U.S. patent application number 12/954146 was filed with the patent office on 2011-06-30 for customer mapping using mobile device with an accelerometer.
Invention is credited to Mark Carlson, Patrick Faith, Ayman Hammad.
Application Number | 20110161136 12/954146 |
Document ID | / |
Family ID | 44188152 |
Filed Date | 2011-06-30 |
United States Patent
Application |
20110161136 |
Kind Code |
A1 |
Faith; Patrick ; et
al. |
June 30, 2011 |
CUSTOMER MAPPING USING MOBILE DEVICE WITH AN ACCELEROMETER
Abstract
Methods, devices, and systems are presented for detecting where
shoppers in a store stop, turn, and look from accelerometers in
their own smart phones or other mobile devices. These movement
events can be correlated with merchandise on their receipts as well
as the movement events and merchandise on the receipts of other
users so that a map of the store's wares can be generated. The map
can be used to inform manufacturers where their merchandise is
stocked in the store or to advertise to shoppers as they browse the
store.
Inventors: |
Faith; Patrick; (Pleasanton,
CA) ; Carlson; Mark; (Half Moon Bay, CA) ;
Hammad; Ayman; (Pleasanton, CA) |
Family ID: |
44188152 |
Appl. No.: |
12/954146 |
Filed: |
November 24, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61264983 |
Nov 30, 2009 |
|
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|
61264543 |
Nov 25, 2009 |
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Current U.S.
Class: |
705/7.29 ;
705/14.1; 705/14.58 |
Current CPC
Class: |
G06Q 30/0261 20130101;
H04N 21/812 20130101; G06F 21/00 20130101; G06Q 30/0201 20130101;
H04N 21/42204 20130101; H04W 12/06 20130101; G06Q 30/0207 20130101;
G06K 9/00335 20130101; H04L 63/0861 20130101; H04W 4/18
20130101 |
Class at
Publication: |
705/7.29 ;
705/14.1; 705/14.58 |
International
Class: |
G06Q 10/00 20060101
G06Q010/00; G06Q 30/00 20060101 G06Q030/00 |
Claims
1. A method comprising: receiving time series velocity data or time
series orientation data of a mobile device of a user; determining a
movement event from the time series velocity data or time series
orientation data; obtaining a location at a store of the mobile
device during the movement event; correlating the location with
merchandise at the store; performing further processing using the
correlated location and merchandise.
2. The method of claim 1 wherein the movement event includes a stop
and turn event.
3. The method of claim 1 further comprising: sending a coupon or
advertisement pertaining to the merchandise to the mobile
device.
4. The method of claim 3 wherein the sending of the coupon or
advertisement occurs while the user is still at the location.
5. The method of claim 3 wherein the sending of the coupon or
advertisement uses a short message service (SMS) format or a
multimedia messaging service (MMS) format.
6. The method of claim 1 further comprising: sending a message to
the store based on the movement event, thereby alerting the store
to a user's possible interest in the merchandise.
7. The method of claim 1 further comprising: receiving a list of
merchandise purchased by the user; and confirming an item of
merchandise on the list is associated with the location.
8. The method of claim 1 wherein the time series velocity or time
series orientation data is from the user bending over, stooping, or
crouching.
9. The method of claim 1 wherein the receiving includes receiving
both time series velocity data and time series orientation data of
a mobile device of a user.
10. The method of claim 1 further comprising: building a
merchandise map of the store based on multiple correlated movement
event and merchandise locations.
11. The method of claim 1 further comprising: moving the
merchandise to a different location at the store based on a number
of correlated location correlations.
12. The method of claim 1 wherein the location is inside a
store.
13. The method of claim 1 wherein the operations are performed in
the order shown.
14. The method of claim 1 wherein each operation is performed by
the processor operatively coupled to a memory.
15. A machine-readable storage medium embodying information
indicative of instructions for causing one or more machines to
perform the operations of claim 1.
16. A computer system executing instructions in a computer program,
the computer program instructions comprising program code for
performing the operations of claim 1.
17. A method comprising: receiving movement event locations of
mobile devices of users; receiving a list of items purchased from a
store by each of the users; correlating movement event locations of
some of the users with a common item of merchandise on the users'
purchase lists; and performing further processing using the
correlated movement event locations and merchandise.
18. The method of claim 17 further comprising: receiving time
series velocity data or time series orientation data of the mobile
devices; determining movement events based on the time series
velocity data or time series orientation data; and obtaining the
movement event locations using the movement events.
