U.S. patent application number 16/684754 was filed with the patent office on 2020-06-18 for method and apparatus for payment, return on investment, and impact reporting.
The applicant listed for this patent is Groupon, Inc.. Invention is credited to Mike Aparicio, Raju BALAKRISHNAN, Natalia COROMINAS, Adam GEITGEY, Latife GENC-KAYA, Michael Hines, Jadam Kahn, Amit KOREN, Gaston L'HUILLIER, Kamson LAI, Francisco Jose LARRAIN, Derek Nordquist, Cristian ORELLANA, Shafiq Shariff, Todd Webb.
Application Number | 20200193467 16/684754 |
Document ID | / |
Family ID | 54368206 |
Filed Date | 2020-06-18 |
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United States Patent
Application |
20200193467 |
Kind Code |
A1 |
Shariff; Shafiq ; et
al. |
June 18, 2020 |
Method And Apparatus For Payment, Return On Investment, And Impact
Reporting
Abstract
The unified payment system, product and method provide an
effective and efficient way to better communicate to a merchant the
value of running a promotion and determine a deal structure that
works for the merchant, the customer, the promotion system, or any
combination thereof. The unified payment system, product and method
provide real-time ROI calculations that a merchant and sales
representative can collaboratively simultaneously work on to
identify a deal structure for the merchant to select. In this way,
the merchant and sales representative may arrive at a mutually
acceptable payment plan.
Inventors: |
Shariff; Shafiq; (Chicago,
IL) ; Nordquist; Derek; (Chicago, IL) ; Hines;
Michael; (Chicago, IL) ; Aparicio; Mike;
(Chicago, IL) ; Webb; Todd; (Wheaton, IL) ;
Kahn; Jadam; (Chicago, IL) ; BALAKRISHNAN; Raju;
(Chicago, IL) ; COROMINAS; Natalia; (Chicago,
IL) ; GEITGEY; Adam; (Chicago, IL) ;
GENC-KAYA; Latife; (Chicago, IL) ; KOREN; Amit;
(Chicago, IL) ; LAI; Kamson; (Chicago, IL)
; LARRAIN; Francisco Jose; (Palo Alto, CA) ;
L'HUILLIER; Gaston; (Cambridge, MA) ; ORELLANA;
Cristian; (Chicago, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Groupon, Inc. |
Chicago |
IL |
US |
|
|
Family ID: |
54368206 |
Appl. No.: |
16/684754 |
Filed: |
November 15, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14622002 |
Feb 13, 2015 |
10558991 |
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PCT/US2013/054714 |
Aug 13, 2013 |
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16684754 |
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13841347 |
Mar 15, 2013 |
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14622002 |
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13841854 |
Mar 15, 2013 |
10614480 |
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13841347 |
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61824850 |
May 17, 2013 |
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61682762 |
Aug 13, 2012 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 30/0207 20130101;
G06Q 10/067 20130101; G06Q 30/0247 20130101; G06Q 30/0203 20130101;
G06Q 30/0211 20130101; G06Q 10/063 20130101; G06Q 10/0639
20130101 |
International
Class: |
G06Q 30/02 20060101
G06Q030/02 |
Claims
1-167. (canceled)
168. A method, for monitoring merchant costs associated with a
promotion deal structure, comprising: receiving at least one
merchant cost criteria indicative of one or more attributes of a
merchant deal structure; automatically generating, from at least a
historical database, at least one additional merchant cost
criteria; storing a plurality of merchant cost criteria in a
merchant deal structure database; calculating, based on at least
the plurality of merchant cost criteria, a first amount indicative
of a pay down cost; calculating, based on at least the plurality of
merchant cost criteria, a second amount indicative of a product
cost; automatically updating the merchant deal structure database
with at least a plurality merchant costs; and generating a cost
report renderable for display on a user device.
169. The method of claim 168, further comprising: calculating,
based on at least the plurality of merchant cost criteria, a third
amount indicative of a marginal cost; and calculating, based on at
least the plurality of merchant cost criteria, a fourth amount
indicative of a marketing service cost.
170. The method of claim 168, wherein the cost report comprises at
least a breakdown of all calculated costs and a return rate
populated with a predetermined percentage based on a historical
analysis of at least one previous promotion.
171. The method of claim 168, wherein the plurality of merchant
cost criteria comprises at least a product cost percentage that
identifies a variable cost to offer a promotion voucher.
172. The method of claim 168, wherein the plurality of merchant
cost criteria further comprises at least one of an additional
spending criteria, a repeat customer criteria, a return on
investment (ROI) criteria, or a merchant revenue criteria.
173. The method of claim 168, wherein the cost report comprises a
graphical consumer interface (GUI) configured for remote off-line
customization by an associated merchant or marketing service.
174. The method of claim 168, further comprising: providing a
promotion forecast using automatically calculated outcomes based on
at least one marketing input comprising consumer demographics,
historical data, expected profit, expected number of new customers,
an indication of the investment spent per new customer, or an
indication of a ratio showing an expected return on investment.
175. An apparatus comprising at least one processor and at least
one memory including computer program code, the at least one memory
and the computer program code configured to, with the at least one
processor, cause the apparatus to: receive at least one merchant
cost criteria indicative of one or more attributes of a merchant
deal structure; automatically generate, from at least a historical
database, at least one additional merchant cost criteria; store a
plurality of merchant cost criteria in a merchant deal structure
database; calculate, based on at least the plurality of merchant
cost criteria, a first amount indicative of a pay down cost;
calculate, based on at least the plurality of merchant cost
criteria, a second amount indicative of a product cost;
automatically update the merchant deal structure database with at
least a plurality merchant costs; and generate a cost report
renderable for display on a user device.
176. The apparatus of claim 175, further caused to: calculate,
based on at least the plurality of merchant cost criteria, a third
amount indicative of a marginal cost; and calculate, based on at
least the plurality of merchant cost criteria, a fourth amount
indicative of a marketing service cost.
177. The apparatus of claim 175, wherein the cost report comprises
at least a breakdown of all calculated costs and a return rate
populated with a predetermined percentage based on a historical
analysis of at least one previous promotion.
178. The apparatus of claim 175, wherein the plurality of merchant
cost criteria comprises at least a product cost percentage that
identifies a variable cost to offer a promotion voucher.
179. The apparatus of claim 175, wherein the plurality of merchant
cost criteria further comprises at least one of an additional
spending criteria, a repeat customer criteria, a return on
investment (ROI) criteria, or a merchant revenue criteria.
180. The apparatus of claim 175, wherein the cost report comprises
a graphical consumer interface (GUI) configured for remote off-line
customization by an associated merchant or marketing service.
181. The apparatus of claim 175, further caused to: provide a
promotion forecast using automatically calculated outcomes based on
at least one marketing input comprising consumer demographics,
historical data, expected profit, expected number of new customers,
an indication of the investment spent per new customer, or an
indication of a ratio showing an expected return on investment.
182. A computer program product comprising at least one
non-transitory storage medium for storing computer program code,
that, when executed by an apparatus, cause the apparatus to:
receive at least one merchant cost criteria indicative of one or
more attributes of a merchant deal structure; automatically
generate, from at least a historical database, at least one
additional merchant cost criteria; store a plurality of merchant
cost criteria in a merchant deal structure database; calculate,
based on at least the plurality of merchant cost criteria, a first
amount indicative of a pay down cost; calculate, based on at least
the plurality of merchant cost criteria, a second amount indicative
of a product cost; automatically update the merchant deal structure
database with at least a plurality merchant costs; and generate a
cost report renderable for display on a user device.
183. The computer program product of claim 182, further caused to:
calculate, based on at least the plurality of merchant cost
criteria, a third amount indicative of a marginal cost; calculate,
based on at least the plurality of merchant cost criteria, a fourth
amount indicative of a marketing service cost; and provide a
promotion forecast using automatically calculated outcomes based on
at least one marketing input comprising consumer demographics,
historical data, expected profit, expected number of new customers,
an indication of the investment spent per new customer, or an
indication of a ratio showing an expected return on investment.
184. The computer program product of claim 182, wherein the cost
report comprises at least a breakdown of all calculated costs and a
return rate populated with a predetermined percentage based on a
historical analysis of at least one previous promotion.
185. The computer program product of claim 182, wherein the
plurality of merchant cost criteria comprises at least a product
cost percentage that identifies a variable cost to offer a
promotion voucher.
186. The computer program product of claim 182, wherein the
plurality of merchant cost criteria further comprises at least one
of an additional spending criteria, a repeat customer criteria, a
return on investment (ROI) criteria, or a merchant revenue
criteria.
187. The computer program product of claim 182, wherein the cost
report comprises a graphical consumer interface (GUI) configured
for remote off-line customization by an associated merchant or
marketing service.
Description
TECHNICAL FIELD
[0001] The present description relates to an effective and
efficient way to better communicate a return on investment value to
a merchant of running a transaction, such as a promotion, and
determine a transaction structure that is conducive to the goals of
the merchant, the customer, the promotion system, or any
combination thereof. This description more specifically relates to
how to provide real-time ROI calculations that a merchant and sales
representative may collaboratively and simultaneously work on to
identify a transaction structure for the merchant to select.
BACKGROUND
[0002] Promotion and marketing services often work with merchants
to identify promotions to offer to potential customers. By
developing appropriate promotions, merchants may increase profit, a
promotion and marketing service may generate revenue, and customers
may find new and interesting goods and/or services at discount
prices.
[0003] After offering a promotion on behalf of a merchant, the
promotion and marketing service may distribute revenue to the
merchant for promotions sold to customers. However, when a customer
seeks a refund of a promotion, the merchant may not be owed any
money for the refunded promotion. In order to account for potential
refunds, the promotion and marketing service may pay merchants less
than what is fully owed. If there are refunds, the promotions
system reduces the outstanding amount due to the merchant by the
merchant's share of the refunded revenue (or, in the case of a
merchant that has already been paid the entire amount due or that
has an outstanding amount due to the promotion and marketing
service, the reduction is carried over into another session: the
next promotion).
[0004] Applicant has identified deficiencies and problems
associated with the use of these systems. As described in detail
below, Applicant has solved these identified problems by developing
a solution that is embodied by the present invention.
BRIEF SUMMARY
[0005] In some example embodiments, a promotions system may be
configured to generate a real-time ROI as output for one or more
promotions. In some examples, the ROI may be operable to optimize
the selection of promotions during negotiation between merchants
and a promotion and marketing service. The system includes a
communications interface configured to receive inputs indicative of
one or more attributes of the promotion, an upsell amount exceeding
a value of the promotion, and one or more indicators of repeat
business in response to the promotion, and a processor in
communication with the interface.
[0006] The system provides, in some examples, a better way to
communicate the value to merchants of running a promotion and
arrive at a deal structure that works for both the merchant and the
promotion and marketing service. The system avoids sub-optimal
deals for merchants that result from the merchant's lack of
understanding. The real-time ROI calculation tool allows merchants
and sales representatives to collaboratively work at the same time
with common visual representation. A sales representative may
dynamically lock or unlock certain fields from merchant
manipulation, may allow off-line merchant manipulation of the tool,
and may enable the use of predictive wizards, analytics/demographic
information, and similar promotions to help arrive at a deal
structure. The real-time ROI calculation tool also, for example,
provides a similar view on the sales representative's side as the
merchant's side, so that changes made on either side are
immediately reflected by both the sales representative's side and
the merchant's side. The sales representative may decide to lock
certain fields to prevent a merchant from editing. The system also
notifies the sales representative when a merchant opens and edits
the ROI criteria.
[0007] The unified payment and ROI system further protects
promotion and marketing services from potential exposure to
unsecured monetary risk. Embodiments of the payment mechanism
includes the following: effectively, when a sale is made in a
particular period of time, the promotion and marketing service may
hold back a certain configurable percentage of the revenue received
from selling vouchers for promotions (such as 25%), so that there's
a buffer in the bank. When the vouchers expire, the payment and
marketing service may distribute the associated revenue that has
been held back. The holdback amount may depend on whether the
amount in the buffer is static or dynamic, and the amount may be
based on the status of the underlying vouchers (e.g., whether they
have expired).
