Dataset Overview

This dataset provides detailed information on website traffic, including page views, session duration, bounce rate, traffic source, time spent on page, previous visits, and conversion rate.

Dataset Description

• Page Views: The number of pages viewed during a session.
• Session Duration: The total duration of the session in minutes.
• Bounce Rate: The percentage of visitors who navigate away from the site after viewing only one page.
• Traffic Source: The origin of the traffic (e.g., Organic, Social, Paid).
• Time on Page: The amount of time spent on the specific page.
• Previous Visits: The number of previous visits by the same visitor.
• Conversion Rate: The percentage of visitors who completed a desired action (e.g., making a purchase).

Data Summary

• Total Records: 2000
• Total Features: 7

Key Features

1. Page Views: This feature indicates the engagement level of the visitors by showing how many pages they visit during their session.
2. Session Duration: This feature measures the length of time a visitor stays on the website, which can indicate the quality of the content.
3. Bounce Rate: A critical metric for understanding user behavior. A high bounce rate may indicate that visitors are not finding what they are looking for.
4. Traffic Source: Understanding where your traffic comes from can help in optimizing marketing strategies.
5. Time on Page: This helps in analyzing which pages are retaining visitors' attention the most.
6. Previous Visits: This can be used to analyze the loyalty of visitors and the effectiveness of retention strategies.
7. Conversion Rate: The ultimate metric for measuring the effectiveness of the website in achieving its goals.

Usage

This dataset can be used for various analyses such as:

• Identifying key drivers of engagement and conversion.
• Analyzing the effectiveness of different traffic sources.
• Understanding user behavior patterns and optimizing the website accordingly.
• Improving marketing strategies based on traffic source performance.
• Enhancing user experience by analyzing time spent on different pages.

Acknowledgments

This dataset was generated for educational purposes and is not from a real website. It serves as a tool for learning data analysis and machine learning techniques.

Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly

DISCLAIMER- I DO NOT OWN THIS DATASET. THIS IS BEING USED ONLY FOR THE SAKE OF THE NOTEBOOK. This dataset contains data about the daily traffic on a website, in a given time period. It has only 2 columns, the first being the 'date' column and the second being the 'number of visits' column. It is a pretty simple dataset, so it wouldn't require much cleaning and preprocessing. There might be few 'nan' values, so you ought to fill/drop them at your convenience. If you like the data, please do upvote as it helps me out. Thank you, and have a great time.

Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

This dataset provides detailed insights into website traffic metrics and user engagement statistics, collected from SimilarWeb. The data includes information on various websites, such as rank, category, average visit duration, pages per visit, and bounce rate. This data aims to facilitate an understanding of online behavior and performance trends across different sectors, making it a valuable resource for researchers, marketers, and data analysts. The dataset is ideal for exploring patterns in web traffic and user interaction and conducting comparative analyses across various website categories.

Important Warning: Running this code within Kaggle may result in a ban, as scraping activities are prohibited on the platform. There is no guarantee that any ban will be lifted, as Kaggle staff may interpret scraping as a denial-of-service attack. Although I have implemented measures to reduce server load, such as adding sleep intervals, it is advisable to run this code locally to ensure compliance with Kaggle's policies.

Explore the Website Traffic Dataset featuring structured analytics data including page views, session duration, bounce rate, traffic sources, user behavior metrics, and conversion rates. Suitable for AI-driven marketing analytics, predictive modeling, and performance optimization.

The Global Web Traffic Dataset is a synthetic dataset simulating 2,000 website visits from users across 20 countries. Each record represents a unique visit and includes date, country, traffic source, device type, browser, page visited, session duration, pages viewed, bounce, and conversion.

This dataset is programmatically generated to mimic realistic user behavior. Devices, traffic sources, session durations, pages viewed, bounce rates, and conversions are generated using probability-weighted sampling and realistic ranges. All data is synthetic, containing no personal or sensitive information, making it safe and reusable for educational and professional purposes.

Intended Uses:

Exploratory Data Analysis (EDA): Identify trends in global web traffic.

Data Visualization: Build dashboards, heatmaps, and charts.

Machine Learning Practice: Train models for predicting bounce, session duration, or conversions.

Educational & Research Projects: Learn web analytics, user behavior modeling, or data preprocessing.

Web traffic statistics for the top 2000 most visited pages on nyc.gov by month.

This dataset was used in the Kaggle Wikipedia Web Traffic forecasting competition. It contains 145063 daily time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-10.

The original dataset contains missing values. They have been simply replaced by zeros.

This dataset contains 145063 time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2022-06-30. This is an extended version of the dataset that was used in the Kaggle Wikipedia Web Traffic forecasting competition. For consistency, the same Wikipedia pages that were used in the competition have been used in this dataset as well.The colons (:) in article names have been replaced by dashes (-) to make the .tsf file readable using ourdata loaders.

The original dataset contains missing values. They have been simply replaced by zeros.

