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Cross-Border E-commerce User Log Data
E-commerce & Online Transactions
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About
Data provides detailed logs from an e-commerce website, capturing user interaction metrics vital for analysing global retail strategy. This material reflects the ongoing shift in consumer behaviour, where inflationary pressures and rising living costs prompt global consumers to seek the best deals online and across borders. E-commerce is recognised as a key retail channel generating strong revenue, meaning manufacturers must establish strategies to boost online sales momentum and continue growth. The logs include detailed information on access dates, session durations, network protocols used, and critical demographic details. This resource helps brands test product performance across different platforms and markets, supporting strategic investment in advertising and promotions to maximise overall Return on Investment (ROI). Global online shopping festivals are considered a crucial strategic tool for transforming the e-commerce evolution.
Columns
The dataset contains 10 of the original 15 columns across 173,000 records:
- accessed_date: The date and time of the access event. Dates span from 14 March 2017 to 22 March 2017.
- duration_(secs): The duration of the session in seconds. Values range from 1,500 to 5,000, with a mean duration of 3,250 seconds. This field is 100% valid.
- network_protocol: The protocol used for access. TCP is the most common (74%), followed by HTTP (20%). There are 4 unique protocol values. This field is 100% valid.
- ip: The anonymised IP address used for access, containing approximately 137k unique values. This field is 100% valid.
- bytes: The size of data transferred in bytes. Values range from 28 to 933,000 bytes, with a mean size of 1.54k bytes. This field is 100% valid.
- accessed_Ffom: The platform or device used for access. The Android App is the most common platform (22%) among 8 unique values. This field is 100% valid.
- age: The age information of the user. The value '0' is the most frequent category (42%) among 54 unique values. This field is 100% valid.
- gender: The gender of the user. Female is the most common category (54%), followed by Male (36%). This field is 100% valid.
- country: The country of access. There are 27 unique countries recorded, with IT (Italy) being the most frequent entry (20%). This field is 100% valid.
- membership: The user's membership status. Premium is the most common status (62%), followed by Normal (29%). This field is 100% valid.
Distribution
The material is distributed as a single CSV file named
E-commerce Website Logs new.csv, which is 19.12 MB in size. The dataset provides 173,000 records. All included columns are 100% valid, meaning there are zero mismatched or missing records in these fields. The expected update frequency is Annually.Usage
This resource is designed to support brands and manufacturers in capitalising on global online shopping festivals and events. It is useful for testing and tracking product performance across different markets and platforms. Users can employ the data to help decide where to allocate resources and invest in advertising and promotions, thereby improving overall business ROI. The data also supports exploration of cross-border opportunities. Advanced applications include analysis using Data Visualization, Data Analytics, Computer Vision, and BigQuery.
Coverage
The data covers e-commerce website access logs. The temporal scope spans from 14 March 2017 to 22 March 2017. Geographic coverage includes users accessing the platform from 27 unique countries. The content details user interaction metrics, network specifics, and demographic data including age, gender, and membership status.
License
CC0: Public Domain
Who Can Use It
The dataset is intended for manufacturers, brands, and analysts. It is highly valuable for those seeking cross-border opportunities or those working in business strategy, data analytics, and data visualization who aim to boost online sales growth. The material holds a maximum usability rating of 10.00.
Dataset Name Suggestions
- Global E-commerce Website Access Logs 2017
- Retail Strategy and Online Shopping Metrics
- Cross-Border E-commerce User Log Data
Attributes
Original Data Source: Cross-Border E-commerce User Log Data
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