[0008] The new payment mechanism is flexible, simple and easy to
explain to merchants, applicable to various products, and accounts
for risk (refund, out-of-business, bad merchants, fraud). The new
payment mechanism is as attractive to merchants as the current
payment grid, takes advantage of automation (transparent Merchant
Center), provides a backwards compatible architecture, accommodates
promotions with no predetermined ending, is cash flow neutral
(e.g., if possible, but merchant benefits may outweigh), and
provides the ability to pay for multiple promotions in a single
transaction.
[0009] The payment mechanism may make initial calculation
assumptions. For instance, initial payments may be disbursed to
merchants a predetermined time (e.g., seven days) after the start
of a feature period; payment for subsequently purchased vouchers
may be forwarded on a recurring basis (e.g., the 1st and 16th of
each month); and additionally, holdback payments for expired
vouchers may be paid in the first recurring payment date after
expiration of the vouchers (when these assumptions are not true,
the average days until complete payment may be higher).
Accordingly, with vouchers expiring after 180 days, 80% of the
merchant share of the voucher revenue will be received by the
merchant with only nominal delay, and 20% of the merchant share
will be received by the merchant upon expiration of the vouchers
(i.e., after 180 days), which results in complete payment for each
voucher in an average of 36 days; with vouchers expiring after 90
days, there will be complete payment for each voucher in an average
of 18 days. Accordingly, the payment mechanism provides business
benefits, including: better merchant experience, the removal of
volume caps on a deal meter, the ability to have a perpetual
contract (with multiple feature periods), inventory-based payment
rather than merchandising (feature periods), applicability to new
products, and greater consistency of payments to merchants (rather
than sending lots of payments on a seemingly random schedule).
[0010] Controls or risk management monitored and reserve
calculation is updated and documented to reflect inclusion of the
new terms and the calculation reflects the scope of deployment of
the new terms. The system may dynamically determine and adjust the
amount to withhold based on the length of redemption period, the
velocity of redemptions/refunds, industry trends, the category of
the promotion, and the merchant's previous performance. The system
may perform withholding analysis before paying the merchant.
[0011] An initial payment may be forwarded to a merchant a
configurable number of days following the start of the feature
period. Thereafter, payments will be forwarded to the merchant on a
recurring basis (e.g., on the 1st and 16th of each month). For
example, each payment may consist of eighty percent (80%) of the
total remittance amount collected from the previous period. After
the voucher's promotional value expiration, the remaining twenty
percent (20%), less any other refunds, shall be included with the
next recurring payment to the merchant. Three easy-to-understand
ways are used to tune the process according to the product: using
the payment schedule, using the net percentage rules, and using the
event rules.
[0012] The merchant is informed that, for example, seven days after
the merchant's campaign feature period begins, the merchant may
expect to receive a first payment for 80% of sales. Then twice a
month the merchant will receive a payment for 80% of additional
sales for the period. The merchant will receive the remaining 20%
for each period, less any other refunds, when the vouchers sold in
that period expire.
[0013] Other systems, methods, and features will be, or will
become, apparent to one with skill in the art upon examination of
the following figures and detailed description. It is intended that
all such additional systems, methods, features and be included
within this description, be within the scope of the disclosure, and
be protected by the following claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] The system, method and product may be better understood with
reference to the following drawings and description. Non-limiting
and non-exhaustive descriptions are described with reference to the
following drawings. The components in the figures are not
necessarily to scale, emphasis instead being placed upon
illustrating principles. In the figures, like referenced numerals
may refer to like parts throughout the different figures unless
otherwise specified.
[0015] FIG. 1 shows an example graphical consumer interface for
merchants in accordance with example embodiments;
[0016] FIG. 2 shows an example revenue and profit impact control
interface for sales representatives in accordance with example
embodiments;
[0017] FIG. 2a shows an additional example revenue and profit
impact control interface for sales representatives, in accordance
with example embodiments;
[0018] FIG. 2b shows an example revenue and profit impact deal
option creation page, in accordance with example embodiments;
[0019] FIG. 2c shows merchant share of revenue calculation;
[0020] FIG. 2d shows merchant share of revenue and revenue from
additional spend calculation;
[0021] FIG. 2e shows merchant share of revenue, revenue from
additional spend and repeat customer revenue calculation;
[0022] FIG. 2f shows revenue and costs according to the merchant
share, additional spend and repeat customer activity;
[0023] FIG. 3 shows a display interface for a mobile device;
[0024] FIG. 3a shows another display interface for a mobile
device;
[0025] FIG. 3b shows one other display interface for a mobile
device;
[0026] FIG. 3c illustrates an example graphical consumer interface
for a merchant, showing demographic information relating to a
promotion;
[0027] FIG. 3d illustrates an example graphical consumer interface
for a merchant, showing customer survey information relating to a
promotion;
[0028] FIG. 3e illustrates an example graphical consumer interface
for a merchant, showing revenue, cost, and profit information
regarding a promotion;
[0029] FIG. 3f illustrates an example graphical consumer interface
that a merchant may use to update the marginal cost of a
promotion;
[0030] FIG. 4 shows a configuration of the ROI system;
[0031] FIG. 5 shows a diagram of logic of how the merchant revenue
is calculated;
[0032] FIG. 6 shows a flow diagram of logic of how the merchant
cost is calculated;
[0033] FIG. 7 shows a flow diagram of logic of how the merchant
profit is calculated;
[0034] FIG. 7a shows a flow diagram of example operations used by
the system to train and execute an ROI prediction model;
[0035] FIG. 7b shows a flow diagram of example operations used by
the payment system to schedule and distribute funds to a merchant;
and
[0036] FIG. 8 shows a configuration of the unified payment and ROI
system.
DETAILED DESCRIPTION
[0037] The principles described herein may be embodied in many
different forms. Not all of the depicted components may be
required, however, and some implementations may include additional,
different, or fewer components. Variations in the arrangement and
type of the components may be made without departing from the
spirit or scope of the claims as set forth herein. Additional,
different or fewer components may be provided.
Definitions
[0038] As used herein, a promotion may include, but is not limited
to, any type of offered, presented or otherwise indicated reward,
discount, coupon, credit, deal, incentive, discount, media or the
like that is indicative of a promotional value or the like that
upon purchase or acceptance results in the issuance of an
instrument that may be used toward at least a portion of the
purchase of particular goods, services and/or experiences defined
by the promotion. An example promotion, using a running company as
the example merchant, is $25 for $50 toward running shoes. In some
examples, the promotion defines an accepted value (e.g., a cost to
purchase the promotion), a promotional value (e.g., the value of
the resultant instrument beyond the accepted value), a residual
value (e.g., the value upon return or upon expiry of one or more
redemption parameters), one or more redemptions parameters and/or
the like. For example, using the running company promotion as an
example, the accepted value is $25 and the promotional value is
$50. In this example, the residual value may be equal to the
accepted value.
[0039] As used herein, a promotion and marketing service may
include a service that is accessible via one or more computing
devices and is operable to provide example promotion and/or
marketing services on behalf of one or more providers that are
offering one or more instruments that are redeemable for goods,
services, experiences and/or the like. The promotion and marketing
service is further configured to illustrate or otherwise inform one
or more consumers of the availability of one or more instruments in
the form of one or more impressions. In some examples, the
promotion and marketing service may also take the form of a
redemption authority, a payment processor, a rewards provider, an
entity in a financial network, a promoter, an agent and/or the
like. As such, the service is, in some example embodiments,
configured to present one or more promotions via one or more
impressions, accept payments for promotions from consumers, issue
vouchers upon acceptance of an offer, participate in redemption,
generate rewards, provide a point of sale device or service, issue
payments to providers and/or or otherwise participate in the
exchange of goods, services or experiences for currency, value
and/or the like. The service may additionally process refund
requests received from consumers who have been issued vouchers. For
example, using the aforementioned running company promotion, a
customer who has paid the service $25 for a voucher, may
subsequently request a refund of the residual value of the
promotion in conjunction with returning and/or otherwise
invalidating the voucher. The promotion and marketing service may
accordingly credit $25 to the customer and ensure that the voucher
is destroyed and/or otherwise invalidated.
[0040] As used herein, a voucher may include, but is not limited
to, any type of gift card, tender, electronic certificate, medium
of exchange, or the like that embodies the terms of the promotion
from which the voucher resulted and may be used toward at least a
portion of the purchase, acquisition, procurement, consumption or
the like of goods, services and/or experiences. In some examples,
the voucher may take the form of tender that has a given value that
is exchangeable for goods, services and/or experiences and/or a
reduction in a purchase price of a particular good, service or
experience. In some examples, the voucher may have multiple values,
such as accepted value, a promotional value and/or a residual
value. For example, using the aforementioned example of a running
company, the promotional value may be received as an electronic
indication in a mobile application that shows $50 to spend at the
running company. In some examples, the accepted value of the
voucher is defined by the value exchanged for the voucher. In some
examples, the promotional value is defined by the promotion from
which the voucher resulted and is the value of the voucher beyond
the accepted value. In some examples, the residual value is the
value after redemption, the value after the expiry or other
violation of a redemption parameter, the return or exchange value
of the voucher and/or the like.
[0041] As used herein, an impression may include a communication, a
display, or other perceived indication, such as a flyer, print
media, e-mail, text message, application alert, mobile
applications, other type of electronic interface or distribution
channel and/or the like, of one or more promotions. For example,
using the aforementioned running company as the example provider,
an impression may comprise an e-mail communication sent to
consumers that indicates the availability of a $25 for $50 toward
running shoes promotion.
[0042] Overview A merchant typically has several venues in which to
offer the sale of the merchants' product or service. One such venue
is a website, which may assist the sale of the product or service
offered by the merchant. However, it may be difficult for the
merchant to determine the impact to the merchant's business of
using the website. To assist in determining the impact, a Return On
Investment (ROI) system may be used. The ROI system, illustrated in
more detail in FIG. 4, may be a server-based system configured to
receive input from multiple sources, such as from a merchant
computing device and a sales representative computing device, in
order to determine the impact of using the website.
[0043] For example, each of the merchant computing device and the
sales representative computing device may access the server-based
ROI system in order to receive a revenue and profit impact (RPI)
control interface 100 (discussed in more detail in FIG. 1). The
merchant, via the merchant computing device, and the sales
representative for the website, via the sales representative
computing device, may input different parameters relevant to the
impact of the website assisting in the transaction. In turn, the
ROI system is configured to receive the input from the different
parties, and push the RPI of the website transaction to the
merchant computing device and the website-representative computing
device. In this way, the merchant and the sales representative may
both contribute to the determination of the impact of the website
assisting in the transaction. Further, because one, some, or all of
the parameters relevant to the impact of the website assisting in
the transaction are changeable, the merchant and the sales
representative may change various parameters to iteratively
determine the impact.
[0044] The ROI system may be integrated with different systems of
the website. For example, the ROI system may communicate with a
historical database illustrating historical data of previous
transactions. The ROI system may access the historical database in
order to populate one or more parameters relevant to the impact of
the website assisting in the transaction. As another example, the
ROI system may communicate with a webpage database, which may store
data to generate webpages. More specifically, after the merchant
and the website representative agree on the terms of the
transaction, the ROI system may access the webpage database,
generate a webpage using the webpage database and the agreed terms
of the transaction, and present the generated webpage to the
merchant, via the merchant computing device, and to the website
representative, via the website representative computing device.
The ROI system may, in turn, receive input (such as changes) to the
generated website from the merchant or the website
representative.