The data were downloaded from theWikimedia REST API. According to the conditions of the API, this dataset is licensed underCC-BY-SA 3.0andGFDLlicenses.

Website Traffic Analysis

Website traffic analysis is the process of monitoring and evaluating the visitors to a website. It provides insights into how users are interacting with the site, where they are coming from, which pages they visit most often, and how long they stay. By analyzing this data, businesses can understand user behavior, improve site performance, and optimize content to increase engagement and conversions.

Key metrics include the number of visitors, page views, bounce rate, traffic sources (organic, referral, direct), and geographic location. Website traffic analysis is essential for enhancing SEO, refining marketing strategies, and boosting overall user experience.

This dataset contains 145063 time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2022-06-30. This is an extended version of the dataset that was used in the Kaggle Wikipedia Web Traffic forecasting competition. For consistency, the same Wikipedia pages that were used in the competition have been used in this dataset as well.The colons (:) in article names have been replaced by dashes (-) to make the .tsf file readable using our data loaders.

The data were downloaded from the Wikimedia REST API. According to the conditions of the API, this dataset is licensed under CC-BY-SA 3.0 and GFDL licenses.

Click Web Traffic Combined with Transaction Data: A New Dimension of Shopper Insights

Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Click enhances the unparalleled accuracy of CE Transact by allowing investors to delve deeper and browse further into global online web traffic for CE Transact companies and more. Leverage the unique fusion of web traffic and transaction datasets to understand the addressable market and understand spending behavior on consumer and B2B websites. See the impact of changes in marketing spend, search engine algorithms, and social media awareness on visits to a merchant’s website, and discover the extent to which product mix and pricing drive or hinder visits and dwell time. Plus, Click uncovers a more global view of traffic trends in geographies not covered by Transact. Doubleclick into better forecasting, with Click.

Consumer Edge’s Click is available in machine-readable file delivery and enables: • Comprehensive Global Coverage: Insights across 620+ brands and 59 countries, including key markets in the US, Europe, Asia, and Latin America. • Integrated Data Ecosystem: Click seamlessly maps web traffic data to CE entities and stock tickers, enabling a unified view across various business intelligence tools. • Near Real-Time Insights: Daily data delivery with a 5-day lag ensures timely, actionable insights for agile decision-making. • Enhanced Forecasting Capabilities: Combining web traffic indicators with transaction data helps identify patterns and predict revenue performance.

Use Case: Analyze Year Over Year Growth Rate by Region

Problem A public investor wants to understand how a company’s year-over-year growth differs by region.

Solution The firm leveraged Consumer Edge Click data to: • Gain visibility into key metrics like views, bounce rate, visits, and addressable spend • Analyze year-over-year growth rates for a time period • Breakout data by geographic region to see growth trends

Metrics Include: • Spend • Items • Volume • Transactions • Price Per Volume

Inquire about a Click subscription to perform more complex, near real-time analyses on public tickers and private brands as well as for industries beyond CPG like: • Monitor web traffic as a leading indicator of stock performance and consumer demand • Analyze customer interest and sentiment at the brand and sub-brand levels

Consumer Edge offers a variety of datasets covering the US, Europe (UK, Austria, France, Germany, Italy, Spain), and across the globe, with subscription options serving a wide range of business needs.

Consumer Edge is the Leader in Data-Driven Insights Focused on the Global Consumer

Top 25 Daily Page Views for the main website of Los Angeles

Encrypted Web Traffic Dataset: Event Logs and Packet TracesThis repository contains the dataset and supplementary materials for the following paper submitted to the Data in Brief journal:Stanislav Špaček, Petr Velan, Pavel Čeleda and Daniel Tovarňák. Encrypted Web Traffic Dataset: Event Logs and Packet Traces.StructureAnonymization - the anonymization folder contains the scripts and settings that were used to anonymize the data capture.Dataset - the dataset folder contains the host-based and network parts of the dataset in two separate files.Pcap2flow - the pcap2flow folder contains the tools, settings, and guide to convert the packet dump in the dataset into aggregated IP flows.This work is licensed under a Creative Commons Attribution 4.0 International License.

This dataset contains the estimates of the vehicle miles traveled (VMT) for interstate highways and how the total travel measured by VMT compares with travel that occurred in the same week of the previous year.

Research data on traffic exchange limitations including low-quality traffic characteristics, search engine penalty risks, and comparison with effective alternatives like SEO and content marketing strategies.

YouTube flows

This is the aggregated version of the daily dataset used in the Kaggle Wikipedia Web Traffic forecasting competition. It contains 145063 time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-05, after aggregating them into weekly.

The original dataset contains missing values. They have been simply replaced by zeros before aggregation.

The data set provided (traffic.csv) contains web traffic data ("events") from a few different pages ("links") over 7 days including various categorical dimensions about the geographic origin of that traffic as well as a page's content: isrc.