There is a wealth of information in Google Analytics, helping website owners gain a deeper understanding of who’s visiting their site and how often; what they click on and their navigation path; and what pages or links lead to particular outcomes like downloads or purchases. Google Analytics shows how effective site search is in generating clickthroughs and conversions, shopping cart abandonment rates and more.
However, without knowing how to interpret the data and what it’s telling you, you’re not getting the whole picture. For example, you might put too much attention on raw totals, when it makes more sense to look for trends or compare different segments of data. Or, you might inadvertently exclude traffic that you should keep measuring.
The engineers I work with have developed a useful list of common mistakes that website owners make when using Google Analytics and site search, along with guidance for better understanding of what’s happening on your site.
Mistake #1: Trusting that your site search statistics are correct. By default, Google Analytics tracks every page against the URL of the page loaded. Assuming that your search page has the URL “http://sub.domain.com/search?w=keyword” Google Analytics tracks the page as “/search?w=keyword.”
When setting up site search reporting, you specify the query parameter that defines a search page view. In the above case, the query parameter value would be “w.” This means that any URL on your site that contains the query parameter “w=xyz” will be tagged as a site search page view.
The problem here is that this query parameter may exist on non-site search pages. It’s not always easy to see that these pages exist. There could be non-site search pages that have this query parameter in the URL – which means site search reports may not be accurate, and you will not get a clear picture of how site search is performing.
The solution is to use advanced segments instead, since they’ll allow you to be more specific about the site search segmentation and will give you the platform to be more precise about identifying visits with a site search page view. For example, you can say something like: “Include pages that begin with /search” or “Include pages that contain the query parameter w.”
It’s also a good idea to avoid using site search URLs in your navigation and/or PPC campaigns. Get a different URL structure for the same page setup, such as http://sub.domain.com/ppc/keyword or http://sub.domain.com/nav/brand/nike/0.
Mistake #2: Focusing on the totals. Google Analytics will always underreport results, given that it is focused on JavaScript tracking. Therefore, results don’t take into account that there is a small percentage of site visitors who will click away before allowing the page to load long enough for the tracking code to fire. There are also site visitors who will have JavaScript and/or cookies disabled.
Thus, you shouldn’t be too concerned with exact results. Instead, focus on trends and comparing different segments of data (e.g. visits with site search versus visits without site search) or time periods (e.g. visits with search in June compared to July).
Mistake #3: Forgetting about AJAX. The AJAX programming language has become ubiquitous on the web in recent years, since it allows site visitors to load content without reloading an entire web page. You’ll often see AJAX used for search results so that users can quickly access more results without waiting for new pages to load.
Before the widespread use of AJAX, if a user wanted to click on a new page of results or perhaps select different refinements, the page would have to be loaded again and the Google Analytics code would have tracked it as another page view. But with AJAX, these interactions on your site are no longer tracked. It has become common to use virtual page views or event tracking depending on what you are trying to track.
This is a simple JavaScript function call with a URL as a parameter. Here are two examples depending on the version of tracking you are using:
gaq.push([‘_trackPageview’, ‘/search?w=keyword&pagenumber=2’])
ga.send(‘send’, ‘pageview’, ‘/search?w=keyword&pagenumber=2’)
Mistake #4: Using too many profile filters: Profile filters are useful to help scrub your data at a global level – for example, removing traffic internal to your organization. It’s easy to get carried away and use so many of them that you exclude traffic that should be part of your results.
Familiarize yourself with advanced segments to help segment the data for analysis, rather than always excluding it from a profile. And always keep one unfiltered profile – this can be your fallback when the filtered profiles are causing data loss.
It’s best to exclude internal traffic by IP range (or some similar factor) since it’s probably from employees and therefore not your target audience – the traffic will skew your analytics data. An example would be a call center that is processing phone orders using your website. These are likely to have a much higher conversion rate than your actual site visitors.
Mistake #5: Comparing apples with oranges. Google Analytics allows you to easily pull a report with conversion stats. This is both good and bad: It’s too easy to pull incorrect data and base the rest of your analysis or report on the bad data.
Maybe this conversation sounds familiar to you: “This week, we had a 4% conversion rate – but we usually average 4.5%, so we need to fix this.” However, it’s a bad idea for you and your colleagues to take such fluctuations as business gospel. When pulling data on a particular date range, you might miss out on weekly or monthly peaks that could contribute to higher conversions. You also might exclude days that have lower conversions. There are other factors to consider like seasonal changes, clearance sales and email campaigns, to name a few.
Often the conversion data you’re pulling from Google Analytics is different from revenue data coming from elsewhere in the business. This revenue or other data might include PPC (pay per click) traffic coming from search pages used as landing pages, which should be excluded from the “visits with site search” segment since the visitor hasn’t actually interacted with the search box.
Take note that Google has recently released a new Universal Analytics tool, which includes some important changes we’re excited to see. We’re still waiting to see what the main gains will be, but I personally am happy that the number of custom dimensions offered has been increased for regular and premium account holders.
The data in Google Analytics can help guide decisions about changes to site search, products and navigation design – all of which can boost your chances of improving conversions and generating more revenue. Just make sure you’re looking at this data with a critical eye, and fine-tuning Google Analytics so that the results are meaningful.
