Web analytics

At Web analytics is the analysis of the behavior of visitors to a website. This includes tracking, reviewing, and reporting data to measure web activity, including the use of a website and its components such as web pages, images, and videos.

Among the data provided by Web analytics collected include traffic sources, referring websites, page views, paths traveled, and conversion rates. The data collected is often part of customer relationship management (CRM) analytics to enable and optimize better business decisions.

The Web analytics allows a company to retain customers, attract more visitors and increase the sales volume of each customer.

Analyses can help in the following ways:

• Determining the likelihood that a given customer will buy a product again after having bought it in the past.

• Personalize the website for customers who visit it repeatedly.

• Observe how much money individual customers or certain groups of customers spend.

• Observe the geographic regions from which the most and least customers visit the site and purchase specific products.

• Make predictions about which products customers are most and least likely to buy in the future.

The goal of the Web analytics is to serve as a business benchmark to promote certain products to customers who would be most likely to buy them, and to determine which products a particular customer is most likely to buy. This can help improve the relationship between revenue and marketing costs.

In addition to these functions, Web Analytics Track the click and drill down behavior of customers within a website, identify the pages from which customers come most frequently, and communicate with browsers to track and analyze online behavior. The results of the Web analytics are provided in the form of tables, charts and diagrams.

Web analytics process

The Web analytics-process includes the following steps:

Set goals.

The first step in the web analytics process is for companies to establish goals and the desired end results. These goals may include revenue growth, customer satisfaction, and brand awareness. Business goals can be both quantitative and qualitative.

Collecting data.

The second step of the Web analytics is the collection and storage of data. Companies can collect data directly from a website or web analytics tool like Google Analytics collect. The data comes mainly from Hypertext Transfer Protocol requests - including network- and application-level data - and can be combined with external data to interpret web usage. For example, a user's Internet Protocol address is associated with many factors, including geographic location and click-through rate.

Process data.

In the next phase of the Web analytics-Trichters, companies must process the collected data into actionable information.

Identification of Key Performance Indicators (KPIs).

In the Web analytics a KPI is a quantifiable measure for monitoring and analyzing user behavior on a website. Examples include bounce rates, unique users, user sessions, and on-site searches.

Developing a strategy.

This phase is about using the insights gained to formulate strategies that align with the organization's goals. For example, on-site search queries can help an organization develop a content strategy based on what users are searching for on its website.

Experiment and test.

Companies need to experiment with different strategies to find the one that delivers the best results.

A/B testing, for example, is a simple strategy for finding out how an audience responds to different content. This involves creating two or more versions of content and then showing them to different audiences to see which version of the content performs better.

What are the two main categories of web analytics?

The two main categories of Web analytics are the off-siteWeb analytics and the on-siteWeb analytics.

Off-Site Web Analytics

The term off-siteWeb analytics refers to monitoring visitor activity outside of a company's website to measure potential audiences.

The off-siteWeb analytics provides an industry-wide analysis that reveals how a company compares to its competitors. It is an analysis that focuses on data collected across the Internet, such as social media, search engines, and forums.

On-Site Web Analysis

The on-siteWeb analytics refers to a narrower scope, analyzing the activities of visitors to a particular website to see how the website is performing.

The data collected is typically more relevant to the website operator and can include details about website engagement, such as what content is most popular. Two technological approaches for the Web analytics on site are log file analysis and page tagging.

Log file analysis, also known as log management, analyzes data from log files to monitor the performance of a website, troubleshoot errors, and generate reports. Log files contain records of virtually every action on a network server, such as a web server, email server, database server, or file server.

Page tagging uses a tag management system to insert code snippets into the HyperText Markup Language code of a website to track website visitors and their interactions on the website. These snippets of code are called tags. When companies add these tags to a website, they can be used to track a number of metrics, such as the number of pages viewed, the number of unique visitors, and the number of products viewed.

Web analysis tools

Web analytics tools provide important statistics about a website, such as where visitors come from, how long they stay, how they found the website, and what online activities they performed on the website. Besides the Web analytics these tools are often used for product analysis, social media analysis and marketing analysis.

Google Analytics advantages

Web analytics tools like Google Analytics provide key website statistics to analyze visitor behavior as part of CRM analytics to facilitate and optimize business decisions.

Google Analytics is a web analytics platform that monitors website traffic, behavior and conversions. The platform tracks page views, unique visitors, bounce rates, Uniform Resource Locators, Average length of stay, page abandonment, new and returning visitors, and demographic data.