U.S. patent application number 11/372809 was filed with the patent office on 2007-08-16 for method for controlling when mail is received by a recipient.
This patent application is currently assigned to Pitney Bowes Incorporated. Invention is credited to Kenneth G. Miller, James R. JR. Norris, John W. Rojas, Alla Tsipenyuk, John H. Winkelman.
Application Number | 20070192258 11/372809 |
Document ID | / |
Family ID | 37024413 |
Filed Date | 2007-08-16 |
United States Patent
Application |
20070192258 |
Kind Code |
A1 |
Norris; James R. JR. ; et
al. |
August 16, 2007 |
Method for controlling when mail is received by a recipient
Abstract
A computer controlled method that enables a mailer to control
when recipients will receive mail mailed by the mailer. The method
involves receiving a mailing composition, the desired mailing in
home delivery date ranges and carrier schedules; utilizing a
prediction model built from historical delivery data to predict
when the quantities of mail will arrive for the mailing; and using
the prediction model to determine preferred induction dates for the
mailing.
Inventors: |
Norris; James R. JR.;
(Danbury, CT) ; Winkelman; John H.; (Southbury,
CT) ; Miller; Kenneth G.; (Bethel, CT) ;
Rojas; John W.; (Norwalk, CT) ; Tsipenyuk; Alla;
(Woodbridge, CT) |
Correspondence
Address: |
PITNEY BOWES INC.;35 WATERVIEW DRIVE
P.O. BOX 3000
MSC 26-22
SHELTON
CT
06484-8000
US
|
Assignee: |
Pitney Bowes Incorporated
Stamford
CT
|
Family ID: |
37024413 |
Appl. No.: |
11/372809 |
Filed: |
March 10, 2006 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
60663027 |
Mar 18, 2005 |
|
|
|
Current U.S.
Class: |
705/406 |
Current CPC
Class: |
G06Q 10/04 20130101;
G06Q 30/02 20130101; G06Q 10/06 20130101; H04M 2203/402 20130101;
G06Q 10/08 20130101; H04M 3/51 20130101; G06Q 20/102 20130101; G06Q
10/0833 20130101; G06Q 10/06312 20130101 |
Class at
Publication: |
705/406 |
International
Class: |
B65B 35/00 20060101
B65B035/00 |
Claims
1. A method utilizing a computer to control a mailing and when mail
pieces will arrive at various destinations for a range of dates
comprising the steps of: receiving a plurality of mail pieces and
information regarding the mailing, desired mailing recipient
delivery date ranges and carrier schedules; utilizing a prediction
model built from historical delivery data to predict when the
plurality of mail pieces will be delivered; and using the
prediction model to determine preferred induction dates for the
mailing.
2. The method claimed in claim 1, wherein the mailing is part of a
mailing campaign.
3. The method claimed in claim 2, wherein the mailing campaign
contains a plurality of mailing shipments that contain a plurality
of containers containing a plurality of mail pieces.
4. The method claimed in claim 3, where the prediction model is
used to determine the preferred induction dates in order to deliver
the mail within in-home delivery requirements.
5. The method claimed in claim 4, further including the step of
controlling the volume of mail by delivering an equal amount of
mail on each day in the mailing in home delivery date range.
6. The method claimed in claim 5, further including the step of
choosing mail induction dates that will evenly deliver mail for
different mailing shipments throughout the in home date range.
7. The method claimed in claim 4, further including the step of
controlling the quantities of mail by maximizing an amount of mail
delivered on a specific date within the mailing in home delivery
date range.
8. The method claimed in claim 7, further including the step of
choosing mail induction dates that will deliver mail on the same
days for different mailing shipments throughout the in home date
range.
9. The method claimed in claim 4, further including the step of
controlling the quantities of mail by maximizing an amount of mail
delivered on a specific date outside the mailing in home delivery
date range.
10. The method claimed in claim 4, further including the step of
controlling the volume of mail by delivering an equal amount of
mail on each day outside the mailing in home delivery date
range.
11. The method claimed in claim 4, wherein the recipient mail
volumes are controlled by changing the induction date of the
mail.
12. The method claimed in claim 4, wherein the recipient mail
volumes are controlled by changing the facility in which the mail
is inducted.
13. The method claimed in claim 4, wherein the recipient mail
volumes are controlled by rearranging one or more mail shipments by
combining the mail shipments.
14. The method claimed in claim 4, wherein the recipient mail
volumes are controlled by rearranging one or more mail shipments by
splitting the mail shipments.
15. The method claimed in claim 1, wherein the mailing composition
is selected from the induction facilities data, the processing
facilities data, the number of mail pieces destined for each of the
induction and processing facilities, the sort density for mail
pieces in the mailing, destination zip codes of the mail pieces and
the desired delivery days or dates for the mail pieces.
16. The method claimed in claim 15, further including the step of:
calculating appropriate induction dates for each and every
induction and processing facility, based upon the number of mail
pieces destined for each facility, the sort density for the mail
pieces in the mailing, the desired delivery days or dates and the
destination zip code.
17. The method claimed in claim 16, further including the step of:
calculating the probable distribution of receipt of the mail based
upon historic carrier performance.
18. The method claimed in claim 1, wherein the mailing is part of a
direct marketing campaign.