19. A method comprising: providing an advertisement for merchandise
to a user; receiving velocity and orientation data of a mobile
device of the user; determining a movement event from the velocity
and orientation data; obtaining a location of the mobile device at
the movement event; correlating the location with the advertised
merchandise; and performing further processing using the
correlation.
20. The method of claim 19 further comprising: sending a further
advertisement or coupon for the merchandise to the mobile device
based on the correlation.
Description
CROSS-REFERENCES TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 61/264,543, filed Nov. 25, 2009 (Attorney Docket
No. 016222-056900U5), and U.S. Provisional Application No.
61/264,983, filed Nov. 30, 2009 (Attorney Docket No.
016222-057000US). The applications above are hereby incorporated by
reference in their entireties for all purposes.
BACKGROUND
[0002] 1. Field of the Art
[0003] Generally, systems and methods are disclosed for determining
customers' various interests in items in stores by analyzing the
physical movements of the customers. More specifically, methods and
systems are disclosed for correlating customers' movements as
measured by accelerometers in their mobile phones with items on
store shelves.
[0004] 2. Discussion of the Related Art
[0005] Cellular phones, portable music players, handheld global
positioning system (GPS) devices, personal digital assistants, and
other mobile devices have become popular among the general public.
Some of the functions of these devices include mapping a user's
current location and offering directions to where he or she wishes
to go, connecting the user to the Internet, and/or store calendar
reminders and shopping lists. Entertainment, such as songs, videos,
and video games, are playable on some mobile devices so that a user
does not get bored while waiting for others. So handy are many of
the mobile devices that people often carry them around wherever
they go.
[0006] Some mobile devices include integrated accelerometers. The
accelerometers can be part of an inertial measurement unit (IMU)
within the housing of a mobile device. An IMU that is fed with
periodic calibrations from global positioning system (GPS)
measurements has been found to be an effective way to measure
position. Accelerometers can be used as an internal input device
for the mobile device itself. For example, a drawing application on
the mobile device can be shaken to clear its screen, much like a
mechanical Etch A Sketch.RTM. toy. With accelerometers, a mobile
device can be used as an input device for other devices. For
example, a mobile device can act as a tennis racket grip for a
video game depicting virtual tennis. Accelerometers in smart
phones, such the Apple iPhone and Google Android devices, have been
creatively applied to measure user's intentional movements of the
smart phones for games.
[0007] Although video games and traditional IMU functions are
natural uses for accelerometers in mobile devices, the inventors of
the present application recognize that the accelerometers carried
around by people in their smart phones may be advantageous in
other, nontraditional areas. Particularly, mining accelerometer
data, which might be continuously generated by a smart phone
anyway, for a shopper's movements while browsing a store and when
the shopper is not necessarily focusing on the mobile device may be
helpful.
BRIEF SUMMARY
[0008] The present disclosure generally relates to methods,
devices, and systems for using accelerometers in mobile devices to
map where shoppers interests are inside a retail store. The
locations of interest, which can found by measuring `stop and
turns` or other physical patterns with accelerometers, can be
correlated with products on the store shelves or on the shoppers'
receipts. The locations of products on store shelves can then be
mapped with accuracy. The maps of products on store shelves can be
sold to product manufacturers, consumers, and even the stores
themselves.
[0009] If multiple shoppers have stopped at the same place in a
store aisle and they all have the same item on their receipts, then
it may be assumed that the item is stocked in the aisle location at
which they all stopped. The more shoppers for which this is the
case, the more likely that the item is indeed at the particular
aisle location. Over the course of a week, with thousands of
shoppers going into the store, such as a supermarket, department
store, or other high volume retail store, fairly good probabilities
can be assigned to locations of merchandise in the stores.
[0010] The locations of items on store shelves can be determined by
an entity without the labor of having to go into the stores
themselves. Many items can be mapped with more accuracy over time
as more shoppers shop the stores. With the resulting maps in some
embodiments, coupons can be texted to the users' mobile phones as
they pass by items. Complementary items can be advertised as
well.
[0011] An embodiment in accordance with the present disclosure
relates to a method of correlating merchandise location at a store.
The method includes receiving time series velocity data or time
series orientation data of a mobile device of a user, determining a
movement event, such as a stop and turn event, from the time series
velocity data or time series orientation data, obtaining a location
at a store of the mobile device during the movement event, and
correlating the location with merchandise at the store. The method
further includes performing further processing using the correlated
location and merchandise, such as sending a coupon or advertisement
pertaining to the merchandise to the mobile device in a short
message service (SMS) format or multimedia messaging service (MMS)
format.
