8 Common Mistakes When Using Web Analytics

By Kat Liendgens — Tuesday, January 13th, 2015 at 10:00am
8 Common Mistakes When Using Web Analytics

You’re diligently tracking your web analytics. You frequently make an effort to dissect your data and compile reports for various stakeholders. You try to gain valuable insights and communicate them to the higher-ups. There’s no question that analytics require a significant amount of time and dedication, so you want to make sure to follow best practices and to avoid simple mistakes. Avinash Kaushik wrote an excellent book, “Web Analytics 2.0”, in which he dives deep into how to get the most out of your data. While reading it, I noticed eight common pitfalls to watch out for with analytics. Let’s take a look...

#1 - Obsessing Over Pageviews

Some of the easiest metrics to report on are pageviews. They’re easily accessible, and most stakeholders know exactly what they mean. In fact, how often have your managers, directors, or VPs asked you about how much web traffic you’ve been generating? The conversation immediately zeroes in on pageviews. While they’re a fine metric to track, they don’t give you as many valuable insights as you need. For instance, you won’t know how much traffic came from humans, versus bots crawling your site. In addition, you still won’t be able to appropriately interpret the quality of your visitors. Are you attracting the right type of audience? Furthermore, without looking at trends over time, you have no idea whether the changes you’re making are effective. Similarly, if you have no way to correlate all of your actions with the results that your data shows, it’s challenging at best to come up with a repeatable strategy.

#2 - Not Establishing Context for Your Data

One of the most detrimental things you can do when reviewing analytics data is to jump to conclusions. Without context, any metric is just a meaningless number. So be sure to show both trends over time, and point out specific events that caused those ebbs and flows. In addition, don’t forget to segment your data as much as possible. For instance, you may look at your ratio of new versus returning visitors. There’s not a ton of insight from this data unless you add segments. For instance, you may segment the data by traffic type and see that your returning visitors have a much lower percentage if they’re using mobile devices. Now that’s something you can act on by focusing on your website’s mobile experience.

#3 - Focusing On Averages

In an effort to interpret your data quicker, you may look at metrics such as “Average time on page”. But does that really help you? If the average time on page is ten seconds, you may get discouraged and conclude that nobody wants to read your content. But if you drill down further, you might uncover that a large percentage of the short pageviews were one second views, likely by bots, while there’s also a significant amount of views that lasted several minutes. As you can see, averages don’t always tell the whole story.

#4 - Only Reporting Raw Data

Analytics are great at showing you what is happening, but not why something is happening. If you only report on raw data, your efforts are useless. Instead, drill down into segments and look at events that happened during a specific time frame in order to provide better insights into the reasons why your data is what is. But don’t stop there. After sharing your insights, explain which actions you will take. After all, if data doesn’t change the way you do your job, why would you even concern yourself with it? The next time you’re presenting your analytics report, be sure to include insights and action items.

#5 - Not Focusing On Results

Let’s be clear: one million visitors is not a business goal. It can be used as a benchmark to measure whether you’re on the right trajectory to achieving your goals (if you have enough context). What you really want to do is show how your efforts help achieve organizational goals. Never lose sight of this important fact. At the end of the day, page views or sessions don’t pay the bills. Conversions and outcomes do.

#6 - Being Reluctant To Test

The main purpose for tracking and examining your analytics data is to empower you to become more effective and to increase your ROI, which is only possible if you don’t accept the status quo of your website. The only way to improve is to test - frequently. This doesn’t mean that you have to do major overhauls of your site every few months. Start small. Pick your five worst performing landing pages and make changes to the design, the wording, the value proposition, or your calls to action. A/B test certain aspects of each page. Track your results to figure out what works.

#7 - Ignoring Social Analytics

A large portion of your target audience engages with you on social media channels, so don’t forget to include pertinent social statistics in your analytics report. Don’t just measure clicks, but also engagement, such as comments, shares, likes, poll submissions, and mentions. Incorporate those data points into your analytics reports where it makes sense and demonstrates how your social media efforts are increasing engagement and how engagement drives outcomes.

#8 - Forgetting About Offline Activity

Today’s marketing and sales funnel is very complex. Your target audience doesn’t just go to your website and convert instantly. There are many potential touch points, some of which happen offline. For example, a prospect may see your billboard or scan your QR code from a print ad. A prospective student may come to an open house event. Be sure to track all interactions with your audience, so that you can get a more holistic picture of how well your marketing efforts are paying off.

What about you? What are some other pitfalls to avoid when it comes to analytics?

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