[0045] FIG. 1 shows a Revenue and Profit Impact (RPI) control
interface 100 generated by the ROI system and also referred to as a
return on investment (ROI) calculator for merchants. The system may
generate a merchant view (as shown in FIG. 1) and a sales
representative view (as shown in FIG. 2). As discussed above, the
RPI control interface 100 illustrates the revenue and profit impact
of using the website to assist in the merchant transaction.
[0046] As one example, the transaction may comprise a promotion
facilitated by the website. In particular, the transaction may
comprise a promotion in the form of a Groupon.RTM. voucher, example
terms of which are illustrated in FIG. 1, from the perspective of
the merchant. The terms shown in FIG. 1 are for illustration only,
and other types of transactions are contemplated.
[0047] The RPI control interface 100 illustrates one or more
parameters related to the promotions. For example, the RPI control
interface 100 illustrates "Your Groupon Check" 102 selectable
criteria, including the average check amount for two individuals
104, Groupon (voucher) Price 106, (Avg) Groupon value 108,
customers per voucher 110, unit cap 112 and merchant share 114. The
RPI control interface 100 provides "Additional Spend" selectable
criteria 116 that includes upsell 118, "Repeat Customers"
selectable criteria 120 that includes return rate percentage 122
and return visits per year 124, and "Merchant Costs" 126 selectable
criteria that includes food cost percentage 128. The fields
illustrated in FIG. 1 are merely for illustration purposes.
[0048] The various fields in FIG. 1 may be fixed or may be
changeable via input from the merchant or sales representative.
Initial entries in the various fields may be based on a past
promotion offered by the merchant, or may be individual preselected
by the sales representative. The initial entries may instead be
randomly generated or may be generated based on entries that are
historically common for similarly situated merchants (e.g.,
merchants having a similar merchant type, size, service, location
etc.). In yet another alternative, the fields may be initially left
blank initially, and are only filled in during an actual
negotiation between the merchant and the sales representative. As
shown in FIG. 1, for example, various fields are in gray,
indicating that those fields have been locked by the sales
representative and are not changeable by merchant input. In
particular, fields 106, 108, 114 are illustrated in gray. By
contrast, fields 104, 110, 112, 118, 122, 124, and 128, which are
not grayed out, may be changed by the merchant. In this way,
merchant input may be used to change various fields to better
illustrate the potential effects of offering the promotion. For
example, the return rate 122 may initially be populated with a
predetermined percentage based on historical analysis of previous
promotions. Thereafter, the return rate 122 may be changed via
consumer input. In this way, the RPI control interface 100 may be
used iteratively to determine the potential effect of offering the
promotion program.
[0049] The average check for two 104 identifies the average amount
a single party of customers spends at a merchant's business in a
single visit. The Groupon Price 106 identifies the amount at which
a Groupon customer will purchase the merchant's offer. As one
example, Groupon may offer at least a 50% discount of the average
retail value to attract new customers to the merchant's business.
The (Avg) Groupon Value 108 identifies the promotional amount a
customer receives toward the purchase of specified goods or
services at the merchant's. For promotions related to experiences,
this is the amount a customer typically spends for items included
in the experience. The Customers/Groupon 110 identifies the average
size of a party for a single visit (e.g., 3 out of 4 merchants
report that Groupon customers bring friends when redeeming their
Groupon voucher). For experiences, this represents the number of
customers who will participate in the experience. The Unit Cap 112
identifies the number of units that Groupon can sell over the
duration of a promotion campaign. Based on previous history, it is
estimated that approximately 20% of units will be redeemed in each
of the first and last months of the campaign, with a continuous
stream of redemptions in the intervening months. The Merchant Share
114 identifies the revenue that the merchant may expect to receive
from a Groupon. The merchant receives payment shortly after the
merchant's offer is purchased, so that the payment can be used to
help pay down costs associated with producing the merchant's
offer.
[0050] The Merchant Share 114, which may otherwise be known as the
provider margin, may be manually entered or may be automatically
calculated by the ROI system based on one or more of the following
values: a historical information margin that compares reviews of
the merchant to reviews of similar merchants; a provider profile
margin, taking into account a merchant quality score; a promotion
structure margin, which takes into account the size of the
discount, the Unit Cap 112, historical margins, and margins for
similar discounts and units; or a positive ROI margin, which
identifies a minimum margin that provides the merchant with a
positive ROI. Such values may be used alone or aggregated through a
linear combination or other similar aggregation method. Further
explanation of such values and associated calculations is provided
by U.S. Provisional Patent Application 61/770,174, titled "METHOD
FOR DETERMINING PROVIDER PARAMETERS INCLUDING A PROVIDER MARGIN,"
and U.S. patent application Ser. No. 13/832,804, titled "METHOD FOR
DETERMINING PROVIDER PARAMETERS INCLUDING A PROVIDER MARGIN," which
are each respectively incorporated by reference in their
entireties.
[0051] The "Additional Spend" 116 selectable criteria include
upsell amount 118, which identifies the amount a customer spends on
goods or services that exceeds the value of the Groupon voucher.
Based on analysis of previous Groupon voucher redemptions, it is
estimated that customers on average spend 55% more than the value
of their Groupon voucher.
[0052] The "Repeat Customers" 120 selectable criteria includes
Return Rate % 122 that identifies the percentage of new customers
the merchant typically attracts back to the merchant's business.
Based on analysis of repeat customers, the system estimates that
the return rate % 122 for customers whose arrival is prompted by
purchasing a Groupon is similar to that of other new customers who
come in.
[0053] The "Merchant Costs" 126 selectable criteria includes Food
Cost % 128 that identifies the incremental (variable) cost to
produce the value of the Groupon voucher. With Groupon, this cost
may be incurred when a customer redeems his or her voucher. Average
food and beverage costs may range from 28-35% of the purchase
price.
[0054] The merchant's revenue ("Your Revenue") 130 includes revenue
from "Repeat Customer Revenue" 132, "Additional Spend Revenue" 134
and "Your Groupon Check" 136. As shown in FIG. 1, the ROI system
calculates repeat customer revenue 132 using the following
formula:
Repeat Customer Revenue = Unit Cap .times. Customers Groupon
.times. Average Check for 2 .times. ( Return Rate % ) .times.
Return Visits Year ##EQU00001##
[0055] In this example, with a unit cap of 100, 2 customers per
Groupon, an average check for two of $60, a return rate of 10%, and
2 return visits per year, the repeat customer revenue 132 of this
example is 100.times.2.times.60.times.10%.times.2, or $2,400.
[0056] Further, the ROI system calculates additional spend revenue
134 using the following formula:
Additional Spend Revenue=Unit Cap.times.Average Upsell
In this example, with a unit cap of 100 and an average upsell of
$20, the additional spend revenue 134 of this example is
100.times.20, or $2,000.
[0057] Finally, the ROI system calculates Your Groupon Check
revenue 136 using the following formula:
Your Groupon Check=Unit Cap.times.Merchant Share
In this example, with a unit cap of 100 and a merchant share of
$10, the Your Groupon Check revenue 136 is 100.times.10, or
$1,000.
[0058] Accordingly, the merchant's revenue 148 in this example is
$2,400+$2,000+$1,000=$5,400.
[0059] The merchant's cost ("Your Cost") 138 includes Repeat
Revenue Cost 140, Additional Spend Cost 142, and Check Cost 144.
The ROI system calculates the costs by multiplying the
corresponding revenue by Food Cost % 128. Accordingly, the repeat
revenue cost 140 is the repeat customer revenue 132 multiplied by
the Food Cost 128, or $2,400.times.35%=$840. The additional spend
cost 142 is the additional spend revenue 132 multiplied by the Food
Cost 128, or $2,000.times.35%=$700. Finally, the check cost 144 is
the Unit Cap 112 multiplied by the Average Groupon Value 108
multiplied by the Food Cost 128, or
100.times.$40.times.35%=$1,400.
[0060] Accordingly, the merchant's cost 150 in this example is
$840+$700+$1,400=$2,940.
[0061] The ROI system calculates the merchant's profit (identified
as "Your Profit" 146) as Your Revenue 148 (shown as $5,400) minus
Your Cost 150 (shown as $2,940), which equals Your Profit 152
(shown as $2,460).
[0062] The number of new customers 156 brought in by the promotion
can be calculated by the ROI system as the unit cap 100 multiplied
by the number of customers per Groupon, or 100.times.2=200. The
investment per customer 158 is the check cost 144 minus the Your
Groupon Check cost 154 divided by the number of new customers 156,
or ($1,400-$1,000)/200=$2.
[0063] Finally, the Return On Investment (ROI), which comprises the
revenue generated by each dollar spent on marketing using
promotions, can be viewed as a ratio of the merchant's revenue 148
to the Your Groupon Check cost 154. With a revenue of $5,400 and
total spent of $1,000, the ROI system in this example produces a
ROI ratio 160 of $5,400:$1,000, or 5.4:1.
[0064] The ROI system may automatically update each of the above
calculations and graphical representations as values are entered in
the criteria fields and/or when the consumer selects the "update
calculation" 162.
[0065] FIG. 2 shows a revenue and profit impact control interface
200 generated by the ROI system for sales representatives. The
sales representative may control whether an ROI criteria is
selectable (editable) by the merchant from the merchant's view. The
sales representative may use the revenue and profit impact control
interface 200 to lead a dialogue with the merchant to determine a
mutually agreeable ROI for the merchant. The ROI criteria values
may be selected (e.g., by the sales representative) and/or
automatically selected by the system based on the merchant,
merchant type or some other criteria. Reference deal structures may
be used to prefill the values to pre-populate the return on
investment calculations. For example, the sales representative may
select a default set of ROI criteria from a repository of promotion
criteria 202. The values entered by the merchant and/or the sales
representative are adjusted on the graphical display in real-time.
In this regard, functions described herein as real-time need not
actually occur without any delay at all, but may occur without
perceivable delay, or in other words, in substantially near
real-time. In one such embodiment, the graphical representation may
be updated using a third party service (e.g., www.pusher.com, which
may perform updates with an average delay of 5 milliseconds) that
is responsive to values entered by the merchant and/or the sales
representative. The system provides a way to build a live graphical
representation of a return on investment calculation
collaboratively by a merchant and sales representative.
[0066] The sales representative view includes consumer selectable
icons (e.g., 204, 206, 208, 210) that may not be viewable or
selectable by the merchant. For example, the sales representative
view includes "lock" icons (e.g., 204, 206, 208) that can be
toggled to lock or unlock a parameter. As another example, the data
format of a field may be changed. For example, the "merchant share"
may be represented as a percentage of the total revenue or a dollar
amount for the "merchant share" data format, by toggling icon
210.
[0067] The system provides mouse over 212 views for each of the
sub-components of "Your Revenue" 130 (e.g., "repeat customer" 214,
"additional spend" 216, "merchant share" 218), "Your Cost" 132, and
"Your Profit" 134 calculations that display the calculations used
to calculate the amounts in each category (130, 138, 146).
[0068] FIG. 2a discloses another example revenue and profit impact
control interface 200A. As shown in FIG. 2a, there may be a variety
of items that are displayed for the merchant, in this case
including the Your Groupon Check value 1232 (similar to 136 and
218), the additional upsell revenue 1234 (similar to 134 and 216),
and the repeat customer revenue 1236 (similar to 132 and 214),
which together comprise the overall merchant revenue 1148 (similar
to 148), as well as check cost 1144 (similar to check cost 144),
among other similar values. Moreover, in the example shown in FIG.
2a, the total number of customers 1156 (similar to new customers
156 above) may be displayed. In addition, the ROI system may
display the investment per customer 1158 (similar to investment per
customer 158), and the total merchant investment 1160. In the
depicted embodiment, the total merchant investment 1160 comprises
the check cost 1144 minus the Your Groupon Check value 1232 (which
is also presented outside of the context of the bar chart as
element 1172). Finally, in the example shown in FIG. 2a, the ROI
system may display the full price revenue generated, which
comprises the upsell revenue 1234 plus the repeat customer revenue
1236.