[0012] The method can include sending a message to the store based
on the movement event, thereby alerting the store to a user's
possible interest in the merchandise.
[0013] An embodiment in accordance with the present disclosure
relates to a method of correlating movement events of shoppers with
items purchased by them. The method includes receiving movement
event locations of mobile devices of users, receiving a list of
items purchased from a store by each of the users, and correlating
movement event locations of some of the users with a common item of
merchandise on the users' purchase lists. The method further
includes performing further processing using the correlated
movement event locations and merchandise.
[0014] An embodiment in accordance with the present disclosure
relates to a method of correlating movement events of shoppers with
advertisements. The method includes providing an advertisement for
merchandise to a user, receiving velocity and orientation data of a
mobile device of the user, determining a movement event from the
velocity and orientation data, obtaining a location of the mobile
device at the movement event, and correlating the location with the
advertised merchandise. The method further includes performing
further processing using the correlation.
[0015] Other embodiments relate to machine-readable tangible
storage media and computer systems which employ or store
instructions for the methods described above.
[0016] A further understanding of the nature and the advantages of
the embodiments disclosed and suggested herein may be realized by
reference to the remaining portions of the specification and the
attached drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] FIG. 1 illustrates a "stop and turn" event of a shopper on a
store aisle in accordance with an embodiment.
[0018] FIG. 2A is a chart of time series velocity data in
accordance with an embodiment.
[0019] FIG. 2B is a chart of time series orientation data in
accordance with an embodiment.
[0020] FIG. 3 illustrates a receipt in accordance with an
embodiment.
[0021] FIG. 4 illustrates a store map in accordance with an
embodiment.
[0022] FIG. 5 illustrates a store map in accordance with an
embodiment.
[0023] FIG. 6 illustrates MMS coupons in accordance with an
embodiment.
[0024] FIG. 7 is a flowchart illustrating a process in accordance
with an embodiment.
[0025] FIG. 8 is a flowchart illustrating a process in accordance
with an embodiment.
[0026] FIG. 9 is a flowchart illustrating a process in accordance
with an embodiment.
[0027] FIG. 10 shows a block diagram of a portable consumer device
in accordance with an embodiment.
[0028] FIG. 11 shows a block diagram of an exemplary computer
apparatus that can be used in some embodiments.
[0029] The figures will now be used to illustrate different
embodiments in accordance with the invention. The figures are
specific examples of embodiments and should not be interpreted as
limiting embodiments, but rather exemplary forms and
procedures.
DETAILED DESCRIPTION
[0030] Generally, the present disclosure relates to methods,
devices, and systems for using accelerometers in people's smart
phones to detect where they stop in a store, correlating those
locations with merchandise or advertisements on their receipts, and
then producing maps of the locations of merchandise or
advertisements in the store. The maps can be used to advertise
further, rearrange products for better placement, send coupons to
users who are passing by the same locations, and/or otherwise use
the location data.
[0031] Privacy, or at least the feeling of being tracked, can be a
concern to some people. Analyzing another's movements by using the
measurement devices and processing power within the trackee's own
personal electronics can be a further concern. Tracking user
movements in a store using the users' own smart phones may be
socially unacceptable in some contexts but socially acceptable in
others. Consent of the users may be paramount in what is considered
acceptable. Consent of the user can be established in many ways.
Users may voluntarily opt in to their movements being tracked in a
store for discounts, monetary awards, or the potential of winning a
sweepstakes. Because consent of minors may be potentially unnerving
to parents, tracking could be limited to certain groups of people,
such as adults who have opted in to a store-selected tracking
program.
[0032] Technical advantages of embodiments are manifold. The labor
of walking around and mapping stores is virtually free. Shoppers
are already there looking at items. They carry their own electronic
devices that measure, store, and transmit their locations. Shoppers
do not need to be provided with extra equipment, save a software
application that can read, send, and store the accelerometer data
on their device. Another advantage is that the attention of
real-world users is mapped. It is as if people's answers to a
survey are submitted through their actions and not merely through
their verbal (i.e., oral or written) responses. Shoppers can forget
that they are being tracked so that their movements are more
natural and psychologically close to movements of unaware shoppers.
Maps and other data can be sold to manufacturers or wholesalers
that are a great geographical distance from the mapped store. For
example, a manufacturer in Arkansas does not need to go visit a
store that sells its products in California to determine where its
items are placed. It can analyze the data from afar and negotiate
with the store for better positioning of its products (e.g., on end
caps as opposed to on a low shelf in middle of an aisle; near
complementary items as opposed to far away). The stores themselves
can look at the same data and optimize their placement of
high-profit items and advertisements. Consumers may look at maps of
store merchandise to determine the most popular merchandise in a
store. Much like `most popular products` lists on retail-sale web
sites, there can be a `most popular parts of a store` for
particular brick and mortar stores.
[0033] "Time series data" includes a set of data points for which
each data point corresponds to a time. Time series data may be
stored in chronological or any other order. The time periods
between respective data points may be equally spaced, such as that
collected by periodic sampling, or unequally spaced, such as that
collected by event driven sampling. An object's trajectory data
through space, having only position (e.g., x, y, and z location)
coordinates, is considered time series data because each coordinate
was derived from position data corresponding to a time at which an
object was at the corresponding position.
[0034] "Time series velocity data" includes time series data that
includes velocity or speed of an object. For example, data points
having the of the speed of a consumer walking through a store aisle
is time series velocity data.
[0035] "Time series orientation data" includes time series data
that includes angular orientation of an object. For example, data
points having the pitch, roll, and yaw of a mobile phone in the
pocket of consumer's jacket is time series orientation data.
[0036] A "movement event" an event in which a position, velocity,
and/or orientation of an object has changed significantly from an
otherwise normal course or where there is an abrupt change in
movement. For example, a movement event can include suddenly moving
toward the shelves in an aisle from a normal position of in the
center of an aisle. As another example, a movement event can
include an event in which the physical speed of a has halved,
quartered, etc. from a normal walking speed. A user may be slowing
to contemplate an item on a shelf. A movement event can include an
event in which the yaw of a phone has slewed over 90 degrees, 60
degrees, 45 degrees, 30 degrees, or less. A user may rotate to look
at an item on a shelf. A movement event can include events in which
a user is detected to bend over, stoop, or crouch. For example, a
user bending over could be detected by sensing that his phone's
velocity goes to zero and its orientation changes pitch by 60
degrees. A user crouching could be detected by sensing that his
phone's velocity goes to zero and its position is lowered by 1, 2,
3, or more feet.
[0037] A "stop and turn" is a movement event in which a user has
slowed down or stopped and has changed his or her orientation. This
can indicate that the user has stopped to look at something on a
store shelf or otherwise reveal that the user has focused on
something in the store. While the user's stop and turn may have
nothing to do with what is on a store shelf because the user may be
just tying his or her shoe, answering her cell phone, speaking with
a store employee, or other `false alarms,` a stop and turn event
correlated to the same location as stop and turn events of other
users can indicate a higher likelihood that the user is indeed
looking at something in the store. A "slow and turn" event is a
stop and turn event.
[0038] FIG. 1 illustrates a "stop and turn" event of a shopper on a
store aisle in accordance with an embodiment. In situation 100,
shopper 108 carries mobile device 116 in his hand 110. As he walks,
user 108 steps here and there, planting footsteps 112, and
supporting mobile device 116 through space described by trajectory
114.
[0039] Trajectory 114 can be described with respect to Euclidean,
orthogonal axes, x, y, and z. such as those shown as x axis 102, y
axis 104, and z axis 106. Other coordinate systems are, of course,
applicable as well. In addition to trajectory 114, the orientation
of the mobile device can be described by reference to pitch axis
118, roll axis 120, and yaw axis 122. Each of the components of
trajectory 114 or orientation can be saved as data series with
respect to time. For example, x-position data in inches can be
saved with respect to time in seconds.
[0040] Time series data, such as that describing trajectory 114, is
analyzed to detect stop and turn event 124. Exemplary stop and turn
event 124 includes an x-velocity going to zero (and negative for a
short bit) and a z-velocity that takes the phone to the side of an
aisle. Stop and turn event 124 may also be indicated by a change in
the yaw of mobile device 116 as shopper 108 turned to walk toward
the side of the aisle.
[0041] A location at the store of the mobile device during stop and
turn event 124 is analyzed in order to correlate it with
merchandise in the store aisle. In the exemplary embodiment, the
position of stop and turn event 124 is found to most closely match
that of position 128 on the store shelves. Merchandise 126 is known
to sit at position 128, so stop and turn event 124 is correlated
with merchandise 126. Because shopper 108 did not bend over, stoop,
or crouch, that may indicate that shopper 108 was indeed attracted
to merchandise 126 as opposed to merchandise on lower or higher
shelves.
[0042] Alternatively or in conjunction with shopper 108's apparent
interest in merchandise 126 is his apparent interest in
advertisement 130. Advertisement 130, a `SALE!` sign, may have
attracted shopper 108 to come look at merchandise 126. Stop and
turn event 124 can be correlated with the placement of
advertisement 130. If many people are attracted to the sign, even
if the store shelves are bare of merchandise 126, then it may
indicate that shoppers' attentions are attracted to the
advertisement and that the advertisement is effective in that way.
Conversely, if no shoppers' attentions are attracted to the
advertisement, that may indicate that the advertisement fails to
grab viewers' attentions.
[0043] FIG. 2A is a chart of time series velocity data in
accordance with an embodiment. Speed 232 is plotted against time
234. Accelerometer data from three accelerometers aligned
orthogonally with one another is integrated and combined to plot
curve 236 of the time series data. Curve 236 stretches from when an
owner of the mobile device in which the accelerometers are located
walks down and aisle and sees a product he likes to when he resumes
walking again.
[0044] During time period 240, the owner of the mobile device walks
down a store aisle at a regular, slow pace. Curve 236 is at a
fairly constant, steady speed. During time period 242, the owner
slows to look at an item on a store shelf. The speed drops from a
normal slow pace to a plodding, slower pace as the owner's
attention is consumed and he saunters over to the shelf. During
time period 244, the owner of the mobile device is stopped in front
of a store shelf. The speed of the mobile phone is zero as its
owner contemplates merchandise on the shelf that caught his eye.
During time period 246, the owner scoots a few feet to the left or
right and scans for similar products, competing products, prices,
etc. The curve indicates that the owner is fidgeting around. During
time period 248, the owner resumes walking down the aisle at a
normal pace. The curve marches back up to its previous, normal slow
pace.
[0045] As time periods 242, 244, and 246 on the figure indicate,
the user has slowed and stopped as opposed to the normal pace of
time periods 240 and 248. In this embodiment, the time series data
indicates a stop event.
[0046] FIG. 2B is a chart of time series orientation data in
accordance with an embodiment. Yaw orientation 262 of the device is
plotted against time 234. Accelerometer data and/or gyroscopic data
is combined to plot curve 266 of the time series data. Curve 266
stretches for the same duration as curve 236 (FIG. 2A).
[0047] During time period 250, the owner of the mobile device is
facing down the aisle as indicated by an almost zero yaw angle.
During time period 252, the owner turns toward an item on a shelf
that has attracted his attention. Curve 266 increases to about
60-90 degrees as the owner's body turns. During time period 254,
the owner looks back at the shelves he just passed to scan for
similar products, competing products, price tags, etc. The curve
increases past 90 degrees to about 135 degrees as the owner's body
turns even more. During time period 256, the owner looks ahead and
starts scooting forward a little during his forward scan of the
shelves and price tags. The curve falls back down to around 60
degrees. During time period 258, the owner turns back toward the
center of the aisle and starts walking. Curve 266 shows a negative
yaw that goes back to zero as the user gets back to walking down
the center of the store aisle.
[0048] As time periods 252, 254, and 256 on the figure indicate,
the user has turned from his normal orientation of facing down the
aisle. In this embodiment, the data in these time periods indicate
a turn event.
[0049] Analyzing both the velocity data of FIG. 2A and the
orientation data of FIG. 2B, stop and turn event 238 is determined.
The position of the mobile device during stop and turn event 238
can be obtained from the mobile device's GPS antenna (with help
from a differential GPS antenna if available) and then recorded.
The position can be correlated with merchandise whose positions are
already known on the store shelves, or the positions can be
correlated with items purchased.
[0050] FIG. 3 illustrates a receipt in accordance with an
embodiment. Store receipt 270, shown here in paper form for
illustrative purposes only, can list many purchased items,
including item 272. This item may or may not be correlated with a
stop and turn event or other movement event of a user at the store.
If many shoppers have stopped and turned in a particular location
of the store, and they all have item 272 on their purchase lists,
then it can be inferred that item 272 is located at the location of
the stop and turn events.