19. The method claimed in claim 18, wherein the mail in the direct
marketing campaign contains an offer.
20. The method claimed in claim 1, wherein the mail in the mailing
is transactional mail.
Description
[0001] This Application claims the benefit of the filing date of
U.S. Provisional Application No. 60/663,027 filed Mar. 18, 2005,
which is owned by the assignee of the present Application.
CROSS REFERENCE TO RELATED APPLICATIONS
[0002] Reference is made to commonly assigned co-pending patent
application Docket No. F-986-O1 filed herewith entitled "Method For
Predicting When Mail Is Received By A Recipient" in the name of
John H. Winkelman and Docket No. F-986-O3 filed herewith entitled
"Method For Predicting Call Center Volumes" in the names of Docket
No. F-986-O4 filed herewith entitled, "Method for Dynamically
Controlling Call Center Volumes," in the names of Alla Tsipenyuk,
John H. Winkleman, John W. Rojas, Kenneth G. Miller and James R.
Norris, Jr. Docket No. F-986-O5 filed herewith entitled, "Method
for Determining the best Day of the week For a Recipient to receive
a mail piece," in the names of John H. Winkleman, John W. Rojas,
Kenneth G. Miller, Alla Tsipenyuk and James R. Norris, Jr.
FIELD OF THE INVENTION
[0003] This invention relates to mailing mail pieces and, more
particularly, to controlling the day of the week when a mail piece
is delivered to a recipient.
BACKGROUND OF THE INVENTION
[0004] Direct marketers have used the mail to sell products to
customers for almost as long as there has been mail. For direct
marketers the USPS is viewed as a black box where the time required
to process and deliver the mail is based on guess work and rule of
thumb. Where First class mail has delivery standards associated
with it, Standard class mail has less stringent delivery standards
associated with it. For most of the country First class mail will
be processed and delivered within three days. Once the USPS accepts
Standard mail the time to process and deliver the mail will be from
1 to 14+ days. Direct marketers have learned to live with this lack
of real knowledge when a mailing will be delivered in home or place
of business.
[0005] A disadvantage of the prior art is that direct marketers use
rules of thumb to determine in home or place of business or place
of business date range for a mailing, which is not very accurate.
One of the methods used is to base in home or place of business
volumes on when the mailing was shipped from the mail production
facility to the USPS induction facility, i.e. when the mailing is
dropped. In home or place of business volumes would be so many days
after the mailing dropped, such as from 1 to 10 days from the
mailing drop date.
[0006] Another method used is to add seeds to the mailing to
determine when the seeded mail is delivered and assign that
delivery date to all the mail going to that destination city, state
or all the mail in the tray the seed is in. Seeding involves
sending a mail piece to a known address of a service firm and
having the firm date stamp the mail piece and send the mail piece
back to the direct mail marketer. A large number of seeds would be
200 or so which is not enough to cover the 350 USPS Destination
Sectional Control Facilities in the United States. The direct mail
marketer then infers the in-home dates for the mailing as a whole
by correlating the shipment date of the mail (when it leaves the
letter shop) and when the seed indicated that they received the
mail piece. The direct mail marketer then assumes that all mail
going to the area that the seed is in arrives on the same day or on
some window around the seed date.
[0007] Another disadvantage of the prior art is that a mailer is
unable to control when the mail will be delivered to a recipients
home or place of business. A further disadvantage of the prior art
is that a mailer does not know when the mail piece arrived at the
recipient's home or place of business.
SUMMARY OF THE INVENTION
[0008] This invention overcomes the disadvantages of the prior art
by controlling when a direct marketing prospect will receive a mail
piece. The foregoing is accomplished by establishing when to induct
mail at each of the many Destinations Bulk Mail Centers (BMC) in
the United States; establishing when to induct mail at each of the
many, i.e., 350 Destination sectional Control facility (SCF) in the
country; establishing the achievable service level--percentage of
mail that can be expected to arrive in the desired in-home window
that the direct mail marketer is trying to achieve.
[0009] An advantage of this invention is that it accounts for
seasonal variability in mail delivery performance based upon USPS
staffing and system loading.
[0010] An additional advantage this invention is that it accounts
for the sortation density of all trays of mail within the
mailing.
[0011] A further advantage of this invention is that it accounts
for where the mail is going in terms of destination zip codes and
USPS performance against those zip codes.
[0012] A still further advantage of this invention is that it
accounts for and adjust expected in home or place of business
curves for non-controllable circumstances such as natural events or
national security issues.
[0013] This invention also takes into consideration: the impact
that private logistics companies have on trucking, storing and
ultimately inducting standard `A` mail; the impact that when the
USPS will actually accept truck loads of mail from high volume
mailers; the shape, weight and format of the mail; and the
conformance of the mail to USPS automation processing
standards.
[0014] This invention overcomes the disadvantages of the prior art
by determining when the prospect receives the offer; determining
the day of week or day of month that produces the highest response
rate; and determining prospect behavior in terms of gap between
receiving the offer and acting on it.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] FIG. 1 is a flow chart of a prior art direct mail marketing
process;
[0016] FIG. 2 is a flow chart showing how to predict recipient
delivery distribution for a mailing;
[0017] FIG. 3 is a flow chart that generates the actual mail
shipment induction date and triggers a prediction update.
