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This chapter is from the book

Measuring Web Effectiveness

How do you know how well you are doing on Google? That is a rather easy question: You simply search on your keywords and see where your page ends up in the results. How do you know the volume of visitors you get from Google? This question is a little harder: You use a Web analytics tool such as Unica Netinsight to find out where your visitors are coming from and then filter the results to show only those who come from Google. You can also run reports in modern Web analytics tools that show what keywords brought users to your pages, and in what volume.

The more detailed you want to get in understanding the effectiveness of your search efforts, the harder the questions become. You can get a lot of information related to data such as Google ranking, Google referrals, raw traffic, no-results keywords, click throughs, and customer feedback specific to search, but correlating that data is quite difficult. The goal of this kind of research is to measure engagement: How many users are doing the things you want them to do on a page, such as downloading a white paper, filling a survey, taking a poll, or making a comment? We will discuss a best practice in gathering and correlating the various search effectiveness later in the book.

For the purpose of this discussion, suffice it here to say that how you define and measure search effectiveness is a fundamental facet of using search to target audiences with content. Search efforts rarely work exactly as they were drawn up on paper. More often than not, you will find aspects of your search efforts that underperform expectations. In these cases, you will have to go back to your pages and fine-tune your content to better target your desired audience. If you find a high bounce rate, for example, you might need to change the language on the page to develop better engagement with your target audience. The practices outlined above and detailed later in this book can help you do a better job of search optimization when you first develop and publish content. But language on the Web is a complex medium, and you can expect to have to do a certain amount of reworking to achieve better engagement. For this reason, measurement is a critical phase in search optimization work.

Also, to compete for users, search engines are evolving rapidly. If an engine changes after you publish information, it might make sense to go back and tweak your pages in ways that can help you rank better for it. To do this, you need analytics tools and best practices. We will describe how to use available Web analytics tools to measure search effectiveness and develop action items to improve existing content in the process.

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