[0051] FIG. 4 illustrates a store map in accordance with an
embodiment. In map 400, a shopper's path through the store, derived
from time series data of the shopper's smart phone 416, is shown as
path 420. Path 420 is overlaid on predetermined map of store aisles
402.
[0052] Stop and turn events 404, 406, 408, and 410 are detected by
analyzing the time series data of smart phone 416's accelerometers.
The stop and turn events are shown almost immediately clustered
around where the shopper enters the store. The shopper has gone to
one of the first aisles and begun browsing at the beginning for the
item that he needs. After checking a couple items, indicated by
stop and turn events 404 and 406, and crossing the aisle to check
out another item, indicated by movement event 408, the shopper
turns to find what he was apparently looking for, indicated by stop
and turn event 410. After stop and turn event 410, the shopper
makes way for the checkout line and door.
[0053] Stop and turn events 404, 406, 408, and 410 are correlated
with the closest positions on the store shelves, 424, 426, 428, and
430, respectively. If merchandise positions are already known, then
the shopper's stop and turn event positions are correlated with
merchandise at positions 424, 426, 428 and 430.
[0054] FIG. 5 illustrates a store map in accordance with an
embodiment. In map 500, another shopper's path, derived from time
series data of the shopper's smart phone 516, is shown as path 520.
Path 520 is overlaid on map of store aisles 402.
[0055] Stop and turn events 504, 506, 508, 510, 512, 514, 516, and
518 are detected by analyzing the time series data of smart phone
516's accelerometers. They are shown scattered throughout the
store. The shopper has meandered her way through many of the
aisles, stopping to look at several items of interest in the middle
of aisles, on end caps, and at the impulse buy racks just before
the checkout stands.
[0056] Stop and turn events 504, 506, 508, 510, 512, 514, 516, and
518 are correlated with the closest positions on the store shelves,
524, 526, 430, 530, 532, 534, 536, and 538, respectively. If
merchandise positions are already known, then the shopper's stop
and turn event positions are correlated with merchandise at
positions 524, 526, 430, 530, 532, 534, 536, and 538.
[0057] Between the shoppers of FIGS. 4 and 5, one of the positions
in the store has garnered both of their interests. The shopper of
FIG. 4 stopped and turned at event 410, and the shopper of FIG. 5
stopped and turned at event 508. Both stop and turn events
correspond to position 430. If both shoppers picked up the same
item, as evidenced by their receipts, then it may be inferred that
the item is at position 430 in the store.
[0058] The position of the item can be saved along with a
probability that the item is at the position. The more shoppers who
have movement events near position 430 and end up with the same
item on their receipts, the higher the probability that the item is
at position 430. With hundreds or thousands of shoppers ambling the
aisles of a store, many item positions can be mapped with
accuracy.
[0059] Certain positions of stores can be allocated ratings in line
with empirical data collected by the aforementioned methods. Some
parts of the store may have many people crouching, bending, or
otherwise stopping and turning to view items on nearby shelves.
Certain times of the day, or certain days of the week may have more
shoppers performing stop and turn events than others. Furthermore,
there might be more movement events in certain areas of the store
on some days, and movement events in other areas of the store on
other days.
[0060] Scavenger hunts and other games may be planned with maps of
items generated from consumers. For example, a scavenger hunt
competitor may use the maps to more quickly find items for which he
is seeking. A store can use item maps to plan or score scavenger
hunts for its employees.
[0061] FIG. 6 illustrates MMS coupons in accordance with an
embodiment. Store map 600 shows shelves, doorways, and other
features 402. After positions of items are mapped by analyzing the
movement events and receipts of other shoppers, the positions may
be used for further marketing. In the exemplary embodiment,
position 430 has been associated with a chocolate bar because
previous shoppers had stopped and turned near position 430 and had
the same chocolate bar on their receipts.
[0062] As a shopper passes by position 430, his smart phone 616 is
sent an MMS message with advertisement coupon 674. The coupon is
sent as the person is wandering past the position so that the logo
on the MMS message is recognized by the user on the shelf. The
shopper gets a valuable coupon that can be stored for use later or
deleted.
[0063] Complementary items can be advertised as well. As the
shopper strolls by position 604, his smart phone is sent an MMS
message with advertisement coupon 676 for peanut butter. The coupon
has a bar code that is scannable from a checkout register scanner.
The shopper can store the coupon for use or delete it
immediately.
