The first step of the analytics process is to define your business metrics, which are typically called key performance indicators (KPIs). In doing this, remember that KPIs go well beyond your website. Site-centric statistics, such as hits, number of visitors, or average visit length, aren’t business metrics. They’re merely ways of measuring activity on your website, and in most cases they can’t tell you anything meaningful about your performance.

To get real business metrics, you need to look at your website in the context of your overall business strategy. Your business is the foundation for everything you end up doing with web-analytics data. And so, you need to determine how the behavior of users on your website relates to your overall business goals.

This isn’t as difficult as it may sound. The easiest way to think about user ehavior is to ask yourself what you want people to do on your site. In web analytics, we refer to these actions as desired behaviors. They include such things as the paths
you want users to take, the marketing initiatives you want them to come into contact ith, and the products you want them to buy. Desired behaviors may be as simple the ovement of customers from your home page to a specific initiative. Or, they may be omplex. For example, a content site may want its users to explore particular site areas hat have higher ad-conversion rates than others. There are as many possible desired ehaviors as there are business objectives; the important thing is to isolate what you ant users to do.

The second step is to monetize these desired behaviors. In other words, you hould figure out the value of each behavior to your business. For example, if you’re rying to drive customers to a particular offer, you should be able to define the likelihood that each new prospect will take you up on it and how much each conversion is worth to your company.

Popularity: 60% [?]

In 2005, Forrester Research asked web professionals what they found to be the hardest part of using analytics in their organizations. Surprisingly, only 24 percent replied “pulling together the data.” By contrast, 53 percent said “acting on the findings.”

This is a big problem. An organization that fails to act on its analytics findings is like a marathon runner who completes 25 miles in record time and then walks home without completing the race. By itself, compiling information won’t help your organization.
The surest way to achieve a 0 percent ROI on web analytics is to look at the data you collect and then do nothing with it.
To get the most out of analytics, you should plan to dedicate about 5 percent of your overall web budget to optimization. That should be enough to take advantage of the opportunities your analytics effort identifies without depriving your organization of the funds it needs for ongoing operations.

Of course, setting aside even such a small percentage of the overall budget to a new line item will raise objections. But any opposition you encounter should be easy to overcome. To justify the expenditure, pick two or three of your top KPIs, and look at their performance over the past 12 months. Next, model the financial impact that would result if you improved their performance by a small amount. Present the benefits of this change, and you should have little difficulty convincing others in your organization to provide the resources needed for optimization.

Popularity: 65% [?]

Setting proper KPIs is a great step toward building a data-driven organization. But often that initial effort turns out to be temporary. A few months later, companies lose sight of those goals. Soon, web-analytics reports become just pieces of paper (or e-mails) that float across desks on their way to oblivion.

To keep your organization thinking about its KPIs, you should make them part of your individual and group goals. As any manager knows, nothing can focus employee attention quite like the promise of financial rewards (or the possibility of a bad performance review). By holding teams and individuals accountable for web performance, you’ll
drive them to improve it.

But if you’re going to tie goals to KPIs, you should also distribute data effectively, the best way to do this is through customized scorecards that highlight individual and group goals.  Any decent analyst or tool provider should be able to set up this kind of reporting for you.

Popularity: 52% [?]

1. In the industry, web analytics has grown to become synonymous with clickstream analysis. However, it is important to recognize there is much more to web analysis than just clickstream data.
2. Website usability and the customer experience are tied very closely. Consider determining the value proposition your site will hold to your customers, and create an architecture that will leverage this.
3. When determining which analytics package to use, keep in mind one of the most important things is to spend majority of your budget on having an expert analyst to review the data, not the software itself.
4. Remember, hits, visits and cookies aside, these are real human beings visiting your website for real purposes.
5. There is one major downfall with all web analytics tools; they can’t tell you why people are coming to your site. Relying solely on clickstream data may result in false inferences. Realize the limitations of clickstream analysis and learn to incorporate “evolution” versus “revolution.”
6. Survey customers frequently to determine your website architecture, asking the 3 following questions: Why are you here? Were you able to complete your task today? If not, why?
7. When analyzing customer survey data, determine the percentage of customers unable to complete their task, and combine these results with the clickstream analysis.
8. The first step to creating a positive customer experience is to determine how you can involve the customer within your planning and revision processes.
9. Use web analytics to measure not only the most popular pages, but the length of the visit per page, the number of pages visited and the primary exit pages on your site.
10. Don’ t be afraid to frequently revise your website. Learn from your analysis and create an action plan to implement your revisions.

Popularity: 74% [?]

Fortunately for SMEs the Internet makes this process very easy. We can know who view the ad, when and how many times, who clicks on it, furthermore we can know where are they from even in which city do they live, what language do they speak and what computer system do they use, all the above information can be obtained in real time bases, which makes online marketing communication much better approach than offline marketing communication.
Not only it is faster and easier to track any marketing campaign online than offline, it is also much less expensive to make any adjustments to the advertising message if there is need to do so. (Rafi Mohammed et al 2003)

Using site visitor activity data:
The best way to understand user’s behaviour is watching them using the website, and analyse their movements and behaviour, all this information needed to do the above, can be obtained from the traffic log file where visitor activity data is stored.

Log files can reveal to SMEs the user’s background such as the exact time they visit, from which country and city they are from, what language they use and if they were referred by search engine what keyword or phrase did they use to come to the webpage, also information such as where do users click? Can they find important features easily? Are visitors spending time on the site, and if so, where? (Chaffey 2004)

Nevertheless server logs are difficult to read therefore web analytics program is needed.
Web Analytics According to Traction Search (2007) web analytics is “a tool that collects data on web site users behaviour”
Bruce Clay the leading provider of search engine marketing services (2007) stated that Web Analytics is essential for improving the performance of web sites and marketing campaigns. It also identifies the areas within the site that can be improved for better performance, and measure and track the results of any marketing campaigns.

However traffic analysis presents more questions than it answers. For instance, the log file may reveal that 90% of the users leave the site after the first page, but it doesn’t explain the reasons for that. Is the site very slow? Or is the design confusing? Or maybe the marketing message was targeting the wrong people?
Therefore for SMEs to be able to use this method effectively and read in-between the charts and graphs the web analytics program provides, they have to have some knowledge of their target market, web design, and Human–computer interaction.

Popularity: 23% [?]