The Japanese review site my-best.com had the highest bounce rate among the most visited retail websites in Japan in July 2024. Operated by mybest, Inc. and part of LY Corporation, the website had a bounce of nearly ** percent, while ranking as the ****** most visited retail website in the same month.

Average Annual Daily Traffic data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain data on the total volume of vehicle traffic on a highway or road for a year divided by 365 days.

Context

The data was taken from http://tomslee.net/airbnb-data-collection-get-the-data. The data was collected from the public Airbnb web site and the code was used is available on https://github.com/tomslee/airbnb-data-collection.

Content

room_id: A unique number identifying an Airbnb listing. The listing has a URL on the Airbnb web site of http://airbnb.com/rooms/room_id
host_id: A unique number identifying an Airbnb host. The host’s page has a URL on the Airbnb web site of http://airbnb.com/users/show/host_id
room_type: One of “Entire home/apt”, “Private room”, or “Shared room”
borough: A subregion of the city or search area for which the survey is carried out. The borough is taken from a shapefile of the city that is obtained independently of the Airbnb web site. For some cities, there is no borough information; for others the borough may be a number. If you have better shapefiles for a city of interest, please send them to me.
neighborhood: As with borough: a subregion of the city or search area for which the survey is carried out. For cities that have both, a neighbourhood is smaller than a borough. For some cities there is no neighbourhood information.
reviews: The number of reviews that a listing has received. Airbnb has said that 70% of visits end up with a review, so the number of reviews can be used to estimate the number of visits. Note that such an estimate will not be reliable for an individual listing (especially as reviews occasionally vanish from the site), but over a city as a whole it should be a useful metric of traffic.
overall_satisfaction: The average rating (out of five) that the listing has received from those visitors who left a review.
accommodates: The number of guests a listing can accommodate.
bedrooms: The number of bedrooms a listing offers.
price: The price (in $US) for a night stay. In early surveys, there may be some values that were recorded by month.
minstay: The minimum stay for a visit, as posted by the host.
latitude and longitude: The latitude and longitude of the listing as posted on the Airbnb site: this may be off by a few hundred metres. I do not have a way to track individual listing locations with
last_modified: the date and time that the values were read from the Airbnb web site.

General information of 8 purchased fish antibiotics.

Product Reviews Software Market size was valued at USD 8.7 Billion in 2024 and is projected to reach USD 28.9 Billion by 2031, growing at a CAGR of 14.7 % during the forecasted period 2024 to 2031

Global Product Reviews Software Market Drivers

The market drivers for the Product Reviews Software Market can be influenced by various factors. These may include:

Growing Significance of Customer Feedback: As online shopping and e-commerce have grown in popularity, customers now heavily consider customer feedback when making selections about what to buy. Product reviews software helps companies gain credibility and confidence from prospective customers by efficiently gathering, organizing, and presenting consumer feedback.

Put Customer Experience (CX) first: Creating a satisfying consumer experience is a top concern for companies in all sectors. With the use of product reviews software, businesses can get client feedback in real time, pinpoint areas for development, and quickly resolve issues, all of which increase customer happiness and loyalty.

Impact on Purchase Behavior: Research indicates that most consumers base their decisions on what to buy on product reviews. Negative reviews might discourage potential consumers, while positive ratings can greatly impact purchasing behavior and increase sales. Businesses can employ user-generated content to boost conversion rates and spur revenue growth by utilizing product reviews software.

Benefits of SEO: Product reviews and other user-generated content are essential to search engine optimization (SEO). Product reviews software can raise a business's search engine rankings, increase organic traffic to its website, and improve online exposure by producing new and pertinent content. These actions will eventually increase sales and brand awareness.

Enhanced Product Insights: Software for product reviews offers insightful data on consumer preferences, problems, and product effectiveness. Businesses can enhance their product offerings and marketing strategies by identifying patterns, evaluating the strengths and weaknesses of their products, and making data-driven decisions by assessing review data and sentiment.

Social Proof and Trust Building: Positive product reviews act as social proof of a product's dependability, worth, and quality. This promotes trust in the brand. Businesses may differentiate themselves from rivals, gain the trust of prospective customers, and establish a solid reputation for their brands in the marketplace by displaying real client feedback.

Competitive Advantage: Companies can maintain their competitiveness in today's congested markets by putting product reviews software into place. Businesses can set themselves apart from competitors who might not have as strong of a review management strategy, foster brand loyalty, and differentiate their products by aggressively controlling and promoting user reviews.

Brand Engagement and Community Building: Software for product reviews encourages communication and engagement between companies and their clients. Companies may create a feeling of community around their products and brand, develop brand champions, and forge deep connections with their audience by replying to reviews, answering customer questions, and requesting feedback.

Continuous Improvement: Product reviews offer insightful information for new and improved products. Businesses may better satisfy consumer wants and expectations by identifying areas for improvement, iterating on product features, and continuously evolving their offers by listening to customer input.

Baseline information of 9 reviewed antibiotics.

A review paper on different pattern classification techniques based on web usage mining with neural network Area of data mining includes data preprocessing data classification cluster analysis Association etc The traffic on World Wide Web is increasing day by day and large amount of data generated due to user s interaction with web sites Web mining is the application of data mining techniques which includes web usage mining web content mining and the third one is web structure min

Introduction

Yelp Statistics: Yelp is a popular online platform that helps users find local businesses based on reviews and ratings from other customers. In 2024, Yelp continues to hold a significant presence, particularly in the U.S., where most of its traffic and revenue are generated. Yelp offers both a website and a mobile app, making it easy for people to access business information and read reviews.

Businesses can also advertise on Yelp, using the platform to reach new customers and manage their online reputation. With its comprehensive review system, Yelp plays a vital role in connecting people with trusted local businesses. This article will help you understand Yelp's key statistics and trends, providing valuable insights for businesses aiming to optimize their presence on the platform.

In 2024, Yelp had a total of ***** million monthly mobile web visitors, and over ** million monthly desktop visitors. Almost ** million visitors accessed Yelp via the mobile app. Mobile web visits were at their highest in 2019, with over ** million visitors accessing the site via desktop per month.

Redirect Notice: The website https://transbase.sfgov.org/ is no longer in operation. Visitors to Transbase will be redirected to this page where they can view, visualize, and download Traffic Crash data.

A. SUMMARY This table contains all crashes resulting in an injury in the City of San Francisco. Fatality year-to-date crash data is obtained from the Office of the Chief Medical Examiner (OME) death records, and only includes those cases that meet the San Francisco Vision Zero Fatality Protocol maintained by the San Francisco Department of Public Health (SFDPH), San Francisco Police Department (SFPD), and San Francisco Municipal Transportation Agency (SFMTA). Injury crash data is obtained from SFPD’s Interim Collision System for 2018 through the current year-to-date, Crossroads Software Traffic Collision Database (CR) for years 2013-2017 and the Statewide Integrated Transportation Record System (SWITRS) maintained by the California Highway Patrol for all years prior to 2013. Only crashes with valid geographic information are mapped. All geocodable crash data is represented on the simplified San Francisco street centerline model maintained by the Department of Public Works (SFDPW). Collision injury data is queried and aggregated on a quarterly basis. Crashes occurring at complex intersections with multiple roadways are mapped onto a single point and injury and fatality crashes occurring on highways are excluded.

The crash, party, and victim tables have a relational structure. The traffic crashes table contains information on each crash, one record per crash. The party table contains information from all parties involved in the crashes, one record per party. Parties are individuals involved in a traffic crash including drivers, pedestrians, bicyclists, and parked vehicles. The victim table contains information about each party injured in the collision, including any passengers. Injury severity is included in the victim table.

For example, a crash occurs (1 record in the crash table) that involves a driver party and a pedestrian party (2 records in the party table). Only the pedestrian is injured and thus is the only victim (1 record in the victim table).

To learn more about the traffic injury datasets, see the TIMS documentation

B. HOW THE DATASET IS CREATED Traffic crash injury data is collected from the California Highway Patrol 555 Crash Report as submitted by the police officer within 30 days after the crash occurred. All fields that match the SWITRS data schema are programmatically extracted, de-identified, geocoded, and loaded into TransBASE. See Section D below for details regarding TransBASE.

