Abstract:
A method utilizing a computer to predict what volumes of mail will arrive at a given destination on a given date. The method is accomplished by: utilizing the composition of a mailing campaign that contains a plurality of mailing shipments that contain a plurality of containers containing a plurality of mail pieces; making a prediction curve for each container when the shipment is inducted at a carrier facility; and building a mailing campaign prediction based upon the container predictions; wherein each shipment prediction curve is added to the mailing campaign prediction at the date when the shipment is inducted at the carrier facility.

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-O2 filed herewith entitled “Method for controlling When Mail Is Received By A Recipient” in the names of James R. Norris, Jr., John H. Winkelman, Kenneth G. Miller, John W. Rojas and Alla Tsipenyuk. Docket No. F-986-O3 filed herewith entitled “Method For Predicting Call Center Volumes” in the names of Kenneth G. Miller, John H. Winkelman, John W. Rojas, Alla Tsipenyuk and James R. Norris, Jr. Docket No. F-986-O4 filed herewith entitled, “Method for Dynamically Controlling Call Center Volumes,” in the names of Alla Tsipenyuk, John H. Winkelman, 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. Winkelman, John W. Rojas, Kenneth G. Miller, Alla Tsipenyuk and James R. Norris, Jr.  
       FIELD OF THE INVENTION  
       [0003]     This invention relates to predicting the delivery date of mail and more particularly to predicting a mailing&#39;s daily recipient delivery distribution volumes using a mailing&#39;s shipment container, mail piece level data, historical USPS processing and delivery data, USPS facility processing status data, and shipment processing data.  
       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 does not. 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 of when a mailing will be delivered in home. A disadvantage of the prior art is that direct marketers use rule of thumb to determine in home date range for a mailing, which is not very accurate. One of the methods used is to base in home volumes on when the mailing was shipped from the mail production facility to the USPS induction facility, i.e. when the mailing dropped. In home volumes would be so many days after the mailing dropped, such as from 1 to 10 days from the mailing drop date.  
         [0005]     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.  
         [0006]     Another problem is mail going to that destination or in the tray will be delivered over multiple days where as the seed will only give a point in time and not a date range.  
       SUMMARY OF THE INVENTION  
       [0007]     This invention overcomes the disadvantages of the prior art by enabling the mailer to know what volumes of mail arrive at a recipient&#39;s home or place of business on a given date. This also enables the mailer to determine who received the mail. The foregoing is accomplished by determining the composition of the mailing shipment; determining for each shipment the number of days from the start of the mailing to the induction at the USPS facility, or other carrier facility, i.e., Federal Express, United Parcel Service, DHL, etc.; for each shipment retrieve the container for that shipment; for each container, retrieve the prediction curve for that container; build a shipment prediction based on many container predictions; wherein each shipment prediction curve is added to the mailing at the date when the shipment is inducted at the USPS facility so that a campaign prediction may be built based upon the many shipment predictions.  
         [0008]     An advantage of the foregoing is that it enables the mailer to know when their prospective recipient&#39;s are most likely to receive a mail piece. The foregoing helps the mailer&#39;s staffing and coordination with other channels, i.e., enables the mailer to make follow up phone calls to recipients.  
         [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. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0014]      FIG. 1  is a flow chart of a prior art direct mail marketing process;  
         [0015]      FIG. 2  is a flow chart showing how to predict recipient delivery distribution for a mailing;  
         [0016]      FIG. 3  is a flow chart that generates the actual mail shipment induction date and triggers a prediction update.  
         [0017]      FIG. 4  is a flow chart that loads facility conditions and status information and triggers prediction updates if changes are detected.  
         [0018]      FIG. 5  is an actual vs. predicted in-home curve for controlled mailing.  
         [0019]      FIG. 6  is a drawing showing the predicted vs. partial actual in-home curves for a controlled mailing.  
         [0020]      FIG. 7A  is a mailing facility condition plant report.  
         [0021]      FIG. 7B  is a mailing facility loading plant report.  
         [0022]      FIG. 8  is a flow chart showing how to compile historic USPS container level delivery data.  
         [0023]      FIG. 9A  is a drawing showing curves generated for the Dallas Tex. BMC.  
         [0024]      FIG. 9B  is a drawing showing curves generated for the Denver Colo. BMC.  
         [0025]      FIG. 9C  is a drawing showing curves generated for the Los Angles Calif. BMC.  
         [0026]      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 ).  
         [0027]      FIGS. 11A-11D  depicts sample data representative of the mailing container level data shown in step  1580  ( FIG. 8 ) in tabular form.  
         [0028]      FIG. 12  is a flow chart showing how to determine the in-home date for a mail piece.  
         [0029]      FIGS. 13A-13B  is a table of drop shipment appointment close out dates. 
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0030]     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 printing the addresses 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 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.  
         [0031]      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.  
         [0032]     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 .  
         [0033]     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.  
         [0034]      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.  
         [0035]      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 .  
         [0036]      FIG. 5  is an actual vs. predicted in-home curve for controlled mailing.  
         [0037]      FIG. 6  is a drawing showing the predicted vs. partial actual in-home curves for a controlled mailing.  
         [0038]      FIGS. 5 and 6  illustrate the correlation between the mailing campaign prediction and the actual in-home results for a mailing that was controlled to be dropped over a four week period. The Figs. are a visual representation of the predicted mail quantities and dates for two different mailing campaigns. The presented curves represent the aggregation of the predicted in home curve for the shipments belonging to each campaign respectively. Each shipment in home curve prediction is referenced from the scheduled induction date for that shipment.  
         [0039]     The expected result was that ¼ of the mail would arrive on Tuesday, Wednesday and Thursday of each week for a period of four weeks.  FIG. 5  shows the predicted and actual results after the mailing was completed and  FIG. 6  shows how actual results are gathered as the mailing campaign is in progress.  
         [0040]      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.  
         [0041]      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.  
         [0042]     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.  
         [0043]     Space  907  is the row where the Totals are tallied for each column. 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.  
         [0044]     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.  
         [0045]      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 .  
         [0046]     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.  
         [0047]      FIGS. 9A-9C  show example curves generated for BMC&#39;s and SCF&#39;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&#39;s and/or SCF across different regions.  
         [0048]     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.  
         [0049]      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 ).  
         [0050]     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 .  
         [0051]     In  FIG. 10 B  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.  
         [0052]     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.  
         [0053]     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.  
         [0054]     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 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.  
         [0055]     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=zip code 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 .  
         [0056]     Mail piece level data ( FIGS. 10A-10F ) is combined or aggregated into container level data and tabulated as shown in  FIGS. 11A-11D .  
         [0057]      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 .  
         [0058]     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 .  
         [0059]     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 .  
         [0060]     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 ).  
         [0061]      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 . 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.  
         [0062]     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 .  
         [0063]      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  35   a , the name of the facility where the shipment is scheduled to arrive. Space  36  is the header for space  36   a , the date and time when the truck arrived. Space  37  is the header for space  37   a , the date and time when the truck started to be unloaded.  
         [0064]     Space  38  is the header for space  38   a , the date and time when the truck completed unloading. Space  39   a  is the header for Space  39   a , the Trailer Number, identifying the truck that delivered the mail.  
         [0065]     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&#39;s residence or place of business.  
         [0066]     The above specification describes a new and improved method for enabling a mailer to predict what volumes of mail will arrive at a recipient&#39;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.