[0018] FIG. 4 is a flow chart that loads facility conditions and
status information and triggers prediction updates if changes are
detected.
[0019] FIG. 5 is a actual vs predicted in-home curve for controlled
mailing.
[0020] FIG. 6 is a drawing showing the predicted vs partial actual
in-home curves for a controlled mailing.
[0021] FIG. 7A is a mailing facility condition plant report.
[0022] FIG. 7B is a mailing facility loading plant report.
[0023] FIG. 8 is a flow chart showing how to compile historic USPS
container level delivery data.
[0024] FIG. 9A is a drawing showing curves generated for the Dallas
Tex. BMC.
[0025] FIG. 9B is a drawing showing curves generated for the Denver
Colo. BMC.
[0026] FIG. 9C is a drawing showing curves generated for the Los
Angles Calif. BMC.
[0027] FIGS. 10A-10F is a table showing sample mail piece historic
delivery times for the North Metro facility which is used to create
container level data shown in step 1580 (FIG. 8).
[0028] FIGS. 11A-11D depicts sample data representative of the
mailing container level data shown in step 1580 (FIG. 8) in tabular
form.
[0029] FIG. 12 is a flow chart showing how to determine the in-home
date for a mail piece.
[0030] FIGS. 13A-13B is a table of drop shipment appointment close
out dates.
[0031] FIG. 14A is a flow chart of a Process for controlling a
mailing campaign.
[0032] FIG. 14B is a flow chart of an algorithm for controlling the
mail.
[0033] FIG. 15 is a flow chart showing how to determine the best
shipment induction date as used by the algorithm in FIG. 14B.
DETAILED DESCRIPTION OF THE INVENTION
[0034] Referring now to the drawings in detail and, more
particularly, to Prior Art FIG. 1, the process begins in step 1,
where the direct mail marketer plans the campaign. Inputs into
campaign planning include planning the creative, i.e., the design
of the mail piece, offer and incentive in step 130 and acquiring
mailing lists in step 120; then selecting prospects in step 112 by
comparing respondent profiles in step 111 from different marketing
tests, i.e., previous campaigns in step 110. Once the marketer has
created the artwork, selected the prospects to be mailed from the
lists available, the campaign is actually created in step 200. Step
200 involves having the various components of the mailing campaign
printed, assembled and on the mail pieces and the address
presorted. From there, the direct mail marketer mails, i.e., drop
ships the mail to the appropriate USPS facility, the offer to all
printing the addresses prospective customers in step 300. Once the
prospective customers receive the offer, some prospects place
orders in step 400. When the prospect orders, the direct mail
marketer captures order processing data in step 410 and correlates
the data with demographic information. That data is fed back into
the order history database in step 110 and used to profile
prospective customers for upcoming campaigns.
[0035] FIG. 2 is a flow chart showing how to predict recipient
delivery distribution for a mailing. The process begins in step
1180 where the mailing prediction process begins and goes to
retrieve shipments in mailing step 1000 or the process may also
begin if it is triggered by the update prediction of step 1190. The
anticipated induction date of the mailing from step 1200 is used
with the retrieve shipment level data in step 1020 and with the
mailing container level data from step 1220 by step 1210 to obtain
the mailing shipment level data. Step 1020 uses mailing shipment
level data from step 1210 including the anticipated induction date
in step 1200 and the induction facility to prepare a prediction for
a shipment. In step 1040 the containers in the shipment are
retrieved.
[0036] In step 1050 the process iterates through each container in
the shipment and in step 1060 the process retrieves the container
level data. Then the process will go to step 1070 to retrieve a
historical container level delivery curve from step 1230. Then in
step 1080 the container delivery distribution is calculated based
upon the historical delivery curve by applying the container piece
count for each day in the distribution and using Sundays, holidays
and other postal delivery processing exceptions. Then in step 1090
the information from step 1080 and the drop ship appointment
facility condition data from step 1240 is utilized to retrieve
container induction and processing facility condition. Step 1091
determines whether or not the information from step 1240 is
available. If step 1091 determines the information is available the
next step in the process is step 1100 to calculate facility
condition offset. If step 1091 determines the information is not
available the next step in the process is step 1120.
[0037] Then step 1120 adds the container delivery curve to the
shipment prediction curve. Then if step 1130 determines that there
are no more containers in the shipment, the process goes to step
1140 to add a shipment prediction curve to a mailing prediction
curve. If step 1130 determines that there are more containers in
the shipment the next step will be step 1050. Now if step 1150
determines that there are no more shipments in the mailing the next
step will be step 1160 to save the mailing prediction. If step 1150
determines that there are more shipments in the mailing the next
step will be step 1010. Step 1170 ends the predict mailing
process.
