Web analytics

Web analytics is the measurement, collection, analysis, and reporting of web data to understand and optimize web usage. Web analytics is not just a process for measuring web traffic but can be used as a tool for business and market research and assess and improve website effectiveness. Web analytics applications can also help companies measure the results of traditional print or broadcast advertising campaigns. It can be used to estimate how traffic to a website changes after launching a new advertising campaign. Web analytics provides information about the number of visitors to a website and the number of page views, or create user behavior profiles. It helps gauge traffic and popularity trends, which is useful for market research. Most web analytics processes come down to four essential stages or steps, which are: Collection of data: This stage is the collection of the basic, elementary data. Usually, these data are counts of things. The objective of this stage is to gather the data. Processing of data into metrics: This stage usually takes counts and makes them ratios, although there still may be some counts. The objective of this stage is to take the data and conform it into information, specifically metrics. Developing KPI: This stage focuses on using the ratios (and counts) and infusing them with business strategies, referred to as key performance indicators (KPI). Many times, KPIs deal with conversion aspects, but not always. It depends on the organization. Formulating online strategy: This stage is concerned with the online goals, objectives, and standards for the organization or business. These strategies are usually related to making profit, saving money, or increasing market share. Another essential function developed by the analysts for the optimization of the websites are the experiments: Experiments and testing: A/B testing is a controlled experiment with two variants, in online settings, such as web development. 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.