Product Recommendations Clickstream

This dataset records detailed user interactions with product recommendations on e-commerce platforms, including click events, session information, device context, and recommendation metadata. It enables businesses to analyze user behavior, optimize recommendation algorithms, and improve conversion rates by understanding which products and placements drive engagement.

  • opened 7 times
  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Improving recommendation engine accuracy and relevance

Sample rows

preview · 8 of 200 rows · all 13 columns
event_idstringdevice_typestringposition_in_recommendationintegerclickedbooleancountrystringuser_idstringsession_idstringevent_timestampdatetimeproduct_idstringrecommendation_idstringreferrer_urlstringuser_agentstringpage_urlstring
evt_00001desktop1trueUSuser_101sess_a12022-12-31T23:59:59Zprod_ZX01rec_set_01https://www.google.com/search?q=shoesMozilla/5.0 (Windows NT 10.0; Win64; x64)https://shop.example.com/product/ZX01
evt_00002mobile2falseINuser_102sess_b12023-06-30T00:00:00Zprod_YQ77rec_algo_alphahttps://facebook.comMozilla/5.0 (Linux; Android 11; Pixel 5)https://shop.example.com/recommendations?cat=summer
evt_00003tablet3trueDEuser_103sess_c12024-02-29T23:59:59Zprod_KL22rec_set_02blankMozilla/5.0 (iPad; CPU OS 14_2 like Mac OS X)https://shop.example.com/product/KL22
evt_00004desktopblankfalseGBuser_104sess_d12023-01-01T00:00:01Zprod_MN88blankblankMozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7)https://shop.example.com/error
evt_00005mobile5trueJPuser_105sess_e22023-03-15T16:45:00Zprod_BC35rec_set_03https://instagram.comMozilla/5.0 (iPhone; CPU iPhone OS 14_2 like Mac OS X)https://shop.example.com/recommendations?cat=spring
evt_00006tablet10falseRUuser_106sess_f12022-11-11T11:11:11Zprod_TT09rec_algo_betahttps://twitter.comMozilla/5.0 (Android 10; Tablet; rv:68.0)https://shop.example.com/product/TT09
evt_00007desktop1trueUSuser_101sess_a22022-12-25T08:00:00Zprod_QW51rec_set_04https://www.bing.comMozilla/5.0 (Windows NT 10.0; Win64; x64)https://shop.example.com/product/QW51
evt_00008mobileblankfalseARuser_107sess_g12023-02-14T14:14:14Zprod_LV21blankblankMozilla/5.0 (Linux; Android 10; SM-G970F)https://shop.example.com/specials/valentine

What the 200 rows show

from the 200-row sample

Tablet (device type) stands out: mean position_in_recommendation is 46.8, against 6.2 for the rest.

  • 50%clicked = true
  • 3median position_in_recommendation
Mean position_in_recommendation by device_type154 rows
040806.2desktop76 rows6.3mobile45 rows46.8tablet33 rows
position_in_recommendation154 rows, in bands of 10
06012012012000800014050100position_in_recommendation →

Median 3, from 1 to 100.

country163 rows with a value · 37 left blank
  1. US26
  2. GB16
  3. RU16
  4. JP12
  5. NG12
  6. IN11
  7. CA9
  8. SG9
  9. AU9
  10. SE8
13 columns by typefrom the column list below
  • string 10
  • integer 1
  • datetime 1
  • boolean 1

Columns

13 columns in four groups
blueprint · 13 columns
columntypedescriptionexample
Text 10 columns
event_idstringUnique identifier for each clickstream eventuniqueevt_00001
user_idstringUnique identifier for the user who generated the eventuser_101
session_idstringIdentifier for the user's browsing sessionsess_a1
product_idstringUnique identifier for the product that was recommended or clickedprod_ZX01
recommendation_idstringIdentifier for the recommendation set or algorithm that generated the product recommendationoptionalrec_set_01
device_typestringType of device used by the user (e.g., desktop, mobile, tablet)desktop · mobile · tablet · optionaldesktop
user_agentstringBrowser or app user agent string for the sessionoptionalMozilla/5.0 (Windows NT 1…
referrer_urlstringURL from which the user navigated to the recommendationoptionalhttps://facebook.com
page_urlstringURL of the page where the recommendation was displayedhttps://shop.example.com/…
countrystringCountry of the user at the time of the event (if available)optionalUS
Numbers 1 column
position_in_recommendationintegerPosition of the product in the recommended list (e.g., 1 for top recommendation)1 or more · optional1
Dates and times 1 column
event_timestampdatetimeDate and time when the click event occurred2022-12-31T23:59:59Z
True or false 1 column
clickedbooleanIndicates whether the recommended product was clicked by the usertrue

Use it for

  • clicked50%100 of 200 rowsmean position in reco…6.2desktop6.3mobile46.8tablet

    An e-commerce dashboard

    The clicked rate, position_in_recommendation by device_type and a breakdown of country. Excel, Power BI or Tableau.

  • Why do the 33 tablet rows have a mean position_in_recommendation of 46.8?

    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 events with user_id, session_id and event_timestamp to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 13 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows13 columns
Yours10,000 rows13 columnscountry: UK only

blueprint · product-recommendations-clickstream

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 13 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
  • Track user clicks on recommendations
  • Include session length and device type
  • Exclude non-product page views
  • Label successful conversions
Rows
Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

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

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