Product Delivery Route Optimization

This dataset provides granular, structured information on last-mile delivery routes, including route assignments, delivery stops, timing, and package details. It enables comprehensive analysis and simulation of logistics operations to optimize delivery efficiency, reduce operational costs, and improve customer satisfaction. The flat schema design supports integration with mapping, routing, and analytics platforms.

  • last updated 21 Jul 2025
  • by GoMask
The brief that made it

Optimizing last-mile delivery routes for cost and time savings

Sample rows

preview · 8 of 200 rows · all 24 columns
route_idstringdelivery_statusstringtotal_duration_minutesfloatdelivery_address_statestringvehicle_idstringdriver_idstringroute_datedateroute_start_timedatetimeroute_end_timedatetimetotal_distance_kmfloattotal_deliveriesintegerdelivery_idstringroute_id_refstringdelivery_sequenceintegercustomer_idstringdelivery_address_streetstringdelivery_address_citystringdelivery_address_postal_codestringdelivery_address_countrystringscheduled_delivery_timedatetimeactual_delivery_timedatetimepackage_countintegertotal_package_weight_kgfloatdelivery_notesstring
R001completed143NJV001D1012024-06-032024-06-03T07:15:002024-06-03T09:38:0041.23DEL1001R0011C0001812 Maple AveEdison08817USA2024-06-03T08:10:002024-06-03T08:12:0038.6blank
R001completed143NJV001D1012024-06-032024-06-03T07:15:002024-06-03T09:38:0041.23DEL1002R0012C0002155 Oak StPrinceton08540USA2024-06-03T08:55:002024-06-03T09:00:0026.5blank
R001completed143NJV001D1012024-06-032024-06-03T07:15:002024-06-03T09:38:0041.23DEL1003R0013C000370 Parkside BlvdTrenton08609USA2024-06-03T09:30:002024-06-03T09:33:0012.3blank
R002completed165CTV002D1022024-06-032024-06-03T06:55:002024-06-03T09:40:0057.42DEL1004R0021C000419 Elm StreetStamford06901USA2024-06-03T07:45:002024-06-03T07:47:0049.9blank
R002delayed165CTV002D1022024-06-032024-06-03T06:55:002024-06-03T09:40:0057.42DEL1005R0022C0005233 Harbor DrNorwalk06850USA2024-06-03T09:25:002024-06-03T09:33:00513.2Traffic congestion
R003completed90NYV011D1152024-06-022024-06-02T08:20:002024-06-02T09:50:0022.81DEL1006R0031C000648 E 18th StNew York10003USA2024-06-02T09:30:002024-06-02T09:31:0025.1blank
R004completed75CTV003D1062024-06-042024-06-04T07:40:002024-06-04T08:55:0027.52DEL1007R0041C0007333 Cedar StBridgeport06606USA2024-06-04T08:10:002024-06-04T08:11:0013.5blank
R004pending75CTV003D1062024-06-042024-06-04T07:40:002024-06-04T08:55:0027.52DEL1008R0042C0008920 Main StStamford06902USA2024-06-04T08:45:00blank10.7blank

What the 200 rows show

from the 200-row sample

Pending (delivery status) stands out: mean total_duration_minutes is 66.4, against 160.3 for the rest.

  • 156.0median total_duration_minutes
  • 10delivery address countries
  • 44.6median total_distance_km
  • 2median total_deliveries
  • 1median delivery_sequence
  • 2median package_count
Mean total_duration_minutes by delivery_status200 rows
010020066.4pending21 rows159.3completed155 rows145.4failed8 rows177.1delayed16 rows
total_duration_minutes200 rows, in bands of 25
02550949101840452320220125250total_duration_minutes →

Median 156.0, from 0.0 to 240.0.

delivery_address_state200 rows · top 10 of 39 values
  1. NY21
  2. ON15
  3. WA15
  4. CA14
  5. PA13
  6. OH12
  7. TX11
  8. CO10
  9. NA8
  10. OK8
24 columns by typefrom the column list below
  • string 13
  • integer 3
  • float 3
  • date 1
  • datetime 4

Columns

24 columns in three groups
blueprint · 24 columns
columntypedescriptionexample
Text 13 columns
route_idstringUnique identifier for the delivery routeuniqueR001
vehicle_idstringUnique identifier for the vehicle assigned to the routeV001
driver_idstringUnique identifier for the driver assigned to the routeD101
delivery_idstringUnique identifier for each delivery stop on the routeuniqueDEL1001
route_id_refstringIdentifier linking this delivery to its parent routeR001
customer_idstringUnique identifier for the customer receiving the deliveryC0001
delivery_address_streetstringStreet address for the delivery stop812 Maple Ave
delivery_address_citystringCity for the delivery stopEdison
delivery_address_statestringState or province for the delivery stopNJ
delivery_address_postal_codestringPostal or ZIP code for the delivery stop08817
delivery_address_countrystringCountry for the delivery stop10 countriesUSA
delivery_statusstringStatus of the delivery (e.g., pending, completed, failed, delayed)pending · completed · failed · delayedcompleted
delivery_notesstringAdditional notes or comments about the delivery stopoptionalTraffic congestion
Numbers 6 columns
total_distance_kmfloatTotal distance covered in kilometers for the route0 or more41.2
total_duration_minutesfloatTotal duration of the route in minutes0 or more143
total_deliveriesintegerTotal number of deliveries scheduled on this route1 or more3
delivery_sequenceintegerOrder of this delivery in the route sequence (1 = first stop)1 or more1
package_countintegerNumber of packages delivered at this stop1 or more3
total_package_weight_kgfloatTotal weight of packages delivered at this stop in kilograms0 or more8.6
Dates and times 5 columns
route_datedateDate when the delivery route is scheduled or executed2024-06-03
route_start_timedatetimeTimestamp when the route starts2024-06-03T07:15:00
route_end_timedatetimeTimestamp when the route endsoptional2024-06-03T09:38:00
scheduled_delivery_timedatetimeScheduled time for the delivery at this stop2024-06-03T08:10:00
actual_delivery_timedatetimeActual time when the delivery was completed at this stopoptional2024-06-03T08:12:00

Use it for

  • median total d…156.0200 rowsmean total duration m…66.4pend…159.3comp…145.4fail…177.1dela…

    A logistics dashboard

    Total_duration_minutes by delivery_status and a breakdown of delivery_address_state. Excel, Power BI or Tableau.

  • Why do the 21 pending rows have a mean total_duration_minutes of 66.4?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable routes with vehicle_id, driver_id and route_date to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 24 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows24 columns
Yours1,000 rows24 columnsdelivery_address_street: UK only

blueprint · product-delivery-route-optimization

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 24 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each route includes multiple drop points.
  • Travel times influenced by traffic conditions.
  • Vehicle type and load constraints applied.
  • Includes historical delivery performance ratings.
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
product-delivery-route-optimization

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