[0069] In addition to the variety of items that may be displayed to
the merchant, the ROI system may allow a representative to
calculate, compare, and potentially display to a merchant a variety
of deal options. Each deal option can be accessed using a tab 1164
(e.g., Option 1, Option 2, etc.), which refreshes the viewable
display for the sales representative and the merchant to display
the values for the various data fields associated with the selected
deal option. Additionally, the sales representative (or the
merchant) may create a new deal option by selecting tab 1166, which
presents a display described below in connection with FIG. 2b. The
sales representative may select the summary tab 1168, which
presents an overview or comparison of the various deal options that
have been created for a particular merchant. In some embodiments,
representatives and merchants may be able to generate tabs using
the add option of tab 1166, select which tab 1164 to view, or view
a summary of each deal option generated so far.
[0070] FIG. 2b illustrates the add deal option interface 200B. In
some embodiments, once this interface has been presented, entry of
values into the various fields generates a new report in the manner
described above with respect to FIGS. 2 and/or 2a. By selecting the
pencil logo 1170, the sales representative (or, in some
embodiments, the merchant) may enter a new name for the particular
deal option.
[0071] FIG. 2c shows the merchant share 200C of revenue
calculation. The merchant share 200A of a revenue calculation may
be calculated by the ROI system using the inputs to the "Your
Groupon Check" 102 criteria. In this regard, when MyCheck icon 220
is selected, the Revenue and Profit Impact displays the resulting
direct revenue impact 232 of implementing the promotion. The
merchant share 200C of revenue calculation also takes into account
the unit cap 112 (e.g., number of vouchers sold), the Groupon price
106 (e.g., price per voucher), the average Groupon value 108 (e.g.,
value per voucher), the merchant share 114 (e.g., margin), and a
credit card fee per transaction 228.
[0072] Accordingly, the ROI system calculates the direct revenue
impact 232 using the following formula:
MyCheck Revenue=Unit Cap.times.Groupon Price.times.Merchant
Share.times.(1-Credit Card Fee)
[0073] In this example, with a unit cap of 1000, a Groupon Price of
$20, a merchant share of 50%, and a Credit Card Fee of 2.5%, the
MyCheck revenue 232 is 1000.times.20.times.0.5.times. (1-0.025), or
$9,750. Because only the MyCheck icon 220 is selected, the overall
merchant revenue 148 is shown based only on the revenue calculation
due to the promotion.
[0074] FIG. 2d shows an interface that additionally factors in the
revenue generated from upsells. Because MyCheck icon 220 is
selected and Additional Spend icon 222 is also selected, the ROI
system calculates the impact of the merchant share 200D of revenue
and also the revenue from the additional spend calculation. The
merchant share of revenue and revenue from Additional Spend 200D
calculation may be calculated by the ROI system using the inputs to
the "Your Groupon Check" 102 criteria and "Additional Spend" 116
criteria. The merchant share 200D of revenue calculation also takes
into account the additional spend per voucher 118.
[0075] The ROI system calculates the additional upsell revenue 234
using the following formula:
Additional Spend Revenue=Unit Cap.times.Additional Spend Per
Voucher
[0076] In this example, with a unit cap of 1000 and an additional
spend per voucher (118) of $11, the additional upsell revenue 234
is 1000.times.11, or $11,000. Accordingly, the overall merchant
revenue 148 is calculated to be $20,750, based on the MyCheck
revenue 232 and the additional upsell revenue 234.
[0077] FIG. 2e shows an interfaced that additionally factors in the
revenue from repeat customers generated by the promotion. Because
MyCheck icon 220, Additional Spend icon 222, and Repeat Customers
icon 224 are selected, the merchant share 200E of revenue includes
direct revenue from the promotion 232, from additional spend 234,
and from repeat customer revenue 236. The merchant share of revenue
from additional spend and repeat customer revenue calculation 200E
may be calculated by the ROI system using the inputs to the "Your
Groupon Check" 102 criteria, "Additional Spend" 116 criteria and
"Repeat Customer" 120 criteria. The merchant share 200E of revenue
calculation also takes into account the average check for 2 104
(not shown in FIG. 2e), the return rate 122 and the return visits
per year 124.
[0078] The ROI system calculates the repeat customer revenue 236
using the following formula shown above with respect to repeat
customer revenue 132:
Repeat Customer Revenue = Unit Cap .times. Customers Groupon
.times. Average Check for 2 .times. ( Return Rate % ) .times.
Return Visits Year ##EQU00002##
In this example, with a unit cap of 1000, 2 customers per Groupon,
an average check of $35, a return rate of 10%, and 1 return visit
per year, the repeat customer revenue 236 is
1000.times.2.times.35.times.0.1.times.1, or $7,000. Accordingly,
the overall merchant revenue 148 is calculated to be $27,750, based
on the MyCheck revenue 232, the additional upsell revenue 234, and
the repeat customer revenue 236.
[0079] In addition, selection of the "Enable Groupon Rewards" icon
230 allows for a calculation of the impact of a rewards system on
revenue.
[0080] FIG. 2f shows revenue and costs 200F according to the
merchant share, additional spend and repeat customer criteria, as
calculated by the ROI system. Because MyCheck icon 220, Additional
Spend icon 222, and Repeat Customers icon 224 are selected, the
revenue and costs 200F includes direct revenue from the promotion
232, from additional spend 234, and from repeat customer revenue
236. Because Merchant Costs icon 226 is also selected, the ROI
system can further calculate the merchant costs 150 and profit 152.
The merchant costs (140, 142, and 144) are calculated in the manner
described above, and in this example amount to $20,300.
Accordingly, the profit 152 comprises $7,450.
[0081] FIG. 2f additionally shows the number of new customers 156,
the net profit 152, the investment per customer (cost per customer)
158, and the return on investment 160, calculated as described
previously. In addition, FIG. 2f displays to the user a comparison
of advertising costs 238 of using the promotion versus using other
traditional forms of advertising.
[0082] FIG. 3 shows a mobile device display interface 300. The
system may communicate the ROI interface in a way to accommodate
the display of the mobile device. The sales representative may
communicate the ROI calculator to a mobile device of a merchant and
the ROI calculator adapts to the viewing area of the mobile device
being used to view the ROI calculator. For example, the graph may
be displayed in the center area of the display (e.g., using two
columns instead of three columns). Depending on the capability of
the mobile device display interface, the ROI system may collapse
the "your cost" and "your profit" columns (see item 302), and may
arrange information (e.g., 154, 156, 158, 160) so that the
information is easily viewable (see item 304).
[0083] FIG. 3a shows another display interface 300a for a mobile
device such as a tablet computing device. FIG. 3b shows one other
display interface 300b for a mobile device such as a smart
phone.
[0084] In some embodiments, the above-described features may be
used to provide merchants with a rich source of relevant
information about existing promotions. In this regard, the ROI
system may populate and present to merchants a Merchant Impact
Report, which enables the merchant to evaluate the performance of
an existing promotion based on the previously described
calculations, as well as additional data collected by the ROI
system.
[0085] FIG. 3c shows an impressions interface 306 generated by the
ROI system that may be presented to a merchant in connection with a
selected promotion. The impressions interface 306 displays the
number of impressions 308 of the promotion that are sent to
promotion and marketing service subscribers. In this example, the
impressions are sent to subscribers via email, although other
delivery mechanisms (such as those described previously) are
contemplated. For instance, the impressions may be distributed
using a mobile device application or website.
[0086] Some fraction of subscribers receiving impressions may
subsequently purchase the promotion. Because promotions are
purchased from the promotion and marketing service, the promotion
and marketing service is able to compile demographic information
regarding the subscribers who have purchased the promotion and
present such demographic information to the ROI system as
attributes of the promotion. Thereafter, the ROI system can
calculate, based on the attributes of the promotion, the gender,
age, and zip code of the subscribers who have purchased the
promotion.
[0087] Using the impressions interface 306, the ROI system is able
to display to the merchant a gender representation 310 of the
gender of the customers who have purchased the promotion. For
instance, the gender representation 310 may include a percentage of
customers who have purchased the promotion that are male and a
percentage of the customers who have purchased the promotion that
are female.
[0088] Similarly, the impressions interface 306 may display to the
merchant an age representation 312. The age representation 312 may
include the ages of customers who have purchased the promotion. In
one embodiment, the age representation 312 may include a histogram
showing a number of customers who have purchased the promotion in
one or more age ranges.
[0089] Using the impressions interface 306, the ROI system is able
to display to the merchant a representation 314 of the zip codes of
the customers who have purchased the promotion. This representation
may include a histogram showing a number of customers who have
purchased the promotion for each zip code. The representation 314
may also include a map showing the zip codes of the customers who
have purchased the promotion. In one embodiment, the map is a
cluster map, which places a circle over each zip code of a customer
who has purchased the promotion, and varies the size of the circle
based on the number of customers in the zip code.
[0090] Although impressions interface 306 may display demographic
information regarding subscribers who have purchased the promotion,
the impressions interface 306 may additionally or alternatively
display demographic information regarding subscribers to whom
impressions have been delivered (i.e., subscribers who have been
sent an email advertising the promotion).
[0091] FIG. 3d shows a customers interface 316, generated by the
ROI system that may be presented to a merchant in connection with a
selected promotion. The interface 316 displays the number of
customers who have redeemed the promotion 318. In addition, the
customers interface 306 may disclose the percentage of purchased
promotions that have been redeemed 320. Moreover, the promotion and
marketing service may request that the customers who have redeemed
the promotion 318 complete surveys about their experience with the
merchant. Based on the survey results, the customers interface 316
may display additional information to the merchant.
[0092] For instance, based on the survey results, the ROI system
may calculate an average rating of the merchant. The customers
interface 316 may then display the average merchant rating 322
(using, for instance, a number line or other similar graphical
format). In one embodiment, the customers interface 316 may
additionally display a percentage of customers who would recommend
the merchant's business to a friend.
[0093] Similarly, based on the survey results, the ROI system may
determine the number of customers who were new to the merchant at
the time of redeeming the promotion and the number of customers
that had not visited the merchant for a predetermined amount of
time (such as three months) prior to redeeming the promotion.
Accordingly, in one embodiment, the customers interface 316 may
additionally display a chart 324 indicating a percentage of
customers who were new to the merchant at the time of redeeming the
promotion, a percentage of customers that had not visited the
merchant for a predetermined amount of time prior to redeeming the
promotion, and a remaining percentage of customers.
[0094] In one embodiment, the ROI system may calculate, based on
customer rewards information, an estimated percentage of new
customers that will return to the merchant within a predetermined
amount of time of redeeming a voucher. In one embodiment, this
information may be based on metrics, such as but not limited to the
historical return rate of existing customers, tracked using
customer rewards information. In another embodiment, it may be
based on a metric that tracks the number of customers that would
receive an additional promotion for returning. In yet another
embodiment, the estimated percentage of new customers that will
return is based on a metric generated from an evaluation of the
past behavior of the new customers, as shown by the customer
rewards information. Accordingly, in this embodiment, the customers
interface 316 may additionally display the estimated percentage of
new customers that will return to the merchant within the
predetermined amount of time of redeeming a voucher 326 (using, for
instance, a number line or other similar graphical format).
[0095] In some examples embodiments, there may not be a sufficient
data to generate a particular metric or a set of metrics for a
particular merchant, metrics may be unknown for a particular
merchant, additional metrics may be required for a more specific or
accurate ROI value and/or the like. In such cases, a dataset that
is generated based on historical metrics (historical data, survey
results, historic ROI data and/or the like) for all merchants may
be used to train and/or test an ROI prediction model to approximate
ROI and its components (e.g., estimate revenue from consumers who
returned to merchant after a first visit, estimate amount spent by
Groupon customers over the promotion discount, amount paid to the
merchant for total promotions sold). For example, the ROI
prediction model may be trained to classify a particular metric
value as indicative of a positive ROI and/or may learn that the
combination of two metrics can be used as a predictor for number of
consumers who will return to a merchant after a first visit.
