Comprehensive dataset of mobile ecommerce statistics including global sales percentages, conversion rates, traffic data, and growth trends from 2017-2025
Unlock the Power of Behavioural Data with GDPR-Compliant Clickstream Insights.
Swash clickstream data offers a comprehensive and GDPR-compliant dataset sourced from users worldwide, encompassing both desktop and mobile browsing behaviour. Here's an in-depth look at what sets us apart and how our data can benefit your organisation.
User-Centric Approach: Unlike traditional data collection methods, we take a user-centric approach by rewarding users for the data they willingly provide. This unique methodology ensures transparent data collection practices, encourages user participation, and establishes trust between data providers and consumers.
Wide Coverage and Varied Categories: Our clickstream data covers diverse categories, including search, shopping, and URL visits. Whether you are interested in understanding user preferences in e-commerce, analysing search behaviour across different industries, or tracking website visits, our data provides a rich and multi-dimensional view of user activities.
GDPR Compliance and Privacy: We prioritise data privacy and strictly adhere to GDPR guidelines. Our data collection methods are fully compliant, ensuring the protection of user identities and personal information. You can confidently leverage our clickstream data without compromising privacy or facing regulatory challenges.
Market Intelligence and Consumer Behaviuor: Gain deep insights into market intelligence and consumer behaviour using our clickstream data. Understand trends, preferences, and user behaviour patterns by analysing the comprehensive user-level, time-stamped raw or processed data feed. Uncover valuable information about user journeys, search funnels, and paths to purchase to enhance your marketing strategies and drive business growth.
High-Frequency Updates and Consistency: We provide high-frequency updates and consistent user participation, offering both historical data and ongoing daily delivery. This ensures you have access to up-to-date insights and a continuous data feed for comprehensive analysis. Our reliable and consistent data empowers you to make accurate and timely decisions.
Custom Reporting and Analysis: We understand that every organisation has unique requirements. That's why we offer customisable reporting options, allowing you to tailor the analysis and reporting of clickstream data to your specific needs. Whether you need detailed metrics, visualisations, or in-depth analytics, we provide the flexibility to meet your reporting requirements.
Data Quality and Credibility: We take data quality seriously. Our data sourcing practices are designed to ensure responsible and reliable data collection. We implement rigorous data cleaning, validation, and verification processes, guaranteeing the accuracy and reliability of our clickstream data. You can confidently rely on our data to drive your decision-making processes.
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The Google Merchandise Store sells Google branded merchandise. The data is typical of what you would see for an ecommerce website.
The sample dataset contains Google Analytics 360 data from the Google Merchandise Store, a real ecommerce store. The Google Merchandise Store sells Google branded merchandise. The data is typical of what you would see for an ecommerce website. It includes the following kinds of information:
Traffic source data: information about where website visitors originate. This includes data about organic traffic, paid search traffic, display traffic, etc. Content data: information about the behavior of users on the site. This includes the URLs of pages that visitors look at, how they interact with content, etc. Transactional data: information about the transactions that occur on the Google Merchandise Store website.
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What is the total number of transactions generated per device browser in July 2017?
The real bounce rate is defined as the percentage of visits with a single pageview. What was the real bounce rate per traffic source?
What was the average number of product pageviews for users who made a purchase in July 2017?
What was the average number of product pageviews for users who did not make a purchase in July 2017?
What was the average total transactions per user that made a purchase in July 2017?
What is the average amount of money spent per session in July 2017?
What is the sequence of pages viewed?
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
The dataset provides 12 months (August 2016 to August 2017) of obfuscated Google Analytics 360 data from the Google Merchandise Store , a real ecommerce store that sells Google-branded merchandise, in BigQuery. It’s a great way analyze business data and learn the benefits of using BigQuery to analyze Analytics 360 data Learn more about the data The data includes The data is typical of what an ecommerce website would see and includes the following information:Traffic source data: information about where website visitors originate, including data about organic traffic, paid search traffic, and display trafficContent data: information about the behavior of users on the site, such as URLs of pages that visitors look at, how they interact with content, etc. Transactional data: information about the transactions on the Google Merchandise Store website.Limitations: All users have view access to the dataset. This means you can query the dataset and generate reports but you cannot complete administrative tasks. Data for some fields is obfuscated such as fullVisitorId, or removed such as clientId, adWordsClickInfo and geoNetwork. “Not available in demo dataset” will be returned for STRING values and “null” will be returned for INTEGER values when querying the fields containing no data.This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
This is a E-commerce website logs data created for helping the data analysts to practice exploratory data analysis and data visualization. The dataset has data on when the website was accessed, IP address of the source, Country, language in which website was accessed, amount of sales made by that IP address.
Included columns:
Time and duration of of accessing the website
Country, Language & Platform in which it was accessed
No. of bytes used & IP address of the person accessing website
Sales or return amount of that person
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The ICONET project participates to the ORDP with anonymized data sets used in the specific use cases of the 4 Living Labs deployed to test the Physical Internet capabilities as Proof of Concept. The datasets correspond to real and synthetic data provided by the Living Lab leaders and relate to data from daily operations. Specifically, traffic information from the Port of Antwerp 'PI Hub centric Living Lab, Warehouse and Transport data from the Sonae 'PI e-Commerce centric' Living Lab and StockBooking 'PI Warehouse as a Service' Living lab. The data was used in simulation modelling to test, evaluate and validate the case studies' findings. All data published respect data management policies of the project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant Agreement No 769119. Project website: https://www.iconetproject.eu/
In 2025, the single country with the highest share of online traffic to shein.com was the United States. Brazil followed, ranking second with about 11.4 percent of shein.com web traffic coming from the country, followed by France with 6.46 percent.
Cart abandonment rates have been climbing steadily since 2014, after reaching an all-time high in 2013. In 2023, the share of online shopping carts that is being abandoned reached 70 percent for the first time since 2013. This is an increase of more than 10 percentage points compared to the start of the time period considered here. Mobiles vs. desktops When global consumers shop online, they spend considerably more when doing so on desktop computers. In December 2023, the average value of e-commerce purchases made through desktops was approximately 159 U.S. dollars. Purchases completed on mobiles and tablets were of comparable values, ranging between 100 and 105 U.S. dollars. Even though consumers spent more when conducting their shopping on computers, they were more inclined to add products to their shopping carts when using mobile devices. Ultimately, mobile devices provide a convenient and more accessible way to shop, but desktop computers remain the preferred choice for more expensive purchases. Where do consumers shop online? Across the globe, digital marketplaces are shoppers’ number-one online shopping destination. As of April 2024, some 29 percent of consumers voted marketplaces as their favorite e-commerce channel, followed by physical stores and retailer sites. Looking at which retailers’ global shoppers prefer to shop at, amazon.com emerged as the world's most popular online marketplace, based on share of visits. The U.S. portal accounted for around one-fifth of the global online marketplace's traffic in December 2023. Amazon's German and Japanese portal sites ranked third and fifth among the leading online marketplaces, further demonstrating Amazon's dominance over the market.
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Comprehensive dataset of mobile ecommerce statistics including global sales percentages, conversion rates, traffic data, and growth trends from 2017-2025