Shopping Cart Abandonment Insights

This dataset provides granular insights into shopping cart abandonment by capturing detailed session-level data, including customer behavior, checkout progression, device and location context, and abandonment reasons. It enables retailers to identify key drop-off points, analyze abandonment patterns, and recommend targeted website improvements to reduce lost revenue.

  • opened 11 times
  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Identifying and analyzing checkout drop-off points to optimize conversion rates

Sample rows

preview · 8 of 85 rows · all 20 columns
session_idstringabandonment_stagestringcart_valuefloatabandonedbooleanabandonment_reasonstringcustomer_idstringsession_start_timedatetimesession_end_timedatetimecart_item_countintegerdevice_typestringbrowserstringosstringgeolocation_countrystringgeolocation_regionstringentry_pagestringexit_pagestringtime_on_site_secondsintegerpromo_code_usedbooleanreturning_customerbooleanpayment_method_selectedstring
sess_1001shipping73.5truehigh shipping costcust_0012024-05-28T10:23:182024-05-28T10:41:492desktopChromeWindows 10USACalifornia/home/checkout/shipping1111falsetruenone
sess_1002cart24.99truejust browsingblank2024-05-28T12:14:002024-05-28T12:16:191mobileSafariiOSCanadaOntario/category/electronics/cart139falsefalsenone
sess_1003completed152.8falseblankcust_0022024-05-28T13:02:452024-05-28T13:25:135desktopFirefoxWindows 11USATexas/deals/summer/confirmation1348truetruecredit_card
sess_1004payment62truepayment failurecust_0032024-05-29T09:12:302024-05-29T09:15:402mobileChromeAndroidUKEngland/search?q=shoes/checkout/payment190falsefalsecredit_card
sess_1005cart18.95truefound better price elsewhereblank2024-05-29T11:45:022024-05-29T11:47:231tabletEdgeWindows 10AustraliaVictoria/category/books/cart141falsefalsenone
sess_1006completed87.45falseblankcust_0042024-05-29T15:10:092024-05-29T15:18:233mobileChromeAndroidUSANew York/product/12345/confirmation494falsefalsepaypal
sess_1007review205truesite crashedcust_0052024-05-29T18:23:552024-05-29T18:28:417desktopChromemacOSUSAWashington/home/checkout/review286truetruegoogle_pay
sess_1008completed45.25falseblankcust_0062024-05-30T08:10:012024-05-30T08:31:432desktopEdgeWindows 11USAIllinois/search?q=accessories/confirmation1302falsetrueapple_pay

What the 85 rows show

from the 85-row sample

Cart (abandonment stage) stands out: mean cart_value is 3.7, against 70.5 for the rest.

  • 56%abandoned = true
  • 45.3median cart_value
  • 3device types
  • 5payment method selecteds
  • 6browsers
  • 6exit pages
Mean cart_value by abandonment_stage85 rows
040803.7cart20 rows49.0shippi…9 rows75.6payment10 rows71.3review9 rows74.1comple…37 rows
cart_value85 rows, in bands of 25
0153028161712541020125225cart_value →

Median 45.3, from 0.0 to 220.0.

abandonment_reason48 rows with a value · 37 left blank
  1. just browsing11
  2. no intention to buy5
  3. high shipping cost4
  4. site crashed4
  5. payment declined4
  6. changed mind4
  7. slow site3
  8. card expired3
  9. payment failure2
  10. found better price elsewhere1
20 columns by typefrom the column list below
  • string 12
  • integer 2
  • float 1
  • datetime 2
  • boolean 3

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 12 columns
session_idstringUnique identifier for a customer's shopping session.uniquesess_1001
customer_idstringUnique identifier for the customer (can be anonymous or registered).optionalcust_001
abandonment_stagestringThe last checkout stage reached before abandonment (e.g., cart, shipping, payment, review).cart · shipping · payment · review · completed · optionalshipping
abandonment_reasonstringCaptured reason for abandonment if provided (e.g., high shipping cost, payment failure, slow site).optionalhigh shipping cost
device_typestringType of device used during the session (e.g., desktop, mobile, tablet).desktop · mobile · tablet · otherdesktop
browserstringWeb browser used during the session.6 browsers · optionalChrome
osstringOperating system of the device used.8 oses · optionalWindows 10
geolocation_countrystringCountry inferred from the user's IP address.optionalUSA
geolocation_regionstringRegion or state inferred from the user's IP address.optionalCalifornia
entry_pagestringURL or identifier of the first page visited in the session.optional/home
exit_pagestringURL or identifier of the last page visited before abandonment or checkout.6 pages · optional/checkout/shipping
payment_method_selectedstringPayment method selected during checkout, if any (e.g., credit_card, paypal, none).6 values · optionalnone
Numbers 3 columns
cart_valuefloatTotal value of items in the cart at the time of abandonment or checkout.0 or more73.5
cart_item_countintegerNumber of items in the cart at abandonment or checkout.0 or more2
time_on_site_secondsintegerTotal time spent on the site during the session, in seconds.0 or more1111
Dates and times 2 columns
session_start_timedatetimeTimestamp when the shopping session started.2024-05-28T10:23:18
session_end_timedatetimeTimestamp when the shopping session ended or was abandoned.2024-05-28T10:41:49
True or false 3 columns
abandonedbooleanIndicates if the cart was abandoned (true) or completed (false).true
promo_code_usedbooleanIndicates if a promo code was applied during the session.false
returning_customerbooleanIndicates if the customer has shopped before (true) or is new (false).optionaltrue

Use it for

  • abandoned56%48 of 85 rowsmean cart value by ab…3.7cart49.0ship…75.6paym…71.3revi…

    An e-commerce dashboard

    The abandoned rate, cart_value by abandonment_stage and a breakdown of abandonment_reason. Excel, Power BI or Tableau.

  • Why do the 20 cart rows have a mean cart_value of 3.7?

    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 sessions with customer_id, session_start_time and session_end_time to fill a screen in front of a buyer.

Not quite right?

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This dataset85 rows20 columns
Yours10,000 rows20 columnsgeolocation_country: UK only

blueprint · shopping-cart-abandonment-insights

Behind this dataset

Same schema. As many rows as you need.

These 85 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
  • Capture session and item details for each abandonment
  • Log timestamp and device type
  • Identify if user is returning or new
  • Flag carts abandoned after adding 2+ items
  • Link abandonment to marketing source if available
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
shopping-cart-abandonment-insights

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