[0064] The chocolate and peanut butter, in this instance being
considered complementary items, can be dual-marketed to those who
browse the same aisles of a store. In an alternate embodiment,
coupon 676 for peanut butter can be sent to a shopper as he stops
and turns by position 430, the location of chocolate bars. The
sending of the advertisement coupon at this location may seed a
thought in the consumer that peanut butter may taste good with a
chocolate bar that he just took from a store shelf. Whether the
coupon worked can be determined by whether there is a stop and turn
event detected later at position 604.
[0065] FIG. 7 is a flowchart illustrating a process in accordance
with an embodiment. Operations in the flowchart can be performed by
a computer processor or non-computer mechanisms. The process can be
coded in software, firmware, or hardware. Process 700 includes
operations that are optional. In operation 702, time series
velocity data and/or time series orientation data of a mobile
device of a user is received. In operation 704, a movement event,
such as a stop and turn event, is determined from the time series
velocity data and/or time series orientation data. In operation
706, a location at a store of the mobile device during the movement
event is obtained. In operation 708, the obtained location is
correlated with merchandise at the store. In operation 710, further
processing is performed using the correlated location and
merchandise. In operation 712, a coupon or advertisement pertaining
to the merchandise is sent to the mobile device. In operation 714,
a merchandise map of the store is built based on multiple
correlated movement events and merchandise locations.
[0066] FIG. 8 is a flowchart illustrating a process in accordance
with an embodiment. Process 800 includes operations that are
optional. In operation 802, time series velocity data and/or time
series orientation data of mobile devices of users is received. In
operation 804, movement events are determined based on the time
series velocity data and/or time series orientation data. In
operation 806, movement event location are obtained using the
movement events. In operation 808, the movement event locations of
the mobile devices of users are received. In operation 810, a list
of items purchased from a store by each of the users is received.
In operation 812, movement event locations of some of the users are
correlated with a common item of merchandise on the users' purchase
lists. In operation 814, further processing is performed using the
correlated movement event locations and merchandise. In operation
816, an advertisement or coupon is sent to at least one of the
mobile devices based on a movement event.
[0067] FIG. 9 is a flowchart illustrating a process in accordance
with an embodiment. Process 900 includes operations that are
optional. In operation 902, an advertisement for merchandise is
provided to a user. In operation 904, velocity and/or orientation
data of a mobile device of the user are received. In operation 906,
a movement event is determined from the velocity and/or orientation
data. In operation 908, a location of the mobile device at the
movement event is obtained. For example, it can be obtained through
a GPS module in the mobile device. In operation 910, the location
is correlated with the advertised merchandise. In operation 912,
further processing is performed using the correlation. In operation
914, a further advertisement or coupon for the merchandise is sent
to the mobile device based on the correlation.
[0068] FIG. 10 shows a block diagram of a portable consumer device
or mobile device and subsystems that may be present in computer
apparatuses in systems according to embodiments.
[0069] An exemplary portable consumer device 1040 in the form of a
phone may comprise a computer readable medium and a body. The
computer readable medium 1044 may be present within the body of the
phone, or may be detachable from it. The body may be in the form a
plastic substrate, housing, or other structure. The computer
readable medium 1044 may be a memory that stores data and may be in
any suitable form including a magnetic stripe, a memory chip,
encryption algorithms, private or private keys, etc. The memory
also preferably stores information such as financial information,
transit information (e.g., as in a subway or train pass), access
information (e.g., as in access badges), etc. Financial information
may include information such as bank account information, bank
identification number (BIN), credit or debit card number
information, account balance information, expiration date, consumer
information such as name, date of birth, etc.
[0070] Information in the memory may also be in the form of data
tracks that are traditionally associated with credit cards. Such
tracks include Track 1 and Track 2. Track 1 ("International Air
Transport Association") stores more information than Track 2 and
contains the cardholder's name as well as account number and other
discretionary data. This track is sometimes used by the airlines
when securing reservations with a credit card. Track 2 ("American
Banking Association") is currently most commonly used. This is the
track that is read by ATMs and credit card checkers. The ABA
(American Banking Association) designed the specifications of this
track and all world banks must generally abide by it. It contains
the cardholder's account, encrypted PIN, plus other discretionary
data.
[0071] The portable consumer device 1040 may further include a
contactless element 1056, which is typically implemented in the
form of a semiconductor chip (or other data storage element) with
an associated wireless transfer (e.g., data transmission) element,
such as an antenna. Contactless element 1056 is associated with
(e.g., embedded within) portable consumer device 1040, and data or
control instructions transmitted via a cellular network may be
applied to contactless element 1056 by means of a contactless
element interface (not shown). The contactless element interface
functions to permit the exchange of data and/or control
instructions between the mobile device circuitry (and hence the
cellular network) and an optional contactless element 1056.
