The It is common knowledge in the Web Analytics

The objective of Web Analytics is to understand and improve the experience of online customers, while increasing revenues for online businesses. Among other techniques (described in part II), this can be done by studying the ways customers navigate a website. According to the Web Analytics Association 6, the official definition of Web Analytics is “the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage.” Web Analytics is not a technology to produce reports; it is a process that proposes a virtuous cycle for website optimization. Based on the field’s best practices, a framework for analyzing website performance should include the following steps:This process will enable a website owner to measure customer acquisition costs against profits, to find how the most profitable visitors are behaving in the website, and to optimize the website to improve its performance or profitability. Following, we discuss each step in detail.  A.

   Defining Goals The answer to the following question is critical in defining a website’s goals: why does your website exist? Each website will have its own unique answer to that question: for example, an ecommerce website should sell products, a support website should answer the customers’ questions, and a news website should provide content. Each website owner must define success according to his/her own objectives and revisit the goals periodically. Website objectives are critical input that will assist in identifying the metrics that help to measure the success of this channel (for many companies, a website is one channel among several others). The website should be accounted for in the same way as other business expenses; investment must be measured against return. One of the key evolutionary trends in the last couple of years is the ability to measure success no matter what the goals of your website are. We could just do ecommerce before; now you can measure success in terms of driving social media campaigns or a support website or a nonprofit website or even a blog (both online and offline).

The only requirement is an articulation of the business goals.  B.   Defining Metrics (KPIs) Measuring goal achievement can be done by creating Key Performance Indicators (KPIs) that show whether the website is getting closer to its objectives or not. It is common knowledge in the Web Analytics community that information is not worth collecting if it does not generate insight. There should be an action linked to each KPI proposed for a website.

For example, if the marketing cost per visitor to a website is measured, there should be two actions related to it: one for a decline in this number, and one for an increase in it. Steve Bennett, former Intuit CEO, is known to push everyone to identify the “critical few”: priorities, goals, metrics, KPIs, anything. If the business were on the line how would you know things are going well or badly? Cutting through the clutter of data, what are the “critical few” metrics? Almost all of us have too many things we measure, too many things that distract us and take away our precious time and attention. But everyone probably has at most three “critical few” metrics that define his/her existence. One important characteristic of a KPI is that it is highly adjustable: each company, department, or person should have its KPIs defined according to the company or personal objectives and interests. One common division of KPIs across the industry is by hierarchy: upper-management receives reports on the overall achievement of the website’s goals; mid-management receives reports on campaign and ‘site optimization results; and analysts receive detailed and technical reports on website performance.

Articulated another way, there should be a clear line of sight between the company’s goals and what each level of the organization is solving for. Good KPIs should contain four attributes: I.          Un-complex: decisions in companies are made by people in several departments with different backgrounds. If only the web analyst understands the KPIs, it is unlikely that decision makers across the company will use it.

 II.          Relevant: each business is unique, even businesses that seem like they might be in the same business. Avinash uses the example of Best Buy and Circuit City. It might be thought that both companies should/would/could measure their website with similar web metrics. However, the only thing they have in common is the fact that they sell large-screen TVs on their website.

Everything else is different: their business models, their priorities, and how each tends to use the web in its multi-channel portfolio. III.          Timely: great metrics must be provided promptly so that decision makers can make timely decisions. Even excellent KPIs are useless if it takes a month to get information when your industry changes every week. IV.

       Instantly useful: it is vital to understand quickly what the KPI is, so that one can find the first blush of insights as soon as s/he look at it One good example of a great KPI that meets all of the preceding criteria is bounce rate (percentage of single pageview visits). It is un-complex because it is easy to understand, explain and propagate. It is relevant because it identifies where you are wasting marketing dollars and which pages under-perform. It is timely because it is a standard in all Web Analytics tools within one click.

And it is instantly useful because the website owner can look at it and know what needs attention; s/he sees 25 to 30% for your ‘site and instantly you know things are fine; s/he looks at a page with a 50% bounce rate and knows it needs attention; s/he sees a campaign or keyword with a 70% bounce rate and knows there is a fire. You will have lots of metrics or KPIs at your disposal, yet only those that meet the preceding four criteria will yield actionable insights that will have a positive impact on your website.  C.   Collecting Data It is vital that data be collected accurately and saved on a local or external database for further analysis. Data collection is crucial to analysis results.

Following we describe the four main ways of capturing behavior data from websites. i.   Web Logs Every time a visitor to a website requests information (for example, when a visitor clicks a link to go to another page in the website) the server of the ‘site registers this request in a log file. The log file can have several different formats, but Extend Log File Format, which is the commonest, saves the following information: the IP of the computer that requested information, date or time at which the transaction was completed, time taken for transaction completion, bytes transferred, records whether a cache hit occurred, and the referrer. Advantages of this method are: The website owner owns the data (as opposed to JavaScript Tagging below), meaning that the owner has full control over the privacy of the information; Web logs are available backwards, which enables the website owner to reanalyze past campaigns and reprocess data; It saves web crawler behavior (crawlers from search engines visit the website to index them and show in search results). ii.   JavaScript Tagging This technology consists of inserting a small JavaScript (which is not allowed to be cached) in every page of a website. This means that every time a visitor opens a page, this JavaScript is activated and the visitor information and actions are saved in a separate file.

 iii.   Web Beacons This technology is used to measure banner impressions and click troughs. Although not used often, web beacons can still be found on the web. A great benefit (and common usage) of web beacons is in tracking customer behavior across different websites. It answers questions such as: how are banner ads performing across multiple websites (where they could be seen by the same or different sets of customers)? Because the same server is collecting the data, reading the cookies and doing the tracking, it is quite easy for advertisers to track, anonymously, the same visitor across multiple sites or different visitors to the same ‘site.  iv.   Packet Sniffing Although packet sniffing is very advanced in terms of technology, it is used mostly for multivariate testing.

Its biggest advantage is that it need not tag pages; all the information goes through the packet sniffer (hardware). D.   Analyzing Data To understand the customer behavior from the data, the (web) analyst should follow a few initial steps.

Following we identify analyses that should help on the conversion of data into insights, which will be essential for optimizing any website. i.   Start from the Basics Any web analytics tool presents a summary report, a group of basic metrics that are available immediately after logging into the tool. Google Analytics shows the following chart: