E-commerce datasets

Customer data, transactions, product catalogs

  • 68 ready-made datasets
  • 8 formats, Excel to Parquet
  • First download free
What the 68 cover1 square = 1 dataset
  • Packaging & sustainability19
  • Orders, returns & payments18
  • Carts & conversion14
  • Vendors & suppliers10
  • Reviews & recommendations7
Grouped by dataset title and tags.

68 datasets · page 3 of 3

Showing all 20 on this page

Carts & conversion

E-Commerce Cart Abandonment Data

User and session identifiers, cart contents, device and location data

This dataset provides detailed records of e-commerce cart abandonment events, including user and session identifiers, cart contents, device and location data, timing, and follow-up actions. It enables retailers to analyze abandonment patterns, optimize recovery strategies, and personalize user experiences to improve conversion rates.

21 cols

  • cart_created_datetime
  • cart_abandoned_datetime
  • total_cart_value
  • cart_category_summary
  • +17
Open in factory
total_cart_value
59.99
cart_category_summary
electronics:2,apparel:1
cart_duration_seconds
522

Reviews & recommendations

Online Product Review Classification

Online product reviews, each labeled with sentiment, product category

This dataset provides a comprehensive collection of online product reviews, each labeled with sentiment, product category, and detailed engagement metrics such as likes, comments, and shares. It is ideal for building sentiment analysis models, monitoring content for moderation, and understanding customer engagement trends across various product categories.

12 cols

  • product_category
  • review_text
  • review_rating
  • review_date
  • +8
Open in factory
product_category
electronics
review_rating
4.9
sentiment_label
positive

Carts & conversionTop 10 most opened

E-Commerce Cart Abandonment Patterns

User segments, device types, and recovery methods

This dataset provides detailed records of e-commerce shopping cart creation, abandonment events, and recovery outcomes, including user segments, device types, and recovery methods. It enables retailers to analyze cart abandonment patterns, identify key reasons for lost sales, and measure the effectiveness of recovery campaigns across different customer groups and channels.

18 cols

  • cart_abandoned
  • cart_abandoned_at
  • cart_recovered
  • cart_recovered_at
  • +14
Open in factory
cart_abandoned
false
total_cart_value
3200.5
user_segment
VIP

Reviews & recommendations

E-Commerce Product Recommendation Logs

E-commerce product recommendations, capturing user interactions

This dataset provides detailed logs of e-commerce product recommendations, capturing user interactions, engagement outcomes, and algorithm details for each recommendation event. It enables analysis of personalization effectiveness, user behavior, and click-through rates to optimize product discovery and recommendation strategies.

17 cols

  • recommendation_rank
  • product_category
  • product_price
  • algorithm_type
  • +13
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recommendation_rank
1
product_category
electronics
product_price
849.99

Carts & conversion

E-Commerce Session Conversion Data

Session-level logs for e-commerce platforms, detailing user interactions

This dataset provides granular session-level logs for e-commerce platforms, detailing user interactions, cart activity, conversion outcomes, and behavioral events. It enables retailers and analysts to identify conversion drivers, measure abandonment, and optimize the online shopping experience through actionable insights and predictive modeling.

24 cols

  • session_start_time
  • session_end_time
  • session_duration_seconds
  • conversion
  • +20
Open in factory
session_duration_seconds
3101
conversion
true
session_value
1422.5

Reviews & recommendationsTop 10 most opened

E-Commerce Reviews Sentiment Dataset

Review text, star ratings, sentiment labels

This dataset contains detailed e-commerce product reviews, including review text, star ratings, sentiment labels, and metadata such as helpful votes and verified purchase status. It is ideal for training and evaluating sentiment analysis models, understanding customer feedback, and powering recommendation engines. The rich structure supports both NLP research and practical business applications.

12 cols

  • review_title
  • review_text
  • sentiment_label
  • review_date
  • +8
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review_title
Amazing Sound Quality!
sentiment_label
positive
product_name
Wireless Bluetooth Earbuds

Carts & conversion

E-Commerce Purchase Sequences Dataset

Timestamped records of e-commerce user sessions

This dataset provides detailed, timestamped records of e-commerce user sessions, capturing every step of the shopper journey from browsing and searching to cart actions and purchases. Each event is linked to session, user, and product information, enabling comprehensive analysis for personalization, recommendation systems, and user behavior modeling. The dataset is ideal for developing and benchmarking algorithms that require sequential purchase and interaction data.

