47, wherein the step of classifying the
consumer into one of the plurality of consumer groups is based upon a combination of the
consumer's transaction personality and the consumer's demographic data.
51. The computer system of claim 45, wherein the transaction vehicle includes
a first product, and the step of establishing a business transaction strategy for the
transaction vehicle includes one or more steps taken from a group consisting of the steps
of:
setting a price for the first product;
establishing a product promotion for the first product;
modifying a product promotion for the first product;
modifying a product position for the first product within a retail establishment;
modifying a product display for the first product within a retail establishment;
modifying a coupon strategy for the first product;
setting a price for a second product having a predetermined relationship with the
first product;
establishing a product promotion for a second product having a predetermined
relationship with the first product;
modifying a product promotion for a second product having a predetermined
relationship with the first product;
modifying a product position for a second product having a predetermined
relationship with the first product within a retail establishment;
modifying a product display for a second product having a predetermined
relationship with the first product within a retail establishment; and
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modifying a coupon strategy for a second product having a predetermined
relationship with the first product.
52. The computer system of claim 51, wherein the step of classifying a
plurality of consumers into a plurality of consumer groups includes the steps of, for each
consumer:
determining from the consumer transaction history a transaction personality; and
classifying the consumer into one of the plurality of consumer groups based, at
least in part, upon the consumer's transaction personality.
53. The computer system of claim 52, wherein the transaction personality is
based upon one or more tendencies taken from a group consisting of:
a consumer's price-sensitivity;
a consumer's brand loyalty;
a consumer's product loyalty;
a consumer's attention to promotions;
a consumer's use of coupons;
a consumer's attention to product layout;
a consumer's payment method; and
a consumer's tendency to negotiate.
54. The computer system of claim 45, wherein the transaction vehicle includes
a promotional item.
55. The computer system of claim 54, wherein the step of establishing a
business transaction strategy for the transaction vehicle includes one or more steps taken
from a group consisting of:
modifying a promotional strategy associated with the promotional item;
setting a price for a product associated with the promotional item;
establishing a product promotion for a product associated with the promotional
item;
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modifying a product promotion for a product associated with the promotional
item;
modifying a product position for a product associated with the promotional item
within a retail establishment;
modifying a product display for a product associated with the promotional item
within a retail establishment; and
modifying a coupon strategy for a product associated with the promotional item.
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A method for pricing products such as goods that are sold in a retail store. The method of the present invention is carried out using the following five-step process: (a) evaluating transaction data for a plurality of consumers; (b) classifying the plurality of consumers into a plurality of consumer groups; (c) identifying a product category; (d) classifying products in the product category into a plurality of product groups, the product groups being based at least in part on the plurality of consumer groups; and (e) setting the retail price of a product in the product category, the retail price being based at least in part on the product group into which the product is classified.