[0072] Contactless element 1056 is capable of transferring and
receiving data using a near field communications ("NFC") capability
(or near field communications medium) typically in accordance with
a standardized protocol or data transfer mechanism (e.g., ISO
14443/NFC). Near field communications capability is a short range
communications capability, such as RFID, Bluetooth.RTM., infra-red,
or other data transfer capability that can be used to exchange data
between the portable consumer device 640 and an interrogation
device. Thus, the portable consumer device 1040 is capable of
communicating and transferring data and/or control instructions via
both cellular network and near field communications capability.
[0073] The portable consumer device 1040 may also include a
processor 1046 (e.g., a microprocessor) for processing the
functions of the portable consumer device 1040 and a display 1050
to allow a consumer to see phone numbers and other information and
messages. The portable consumer device 1040 may further include
input elements 1052 to allow a consumer to input information into
the device, a speaker 1054 to allow the consumer to hear voice
communication, music, etc., and a microphone 1048 to allow the
consumer to transmit her voice through the portable consumer device
1040. The portable consumer device 1040 may also include an antenna
1042 for wireless data transfer (e.g., data transmission).
[0074] Portable consumer device 1040 may be used by a buyer to
initiate push payments. In some implementations, portable consumer
device 1040 can include an interface to allow the buyer to create a
payment request message. The portable consumer device 1040 can then
send the payment request message to a payment processing network
using contactless element 1056 or over a wireless or wired
communications channel.
[0075] Portable consumer device 1040 can include accelerometer(s)
1058. Multiple accelerometers can be oriented orthogonally or
non-orthogonally to each other.
[0076] FIG. 11 shows a block diagram of an exemplary computer
apparatus that can be used in some embodiments.
[0077] The subsystems shown in the figure are interconnected via a
system bus 1110.
[0078] Additional subsystems such as a printer 1108, keyboard 1118,
fixed disk 1120 (or other memory comprising computer readable
media), monitor 1114, which is coupled to display adapter 1112, and
others are shown. Peripherals and input/output (I/O) devices, which
couple to I/O controller 1102, can be connected to the computer
system by any number of means known in the art, such as through
serial port 1116. For example, serial port 1116 or external
interface 1122 can be used to connect the computer apparatus to a
wide area network such as the Internet, a mouse input device, or a
scanner. The interconnection via system bus 1110 allows the central
processor 1106 to communicate with each subsystem and to control
the execution of instructions from system memory 1104 or the fixed
disk 1120, as well as the exchange of information between
subsystems. The system memory 1104 and/or the fixed disk 1120 may
embody a computer readable medium.
[0079] It should be understood that the present invention as
described above can be implemented in the form of control logic
using computer software in a modular or integrated manner. Based on
the disclosure and teachings provided herein, a person of ordinary
skill in the art can know and appreciate other ways and/or methods
to implement the present invention using hardware and a combination
of hardware and software
[0080] Any of the software components or functions described in
this application, may be implemented as software code to be
executed by a processor using any suitable computer language such
as, for example, Java, C++ or Perl using, for example, conventional
or object-oriented techniques. The software code may be stored as a
series of instructions, or commands on a computer readable medium,
such as a random access memory (RAM), a read only memory (ROM), a
magnetic medium such as a hard-drive or a floppy disk, or an
optical medium such as a CDROM. Any such computer readable medium
may reside on or within a single computational apparatus, and may
be present on or within different computational apparatuses within
a system or network.
[0081] The above description is illustrative and is not
restrictive. Many variations of the invention will become apparent
to those skilled in the art upon review of the disclosure. The
scope of the invention should, therefore, be determined not with
reference to the above description, but instead should be
determined with reference to the pending claims along with their
full scope or equivalents.
[0082] One or more features from any embodiment may be combined
with one or more features of any other embodiment without departing
from the scope of the invention.
[0083] A recitation of "a", "an" or "the" is intended to mean "one
or more" unless specifically indicated to the contrary. A
recitation of "she" is meant to be gender neutral, and may be read
as "he" or "she", unless specifically indicated to the
contrary.
[0084] All patents, patent applications, publications, and
descriptions mentioned above are herein incorporated by reference
in their entirety for all purposes. None is admitted to be prior
art.
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