[0096] In some example embodiments, the machine learning model may
be used to generate predictive algorithms for ROI and its
components for a merchant that is running a current promotion. The
machine learning model may be operable to input one or more metrics
relating to the current merchant and the current promotion. Based
on the similarity determined between the one or more metrics, the
current promotion and/or the merchant, the ROI predictive model may
generate one or more estimated metrics. The estimated metrics are
suggestive of probabilistic values when compared to the trained
model. In some example embodiments, the estimated metrics may be
used in calculations that provide an estimate of ROI and/or ROI
components. The ROI and the components thereof may therefore be
predicted and displayed, such as is shown in 148-152 of FIG.
3e.
[0097] FIG. 3e shows a revenue interface 328, generated by the ROI
system, which may be presented to a merchant in connection with a
selected promotion. The revenue interface 328 displays the
financial impact of the promotion. For instance, it may display the
revenue 330 generated by the promotion so far. Revenue 330 may
comprise the merchant's revenue 148 as discussed previously. In
addition, the customers interface 306 may display a breakdown of
the merchant's financial information 332. This information includes
the merchant's revenue 148, merchant's cost 150, and merchant's
profit 152, calculated by the ROI system as previously described.
In one embodiment, this financial information 332 may be displayed
as a histogram.
[0098] In another embodiment, the merchant's financial information
332 may be configurable when the merchant uses an input device to
select the cost editor 334. The merchant may edits its cost (e.g.,
projected, estimated, or actual) using the cost editor 334. For
example, in the depicted embodiment, the merchant may edit its cost
from 11% (as shown) to 13% upon receiving notice that its cost of
materials for certain raw materials have risen.
[0099] Alternatively or additionally and in some embodiments, the
ROI system may be configured to determine a positive ROI margin
.mu..sub.r for display n connection with the Merchant Impact Report
herein described and illustrated in connection with FIGS. 1-3f.
According to one embodiment, the ROI system may be configured to
determine a positive ROI margin based upon past promotions offered
and the margin thresholds necessary for a positive ROI in those
past promotions. In another embodiment, the ROI system may be
configured to determine a positive ROI margin based at least upon a
Monte Carlo simulation used to derive an empirical distribution,
from which the probability of 7 being positive may be determined,
where .pi. is the profit per instrument divided by the unit price.
The unit price may be defined as the price a consumer pays for the
goods, services, experiences and/or the like.
[0100] In this regard, .pi., the profits per instrument divided by
the unit price may be expressed by the equation,
.pi.=pf[(.mu.+s+r)-k(v+s+r)]-p(1-f)(v-.mu.)+f(1-p)[(p+s'+r')-k(1+s'+r')]-
-(1-p)(1-f)(1-.mu.)
wherein, v is the unit value divided by the unit price. The unit
value may be defined as the original price of the good, service
and/or experience before the promotion was offered. Further, [0101]
1. r is the average return amount spent by a consumer divided by
the unit price (i.e. revenue associated with repeat business (e.g.,
214) per unit price), [0102] 2. r' is the average return amount
spent after the expiration of the promotion period divided by the
unit price (i.e., revenue associated with repeat business after
promotion expiration per unit price), [0103] 3. s is the average
amount spent in addition to the promotion divided by the unit price
(i.e., revenue upsale per unit price), [0104] 4. s' is the average
amount spent in addition to the promotion after the promotion
period expires divided by the unit price (i.e., non-redemption
revenue per unit price), [0105] 5. k is the variable cost as a
percentage of the total check amount (i.e., the variable cost as a
percentage of the total amount of a consumer's transaction), [0106]
6. f is the new customer fraction (i.e., the amount of new
consumers that had not previously purchased goods and/or services
from the provider), and [0107] 7. p is the final redemption
percentage (i.e., the percentage of instruments that are redeemed).
In addition, the above variables may be computed with respect to
the particular merchant's category.
[0108] In estimating the positive ROI margin, the ROI system may be
configured to utilize certain assumptions when performing the Monte
Carlo simulations. For example, the ROI per instrument may be
assumed to be independent from the volume of the units sold. As
such, when 7, the profits per instrument divided by the unit price,
is greater than zero, the ROI may be interpreted as being positive
for the promotion campaign. In some embodiments, the ROI system may
assume a correlation exists between the unit price and whether a
consumer purchases additional goods and services and/or returns to
the provider/merchant in the future for other goods, services and
the like.
[0109] According to some embodiments, the provider parameter system
may also assume that redeeming promotions by existing consumers is
a cannibalization of sales. Further, it may be assumed that a
consumer would spend the same amount regardless of having a
promotion instrument, such as a coupon. The ROI system may further
assume a final redemption rate of 85%. In another embodiment, the
provider parameter system may use a redemption rate percentage from
the provider's past promotions. Further, it may be assumed that all
expired instruments will be redeemed at the unit price. In some
embodiments, the amount spent in addition to the promotion and the
amount spent in a subsequent visit by a consumer may be assumed to
be zero for expired instruments.
[0110] As such, the positive ROI margin may be determined using the
approximated distributions obtained by the Monte Carlo simulations
and consumer input data corresponding to the category of the
merchant c, the discount provided d, and the cost of goods sold
percentage k (e.g., 128, etc.), as represented by the equation,
.mu. r ( m i , d ) = { .mu. P ( .pi. ( .mu. , c m i , k c m i , 1 d
) ) > 0 } ##EQU00003##
where the discount provided d is defined as 1/v. According to one
embodiment, the positive ROI margin may be determined to be 0.61
for a spa and health services provider, such as Acme Spa
Company.
[0111] FIG. 3f shows one example cost editor interface displayed by
the ROI system upon merchant selection of the cost editor 334. The
cost editor interface enables the merchant to select the percentage
of the cost of each promotion that goes towards marginal costs of
fulfilling the promotion. In one such embodiment, food cost 128,
discussed previously, corresponds to the marginal cost selected
using cost editor 334. In other embodiments, food cost 128 may only
be one of many factors that go into a merchant's calculation of the
marginal cost of fulfilling a promotion. In yet other embodiments
(e.g., non-food serving embodiments such as spas, etc.), food cost
128 may not be relevant to the marginal cost of fulfilling the
promotion.
[0112] In the depicted embodiment, the merchant may interact with
the cost editor interface by manipulating slider 336 until the
appropriate percentage is displayed. Because the marginal cost of
fulfilling a promotion is highly dependent upon the merchant and
the promotion offered, slider 336 enables a merchant to calculate
these costs in any manner, and need not force the merchant to use a
preconfigured formula. For any given percentage selected using
slider 336, the cost editor interface may display the value of the
promotion 338 and, based on the percentage selected using slider
336, the interface may display the marginal cost of fulfilling each
promotion 340. Based on the value selected using slider 336, the
merchant will be returned to the revenue interface 328, which will
present an updated breakdown of the merchant's financial
information 332, as recalculated by the ROI system in view of the
changed marginal cost. For example, in connection with FIG. 3e, the
ROI system may provide updated calculations for merchant cost 150
and merchant profit 152 based on the newly edited cost information
(e.g., 13%).
[0113] Using these additional Merchant Impact Report interface
tools, the ROI system enables merchants to develop a much more
sophisticated understanding of the value provided by their
promotions.
System Architecture
[0114] FIG. 4 shows a configuration 400 of the ROI system. The
merchant 402 and sales representative 404 may calculate multiple
ROI configurations and store the ROI configurations for use
(retrieval) in a promotion repository 406 to build other promotions
and/or use for comparison for configuring subsequent promotions.
From the ROI sales representative view, the sales representative
may select, from previously calculated promotions, a default
promotion for a merchant in order to initiate a dialogue with the
merchant. The ROI system may generate the merchant deal page(s)
(410) corresponding to the merchant's promotion that is viewable by
the public in order to purchase the merchant's promotion. For
example, potential customers may purchase the transaction via a
website. In response to agreeing on the parameters of the
transaction, the ROI system may generate a webpage for use on the
website that reflects the agreed parameters of the transaction.
Further, the merchant and/or sales representative may review the
webpage and make changes. Similar to the determination of the
parameters for the transaction, the merchant (via the merchant
computing device) and the sales representative (via the website
representative computing device) may both make changes to the
webpage.
Return on Investment System Operations
[0115] FIGS. 5-7 show example operations for generating merchant
revenue, cost, profit, and ROI information. The ROI information
depends upon revenue, cost, and profit related to a promotion,
values which themselves may vary based on the several attributes
assigned to the promotion and on projections forecasting expected
customer engagement as a result of the promotion, as will be
described below.
[0116] FIG. 5 shows a diagram of logic 500 of how merchant revenue
is calculated. In step 502, the system receives merchant criteria
selections. These selections may be received from the merchant or
from a sales representative of the promotion and marketing service
who interacts with the merchant. These selections comprise inputs
indicative of one or more attributes of the promotion, an upsell
amount, and one or more indicators of repeat business in response
to the promotion. The attributes may include the average check
amount for two individuals, the voucher price, the average voucher
value, the number of customers per voucher, a unit cap, a merchant
share, a food cost percentage, a number of impressions, and
demographic information about the customers. The indicators of
repeat business may include return rate percentage and return
visits per year. Using the received attributes, upsell amount, and
indicators of repeat business, the merchant's revenue (shown as
"Your Revenue" 130 in FIG. 1) is calculated based on revenue from
"repeat customer revenue" 132, "additional spend revenue" 134 and
"Your Groupon Check" 136 amount calculated based on the received
criteria (e.g., merchant selected criteria).
[0117] In operation 504, the ROI system calculates, based on one or
more of the attributes received in operation 502, a first amount
indicative of revenue generated from the promotion. In one
embodiment, the repeat customer revenue is calculated using the
following formula (as previously described):
Repeat Customer Revenue = Unit Cap .times. Customers Groupon
.times. Average Check for 2 .times. ( Return Rate % ) .times.
Return Visits Year ##EQU00004##
[0118] In operation 506, the ROI system calculates, based on the
upsell amount received in operation 502, a second amount indicative
of revenue generated from promotion upsells. This second amount may
comprise revenue generated from upsells attendant to administering
the promotion. In one embodiment, this second amount is calculated
using the following formula (as previously described):
Additional Spend Revenue=Unit Cap.times.Average Upsell
[0119] In operation 508, the ROI system calculates, based on the
one or more indicators of repeat business received in operation
502, a third amount indicative of revenue generated from repeat
business attendant to administering the promotion. In one
embodiment, the merchant's check revenue 136 is calculated using
the following formula (as previously described):
Your Groupon Check=Unit Cap.times.Merchant Share
[0120] In operation 510, the merchant's revenue is determined from
the first, second, and third amounts.
[0121] Subsequently, the ROI system calculates, based on the one or
more attributes of the promotion, a fourth amount indicative of
costs from the promotion. In this regard, FIG. 6 shows a flow
diagram of logic 600 of how this cost is calculated. In operation
602, the ROI system receives the merchant criteria selections. The
merchant's total cost includes the repeat revenue cost, the
additional spend cost, and the merchant's check cost. The costs may
be calculated by multiplying the corresponding revenue by the
received food cost, as described previously. Accordingly, in
operation 604, the ROI system calculates the repeat revenue cost.
In one embodiment, this calculation comprises multiplying the
repeat customer revenue 132 by the Food Cost 128. In operation 606,
the ROI system calculates the additional spend cost. In one such
embodiment, this calculation comprises multiplying the additional
spend revenue 132 by the Food Cost 128. In operation 608, the ROI
system calculates the merchant's check cost 144, which in one
embodiment comprises multiplying the Your Groupon Check revenue 136
by the Average Groupon Value 108 and the Food Cost 128.
Accordingly, in operation 610, the ROI system determines the
merchant's total cost by adding together the repeat revenue cost,
the additional spend cost, and the merchant's check cost.
