One of the most important components of any Web redesign project is usage data. The good news is that data is readily available. The bad news is that many Web managers and their designers still rely heavily on instinct or personal preferences instead of taking advantage of data to drive their redesign decisions.
Why analyze data?
The great thing about developing products for the Web is that you can see, in real time, exactly how your customers interact with them. Armed with that usage data, you can increase click-throughs to key areas and, with luck, raise Web-based sales.
For example, let’s say your manager wants you to redesign your company’s Web site because sales from your site’s catalog haven’t been as high as expected. Your manager thinks the problem is that users can’t find the catalog, so he wants to spawn a pop-up window showing products from the catalog every time a visitor hits your home page. You don’t like the pop-up idea and suggest drawing more attention to the Catalog tab.
Without usage data to analyze, any decisions you and your manager make will be pure speculation. Maybe users can’t find the link to your product catalog. Maybe users are just using your site to gather information about products. Or maybe your company’s sales forecasts were too optimistic. At this point, any of those maybes is as good as the next, and none of them is going to allow you to say, with confidence, that a new design will be better than your current one.
With time and resources being in short supply these days, you can’t afford not to get it right the first time. Let’s see how to get started collecting usage data.
First steps
Fortunately, laying the foundation for gathering helpful usage data isn’t as difficult as you might think. You can do some things now that will help you set a baseline for your current site’s usage and enable you to make informed decisions about how to improve it.
The first step is to make your URLs easy to track. Sure, you could just measure page views for particular URLs or filenames, but that gives you only some of the data you need. What if there are three ways to get to the same page? How can you determine which path a user took? You need to be able to distinguish between those three links to get a more complete view of how users navigate your site. Let’s use Figure A as our example Web page.
| Figure A |
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Tag your links
A quick and easy way to measure which links are getting clicked is to add unique tags to each of your URLs. For this example, we’ll tag each URL based on its page position. We’ll break the page into three main sections: header, body, and footer. You can have more than one tag for each section; just make sure they are unique.
For the header, we’ll create two unique tags to specify where a user clicked. One is labeled logo and the other is tab. This will allow us to track when a user clicked on the logo to return to the home page vs. clicking the Home tab. It also lets us differentiate between clicks to other pages, such as the catalog, that have multiple entry points.
The catalog URL in the header might look like this:
http://www.yoursite.com/catalog.html?tag=tab
We can apply the same concept to both the body and the footer of the page. Here’s how each of those catalog URLs might look:
http://www.yoursite.com/catalog.html?tag=body
http://www.yoursite.com/catalog.html?tag=footer
In Figure B, I’ve added the various tags to the sample site.
| Figure B |
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Gather the data
Once the new tagged URLs are up and running on the Web site, you can begin to collect the usage data for the site’s catalog. Instead of gathering aggregate usage data for catalog.html, you can now identify the source of each page view based on the unique tags. In addition, you can compare the number of clicks for each of the unique catalog URLs to the other URLs that share the same tag. For example, you can compare the performance of the Catalog tab to the other tab URLs.
Instead of just being able to report that the catalog.html page got 100,000 page views in a month, you can also report that 60 percent of those views came from clicking the Catalog tab, 30 percent came from the link in the body of the home page, and 10 percent came from the footer link. You can also report that the Catalog tab is the most-clicked tab on the site, receiving 30 percent more clicks than the others.
How does this data solve the original problem?
With the data gathered from the tagged URLs, you can now show your manager that the catalog page is actually getting the majority of the site’s page views. The problem with the sales numbers doesn’t appear to be related to a lack of traffic to the catalog page as your manager asserted. So, instead of creating a pop-up window or changing the tabs to get more clicks to the catalog page, you and your manager can now focus on determining why so many users are visiting the page but not following through with a purchase.
Listen to the data
Remember that data alone is never going to give you the solution to your problem. Analysis of the data is just as important as the collection of it, so make sure that you’re willing to listen to the data and continue exploring it. Your findings will help you make more informed decisions. Just don’t be surprised if the data proves both you and your manager wrong.