[0038] FIG. 3 is a flow chart that generates the actual mail
shipment induction date and triggers the prediction update. The
process begins at step 1400 via an automated or user driven
request. Two independent events are detected, in step 1410, mail
arrives at a USPS facility as a Drop Shipment and in step 1415,
mail arrives at a USPS facility for local induction. Step 1411
follows step 1410 where the USPS scans Drop Shipment Form 8125 and
produces an Entry Scan. Step 1416 follows step 1415 where the USPS
scans Local Entry Form 3602 and also produces an Entry Scan. The
Entry Scans are stored in Step 1420 by the USPS Confirm System for
later retrieval. In addition, step 1410 is also followed by step
1430, where the Drop Shipment Appointment System stores information
associated with the drop shipment, such as the truck arrival,
status, load time, etc. Step 1420 and step 1430 are followed by
Step 1440, where the Actual Induction Date is calculated using the
best possible date from the entry scan or the drop shipment
information that is available (If both sets of data are available,
the appointment data is used). Then in step 1450 the Actual
Induction Date is stored and in step 1460 a trigger is generated to
update the mailing campaign prediction.
[0039] FIG. 4 is a flow chart that loads facility conditions and
status information and triggers prediction updates if changes are
detected. The process begins at step 1300, via an automated or user
driven request. The facility conditions are then loaded in step
1315 from step 1310 and stored in step 1317. At the same time,
Facility Loading data is loaded in step 1316 from step 1311 and
stored in step 1317. Step 1320 follows step 1315, where changes to
the facility conditions are detected. In a similar fashion, step
1322 follows step 1316 and detects changes to the facility loading
data. In either case, if changes are detected, steps 1320 and 1322
will trigger a Prediction Update in step 1330.
[0040] FIG. 5 is an actual vs predicted in-home curve for
controlled mailing.
[0041] FIG. 6 is a drawing showing the predicted vs partial actual
in-home curves for a controlled mailing.
[0042] FIGS. 5 and 6 illustrate the variability encountered when
dealing with high volume direct mail marketing campaigns through
the standard approach of controlling drop dates (the date that the
mail leaves the facility that created it).
[0043] In the case of FIG. 6 the mailer elected to create the mail
all at once then drop the 4.5 million or so pieces over 3 days. The
result was a elongated bell curve. The resultant impact was that
the inbound call center, where the prospect called to order the
item, could not handle the call volume. To remediate the situation,
the mailer decided to go to a 4 week induction schedule, targeting
Tuesday, Wednesday and Thursday for receipt of most of the mail for
each week as shown in FIG. 5, where the mailer elected to drop the
mail over a four (4) week period. The expected result was that 1/4
of the mail would arrive each week for a period of four weeks. The
mail control module was used to create the induction plan and the
result was as seen in FIG. 5. By knowing the daily in-home piece
count for the mail and understanding the likely response to those
volumes the mailer was able to staff the call center correctly and
the result yielded a higher order conversion rate for each inbound
call.
[0044] FIG. 7A is a mailing facility condition plant report. Block
20 is the legend block for the report. Spaces 21, 22 and 23
indicate the code used in the report. Space 24 indicates the
condition represented by the code indicated in space 21 and space
25 indicates the condition represented by the code indicated in
space 22. Space 26 indicates the condition represented by the code
indicated in space 23. Space 27 indicates when the report was last
updated. Column 28 indicates the facility name and column 29
indicates the condition of the facility indicated in lines 31 shown
in rows 30 at the date indicated at the top of the column.
[0045] FIG. 7B is a mailing facility loading report that shows
facility appointments over a date range. This report provides
information on the amount or quantity of mail processed by a
specific facility over time and the amount of mail that is
scheduled to be processed by a facility in the near future. Space
900 is the header for the search criteria, including space 901
which is the Facility name header and space 902 which is the
facility name. Space 903 is the Date Range header and space 904 is
the date range for the report.
[0046] The data for the report is defined as follows. Space 905 is
the column header for the Date and space 906 is date for each row
of data.
[0047] Space 907 is the row where the Totals are tallied for each
column.
[0048] Space 908 is the header for the Total Scheduled
Appointments, and space 909 is the total appointments for each
date, and space 910 is the total scheduled appointments for the
facility over the date range specified in space 904, Date Range
above. Space 911 is the header for the columns related to Pallets
scheduled and space 912 is the column header for the total count of
pallets containing parcels scheduled and space 913 is the count of
pallets containing parcels scheduled for each day. Space 914 is the
total count of pallets containing parcels scheduled for all days
and space 915 is the column header for the total count of pallets
containing bundles scheduled. Space 916 is the count of pallets
containing bundles scheduled for each day and space 917 is the
total count of pallets containing bundles scheduled for all
days.
[0049] Space 918 is the column header for the total count of
pallets containing trays scheduled and space 919 is the count of
pallets containing trays scheduled for each day. Space 920 is the
total count of pallets containing trays scheduled for all days.
Space 921 is the column header for the total count of pallets
containing bundles scheduled. Space 922 is the count of pallets
containing bundles scheduled for each day and space 923 is the
total count of pallets containing bundles scheduled for all days.
Space 924 is the column header for the total count of pallets
scheduled and space 925 is the total count of pallets scheduled for
each day. Space 926 is the total count of pallets scheduled for all
days and space 927 is the header for the columns related to cross
docked mail scheduled. Space 928 is the column header for the total
count of cross docked mail containing parcels scheduled and space
929 is the count of cross docked mail containing parcels scheduled
for each day. Space 930 is the total count of cross docked mail
containing parcels scheduled for all days and space 931 is the
column header for the total count of cross docked mail containing
bundles scheduled. Space 932 is the count of cross docked mail
containing bundles scheduled for each day and space 933 is the
total count of cross docked mail containing bundles scheduled for
all days. Space 934 is the column header for the total count of
cross docked mail containing trays scheduled and space 935 is the
count of cross docked mail containing trays scheduled for each day.