[0122] FIG. 7 shows a flow diagram 700 describing an example
mechanism by which merchant profit is calculated. In operation 702,
the ROI system receives the merchant criteria selections. In
operation 705, the ROI system calculates the merchant revenue. In
one embodiment, the merchant revenue is calculated as shown above
in operation 510. Subsequently, in operation 706, the ROI system
calculates the merchant cost. In one embodiment, the merchant cost
is calculated as shown above in operation 610. Finally, in
operation 708, the ROI system determines the merchant profit. In
this regard, the merchant's profit comprises the merchant revenue
minus the merchant cost.
[0123] In some embodiments, the ROI system subsequently generates
(or updates) a graphical representation displaying the first,
second, third, and fourth amounts. In one such embodiment, the
graphical representation comprises a first histogram representative
of the first, second, and third amounts, and a second histogram
representative of the fourth amount. Examples of such graphical
representations may be found in FIGS. 1-3b. The graphical
representation may provide a forecast using a predictive wizard
(i.e., software that automatically calculates outcomes based on
various inputs), analytics/demographics (e.g., historical
information), similar promotions, or any combination thereof. In
some cases, this forecast may include expected profit, an expected
number of new customers, an indication of the investment spent per
new customer, or an indication of a ratio showing an expected
return on investment (shown, for example, in FIG. 1, elements 152,
156, 158, and 160, respectively).
[0124] In some embodiments, the graphical representation may be a
graphical consumer interface (GUI) with which the merchant and
sales representative may provide the inputs used in the
above-described calculations and forecasts. In such embodiments,
the ROI system may receive input from the sales representative to
lock or unlock certain fields in the interface and may allow
off-line merchant manipulation of the graphical representation.
Accordingly, the unified payment and ROI system may generate a
real-time ROI as output for one or more promotions.
ROI Learning Model
[0125] In some example embodiments, attribute analysis for
predicting ROI or ROI components includes a pattern recognition
algorithm for processing historic metrics to determine a given
providers ROI based on the providers attributes. Cluster analysis
and classification algorithms are two examples of pattern
recognition algorithms that may be used to perform processing using
statistical inference. In cluster analysis, an input pattern is
assigned to one of several groups (clusters) of the same type of
patterns. Patterns within the same cluster are likely to be more
similar to each other than they are similar to patterns assigned to
different clusters. A classification algorithm (i.e. classifier)
maps an input pattern into one of several categories in which the
pattern is most likely to belong.
[0126] Machine learning is often used to develop a particular
pattern recognition algorithm (i.e. an algorithm that represents a
particular pattern recognition problem) that is based on
statistical inference. For example, a set of clusters may be
developed using unsupervised learning, in which the number and
respective sizes of the clusters is based on calculations of
similarity of features of the patterns within a previously
collected training set of patterns. In another example, a
classifier representing a particular categorization problem may be
developed using supervised learning based on using a training set
of patterns and their respective known categorizations. Each
training pattern is input to the classifier, and the difference
between the output categorization generated by the classifier and
the known categorization is used to adjust the classifier
coefficients to more accurately represent the problem. A classifier
that is developed using supervised learning also is known as a
trainable classifier.
[0127] In embodiments, content analysis includes a source-specific
classifier that takes a source-specific representation of the
content received from a particular source as an input and produces
an output that categorizes the provider attributes in such a way to
predict certain metric values that can be used to calculate an ROI
or ROI component.
[0128] FIG. 7a shows an example method that may be executed by a
unified payment and ROI system to train and execute an ROI
prediction model that is configured to predict ROI and ROI
components based on provider attributes and one or more historical
metrics. As is shown in block 710, ROI and/or ROI components are
calculated for one or more providers. In some example, embodiments,
the ROI and/or ROI components may be calculated based on one or
more metrics generated from surveys, marketing exposure, financial
engineering, in-store transactions and/or the like. The metrics may
include but are not limited to:
TABLE-US-00001 ID Metric Description 1. Delta In some examples,
Delta is the time period used to define new, lapsed, existing, and
returning transactions. This is an input assumption and the default
may take the form of delta = 90 days. Given a consumer and a
transaction by that consumer, the transaction is considered
new/lapsed if there are no transactions by the same consumer in the
preceding delta days, and vice versa for existing/returning. A
lapsed transaction, for example, has no transactions by the same
consumer in the preceding delta days, but there are transactions by
the same consumer more than delta days ago. Note that if a
transaction is less than delta days from the min_tran_date (see
below), then the status of the transaction as new/lapsed or
returning is undefined. 2. final_redemption_pct The fraction of
Groupons redeemed at the time of campaign expiration. This is an
input assumption and the default may take the form of 0.85. 3.
cc_fee_pct Credit card fee percentage. There is a fee charged by
the credit card company when customers purchase Groupons, in some
examples, using their credit card on the Groupon website. This fee
is a percentage of the transaction amount and it comes out of the
provider's share of the Groupon sales. This is an input assumption
and the default may take the form of 0.025. 4. alpha Significance
level of the confidence intervals. The confidence level is 1-alpha.
This is an input assumption and the default may take the form of
0.05 (95% confidence). 5. cog_pct Cost of goods or services as a
percentage of the total bill. This input assumption is tabulated by
provider category and subcategory. E.g. for providers in category
Restaurants and subcategory American/Traditional, the cog_pct is
0.37. In this case, the provider cost for a total bill of $100
(excluding tips but including tax) is assumed to be $37. 6.
tips_pct Tips as a percentage of the total bill. This is currently
assumed to be 20% for providers in categories Restaurants and
Beauty & Spas and 0% otherwise. This is used, in some examples,
to back out the estimated total bill, excluding tip, from the
actual transaction amount. 7. min_tran_date The date of the first
transaction in the data for a provider, expressed as a number. Use
the mysql function from_days ( ) to get the actual date. 8.
max_tran_date The date of the last transaction in the data for a
provider, expressed as a number. Use the mysql function from_days (
) to get the actual date. 9. num_txn The number of total
transactions in the data for a provider. 10. num_coupons_sold
Number of Groupons sold. 11. num_cstmr Number of unique customers
who purchased Groupons. 12. num_coupons_redeemed_td Number of
Groupons redeemed to-date. 13. num_coupons_redeemed_proj Projected
number of Groupons redeemed at campaign expiration. 14.
num_cstmr_redeemed_td Number of unique customers who redeemed
Groupons to-date. 15. num_cstmr_redeemed_proj Projected number of
unique customers who redeemed Groupon at campaign expiration. 16.
num_email_impressions Number of email impressions. 17.
unit_value_avg The average Groupon unit value weighted by the
number sold. 18. unit_price_avg The average Groupon unit price
weighted by the number sold. 19. unit_buy_price_avg The average
Groupon unit buy price weighted by the number sold. 20.
num_new_cstmr Number of new/lapsed customers activated by Groupon.
This number reflects only those customers who appear in our
transaction data. Generally, these are customers who have used
their Groupon-registered credit cards at the provider. More
specifically, and by way of example, new customers are those who: 1
Bought a Groupon 2 Had an in-store transaction using a registered
credit card after Groupon purchase 3 Have not visited the store in
the delta days before the in-store transaction 4 If visit is by a
lapsed customer, there are no visits between the visit and the
Groupon purchase date 21. num_existing_cstmr Number of existing
customers who use Groupon. See num_new_cstmr above for important
example caveats. Existing customers are those who: 1 Bought a
Groupon 2 Had an in-store transaction using a registered credit
card after Groupon purchase 3 Had visited the store in the delta
days before the in-store transaction 4 The previous visit must be
before the Groupon purchase date 22. new_cstmr_fraction The
customer fraction is defined as, in some examples: new cstmr
fraction = num new cstmr num new cstmr + num existing cstmr This
metric is used to estimate the new customer fraction of all Groupon
customers of the provider, even though it is calculated based only
on the subpopulation of consumers whose transactions we are able to
track. 23. existing_cstmr_fraction The existing customer fraction
is defined as, in some examples: existing cstmr fraction = num
existing cstmr num new cstmr + num existing cstmr Similar to
new_cstmr_fraction, this metric is used to estimate the existing
customer fraction of all Groupon customers of the provider. 24.
new_cstmr_fraction_survey The new customer fraction based on email
survey data. The survey new customers are those who indicated that
they have never been to the provider before. Note that
new_cstmr_fraction_survey does not measure the same thing as
new_cstmr_fraction in some examples, as new_cstmr_fraction include
also lapsed customers. 25. lapsed_cstmr_fraction_survey The lapsed
customer fraction based on email survey data. The survey lapsed
customers are those, in some examples, who indicated that they have
visited the store before, but more than 90 days ago. 26.
new_lapsed_cstmr_fraction_survey The new and lapsed customer
fraction based on email survey data. This metric is analogous to
new_cstmr_fraction in examples where delta = 90. 27.
existing_cstmr_fraction_survey The existing customer fraction based
on email survey data. The survey existing customers are those, in
some examples, who indicated that they have visited the store in
the past 90 days. This metric is analogous to
existing_cstmr_fraction, but only if delta = 90. 28.
new_cstmr_fraction_best This is either new_cstmr_fraction or
new_lapsed_cstmr_fraction_survey. The rule to determine which
metric to use is described, for example, in overspend_avg_best.
This is the customer fraction used in subsequent calculations. 29.
existing_cstmr_fraction_best Existing customer fraction defined,
for example, as 1-new_cstmr_fraction_best. This is the customer
fraction used in subsequent calculations. 30. overspend_avg The
average overspend estimated from data entered by the provider. The
data is, for example, the amount_spent column in the
campaign_membership_coupon table in groupon_production. It is
assumed, in some examples, that the value in the amount_spent
columns is the total bill including the Groupon value but excluding
tips. 31. matched_redemption_overspend_avg The average overspend
estimated from transactions matched to redemptions. 32.
overspend_frac_cat_avg The fraction of consumers who overspend
averaged by provider category. This quantity is, for example,
measured from data entered by providers. 33. overspend_avg_est
Estimated average overspend is calculated for example by:
overspend_avg_est = matched_redemption_overspend_avg *
overspend_frac_cat_avg 34. overspend_avg_best A "best estimate" of
the average overspend and is, in some examples, either
overspend_avg or overspend_avg_est. This metric is used in the
calculation of other metrics, such as the overspend revenue. The
rules to determine which one to use, in some examples, are as
follows: 1 If overspend_avg_est cannot be computed (usually because
there are no matched redemptions), use overspend_avg 2 Else if
overspend_avg cannot be computed (usually because the provider did
not track this number), or if overspend_avg/SE (overspend_avg)
<1 and overspend_avg_est/SE (overspend_avg_est) >1, then use
overspend_avg_est. Here SE(x) is the standard error of x. 3 Else,
use overspend_avg. 35. ret_fraction_new Fraction of new/lapsed
customers who return. 36. ret_freq_new Return frequency of
new/lapsed Groupon customers. The return frequency is computed, for
example, using a maximum likelihood estimate with the assumption
that the number of return visits by a customer follows a Poisson
distribution. 37. ret_freq_new_ret_only Return frequency of
new/lapsed Groupon customers with observed return visits. 38.
avg_spend_ret_new Average spend of new/lapsed Groupon customers on
return visits. 39. ret_fraction_all_new Return fraction of all
new/lapsed customers, both Groupon and non-Groupon. 40.
ret_freq_all_new Return frequency of all new/lapsed customers. 41.
ret_freq_all_new_ret_only Return frequency of all new/lapsed
customers with observed return visits. 42. avg_spend_ret_all_new
Average spend of all new/lapsed customers on return visits. 43.
ret_fraction_new_est Estimated example return fraction of
new/lapsed Groupon customers. For example, can be defined as 0.7 *
ret_fraction_all_new. 44. ret_freq_new_est Estimated example return
frequency of new/lapsed Groupon customers. Currently defined, for
example, as 1.0 * ret_freq_all_new. 45. ret_freq_new_ret_only_est
Estimated return frequency of new/lapsed Groupon customers with
observed return visits. Currently defined, for example, as 0.46 *
ret_freq_all_new_ret_only. 46. avg_spend_ret_new_est Estimated
average spend of new/lapsed Groupon customers on return visits.
