Objectives Of Web Analytics

Taking careers such as web design and analytics, there are numerous studies that have been conducted about how fortune 500 companies invest in web analytics (Chaffey, D., & Patron, M. (2012)). Despite these skyrocketed investments on web analytics, they still find it difficult to make meaningful

Avinash Kaushik’s 10/90 rule states that for every $10 you spend on a web analytics tool, you should be spending $90 on the people to analyze the numbers i.e. a company spending $50k on any paid solution, such as Adobe (Omniture) and Coremetrics, should be spending $450k on a team of web analysts to analyze and gain valuable insights, considering that a web analyst’s typical daily/weekly role is split into the following categories:

Organizations have incredible interests in "Web Analytics", yet regardless they can't make suitable business arrangements. The fundamental target of this standard is to execute web investigation instruments to most astounding worth. In the present procedure numerous huge undertaking organizations spend more than a large portion of a-million dollars a year on costly Web Analytics arrangements as opposed to spending even 50% of that cash on qualified web examiners. Because you are huge and have entry to colossal assets, does not imply that you should go for costly arrangements when there are scarcely any qualified heads to handle web examination in the association. Keeping in mind the end goal to separate themselves from free web investigation

Abstract— Google Analytics is a web analytic tool which provides a transparent view of website traffic and marketing effectiveness. Google Analytics has powerful and advance features that provides insight into the websites and improve website ROI (Return on Investment). This research paper consists of case study on Google Analytics, which demonstrates features Google Analytics provides and reports it generates. On the basis of the evaluation of web usage, web site owners or E-business marketers can enhance the efficiency of marketing, and web traffics.

In the world of technology that we live in today has forced companies in almost every industry to use whatever tools that are available to help them be competitive in their business industry. There are a few ways to do this, one of those ways is the use of Web analytics, which is the collection of raw data from users browsing habits and then taking the raw data and assemble the data into clear comprehensive results. This type of analysis is very useful for companies, as it helps them learn what users are doing and their habits and the best way to target these users.

Sauer (2015) thinks that the first disadvantage of 10/90 rule is spending more money on the tools. He thinks the other mainstream analytics tool other than Google Analytics is Adobe SiteCatalyst, which is estimated to have 100,000 to 250,000 users. He made an assumption that if a company spend 150,000 per year on analytics, according to the 10/90 rule, 1.35 million will be used to hire about 13 analytics based on the industrial current state. Sauer criticized that the Fortune 500 companies he worked for had never hired so many analysts to understand the data, on the contrary, the normal situation is 3 analysts on average for each

In today’s companies, the analytics software plays the important role and guides the future activities to a great extent.

In spite of very huge data, reports, files, large investments made in web analytics, firms find it difficult to make business decisions. Many business leaders underlined the need to invest in people, but none have spelled it how much could be invested on the tools and people. Kaushik (Blog at kaushik.net) found and developed a rule for investment on tools and analyst to solve the problems in arriving at business decisions to become successful in business. He named it as 10/90 rule for web analytics success.

Website are a work in progress and we use analytics data as a tool to constantly help improve the content and calls to action.

Many studies show that while many of the Fortune 500 web-based companies had invested heavily, they had a hard time making reasonable business decisions. Many people argue or rather complain that these businesses had gigabytes as well as terabytes of data of Powerpoint and Excel files. Nevertheless, no meaningful implementable actions were taken. A 10/90 Rule is a rule that is applied to fix this kind of problem. The goal of this rule at this time is to achieve the highest value in executing web analytics in this situation. In this case, the cost of professional vendor services, as well as analytics tool, would account for $10. On the other hand, the need investment in the area of analysts and intellectual resources would account to $90. The main aim here is to achieve grand success for their people.

The second principle is that these web analytics tools just produce millions of data points. This ties into the example provided above about Google Analytics and how it just spits out copious amounts of data. (Kaushik 2010).

There are over 1 billion active websites today and its growth is exponential. Not all of them are optimized and effectively used by the users. Every owner of the website should continuously assess and improve the effectiveness of their website, if they want to address the above question. How they can do that? That is where Web Analytics comes into picture. The process of tracking, collecting, measuring, reporting and analyzing the data collected from the web for understanding and optimizing the web usage is known as Web Analytics. We can track every click of every person on the website. It provides information about number of visitors to a website and number of page views. In other words, Web Analytics is tracking the visitor behavior of

A web analytics dashboard lets you track the execution of your website in real-time, and answer the critical questions like how is your site performing as for your Marketing destinations?" This dashboard example concentrates on a high-level, yet in-depth view of your website 's execution over numerous time periods.

Company’s current position and ability to compete on analytics: I had worked for a healthcare delivery organization whose mission is to enhance the quality of life through improved health, prepare future health care professionals and discover new medical knowledge through research. It is the only Academic Medical center in the region and enjoyed a monopoly for quite some time. With the passage of the Affordable Care Act, the payment model changed from Fee for Service to Bundled payments. The organization was challenged to lower the cost of providing healthcare services without compromising quality of care or research. It had to invest heavily on implementing Electronic Medical Records and systems for reporting to regulatory agencies and insurance companies. The table below highlights the differences between Analytics and Business Intelligence. Note that the organization is in the early phase of implementing BI solutions.

Analytics has been used as isolated initiatives within my company. Different levels of applications of analytics is a reality. Historically, quality department has leading the way in data-driven decision process by using several statistical and quality