![]() ![]() You can also use Excel to measure statistical significance. For example, Quietly Insights, can provide you with statistical significance information and inform you whether something is worth actioning on. One option is using a tool that compiles and calculates this information for you. There are a number of ways that you can understand the statistical significance for metrics on your site. ![]() How Do I Find Statistical Significance for Web Analytics Metrics? You can investigate why spikes or downturns in various metrics occur, even if you haven’t made any changes or started a new campaign.For example, if you recently implemented a Facebook campaign, and found that the campaign month received a significantly higher number of visitors from Facebook, you can conclude that your campaign was effective.You can understand whether your recent campaigns were actually impactful.You can ensure that you don’t take action on information that’s likely due to chance, or just part of your site’s natural rhythms.Here are some ways that calculating statistical significance can benefit your site and overall operations: In short, measuring the statistical significance of metrics on your site helps you better quantify whether your efforts are actually working and know when a mysterious change is worth evaluating. Why Does Statistical Significance Matter? Statistical significance can help determine whether each variance is something out of the ordinary, and therefore worth investigating. Should you be concerned about the down months, or celebrate and analyze the up months? Are particular spikes or dips meaningful changes (actual outliers)? Or, do they reflect the natural ups and downs of running a website? This data fluctuates by day, by month, and by year.įor example, maybe your pageviews are increasing slowly over the year, but there are a few months that performed better or worse than expected. ![]() Well, chances are, your web traffic (or metrics like bounce rate, average time on page, etc.) doesn’t progress in a beautiful, smooth, upwards-trending line. So, how does statistical significance apply to your Google Analytics tracking? If the result is less than 5%, we can say that this change is statistically significant and can’t be explained by random chance, since the probability of seeing this number occur organically is so low. If we compare this month’s data with historical data, we can calculate the probability that July would have earned 1,000 or more users organically. How do we know whether this increase is actually a “significant” change worth looking into? Let’s say that in the month of July, 1,000 users visited your site, an increase compared to June’s 900 users. Here’s an example from a web analytics context: 5% is the universal standard employed by scientists, and is widely viewed as an acceptable risk. In application, this means that this result didn’t just occur by chance, and that it’s likely caused by some factor. In hypothesis testing, the result of an experiment is statistically significant when there’s less than a 5% chance that more extreme results will occur when the same test is conducted in the future. But how do you determine which changes are significant and which are due to external, unsolicited factors? How do you understand if your campaign efforts are directly driving users to your site and increasing traffic, or if certain campaigns are performing better than others? Measuring the statistical significance of the various metrics that affect your site can tell you a lot about the success of your marketing campaigns and can help you to make strategic changes that will benefit your company. What is statistical significance and why does it matter for your site? If you’re wondering how to measure the success of your company’s campaigns and overall marketing efforts, read on.Īnalyzing changing traffic and engagement patterns on your site is a necessity. ![]()
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