Currently defined, for example, as 0.8 * avg_spend_ret_all_new. 47.
ret_fraction_new_best A "best estimate" return fraction of
new/lapsed Groupon customers. Is it either ret_fraction_new or
ret_fraction_new_est. The rules to determine which version to use
are the Same as, in some examples, overspend_avg_best. 48.
ret_freq_new_ret_only_best Same as, in some examples,
ret_fraction_new_best but for return frequency of customers with
observed return visits. 49. avg_spend_ret_new_best Same as, in some
examples, ret_fraction_new_best but for return average spend. 50.
num_ret_vst_td_new Number of return visits to-date by new/lapsed
Groupon customers. Defined as, in some examples: num_ret_vst_td_new
= num_cstmr_redeemed_td * new_cstmr_fraction *
ret_fraction_new_best * ret_freq_new_best * nday/365 Here nday is
the average number of days since redemption averaged over all
Groupon customers. 51. num_ret_cstmr_td_new Number of return
customers to-date by new/lapsed Groupon customers. Defined as, for
example: num_ret_cstmr_td_new = num_cstmr_redeemed_td *
new_cstmr_fraction * ret_fraction_new_best 52. num_email_mkt_vst_td
Number of email marketing visits to-date.
53. num_email_mkt_vst_proj Number of email marketing visits
projected. 54. avg_spend_email_mk Average spend on email marketing
visits. 55. rev groupon_campaign Total revenue from Groupon
campaigns. Estimated based on the number of "collected" coupons and
the unit_buy_price with a correction for the credit card
transaction fee. This may, in some examples, be different from the
actual amount paid to the provider by Groupon. 56. rev email_mkt_td
Revenue to-date from email marketing visits. 57. rev email_mkt_proj
Projected revenue from email marketing visits. 58. rev overspend_td
Overspend revenue to-date from all Groupon customers. Defined as,
in some examples: rev_overspend_td = num_coupons_redeemed_td *
overspend_avg_best 59. rev overspend_proj This is the sum of the
total overspend revenue from expired campaigns and the projected
overspend revenue from active campaigns. The overspend revenue of
expired campaigns is computed the same way as overspend revenue
to-date. The projected overspend revenue is (number of projected
redemptions) * (overspend_avg_best). 60. rev overspend_td_new
Overspend revenue to-date from new/lapsed Groupon customers.
Defined as, in some examples: rev_overspend_td_new = rev
overspend_td * new_cstmr_fraction 61. rev overspend_proj_new
Projected Overspend revenue from new/lapsed Groupon customers.
Defined as, in some examples: rev_overspend_proj_new = rev
overspend_proj * new_cstmr_fraction 62. rev_ret_td_new Return
visits revenue to-date from new/lapsed Groupon customers. Defined
as, in some examples: rev_ret_td_new = num_ret_vst_td_new *
avg_spend_ret_new_best 63. rev ret_proj_new Projected Return visits
revenue from new/lapsed Groupon customers. Defined as, in some
examples: rev ret_proj_new = num_coupons_redeemed_proj *
ret_fraction_new_best * ret_freq_new_ret_only_best *
avg_spend_ret_new_best * new_cstmr_fraction 64. rev tot_td Total
revenue to-date. Defined as, in some examples: rev tot_td =
rev_groupon_campaign + rev overspend_td + rev_ret_td_new + rev
email_mkt_td 65. rev tot_proj Projected total revenue. Defined as,
in some examples: rev tot_proj = rev_groupon_campaign + rev
overspend_proj + rev_ret_proj_new + rev email_mkt_proj 66.
cog_email_mkt_td Cost of goods to-date of email marketing visits.
67. cog_email_mkt_proj cog_email_mkt_proj 68. cog_redemptions_td
Groupon redemption cost of goods to-date. Defined as, in some
examples: cog_redemptions_td = num_coupons_redeemed_td * cog_pct *
(unit_value_avg + overspend_avg_best) 69. cog_redemptions_proj
Projected Groupon redemption cost of goods to- date. Defined as, in
some examples: cog_redemptions_proj = num_coupons_redeemed_proj *
cog_pct * (unit_value_avg + overspend_avg_best) 70.
cog_redemptions_td_new Groupon redemption cost of goods to-date of
new/lapsed customers. Defined as, in some examples:
cog_redemptions_td_new = cog_redemptions_td * new_cstmr_fraction
71. cog_redemptions_proj_new Projected Groupon redemption cost of
goods of new/lapsed customers. Defined as, in some examples:
cog_redemptions_proj_new = cog_redemptions_proj *
new_cstmr_fraction 72. cog_discount_provided_td_existing Discount
provided to existing customers in Groupon campaign to-date. Defined
as, in some examples: cog_discount_provided_td_existing =
existing_cstmr_fraction * num_coupons_redeemed_td *
[unit_value_avg- (unit_buy_price_avg-unit_price_avg * cc_fee_pct)]
73. cog_discount_provided_proj_existing Discount provided to
existing customers in Groupon campaign projected. Defined as, in
some examples: cog_discount_provided_td_existing =
existing_cstmr_fraction * num_coupons_redeemed_proj *
[unit_value_avg- (unit_buy_price_avg-unit_price_avg * cc_fee_pct)]
74. cog_ret_td_new Cost of goods associated with return visits
to-date by new/lapsed Groupon customers. Defined as, in some
examples: cog_ret_td_new = rev_ret_td_new * cog_pct 75.
cog_ret_proj_new Cost of goods (projected) associated with return
visits by new/lapsed Groupon customers. Defined as, in some
examples: cog_ret_proj_new = rev ret_proj_new * cog_pct 76.
cog_tot_td Total cost of goods to-date. Defined as, in some
examples: cog_tot_td = cog_redemptions_td + cog_ret_td_new 77.
cog_tot_proj Total cost of goods projected. Defined as, in some
examples: cog_tot_proj = cog_redemptions_proj + cog_ret_proj_new
78. provider_profit_td Total provider profit to-date. Defined as,
in some examples: provider_profit_td = rev_tot_td-cog_tot_td 79.
provider_profit_proj Total provider profit projected. Defined as,
in some examples: provider_profit_proj = rev tot_proj-cog_tot_proj
80. tax_pct Sales tax percentage 81. num_email_impressions_featured
Number of email impressions in the feature position 82.
invoiced_groupon_campaign Total invoiced payments for the Groupon
campaign 83. payments_groupon_campaign Total payments for the
Groupon campaign 84. payments_groupon_campaign_best Either rev
groupon_campaign or payments_groupon_campaign depending on the
payments data source 85. invoiced_groupon_campaign_best Either
rev_groupon_campaign or invoiced_groupon_campaign depending on the
payments data source
[0129] As is shown in block 712, an ROI prediction model may be
trained using historical calculated ROI, ROI components and related
metrics. In some example embodiments, the ROI prediction model may
take the form of a support vector machine, decision tree learning,
association rule learning, artificial neural networking, inductive
logic programming, clustering, and/or the like.
[0130] Using the previously computed metrics in block 710 (and
related ROI and ROI components) a dataset may be generated that is
configured to train and/or test the ROI prediction model to
approximate ROI and/or ROI components based on certain provider
attributes. In some example embodiments, the training may include
classifying metrics, provider attributes or the like as effecting
or otherwise informative of an ROI value or a particular ROI
component. In other example embodiments, the ROI prediction model
may additionally or alternatively be trained so that it may
estimate a value of a particular metric for a provider based on
that providers stated attributes. As such, the trained ROI
prediction model may provide a predictive algorithm that is
operable to predict ROI and/or ROI components using input provider
attributes.
[0131] As is shown in block 714, one or more attributes may be
received for a given provider. In some examples, the given provider
may take the form of a current provider that is running a
promotion, a provider interested in a running a promotion and/or
the like. As such, in order to provide a predicted ROI and/or ROI
components, the provider may provide attributes such as, size,
category, location, past deal history, sales data, advertising
data, current metrics and/or the like.
[0132] As is shown in block 716, a predicted ROI and/or predicted
ROI components (such as is shown with reference to FIG. 3a) may be
calculated for the provider based on the attributes and the ROI
prediction model. In some example embodiments, the one or more
attributes may be provided to the ROI prediction model. The ROI
prediction model then may compare the receive attributes to its
trained dataset, the comparison generating a prediction of ROI for
the given provider based on ROI metrics for historical providers
having similar attributes. The predicted ROI and/or predicated ROI
components may then be provided for display via the impact report,
such as is shown with reference to FIG. 3e.
Payment System Operations
[0133] In addition to providing a ROI system that generates a
real-time ROI as output for one or more promotions, in some
embodiments the unified payment and ROI system additionally
determines a payment structure for distributing revenue received
from the sale of promotions to customers. The system supports a
perpetual contractual arrangement with many feature periods. In
this regard, a feature period may comprise a time period during
which a promotion is active (and after which vouchers for the
promotion expire). Accordingly, multiple feature periods may be
used for each promotion. Payment is based on inventory sold during
each feature period, rather than merchandising. The system further
supports a limited contract. The system may regularly pay a
merchant what is due the merchant in total using a payment
schedule, rather than sending lots of payments on a seemingly
random schedule.
[0134] As part of the this process, when vouchers for a promotion
are sold in a particular period of time, the promotion and
marketing service may hold back a certain configurable percentage
of the revenue received from selling the vouchers (such as 20%), so
that there's a buffer in the bank. This buffer can be used to
protect the promotion and marketing service from the monetary risk
exposure when customers may seek to request a refund of their
voucher purchase. Although a single refund request may easily be
handled by a promotion and marketing service, hundreds or thousands
of refund requests may be difficult to fulfill without having large
amounts of money in reserve. Moreover, there is no guarantee that
merchants will refund their portion of the revenue to the promotion
and marketing service. Accordingly, without a holdback amount, the
promotion and marketing service would have significant monetary
risk exposure. Accordingly, the unified payment and ROI system
maintains a holdback amount that is only distributed to merchants
after the relevant refund exposure has ended. In this regard, when
vouchers expire, any remaining revenue from the sale of the
vouchers can be distributed to the merchant. The holdback amount
may depend on whether the level in the buffer is static or dynamic,
and the level may be based on the status of the underlying vouchers
related to the buffer (i.e., whether they have expired).
[0135] This payment mechanism is flexible, simple, and easy to
explain to merchants, applicable to various products, and accounts
for risk (refund, out-of-business, bad merchants, fraud). The
payment mechanism is as attractive to merchants as the current
payment grid, takes advantage of automation (transparent Merchant
Center), provides a backwards compatible architecture, accommodates
promotions with no predetermined ending, is cash flow neutral
(e.g., if possible, but merchant benefits may outweigh), and
provides the ability to pay for multiple promotions in a single
transaction.
[0136] The payment mechanism may make initial calculation
assumptions. For instance, initial payments may be disbursed to
merchants a predetermined time (e.g., seven days) after the start
of a feature period; payment for subsequently purchased vouchers
may be forwarded on a recurring basis (e.g., the 1st and 16th of
each month); and additionally, holdback payments for expired
vouchers may be paid in the first recurring payment date after
expiration of the vouchers (when these assumptions are not true,
the average days until complete payment may be higher).
Accordingly, with vouchers expiring after 180 days, 80% of the
merchant share of the voucher revenue will be received by the
merchant with only nominal delay, and 20% of the merchant share
will be received by the merchant upon expiration of the vouchers
(i.e., after 180 days), which results in complete payment for each
voucher in an average of 36 days; with vouchers expiring after 90
days, there will be complete payment for each voucher in an average
of 18 days. Accordingly, the payment mechanism provides business
benefits, including: better merchant experience, the removal of
volume caps on a deal meter, the ability to have a perpetual
contract (with multiple feature periods), inventory-based payment
rather than merchandising (feature periods), applicability to new
products, and greater consistency of payments to merchants (rather
than sending lots of payments on a seemingly random schedule).