Space 936 is the total count of cross docked mail containing trays
scheduled for all days and space 937 is the column header for the
total count of cross docked mail containing bundles scheduled.
Space 938 is the count of cross docked mail containing bundles
scheduled for each day and space 939 is the total count of cross
docked mail containing bundles scheduled for all days. Space 940 is
the column header for the total count of cross docked mail
scheduled and space 941 is the total count of cross docked mail
scheduled for each day. Space 942 is the total count of cross
docked mail scheduled for all days. Space 943 is the header for the
columns related to bed loads scheduled and space 944 is the column
header for the total count of bed loads containing parcels
scheduled. Space 945 is the count of bed loads containing parcels
scheduled for each day and space 946 is the total count of bed
loads containing parcels scheduled for all days. Space 947 is the
column header for the total count of bed loads containing bundles
scheduled and space 948 is the count of bed loads containing
bundles scheduled for each day. Space 949 is the total count of bed
loads containing bundles scheduled for all days and space 950 is
the column header for the total count of bed loads containing trays
scheduled. Space 951 is the count of bed loads containing trays
scheduled for each day and space 952 is the total count of bed
loads containing trays scheduled for all days. Space 953 is the
column header for the total count of bed loads containing bundles
scheduled and space 954 is the count of bed loads containing
bundles scheduled for each day. Space 955 is the total count of bed
loads containing bundles scheduled for all days and space 956 is
the column header for the total count of bed loads scheduled. Space
957 is the total count of bed loads scheduled for each day and
space 958 is the total count of bed loads scheduled for all
days.
[0050] FIG. 8 is a flow chart showing how to compile historic USPS
container level delivery data. The process begins at either step
1500 or step 1510. If the process began at step 1500 where the USPS
scans drop shipment form 8125. Drop shipment form 8125 is used by
the USPS for registering when the drop shipment arrives at a USPS
facility. If the process began at step 1510 the USPS scans entry
form 3062. Drop shipment form 3062 is used by the USPS for
registering when mail is locally inducted by the USPS. In step 1530
the USPS confirm system is utilized. The confirm system receives
the information scanned by the USPS from the mail piece in step
1520 and the information from steps 1500 and 1510. Then entry scan
data from step 1530 is sent to step 1570 mailing shipment level
data and planet code data is sent to step 1590 as mail piece level
data. In addition drop shipment close out data is sent from the
USPS Drop Shipment Appointment System (DSAS) to step 1570 as
mailing shipment level data. In step 1580 mailing container level
data is correlated from shipment level data tied in 1600 and mail
piece level data tied in step 1610.
[0051] Step 1560 utilizes mailing container level data from step
1580 to compile historical mailing delivery data. Step 1550
utilizes historical mailing delivery data from step 1560 to produce
historical container level delivery curves. Step 1540 stores the
historical delivery data for predicting and/or controlling
mailings
[0052] FIGS. 9A-9C show example curves generated for BMC's and
SCF's in three different regions: Dallas Tex., Denver Colo., and
Los Angeles, Calif. The curves show the high variability of in home
mail distributions, both volumes and timing, across BMC and SCF in
the same region. Furthermore, the figures also show the high
variability across different BMC's and/or SCF across different
regions.
[0053] Each of the FIGS. 9A-9C shows graphs for a specific
facility, displaying average distribution of in home mail volumes
from the day of induction to the day of delivery, over a 10 month
period, January to October 2004. In each chart, the x axis is the
number of days since induction and the y axis is the percentage of
the mail delivered on that day.
[0054] FIGS. 10A-10F is a table showing sample mail piece historic
delivery times for the North Metro facility which is used to create
container level data shown in step 1580 (FIG. 8).
[0055] In FIG. 10A the shipment ID, i.e., the identification of the
mailing shipment is shown in column 43. The city and state that the
shipment is delivered to is respectively shown in columns 44 and
45. The three digit zip code is shown in column 46. The zip code
and the zip code plus four are respectively shown in columns 47 and
48. The carrier route for the shipment is shown in column 49. The
delivery point code (DPC) is shown in column 50 and the cell i.e.,
identifies mail with different creative formats within a mailing is
shown in column 51. The mail sequence i.e., internal/identifier for
each mail piece is shown in column 52.
[0056] In FIG. 10B the CLASS of mail is shown in column 53. Column
54 is the name DMLAYOUT_TABLE, the name of the table holding the
address information for this mail piece. Column 55
(IND_FACILITY_NAME) holds the name of the induction facility.
Column 56 (IND_FACILITY_TYPE) holds the type of facility, i.e. BMC,
SCF, etc. Column 57 (IND_FACILITY) holds the zip code for the
induction facility, and column 58 (FIRST_IND_DATE) is the time
stamp of the first scan that occurs in the induction facility.
Column 59 (LAST_IND_DATE) is the optional time stamp of the last
scan that occurs in the induction facility.
