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The fundamental goal of web analytics is to collect and analyze data related to web traffic and usage patterns. Both collect data that can be processed to produce web traffic reports. The second method, page tagging, uses JavaScript embedded in the webpage to make image requests to a third-party analytics-dedicated server, whenever a webpage is rendered by a web browser or, if desired, when a mouse click occurs. The first and traditional method, server log file analysis, reads the logfiles in which the web server records file requests by browsers. There are two main technical ways of collecting the data.

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Many different vendors provide on-site web analytics software and services. However, this meaning has become blurred, mainly because vendors are producing tools that span both categories. Historically, web analytics has been used to refer to on-site visitor measurement.

GoogleВ AnalyticsВ and Adobe AnalyticsВ areВ theВ mostВ widely used on-site web analytics service although new tools are emerging that provide additional layers of information, including heat maps and session replay. This data is typically compared against key performance indicators for performance and is used to improve a website or marketing campaign's audience response. On-site web analytics measures the performance of a specific website in a commercial context.

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This includes its drivers and conversions for example, the degree to which different landing pages are associated with online purchases.

On-site web analytics, the more common of the two, measure a visitor's behavior once on a specific website.

It includes the measurement of a website's potential audience (opportunity), share of voice (visibility), and buzz (comments) that is happening on the Internet as a whole.

Off-site web analytics refers to web measurement and analysis regardless of whether a person owns or maintains a website.

There are at least two categories of web analytics, off-site and on-site web analytics. Other times, the online strategy affects the data collected. So, sometimes the data that is available for collection impacts the online strategy. The goal of A/B testing is to identify and suggest changes to web pages that increase or maximize the effect of a statistically tested result of interest.Д®ach stage impacts or can impact (i.e., drives) the stage preceding or following it.

Experiments and testing: A/B testing is a controlled experiment with two variants, in online settings, such as web development.

These strategies are usually related to making money, saving money, or increasing market share.ДЄnother essential function developed by the analysts for the optimization of the websites are the experiments

Formulating online strategy: This stage is concerned with the online goals, objectives, and standards for the organization or business.

Many times, KPIs deal with conversion aspects, but not always.

Developing KPI: This stage focuses on using the ratios (and counts) and infusing them with business strategies, referred to as key performance indicators (KPI).

The objective of this stage is to take the data and conform it into information, specifically metrics.

Processing of data into information: This stage usually takes counts and makes them ratios, although there still may be some counts.

The objective of this stage is to gather the data. Usually, these data are counts of things.

Collection of data: This stage is the collection of the basic, elementary data.

Most web analytics processes come down to four essential stages or steps, which are:

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