[0137] In accordance with the above-described payment system, FIG.
7b illustrates operations describing an example mechanism by which
the unified payment and ROI system distributes, to a merchant,
revenue from sales of a promotion. In operation 718, the payment
system receives a notice of sale of a promotion, the notice
including a sale amount. In some embodiments, this notice includes
a total number of vouchers sold, and/or the total revenue received
from sales of the vouchers. In operation 720, the payment system
calculates, based on the sale amount, a holdback amount to hold in
reserve, and a payment amount to distribute to a merchant. The
holdback calculation is updated and documented to reflect inclusion
of any new terms and the calculation reflects the scope of
deployment of the new terms. In this regard, the holdback amount
and the payment amount are based on one or more of a configurable
percentage of the sale amount, an expiration date of the promotion,
a number of unredeemed vouchers, a length of a redemption period, a
velocity of redemptions, a velocity of refunds, industry trends, a
category of promotion, and previous performance of the
merchant.
[0138] In operation 722, the payment system generates a payment
schedule for transferring funds to the merchant. For each voucher,
the payment schedule may indicate a date on which to transfer the
payment amount and a date on which to process the holdback amount.
The date on which to process the holdback amount may be based on
the expiration date of the promotion. In one embodiment, an initial
payment may be scheduled for a configurable number of days
following the start of the feature period. Thereafter, payments may
be forwarded on a recurring basis (e.g., the 1st and 16th of each
month).
[0139] In some embodiments, after the voucher's promotional value
expires, the holdback amount (e.g., the remaining twenty percent)
may be processed and any remaining balance is included with the
next recurring payment. In this regard, processing the holdback
amount includes determining an amount of money returned to
consumers to fulfill refund requests, and, subtracting this refund
amount from the holdback amount to calculate a remaining balance
due to the merchant.
[0140] For example, each scheduled payment amount may consist of
eighty percent (80%) of the total amount due to the merchant from
the previous feature period. The merchant is informed that, for
example, seven days after the merchant's campaign feature period
begins, the merchant may expect to receive a first payment for 80%
of sales. Then, twice a month, the merchant will receive a payment
for 80% of any additional sales for the period plus any remaining
balance (20% for each period, less any other refunds) due as a
result of the expiration of vouchers within that period.
[0141] In one embodiment, in operation 724 the payment system may
initiate a transfer of funds according to the payment schedule
(note: the dashed lines indicate that this operation is optional).
In this regard, the system may initiate a transfer of the payment
amount to the merchant based on the payment schedule. Similarly,
the payment system may initiate a transfer of the remaining balance
to the merchant based on the payment schedule.
System Components
[0142] FIG. 8 shows configuration 800 of the unified payment and
ROI system 802. The unified payment system 802 may be deployed as a
general computer system used in a networked deployment. The unified
payment system 802 may represent a remote server or local mobile
device of the consumer. In other words, the unified payment logic
may be executed by one or more processors locally or remotely
located. The computer system may operate as a server or as a client
consumer computer in a server-client consumer network environment,
or as a peer computer system in a peer-to-peer (or distributed)
network environment. The computer system may also be implemented as
or incorporated into various devices, such as a personal computer
(PC), a tablet PC, a set-top box (STB), a personal digital
assistant (PDA), a mobile device, a palmtop computer, a laptop
computer, a desktop computer, a communications device, a wireless
telephone, a land-line telephone, a control system, a camera, a
scanner, a facsimile machine, a printer, a pager, a personal
trusted device, a web appliance, a network router, switch or
bridge, or any other machine capable of executing a set of
instructions 810 (sequential or otherwise) that specify actions to
be taken by that machine. In a particular embodiment, the computer
system may be implemented using electronic devices that provide
voice, video or data communication. Further, while a single
computer system may be illustrated, the term "system" shall also be
taken to include any collection of systems or sub-systems that
individually or jointly execute a set, or multiple sets, of
instructions to perform one or more computer functions.
[0143] The computer system may include a processor 803, such as, a
central processing unit (CPU), a graphics processing unit (GPU), or
both. The processor may be a component in a variety of systems. For
example, the processor may be part of a standard personal computer
or a workstation. The processor may be one or more general
processors, digital signal processors, application specific
integrated circuits, field programmable gate arrays, servers,
networks, digital circuits, analog circuits, combinations thereof,
or other now known or later developed devices for analyzing and
processing data. The processors and memories 804 discussed herein,
as well as the claims below, may be embodied in and implemented in
one or multiple physical chips or circuit combinations. The
processor 803 may execute a software program 810, such as code
generated manually (i.e., programmed).
[0144] The computer system 802 may include a memory 804 that can
communicate via a bus. The memory 804 may be a main memory, a
static memory, or a dynamic memory. The memory 804 may include, but
may not be limited to computer readable storage media such as
various types of volatile and non-volatile storage media, including
but not limited to random access memory, read-only memory,
programmable read-only memory, electrically programmable read-only
memory, electrically erasable read-only memory, flash memory,
magnetic tape or disk, optical media and the like. In one case, the
memory 804 may include a cache or random access memory for the
processor. Alternatively or in addition, the memory 804 may be
separate from the processor, such as a cache memory of a processor,
the memory, or other memory. The memory 804 may be an external
storage device or database for storing data. Examples may include a
hard drive, compact disc ("CD"), digital video disc ("DVD"), memory
card, memory stick, floppy disc, universal serial bus ("USB")
memory device, or any other device operative to store data. The
memory 804 may be operable to store instructions executable by the
processor. The functions, acts or tasks illustrated in the figures
or described herein may be performed by the programmed processor
executing the instructions stored in the memory. The functions,
acts or tasks may be independent of the particular type of
instructions set, storage media, processor or processing strategy
and may be performed by software, hardware, integrated circuits,
firm-ware, micro-code and the like, operating alone or in
combination. Likewise, processing strategies may include
multiprocessing, multitasking, parallel processing and the
like.
[0145] The computer system may further include a display 812, such
as a liquid crystal display (LCD), an organic light emitting diode
(OLED), a flat panel display, a solid state display, a cathode ray
tube (CRT), a projector, a printer or other now known or later
developed display device for outputting determined information. The
display 812 may act as an interface for the consumer to see the
functioning of the processor, or specifically as an interface with
the software stored in the memory or in the drive unit.
[0146] Additionally, the computer system may include an input
device 814 configured to allow a consumer to interact with any of
the components of system. The input device may be a number pad, a
keyboard, or a cursor control device, such as a mouse, or a
joystick, touch screen display, remote control or any other device
operative to interact with the system.
[0147] The computer system may also include a disk or optical drive
unit. The disk drive unit 808 may include a computer-readable
medium 806 in which one or more sets of instructions, e.g.
software, can be embedded. Further, the instructions may perform
one or more of the methods or logic as described herein. The
instructions may reside completely, or at least partially, within
the memory 804 and/or within the processor during execution by the
computer system. The memory 804 and the processor also may include
computer-readable media as discussed above.
[0148] The present disclosure contemplates a computer-readable
medium 806 that includes instructions or receives and executes
instructions responsive to a propagated signal, so that a device
connected to a network 816 may communicate voice, video, audio,
images or any other data over the network 816. Further, the
instructions may be transmitted or received over the network 816
via a communication interface 818. The communication interface may
be a part of the processor or may be a separate component. The
communication interface may be created in software or may be a
physical connection in hardware. The communication interface may be
configured to connect with a network, external media, the display,
or any other components in system, or combinations thereof. The
connection with the network may be a physical connection, such as a
wired Ethernet connection or may be established wirelessly as
discussed below. Likewise, the additional connections with other
components of the system 802 may be physical connections or may be
established wirelessly. In the case of a service provider server,
the service provider server may communicate with consumers through
the communication interface.
[0149] The network may include wired networks, wireless networks,
or combinations thereof. The wireless network may be a cellular
telephone network, an 802.11, 802.16, 802.20, or WiMax network.
Further, the network may be a public network, such as the Internet,
a private network, such as an intranet, or combinations thereof,
and may utilize a variety of networking protocols now available or
later developed including, but not limited to TCP/IP based
networking protocols.
[0150] The computer-readable medium 806 may be a single medium, or
the computer-readable medium 806 may be a single medium or multiple
media, such as a centralized or distributed database, and/or
associated caches and servers that store one or more sets of
instructions. The term "computer-readable medium" may also include
any medium that may be capable of storing, encoding or carrying a
set of instructions for execution by a processor or that may cause
a computer system to perform any one or more of the methods or
operations disclosed herein.
[0151] The computer-readable medium 806 may include a solid-state
memory such as a memory card or other package that houses one or
more non-volatile read-only memories. The computer-readable medium
806 also may be a random access memory or other volatile
re-writable memory. Additionally, the computer-readable medium 806
may include a magneto-optical or optical medium, such as a disk or
tapes or other storage device to capture carrier wave signals such
as a signal communicated over a transmission medium. A digital file
attachment to an email or other self-contained information archive
or set of archives may be considered a distribution medium that may
be a tangible storage medium. The computer-readable medium 806 may
comprise a tangible storage medium. The computer-readable medium
806 may comprise a non-transitory medium in that it cannot be
construed to refer to carrier signals or propagating waves.
Accordingly, the disclosure may be considered to include any one or
more of a computer-readable medium or a distribution medium and
other equivalents and successor media, in which data or
instructions may be stored.
[0152] Alternatively or in addition, dedicated hardware
implementations, such as application specific integrated circuits,
programmable logic arrays and other hardware devices, may be
constructed to implement one or more of the methods described
herein. Applications that may include the apparatus and systems of
various embodiments may broadly include a variety of electronic and
computer systems. One or more embodiments described herein may
implement functions using two or more specific interconnected
hardware modules or devices with related control and data signals
that may be communicated between and through the modules, or as
portions of an application-specific integrated circuit.
Accordingly, the present system may encompass software, firmware,
and hardware implementations.
[0153] The methods described herein may be implemented by software
programs executable by a computer system. Further, implementations
may include distributed processing, component/object distributed
processing, and parallel processing. Alternatively or in addition,
virtual computer system processing maybe constructed to implement
one or more of the methods or functionality as described
herein.
[0154] Although components and functions are described that may be
implemented in particular embodiments with reference to particular
standards and protocols, the components and functions are not
limited to such standards and protocols. For example, standards for
Internet and other packet switched network transmission (e.g.,
TCP/IP, UDP/IP, HTML, and HTTP) represent examples of the state of
the art. Such standards are periodically superseded by faster or
more efficient equivalents having essentially the same functions.
Accordingly, replacement standards and protocols having the same or
similar functions as those disclosed herein are considered
equivalents thereof.
[0155] The illustrations described herein are intended to provide a
general understanding of the structure of various embodiments. The
illustrations are not intended to serve as a complete description
of all of the elements and features of apparatus, processors, and
systems that utilize the structures or methods described herein.
Many other embodiments may be apparent to those of skill in the art
upon reviewing the disclosure. Other embodiments may be utilized
and derived from the disclosure, such that structural and logical
substitutions and changes may be made without departing from the
scope of the disclosure. Additionally, the illustrations are merely
representational and may not be drawn to scale. Certain proportions
within the illustrations may be exaggerated, while other
proportions may be minimized. Accordingly, the disclosure and the
figures are to be regarded as illustrative rather than
restrictive.
[0156] The above disclosed subject matter is to be considered
illustrative, and not restrictive, and the appended claims are
intended to cover all such modifications, enhancements, and other
embodiments, which fall within the true spirit and scope of the
description. Thus, to the maximum extent allowed by law, the scope
is to be determined by the broadest permissible interpretation of
the following claims and their equivalents, and shall not be
restricted or limited by the foregoing detailed description.
* * * * *
References