C. UPDATE PROCESS After review by SFPD and SFDPH staff, the data is made publicly available approximately a month after the end of the previous quarter (May for Q1, August for Q2, November for Q3, and February for Q4).

D. HOW TO USE THIS DATASET This data is being provided as public information as defined under San Francisco and California public records laws. SFDPH, SFMTA, and SFPD cannot limit or restrict the use of this data or its interpretation by other parties in any way. Where the data is communicated, distributed, reproduced, mapped, or used in any other way, the user should acknowledge TransBASE.sfgov.org as the source of the data, provide a reference to the original data source where also applicable, include the date the data was pulled, and note any caveats specified in the associated metadata documentation provided. However, users should not attribute their analysis or interpretation of this data to the City of San Francisco. While the data has been collected and/or produced for the use of the City of San Francisco, it cannot guarantee its accuracy or completeness. Accordingly, the City of San Francisco, including SFDPH, SFMTA, and SFPD make no representation as to the accuracy of the information or its suitability for any purpose and disclaim any liability for omissions or errors that may be contained therein. As all data is associated with methodological assumptions and limitations, the City recommends that users review methodological documentation associated with the data prior to its analysis, interpretation, or communication.

This dataset can also be queried on the TransBASE Dashboard. TransBASE is a geospatially enabled database maintained by SFDPH that currently includes over 200 spatially referenced variables from multiple agencies and across a range of geographic scales, including infrastructure, transportation, zoning, sociodemographic, and collision data, all linked to an intersection or street segment. TransBASE facilitates a data-driven approach to understanding and addressing transportation-related health issues, informed by a large and growing evidence base regarding the importance of transportation system design and land use decisions for health. TransBASE’s purpose is to inform public and private efforts to improve transportation system safety, sustainability, community health and equity in San Francisco.

E. RELATED DATASETS Traffic Crashes Resulting in Injury: Parties Involved Traffic Crashes Resulting in Injury: Victims Involved TransBASE Dashboard iSWITRS TIMS

The timeline shows the number of unique mobile visitors to recommendation platform Yelp from 2016 to 2021, per quarter. The local search and review site's mobile visitor numbers have displayed a steady growth, reaching 31 million unique mobile app devices in the first quarter of 2021.

Blogging Platforms Market is growing at a moderate pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2024 to 2031.

Global Blogging Platforms Market Definition

A blogging platform is a software-related service that provides an internet user with the ability to publish its content like blogs. A content management framework is a special format of a Blogging Site. These platforms provide bloggers with their pre-designed templates and tools in creating technical websites. Blogging sites are content and networking systems in broadcast format, the platforms allow bloggers or writers to publish reviews and articles that can be made through emails, stand-alone websites, social networks and feed systems. The blogging platform has an interactive forum where the published material on the website can be used. Blogging platforms allow users to comment on the engagement of readers or readers and other participants. Contrary to static websites, blogging networks display chronically organized events in the opposite direction. The platforms support key word search features which enables readers to easily find new and new content, while the advanced blogging platforms support ecommerce features. Chronology, ecommerce and keyword search help bloggers generate considerable traffic compared with conventional websites.

Bogging platforms are used for both commercial and non-commercial purpose. Whereas for pay and premium blogging sites, a blogger or an author with the intention of making money from their content requests. Blogging sites have been increasingly commercially applied since last 5 to 6 years where bloggers monetize the sites for blogging. Bloggers will increase their web content in the Google website ranking with new and first hand keywords material published on the web-blogging platforms.

Based on a 2022 analysis, the product display page (PDP) views experience the highest surge beyond the ***-star rating threshold. While products with an average rating from *** to **** generate the most traffic and receive the highest number of reviews, consumers remain hesitant when confronted with an average rating of *** stars.

Nearly 32 million Russians visited the travel website Tutu.ru in August 2023. The service allowed customers to book tickets or accommodation and served as a platform for reviews. The second most popular travel and tourism website was Rzd.ru, the page of Russian Railways.

Topic summary: 102,728 reviews from 1 January 2010 and 1 April 2023.