[0057] In FIG. 10C column 60 (DS_SCHEDULE_DATE) is the date when
the shipment was scheduled for drop shipment. Column 61 (IND_REC
_PK) is a foreign key to the shipment record for this mail piece
and column 62 (FIRST_SCAN_FACILITY) is the zip code of the facility
where the mail piece was first scanned--after induction and column
63 (FIRST_SCAN_DATE) is the time stamp of the first scan at the
processing facility. Column 64 (FIRST_OP_NO) is the operation that
was performed on the mail piece during the first scan, i.e. first
pass sort, second pass sort, etc. and column 65 (LAST_SCAN_FACILTY)
is the zip code of the facility where the mail piece was last
scanned.
[0058] In FIG. 10D column 66 ((LAST_SCAN_DATE) is the time stamp of
the last scan at a processing facility and column 67 (LAST_OP_NO)
is the operation that was performed on the mail piece during the
last scan. Column 68 (NUMBER_SCANS) is a count of the total number
of planetcode scans (or operations) detected on the mail piece and
column 69 (IN_HOME_DATE) is the calculated in home date for the
mail piece, see FIG. 12. Column 70 (IND_FIRST_SCAN _HRS) is the
number of hours between the FIRST_IND_DATE and the FIRST_SCAN_DATE
and column 71 (IND_LAST_SCAN_HRS) is the number of hours between
the FIRST_IND_DATE and the LAST_SCAN_DATE.
[0059] In FIG. 10E column 72 (FIRST_LAST_SCAN_HRS) is the number of
hours between the FIRST_SCAN_DATE and the LAST_SCAN_DATE and column
73 (REC_ID_PK) is the primary key for this mail piece record.
Column 74 (PROBLEM_DATA) is used to flag if there is problem data
for this mail piece and
[0060] Column 75 (IND_FIRST_SCAN_DAYS) is the IND_FIRST_SCAN_HRS
represented as days. Column 76 (IND_LAST_SCAN_DAYS) is the
IND_LAST_SCAN_HRS represented as days and column 77 (PALLET)
identifies the pallet the mail piece is in for the mailing. Column
78 (BAG) identifies the bag the mail piece is in for the
mailing.
[0061] In FIG. 10F column 79 (BUNDLE) identifies the bundle the
mail piece is in Column 80 (TIER) i.e., C=carrier route, P=presort
3 or 5 digit, R=residential and column 81 (AUTO_NON_AUTO) indicates
if the mail piece has an automation compatible post-net code, where
A=zipcode plus 4 plus 2 and N=zip code. Column 82 (PRESORT_TYPE) is
the presort order assigned to the mail piece and column 83
(PRESORT_ZIP) is the zip code for the specific presort type in
column 82. Column 84 (MODELED_IN_HOME_DATE) is the calculated in
home date, see FIG. 12.
[0062] Mail piece level data (FIGS. 10A-10F) is combined or
aggregated into container level data and tabulated as shown in
FIGS. 11A-11D.
[0063] FIGS. 11A-11D depicts sample data representative of the
mailing container level data shown in step 1580 (FIG. 8) in tabular
form. In FIG. 11A the location of the induction facility for the
mailing shipment is shown in column 85. Each row in FIGS. 11A-11D
is representative of an aggregation of containers of mail pieces
represented in rows in FIGS. 10A-10F (belonging to the container).
The type of induction facility i.e., BMC, Auxiliary Sectional
Facility (ASF) or SCF is shown in column 87. The sort level
performed on the mail pieces, i.e., Enhanced Carrier Route
(ECROLT), three digit sort level (AUTO**3-Digit), Auto Carrier
Route (AUTOCR), five digit sort level (AUTO**5-Digit) are shown in
column 88. The induction date of the shipment for the container is
shown in column 89. The induction day of week (DOW) is shown in
column 90.
[0064] In FIG. 11 B is the induction tour when the shipment was
inducted Foreign Key (FK) for the container is shown in column 91
and the induction Day Of Week (DOW) for the container is shown in
column 92. The location of the processing facility of the mailing
shipment is shown in column 86. The induction MOY month of year
(MOY) for the container is shown in column 93 and the induction
year-FK for the container is shown in column 94. The mail piece
count for the shipment is shown in column 95. The percentage of the
container mail pieces that arrived on the induction day (Day0) In
home is shown in column 96.
[0065] In FIG. 11 C the percent of mail pieces that are in the home
one day after postal induction is shown in column 97 and the
percent of mail pieces that are in the home two days after postal
induction is shown in column 98. The percent of mail pieces that
are in the home three days after postal induction is shown in
column 99 and the percent of mail pieces that are in the home four
days after postal induction is shown in column 100. The percent of
mail pieces that are in the home five days after postal induction
is shown in column 101 and the percent of mail pieces that are in
the home six days after postal induction is shown in column 102.
The percent of mail pieces that are in the home seven days after
postal induction is shown in column 103 and the percent of mail
pieces that are in the home eight days after postal induction is
shown in column 104.
