Retail Customer Journey Sessions

This dataset provides granular, session-level insights into retail customer journeys, capturing browsing patterns, cart interactions, and purchase outcomes. It enables comprehensive analysis of customer behavior across devices and segments, supporting sales optimization, conversion funnel analysis, and targeted marketing strategies.

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

Analyzing customer browsing and purchase patterns to optimize conversion funnels

Sample rows

preview · 8 of 200 rows · all 20 columns
session_idstringexit_page_urlstringpages_viewedintegerpurchase_madebooleanbrowserstringcustomer_idstringsession_start_timedatetimesession_end_timedatetimedevice_typestringentry_page_urlstringcart_add_countintegercart_remove_countintegercart_valuefloatpurchase_valuefloatproducts_purchased_countintegersession_duration_secondsintegercustomer_segmentstringcountrystringcitystringreferrer_urlstring
sess-00001/checkout6trueSafaricust-0012023-07-03T09:18:01Z2023-07-03T09:28:23Zmobile/promo/summer-sale2089.9989.992622newUnited KingdomLondonhttps://www.instagram.com/ad/promo1
sess-00002/2falseChromecust-0022023-07-05T18:12:45Z2023-07-05T18:14:20Zdesktop/0000095unknownUnited StatesSan Franciscoblank
sess-00003/cart7falseChromecust-0032023-07-07T13:33:01Z2023-07-07T13:38:20Ztablet/landing/tablet-offer31115.500319returningAustraliaSydneyhttps://mail.yahoo.com/mail/?campaign=promo
sess-00004/checkout19trueOperacust-0042023-07-08T16:02:00Z2023-07-08T16:57:01Zdesktop/products/electronics522149.992149.9933301VIPSingaporeSingaporehttps://partnerdeal.com/aff?code=vip1
sess-00005/login2falseChromecust-0052023-07-01T11:21:10Z2023-07-01T11:23:05Zmobile/00000115unknownIndiaMumbaiblank
sess-00006/cart12trueChromecust-0062023-07-10T07:55:30Z2023-07-10T08:09:44Zdesktop/search?q=laptop41489391.22854returningGermanyBerlinhttps://www.google.com/search?q=shop+electronics
sess-00007/cart5falseSamsung Internetcust-0072023-07-03T22:34:12Z2023-07-03T22:36:19Zmobile/promo/summer-sale1049.9900127newUnited StatesNew Yorkhttps://www.facebook.com/link?adid=summer
sess-00008/8falseSafaricust-0082023-07-05T12:09:59Z2023-07-05T12:28:44Ztablet/landing/tablet-promo20149.5001065returningFranceParishttps://mail.google.com/mail/u/0/#inbox/promo2

What the 200 rows show

from the 200-row sample

/checkout (exit page url) stands out: mean pages_viewed is 18.2, against 5.5 for the rest.

  • 47%purchase_made = true
  • 6median pages_viewed
  • 4device types
  • 4customer segments
  • 36countries
  • 2median cart_add_count
Mean pages_viewed by exit_page_url200 rows
010208.1/cart86 rows2.7/65 rows18.2/checkout40 rows1.2/login9 rows
pages_viewed200 rows, in bands of 2.5
03060592630102411149125012.525pages_viewed →

Median 6, from 1 to 25.

browser179 rows with a value · 21 left blank
  1. Chrome92
  2. Safari43
  3. Opera10
  4. Edge9
  5. Firefox8
  6. Samsung Internet7
  7. Brave6
  8. Unknown3
  9. UC Browser1
20 columns by typefrom the column list below
  • string 10
  • integer 5
  • float 2
  • datetime 2
  • boolean 1

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 10 columns
session_idstringUnique identifier for each customer sessionuniquesess-00001
customer_idstringUnique identifier for the customer (anonymized if needed)cust-001
device_typestringType of device used during the session (e.g., desktop, mobile, tablet)desktop · mobile · tablet · othermobile
browserstringBrowser used during the session (e.g., Chrome, Safari, Firefox)9 browsers · optionalSafari
referrer_urlstringURL of the referring site or campaign that led to the sessionoptionalhttps://www.direct.com/
entry_page_urlstringURL of the first page visited in the session/promo/summer-sale
exit_page_urlstringURL of the last page visited in the session4 urls · optional/checkout
customer_segmentstringCustomer segment or type (e.g., new, returning, VIP)new · returning · VIP · unknown · optionalnew
countrystringCountry from which the session originatedoptionalUnited Kingdom
citystringCity from which the session originatedoptionalLondon
Numbers 7 columns
pages_viewedintegerTotal number of pages viewed during the session1 or more6
cart_add_countintegerNumber of items added to cart during the session0 or more2
cart_remove_countintegerNumber of items removed from cart during the session0 or more0
cart_valuefloatTotal value of items in the cart at session end (in store currency)0 or more · optional89.99
purchase_valuefloatTotal value of the purchase made during the session (0 if no purchase)0 or more89.99
products_purchased_countintegerNumber of products purchased in the session (0 if no purchase)0 or more2
session_duration_secondsintegerTotal duration of the session in seconds1 or more622
Dates and times 2 columns
session_start_timedatetimeTimestamp when the customer session started2023-07-03T09:18:01Z
session_end_timedatetimeTimestamp when the customer session ended2023-07-03T09:28:23Z
True or false 1 column
purchase_madebooleanIndicates if a purchase was completed during the sessiontrue

Use it for

  • purchase made47%93 of 200 rowsmean pages viewed by …8.1/cart2.7/18.2/che…1.2/log…

    An e-commerce dashboard

    The purchase_made rate, pages_viewed by exit_page_url and a breakdown of browser. Excel, Power BI or Tableau.

  • Why do the 40 /checkout rows have a mean pages_viewed of 18.2?

    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?

Make it yours.

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

Preview 20 rows free

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

blueprint · retail-customer-journey-sessions

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
  • Session includes sequential event logs.
  • Sessions linked to anonymized customer IDs.
  • Purchase completion annotated per session.
  • Device and channel recorded per event.
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
retail-customer-journey-sessions

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