24 cols

  • session_start_time
  • session_end_time
  • device_type
  • browser
  • +20
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device_type
desktop
browser
Chrome
event_type
login

Reviews & recommendationsTop 10 most opened

Customer Product Review Dataset

Detailed ratings, review text, sentiment analysis

This dataset provides a comprehensive view of customer product reviews, including detailed ratings, review text, sentiment analysis, and user demographics such as age, gender, and location. It enables advanced sentiment analysis, natural language processing, and customer satisfaction research, making it ideal for businesses seeking to understand product perception and improve customer experience.

17 cols

  • review_title
  • review_text
  • customer_age
  • review_date
  • +13
Open in factory
review_title
Great Value!
customer_age
32
rating
5

Orders, returns & payments

Retail Purchase Transaction Records

Customer, product, store, and payment details

This dataset provides granular, item-level retail purchase transaction records, including customer, product, store, and payment details. It is ideal for mining sales patterns, segmenting customers, powering recommendation systems, and forecasting demand across retail locations. The schema supports robust analytics for operational and strategic retail decision-making.

20 cols

  • transaction_datetime
  • transaction_status
  • store_name
  • customer_loyalty_tier
  • +16
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transaction_status
completed
store_name
MetroMart Downtown
customer_loyalty_tier
Gold

Carts & conversion

Retail Customer Journey Sessions

Session-level insights into retail customer journeys

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.

20 cols

  • session_start_time
  • session_end_time
  • session_duration_seconds
  • customer_segment
  • +16
Open in factory
session_duration_seconds
622
customer_segment
new
device_type
mobile

Orders, returns & payments

Order Fulfillment Step Tracking

Step-by-step log of e-commerce order fulfillment processes

This dataset provides a detailed, step-by-step log of e-commerce order fulfillment processes, capturing timestamps, responsible parties, exceptions, and resolution actions for each phase. It enables granular tracking of operational performance, identification of bottlenecks, and systematic exception handling to optimize fulfillment workflows. Ideal for process improvement, root cause analysis, and service level monitoring in e-commerce logistics.

14 cols

  • step_sequence
  • step_name
  • step_status
  • step_started_at
  • +10
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step_sequence
1
step_name
Order Received
step_status
completed

Carts & conversionTop 10 most opened

Shopping Cart Abandonment Insights

Customer behavior, checkout progression, device and location context

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.

20 cols

  • abandoned
  • abandonment_stage
  • abandonment_reason
  • cart_value
  • +16
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abandoned
true
abandonment_stage
shipping
abandonment_reason
high shipping cost

Carts & conversion

Abandoned Cart Recovery Patterns

User identifiers, cart contents, abandonment timing, recovery outreach

This dataset provides detailed records of abandoned shopping carts in an e-commerce environment, including user identifiers, cart contents, abandonment timing, recovery outreach, and user response. It enables analysis of abandonment patterns, effectiveness of recovery campaigns, and identification of high-value recovery opportunities, supporting data-driven strategies for revenue recovery and customer re-engagement.

21 cols

  • cart_abandoned_at
  • cart_status
  • total_cart_value
  • recovery_action_taken
  • +17
Open in factory
cart_status
abandoned
total_cart_value
78.45
recovery_action_taken
false

Orders, returns & payments

Discount Redemption Behavior Dataset

Customer, order, discount, and campaign details

This dataset provides granular records of promotional discount redemptions in e-commerce, including customer, order, discount, and campaign details. It enables in-depth analysis of redemption patterns, campaign effectiveness, and customer segmentation to optimize future marketing strategies and drive sales growth.

17 cols

  • discount_code
  • discount_type
  • discount_value
  • discount_currency
  • +13
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discount_code
WELCOME10
discount_type
percentage
discount_value
10

Orders, returns & payments

Repeat Purchase Cohort Analysis

Customer retention and repeat purchase behavior by grouping customers into cohorts based

This dataset provides a detailed view of customer retention and repeat purchase behavior by grouping customers into cohorts based on their initial purchase date. It tracks key metrics such as repeat purchase rates, monetary value, and customer activity status, enabling businesses to evaluate the effectiveness of retention strategies and loyalty programs. The structure supports granular analysis of cohort performance over time.

12 cols

  • total_purchases
  • repeat_purchases
  • cohort_period
  • purchase_value_total
  • +8
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total_purchases
1
repeat_purchases
0
cohort_period
0

Carts & conversion

Customer Wishlist Item Trends

Customer wishlist activity, capturing each addition

This dataset provides granular records of customer wishlist activity, capturing each addition and removal of products along with customer demographics and product details. It enables in-depth analysis of product popularity, customer preferences, and demand forecasting, making it ideal for optimizing inventory, marketing strategies, and personalized recommendations.

14 cols

  • customer_age
  • event_type
  • event_datetime
  • product_category
  • +10
Open in factory
customer_age
28
event_type
add
product_category
Electronics

Carts & conversion

Sales Funnel Drop-off Points

Event-level tracking of user progression

This dataset provides detailed, event-level tracking of user progression and abandonment within an e-commerce sales funnel. It enables identification of high-drop-off stages, analysis of abandonment reasons, and segmentation by device, country, and referrer. Ideal for conversion optimization, funnel analysis, and user experience improvement.

14 cols

  • funnel_stage
  • stage_order
  • event_type
  • device_type
  • +10
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funnel_stage
Landing Page
stage_order
1
event_type
progress

Orders, returns & payments

Online Purchase Refund Analysis

Customer details, product and order references, refund reasons

This dataset provides a comprehensive record of online purchase refund requests, including customer details, product and order references, refund reasons, response times, and final resolutions. It enables in-depth analysis of refund patterns, operational response efficiency, and customer retention, supporting data-driven strategies to enhance customer satisfaction and reduce churn.

16 cols

  • refund_reason
  • refund_amount
  • refund_status
  • refund_method
  • +12
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refund_reason
Damaged Item
refund_amount
249.99
refund_status
Completed

Carts & conversion

Abandoned Cart Recovery

Customer identifiers, cart contents, timestamps, recovery attempts

This dataset provides detailed records of abandoned shopping carts from an e-commerce platform, including customer identifiers, cart contents, timestamps, recovery attempts, and outcomes. It enables in-depth analysis of cart abandonment patterns, campaign effectiveness, and customer behavior to optimize checkout processes and boost conversion rates.

18 cols

  • cart_abandoned_at
  • cart_total_value
  • recovered
  • recovered_at
  • +14
Open in factory
cart_total_value
87.45
recovered
false
recovery_channel
email

Reviews & recommendationsTop 10 most opened

Product Recommendation Dataset

Customer profiles, product details, session context

This dataset provides a detailed, transaction-level view of customer shopping behavior, including customer profiles, product details, session context, and the impact of personalized product recommendations. It is ideal for developing and evaluating recommendation systems, analyzing sales conversion, and understanding the effectiveness of targeted offers in retail environments.

32 cols

  • product_name
  • product_category
  • product_brand
  • product_price
  • +28
Open in factory
product_name
Smart Fitness Watch
product_category
Electronics
product_brand
FitPro

What’s inside. Column by column.

Columns and codes found in the sample rows of all 68 e-commerce datasets.

Most common columnsDatasets, of 68
  1. product_id27
  2. customer_id25
  3. order_id17
  4. product_name16
  5. user_id16
  6. device_type15
  7. supplier_name15
  8. session_id14
  9. supplier_id14
A person from the Product Recommendation Dataset datasetGenerated
customer_first_name
Alex
customer_last_name
Jones
customer_gender
male
shipping_city
New York

Generated

Standard codes in the sample rowsDatasets, of 68
  1. ISO 3166 countries43
  2. ISO 4217 currencies12

Not quite what you need? Describe it.

One sentence in. A dataset with that pattern out.

  • £5+ shipping: 2× abandonment
  • Real product categories
  • 3% missing basket values
Preview 20 rows freeNo signup. No card.
Abandonment by shipping cost
0%40%80%31%Free38%£1–566%£5+1
Sample rows for: Shopping sessions where carts with shipping over £5 are abandoned twice as often, with real product categories and 3% of basket values missing.
shipping_gbpcategorybasket_gbpabandoned
5.99Home & Garden64.20yes
0.00Beauty28.50no
6.49Electronics—yes
3.99Fashion41.00no

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