[0066] In FIG. 11D the percent of mail pieces that are in the home
nine days after postal induction is shown in column 105 and the
percent of mail pieces that are in the home ten days after postal
induction is shown in column 106. The percent of mail pieces that
are in the home eleven days after postal induction is shown in
column 107 and the percent of mail pieces that are in the home
twelve days after postal induction is shown in column 108. The
percent of mail pieces that are in the home beyond the second week
of postal induction is shown in column 109 and the ready for
training flag shown in column 110 indicates when the record can be
used as historical container level delivery curves as shown in step
1550 (FIG. 8).
[0067] FIG. 12 is a flowchart indicating how the In Home Date is
calculated for a mail piece, and saved in space 69, IN_HOME_DATE,
in FIG. 10D and is also used to calculate MODELED_IN_HOME_DATE in
space 84 in FIG. 10F.
[0068] The process is applied to each mail piece that is scanned
and starts in step 3000 and is followed by step 3020, where the
last scan for the mail piece is loaded from step 3010, Mail piece
Last Scan Date from USPS Confirm System. Next, step 3030
initializes the In Home Date for the mail piece as the Last Scan
Date and then if step 3040 determines if the mail piece scan
occurred after the delivery cut-off time for that facility, step
3050 will add 24 hours to the in home date, since the mail piece
will not be delivered on the same day. Next if step 3060 determines
that the In Home Date falls on a no-delivery date, such as a
Sunday, Holiday, or exception date, etc, step 3070 will use the
next available delivery date is used as the In Home Date for the
mail piece.
[0069] The process continues at step 3080 where the calculated In
Home Date is saved to space 69 in FIG. 10D, as shown in step 3090.
Finally, the process ends in step 3095.
[0070] FIGS. 13A and 13B is a table of drop shipment appointment
close out data, which is used to calculate the actual mail shipment
induction date as described in FIG. 3. Space 33 indicates the
shipment confirmation number and space 34 indicates the appointment
status of the shipment, with states of Closed, No Show, or Open,
etc. Space 35 indicates the header for space 35a, the name of the
facility where the shipment is scheduled to arrive. Space 36 is the
header for space 36a, the date and time when the truck arrived.
Space 37 is the header for space 37a, the date and time when the
truck started to be unloaded.
[0071] Space 38 is the header for space 38a, the date and time when
the truck completed unloading. Space 39a is the header for Space
39a, the Trailer Number, identifying the truck that delivered the
mail.
[0072] FIG. 14A is a flow chart of a Process for controlling a
mailing campaign. In FIG. 14A, the customer provides mailing
campaign data file in step 500 describing the mail pieces in each
shipment of the mailing campaign. A mailing campaign consists of
one or more shipments. Each shipment consists of a number of trays
or containers of mail sorted to some density for instance 3-digit
zip code level, 5-digit zip code level, or MDC level. Further, each
shipment is to be inducted at a specific BMC of Sectional Control
Facility (SCF). Each tray or container consists of one or more mail
pieces. Of those mail pieces, one or more mail piece in each tray
are uniquely identified with a bar code or bar codes uniquely
identifying that mail piece. Those bar codes are in a format that
is scanned and stored by the USPS. The mail campaign data include
may custom formats such as a comma delimited flat file or an XML
formatted data file, or may follow an industry standard such as
Mail.dat. The customer also inputs to the system the desired days
that the recipient is to receive the mail piece in step 530. The
recipient target interval may be specific days of a week or
specific dates. For instance, the recipient population is to
receive the mail piece on a Tuesday or Wednesday or the recipient
is to receive the mail piece on the 13 or 14 Jan., 2005. The system
shall accept inputs spanning one or more desired in-home days or
dates.
[0073] The induction planner in step 510 using a model of the
processing pattern of all facilities in the system determines the
best day of the week to induct the mail at each of the target
facilities. Step 510 is described in more detail in FIG. 14B. The
system also accepts exception event inputs containing postal
holidays in step 575 and in step 570 catastrophic events that may
shut down or seriously impede the postal system's ability to
process mail. In step 580 the data is stored in an exception data
file or database and accessed by the induction planner. Further,
the system takes as an input the logistics schedule of the shipping
provider for the mailer in step 550 and stores that data in step
560 using a method that allows access by the induction planning
software. The logistics schedule of the shipping provider is the
route schedule for that transportation firm. The system, is able to
plan the induction schedule for the mail around the dates that the
logistics provider actually inducts mail with the destination
facility or facilities. It is not uncommon for the logistics
providers to take mail to some facilities daily and some other
facilities as infrequently as once per week.
[0074] Given all of the inputs, the system calculates an induction
plan in step 510 containing the date to induct the mail for each
destination facility within the USPS. Further, the system outputs
an anticipated arrival curve for each container or shipment or the
mailing campaign as a whole or a part of the campaign. The
anticipated arrival curve provides the mailer with a realistic idea
for when the mail will arrive with the recipient population given
logistics constraints, postal processing variability, postal
holidays and catastrophic events.
[0075] Once the mailer instructs the shipper when to induct the
shipments at each destination processing facility the system
monitors the USPS system in step 590 to measure when the
shipment(s) were actually inducted. Step 590 is described in
further detail in FIG. 3 and step 620 in described in further
detail in FIG. 4. Additionally, the system monitors the DSAS system
in step 620 for facility status information which may delay the
processing and ultimately delivery of mail to the recipients of
that mail. Periodically, the system accesses the stored induction
and facility status data in step 600 and updates the anticipated
in-home curves in step 610.
