E-commerce Cart Abandonment Events

This dataset provides detailed records of e-commerce shopping cart abandonment events, including session identifiers, product details, user context, timing, and recovery outcomes. It enables in-depth analysis of abandonment patterns, user behavior, and the effectiveness of recovery strategies, making it valuable for optimizing conversion rates and customer retention.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Analyzing cart abandonment factors and patterns

Sample rows

preview · 8 of 200 rows · all 20 columns
abandonment_idstringdevice_typestringcart_item_countintegerrecovery_email_sentbooleanbrowserstringsession_idstringuser_idstringcart_created_atdatetimecart_abandoned_atdatetimetime_elapsed_minutesfloatproduct_idsstringproduct_namesstringtotal_cart_valuefloatcurrencystringuser_countrystringuser_citystringrecovery_email_sent_atdatetimerecoveredbooleanrecovered_atdatetimeabandonment_reasonstring
ABD00001mobile2trueChromeSESS-101-AUSR-1001-X2024-05-01T09:13:27Z2024-05-01T09:23:40Z10.22PRD-9884,PRD-8821Wireless Earbuds,Phone Charger62.5USDUSNew York2024-05-01T09:28:12ZfalseblankUser left site
ABD00002tablet1falseSafariSESS-102-Bblank2024-05-02T11:57:13Z2024-05-02T12:01:10Z3.95PRD-7712Bluetooth Mouse22.95NZDNZAucklandblankfalseblankApp crash
ABD00003desktop3trueFirefoxSESS-103-CUSR-1002-Y2024-05-03T14:42:50Z2024-05-03T15:10:07Z27.28PRD-8811,PRD-6623,PRD-5532Yoga Mat,Water Bottle,Running Shoes74.8USDUSChicago2024-05-03T15:13:10Ztrue2024-05-04T13:58:25ZNo promo code
ABD00004other1falseblankSESS-104-Dblank2024-05-04T10:21:33Z2024-05-04T10:22:15Z0.7PRD-7101Travel Adapter13.39GBPGBLondonblankfalseblankblank
ABD00005mobile2trueChromeSESS-105-EUSR-1003-Z2024-05-05T16:03:11Z2024-05-05T16:33:29Z30.3PRD-4445,PRD-9932Graphic T-Shirt,Denim Jeans85USDUSSan Francisco2024-05-05T16:36:54ZfalseblankUser left site
ABD00006tablet2falseOperaSESS-106-Fblank2024-05-06T13:31:45Z2024-05-06T13:35:00Z3.25PRD-2211,PRD-3344USB Cable,Phone Case18.9INRINMumbaiblankfalseblankSite error
ABD00007desktop3trueChromeSESS-107-GUSR-1004-A2024-05-07T19:04:12Z2024-05-07T19:18:58Z14.77PRD-8712,PRD-8765,PRD-5512Organic Tea,Coffee Mug,Laptop Sleeve58.3USDUSAustin2024-05-07T19:20:13ZfalseblankDistracted
ABD00008other1falseblankSESS-108-Hblank2024-05-08T07:29:36Z2024-05-08T07:30:02Z0.43PRD-1134Desk Lamp12.1EURDEBerlinblankfalseblankblank

What the 200 rows show

from the 200-row sample

Mobile (device type) stands out: mean cart_item_count is 3.5, against 1.8 for the rest.

  • 52%recovery_email_sent = true
  • 2median cart_item_count
  • 11currencies
  • 12user countries
  • 13abandonment reasons
  • 11.4median time_elapsed_minutes
Mean cart_item_count by device_type200 rows
0242.5desktop66 rows3.5mobile39 rows1.4tablet79 rows1.0other16 rows
cart_item_count200 rows, in bands of 1
040806679311275147cart_item_count →

Median 2, from 1 to 7.

browser153 rows with a value · 47 left blank
  1. Chrome78
  2. Firefox24
  3. Safari22
  4. Opera17
  5. Samsung Internet12
20 columns by typefrom the column list below
  • string 11
  • integer 1
  • float 2
  • datetime 4
  • boolean 2

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 11 columns
abandonment_idstringUnique identifier for each cart abandonment eventuniqueABD00001
session_idstringUnique identifier for the user's session during which the cart was abandonedSESS-101-A
user_idstringUnique identifier for the user (can be null for guest users)optionalUSR-1001-X
product_idsstringComma-separated list of product IDs in the abandoned cartPRD-9884,PRD-8821
product_namesstringComma-separated list of product names in the abandoned cartBluetooth Mouse
currencystringCurrency code for the cart value (ISO 4217 format)11 currenciesUSD
device_typestringType of device used during the session (e.g., desktop, mobile, tablet)desktop · mobile · tablet · othermobile
browserstringBrowser used during the session5 browsers · optionalChrome
user_countrystringCountry code of the user at the time of abandonment (ISO 3166-1 alpha-2)12 countries · optionalUS
user_citystringCity of the user at the time of abandonmentoptionalNew York
abandonment_reasonstringReason for abandonment if known (e.g., payment issue, high shipping cost, user left site)optionalUser left site
Numbers 3 columns
time_elapsed_minutesfloatTime in minutes between cart creation and abandonment0 or more10.22
total_cart_valuefloatTotal monetary value of the abandoned cart0 or more62.5
cart_item_countintegerNumber of items in the abandoned cart1 or more2
Dates and times 4 columns
cart_created_atdatetimeTimestamp when the shopping cart was created2024-05-01T09:13:27Z
cart_abandoned_atdatetimeTimestamp when the cart was abandoned2024-05-01T09:23:40Z
recovery_email_sent_atdatetimeTimestamp when the recovery email was sent (if applicable)optional2024-05-01T09:28:12Z
recovered_atdatetimeTimestamp when the cart was recovered (if applicable)optional2024-05-04T13:58:25Z
True or false 2 columns
recovery_email_sentbooleanIndicates if a cart recovery email was sent to the usertrue
recoveredbooleanIndicates if the abandoned cart was later recovered (i.e., purchase completed)false

Use it for

  • recovery email…52%103 of 200 rowsmean cart item count …2.5desk…3.5mobi…1.4tabl…1.0other

    An e-commerce dashboard

    The recovery_email_sent rate, cart_item_count by device_type and a breakdown of browser. Excel, Power BI or Tableau.

  • Why do the 39 mobile rows have a mean cart_item_count of 3.5?

    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 abandonments with session_id, user_id and cart_created_at to fill a screen in front of a buyer.

Not quite right?

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

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This dataset200 rows20 columns
Yours1,000 rows20 columnsuser_country: UK only

blueprint · e-commerce-cart-abandonment-events

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 20 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 row corresponds to an abandoned cart
  • User session anonymized
  • Product IDs and quantities listed
  • Time spent before abandonment tracked
  • Device and channel noted
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
e-commerce-cart-abandonment-events

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