Are You Making These Painful Web Analytics Mistakes?

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Data, and analyzing that data, has become such a big thing in the world of online business. But despite the number of advances in web analytics, an alarming number of businesses are making some grave errors when it comes to the practice.

Part of the problem is that businesses often underestimate not just the importance of web analytics, but also the complexity. It’s not as simple to improve your website using web analytics as you may think. That’s why we’re here to help point you in the right direction!

If you want your online business to grow, the use of web analytics is vital. Here are some common analytics mistakes that you can’t afford to make.

Not using them

The ultimate error. In your defence, if you’re not even using web analytics, then it’s impossible to make all the mistakes with analytics that can harm your business, right? But this isn’t actually a useful way of looking at things.

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If you’re not taking advantage of web analytics, then you’re missing out on amazing growth opportunities. And if you do have the necessary tracking capabilities but don’t actually check the analytics data, then you’re basically committing the same error. If you find the whole business complex, then it’s best to use an online business hosting solution that helps make the process easier.

Despairing at low numbers

Many make the mistake of assuming that all low analytics numbers are a bad thing. This isn’t necessarily true – and even the bad ones should be seen in a positive light. There are certain metrics where low numbers are a good thing. Let’s say you’ve got a low rate of people unsubscribing from your website or email service in a given timespan. That’s good!

Now let’s say you’re getting fewer visitors from a particular source. Not a great thing, but having that information is a great thing. You can now make changes and guide your marketing in more effective ways. If you weren’t using analytics, you wouldn’t know what wasn’t working.

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Assuming empirically observed covariation is a sufficient condition for causality

Sorry; logically, this is the most accurate way of getting across the idea implied in the phrase “correlation does not imply causation”. Basically, it’s not wise to assume that a similar trend occurring with two items are definitely related. The terms “cat” and “premium apk” correlate in Google Trends, but this doesn’t mean the growth of one is related to the growth of the other! So if the correlation between, say, the increase of a particular marketing campaign and the increase of visitors from the targeted source doesn’t mean that the marketing campaign is definitely working.

Of course, it’s worth highlighting that correlation does, in fact, often hint at causation; you just need to remember that it’s not the only condition to which you need to pay attention! The problem with analytics is that so many business owners try to read them through the lens of popular terms about statistics that either aren’t true or they don’t understand. Don’t make this mistake!

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