Within the Asia Pacific region, China had the fastest load time for mobile sites with *** seconds, followed by Singapore with an average load time of seven seconds. Nevertheless, the load times are still slower than the recommended load time of ***** seconds. The same research found that for every second of delay in mobile site load time, there was a ** percent drop in conversions.

This statistic compares the time taken to load a web page on 3G and 4G networks in the United Kingdom (UK) as of *********, by provider. In *********, the page-loading time on Three's 4G network was **** seconds and that on its 3G network was **** seconds, faster than any of the other providers.

A bar chart comparing the average page load time reduction (in seconds) achieved by popular WordPress optimization tools such as WP Super Cache, Smush, Autoptimize, and Cloudflare.

The statistic shows the average load time of websites regarding the iPhone 4.3 and Android 2.3.

Introduction

Landing Page Statistics: Landing pages are dedicated web pages designed to convert visitors into leads or customers by focusing on a single, clear call to action. In 2024, the median landing page conversion rate across industries is 6.6%, with top-performing pages exceeding 20%. Email-driven traffic achieves the highest average conversion rate at 19.3%, outperforming paid search (10.9%) and paid social (12%).

Mobile devices account for 82.9% of landing page traffic, yet desktop users exhibit a higher average conversion rate of 12.1% compared to 11.2% for mobile users. Speed is crucial; a one-second delay in page load time can reduce conversions by 7%. Incorporating videos can boost conversions by 86%, and personalized landing pages can convert 202% better than generic ones.

Design elements significantly impact performance. Landing pages with five or fewer form fields convert 120% better than those with more fields. Pages with a single, clear call to action achieve a 13.5% conversion rate, compared to 11.9% for pages with multiple CTAs. Additionally, 38.6% of marketers report that videos enhance landing page conversion rates more than any other element.

Let us check out some of the Landing page statistics concerning landing page performance and the secrets of landing page success.

Overview

In this study, we explore automated reduction of the carbon footprint of web pages through genetic improvement, a process that produces alternative versions of a program by applying program transformations intended to optimize qualities of interest. We introduce a prototype tool that imposes transformations to HTML, CSS, and JavaScript code, as well as image resources, that minimize the quantity of data transferred and memory usage while also minimizing impact to the user experience (measured through loading time and number of changes imposed).

In an evaluation, our tool outperforms two baselines---the original page and randomized changes---in the average case on all projects for data transfer quantity, and 80% of projects for memory usage and load time, often with large effect size. Our results illustrate the applicability of genetic improvement to reduce the carbon footprint of web components, and offer lessons that can benefit the design of future tools.

Data Contained in This Package

• experiment_data/Subject Project-XX-X.xlsx

Each spreadsheet contains data collected as part of our experiments, including the fitness scores of the final solutions.

This dataset holds the electric load profiles of 50 small and mid-size enterprises in Germany. The load profiles are in 15-minute time resolution for one year. The load is shown in kW as an average over 15 minutes.

The dataset is divided into two:

• LoadProfile_20IPs_2016 shows load profiles of 20 industrial plants (IP) for the year 2016.
• LoadProfile_30IPs_2017 shows load profiles of 30 industrial plants (IP) for the year 2017.

The IPs from the dataset for 2016 do not reappear in the dataset for 2017.

The dataset LoadProfile_20IPs_2016 is evaluated in the following publication:

• Covic, N., Braeuer, F., McKenna, R., Pandzic, H., Optimizing Industrial Facilities’ Active Participation
  in Electricity Markets under Uncertainty, 2020.

Both datasets together are evaluated in multiple publications:

• Braeuer, F., Finck, R., McKenna, R., Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO2-minimizing storage dispatch in Germany, Journal of Cleaner Production, Volume 266, 2020, 121588, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2020.121588.
• Braeuer, F., Rominger, J., McKenna, R.,Fichtner, W., Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry, Applied Energy, Volume 239, 2019, Pages 1424-1440, ISSN 0306-2619, https://doi.org/10.1016/j.apenergy.2019.01.050.

Enjoy.

Graph and download economic data for Load Factor for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (LOADFACTOR) from Jan 2000 to May 2025 about flight, passenger, air travel, travel, domestic, and USA.

In 2021, container ships spent an average of around *** days in a port during a port call. Container ships spent the least amount of time at Japanese ports, a median time of **** days. The United States ranked last, taking a median time of **** days to load and unload containers from ships at its ports.