[0076] Once the mail is accepted, those pieces containing scannable
bar codes are processed and tracked through the USPS. The USPS
reports that scan information for each scannable piece. The scanned
data in step 650 is downloaded to the system and tied to the
customer mail piece data in step 670 through an appropriate
database in step 660. The system then uses that data to generate
reports containing when the prospect population is in fact
receiving the mail pieces. Further that data is used to create
conformance reporting back to the mailer in step 640 demonstrating
how much mail was in-homed within the desired window.
[0077] The delivery results of the mailing campaign including
shipment and mail piece information are then used to update the
induction planning model in step 540 thus refining the induction
planner's in step 510 future capability to accurately determine
when mail is to be inducted to achieve desired delivery dates.
[0078] FIG. 14B is a flow chart of an algorithm for controlling the
mail. The process begins in step 2000 control mailing. Then in step
2005 mailing shipments are retrieved from step 2110. Now in step
2010 each shipment from step 2005 is processed one shipment at a
time. Then in step 2020 the data associated with the make up of the
shipment from step 2110 is retrieved. The retrieved data includes
the induction facility and the mail piece count. In step 2030 the
identity of the containers in the shipment are retrieved from step
2120 mailing container level data.
[0079] Now in step 2040 each container in the shipment is
processed. Then step 2050 the data associated with the make up of
the container from step 2120 is retrieved. This data includes the
container processing facility, destination facility, sort level,
mail pieces in the container and make up of the mail piece. Then in
step 2060 the historical level delivery curve associated with the
container in step 2050 is retrieved from step 2130 historical
delivery data. The historical delivery curve is conveyed as a
proportional curve that indicates the percentage of mail pieces
delivered each day.
[0080] In step 2070 the mail pieces delivered per day for this
container is calculated by multiplying the mail piece counts in the
container by the historical container delivery curve. Then, step
2080 adds the container delivery curve calculated in step 2070 to
the shipment delivery curve. Now step 2090 determines whether or
not there are more containers to be processed in the shipment. If
step 2090 determines there are more containers in the shipment to
be processed, the next step will be step 2040. If step 2090
determines there are no more containers in the shipment to be
processed, the next step will be step 2300 to determine the best
shipment induction date. Step 2300 is more fully described in the
description of FIG. 15.
[0081] Then the process goes to step 2100 to determine whether or
not there are more shipments in the mailing campaign. If step 2100
determines that there are more shipments in the mailing campaign
the next step is step 2010. If step 2100 determines that there are
no more shipments in the mailing campaign the next step is step
2140 which prints an induction plan for execution. Now in step 2150
the mailing control algorithm is completed.
[0082] FIG. 15 is a flow chart showing how to determine the best
shipment induction date as used by the algorithm in FIG. 14B. The
process begins at step 2300 determine best shipment induction date.
Then in step 2310 data is retrieved for the desired in home window.
At this time data is exchanged between step 2310 and step 2430
desired in home window to specify the date range when most of the
mail needs to be delivered. Now in step 2320 the process builds a
list of all the possible in home window locations over the shipment
delivery curve, calculating the percentage of mail delivered inside
the window for each window location. The in house window locations
are sorted from best to worst, i.e., from most mail delivered to
least mail delivered in the window.
[0083] In step 2330, the induction date is determined for each in
home window location taking into account Sundays and holidays. Then
step 2340 retrieves the USPS facility acceptance schedule. Step
2340 exchanges information with step 2440 USPS facility acceptance
schedule. At this point the process goes to step 2350. Step 2350
determines whether or not the USPS facility accepts mail on the
induction date. If step 2350 determines that mail is accepted on
the induction date, the process goes to step 2360 to retrieve the
drop ship schedule. Step 2360 exchanges information with step 2450
drop shipper schedule. Then the process goes to step 2370. Step
2370 determines whether or not the drop shipper can deliver the
shipment to the induction facility on the induction date. If step
2370 determines that the shipper can deliver the shipment on the
induction date the process goes to step 2400 update shipment
desired induction date. The next step will be step 2460 return. If
step 2370 determines the drop shipper can not deliver the shipment
on the induction date or if step 2350 determines that the USPS
facility does not accept mail on the induction date then, the next
step is 2390.
[0084] If decision step 2390, determines that the next highest in
home window location does not exist, the process goes to step 2420,
where the shipment is flagged as there is no known induction for
the specified in home window. Then the process goes to step 2460
return.
[0085] It should be understood that although the present invention
was described with respect to mail processing by the USPS, the
present invention is not so limited and can be utilized in any
application in which mail is processed by any carrier. The present
invention may also be utilized for mail other than direct marketing
mail, for instance, transactional mail, i.e., bills, charitable
solicitations, political solicitations, catalogues etc. Also the
expression "in-home" refers to the recipient's residence or place
of business.
[0086] The above specification describes a new and improved method
for enabling a mailer to control when mail will arrive at a
recipient's home or place of business on a given date. It is
realized that the above description may indicate to those skilled
in the art additional ways in which the principles of this
invention may be used without departing from the spirit. Therefore,
it is intended that this invention be limited only by the scope of
the appended claims.
* * * * *