E-commerce Vendor Disruption Alerts

This dataset tracks real-time disruption alerts affecting e-commerce vendors, detailing the nature, severity, and geographic scope of events such as extreme weather, geopolitical incidents, and supply chain breakdowns. It enables SMB operators to monitor supplier risk, assess order impact, and coordinate timely responses to ensure business continuity and customer satisfaction.

  • last updated 15 Dec 2025
  • by GoMask
The brief that made it

Supplier risk assessment and monitoring

Sample rows

preview · 8 of 60 rows · all 16 columns
alert_idstringdisruption_severitystringexpected_delay_daysintegervendor_contact_emailstringvendor_idstringvendor_namestringalert_datetimedatetimedisruption_typestringdisruption_subtypestringaffected_regionsstringorder_ids_impactedstringalert_statusstringresolution_datetimedatetimecreated_bystringlast_updated_datetimedatetimeresolution_notesstring
ALRT_001A23B4moderate4contact@brightgoods.comVEND_1001BrightGoods2024-05-01T09:22:00weatherfloodLouisiana, MississippiORD_301,ORD_302,ORD_303activeblanksystem_auto2024-05-01T12:15:00blank
ALRT_002B45C7severe7sales@urbanstyle.netVEND_1002UrbanStyle2024-05-03T11:10:00supply_chainshortageCaliforniaORD_501,ORD_502resolved2024-05-10T09:05:00jdoe_ops2024-05-10T09:06:00Alternative supplier sourced, orders rerouted.
ALRT_003D67F8critical13info@ecomart.orgVEND_1003EcoMart2024-05-04T13:48:00geopoliticalembargoRussia, Ukraineblankactiveblanksystem_auto2024-05-04T13:52:00blank
ALRT_004E89G2moderate3support@technova.ioVEND_1004TechNova2024-05-05T08:00:00supply_chainstrikeNew JerseyORD_701,ORD_702monitoringblankamartinez2024-05-05T08:15:00blank
ALRT_005F12H4minor0service@petrahome.comVEND_1005PetraHome2024-05-06T14:13:00othersystem outageblankblankresolved2024-05-06T15:10:00system_auto2024-05-06T15:12:00IT team restored service within 1 hour.
ALRT_006H34J6severe8hello@novacrafts.comVEND_1006NovaCrafts2024-05-07T10:30:00weathertornadoKansas, OklahomaORD_901,ORD_902,ORD_903,ORD_904activeblanksystem_auto2024-05-07T10:45:00blank
ALRT_007J56K8critical15admin@greenleaf.bizVEND_1007GreenLeaf2024-05-07T15:55:00geopoliticaltrade banChinaORD_1101activeblankkchan_ops2024-05-07T16:00:00blank
ALRT_008K78M0severe10rapidmart@info.comVEND_1008RapidMart2024-05-08T11:22:00supply_chainport closureLos AngelesORD_1201,ORD_1202activeblanksystem_auto2024-05-08T11:25:00blank

What the 60 rows show

from the 60-row sample

Critical (disruption severity) stands out: mean expected_delay_days is 12.9, against 4.7 for the rest.

  • 6median expected_delay_days
  • 3alert statuses
  • 4disruption types
  • 9created_by values
Mean expected_delay_days by disruption_severity60 rows
010200.67minor12 rows3.9moderate18 rows8.5severe16 rows12.9critical14 rows
expected_delay_days60 rows, in bands of 2
06121289776442101020expected_delay_days →

Median 6, from 0 to 20.

vendor_contact_email55 rows with a value · 5 left blank
  1. [email protected]3
  2. [email protected]3
  3. [email protected]3
  4. [email protected]3
  5. [email protected]3
  6. [email protected]3
  7. [email protected]3
  8. [email protected]3
  9. [email protected]2
  10. [email protected]2
16 columns by typefrom the column list below
  • string 12
  • integer 1
  • datetime 3

Columns

16 columns in three groups
blueprint · 16 columns
columntypedescriptionexample
Text 12 columns
alert_idstringUnique identifier for each disruption alertuniqueALRT_001A23B4
vendor_idstringUnique identifier for the affected e-commerce vendorVEND_1001
vendor_namestringName of the affected e-commerce vendorBrightGoods
vendor_contact_emailstringPrimary contact email for the vendoroptionalcontact@brightgoods.com
disruption_typestringType of disruption impacting the vendor (e.g., weather, geopolitical, supply_chain)weather · geopolitical · supply_chain · otherweather
disruption_subtypestringSpecific subtype or cause of the disruption (e.g., hurricane, strike, embargo, shortage)optionalflood
disruption_severitystringSeverity level of the disruption (e.g., minor, moderate, severe, critical)minor · moderate · severe · criticalmoderate
affected_regionsstringComma-separated list of regions or countries impacted by the disruptionoptionalLouisiana, Mississippi
order_ids_impactedstringComma-separated list of impacted order IDs for the vendoroptionalORD_301,ORD_302,ORD_303
alert_statusstringCurrent status of the alert (e.g., active, resolved, monitoring)active · resolved · monitoringactive
resolution_notesstringDetailed notes or actions taken to resolve the disruptionoptionalSecurity patch applied.
created_bystringIdentifier or name of the user/system that created the alert9 valuessystem_auto
Numbers 1 column
expected_delay_daysintegerEstimated number of days the disruption will delay order fulfillment0 or more · optional4
Dates and times 3 columns
alert_datetimedatetimeDate and time when the disruption alert was issued2024-05-01T09:22:00
resolution_datetimedatetimeDate and time when the disruption was resolved (if applicable)optional2024-05-10T09:05:00
last_updated_datetimedatetimeTimestamp of the last update to the alert record2024-05-01T12:15:00

Use it for

  • median expecte…660 rowsmean expected delay d…0.67minor3.9mode…8.5seve…12.9crit…

    An e-commerce dashboard

    Expected_delay_days by disruption_severity and a breakdown of vendor_contact_email. Excel, Power BI or Tableau.

  • Why do the 14 critical rows have a mean expected_delay_days of 12.9?

    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 alerts with vendor_id, vendor_name and vendor_contact_email to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 16 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 dataset60 rows16 columns
Yours1,000 rows16 columns

blueprint · e-commerce-vendor-disruption-alerts

Behind this dataset

Same schema. As many rows as you need.

These 60 rows came out of a blueprint — 16 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 alert must specify disruption type and severity
  • Vendor region and affected SKU(s) are required
  • Resolution status updated within 48 hours of disruption
  • Disruption cause must be categorized (weather, logistics, regulatory, other)
  • Timestamp and remediation actions are mandatory for each event
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
e-commerce-vendor-disruption-alerts

More in E-commerce

Browse all
Also in E-commerceEco-Friendly Packaging Adoption TrackerOnline Retail Product Return AnalyticsE-Commerce Cart Abandonment DataAll 1,958 datasets

What should your data show?

Preview 20 rows free
No signup. No card.