Analytics can be a scary subject if you don’t understand what they’re all about. Because of this, it’s easy to fall back on what you know from previous calls or reports. That can limit the learnings that you’re passing on to others. Every project is going to be different, and some metrics aren’t necessarily applicable across the board. Before any sort of reporting, establish the goals of the project to choose what metrics will best determine the success of a project or campaign. This is part of what makes up successful data analysis.
If the goal of the campaign is to drive visitors to your site and view a landing page’s content completely, metrics such as time on page and scroll depth will be important to measure and report on. Average time on page above the website’s average and a higher-than-normal scroll depth would be successes that you’d want to emphasize in your reports.
Now, a big buzzword metric is bounce rate. In the example above, if the page is successful at doing its job, the bounce rate will likely be higher. Many people would look at this and think “Oh, no! Something’s wrong with the page. We need to make updates.” But nothing is wrong with the page if scroll depth and time on page are above site averages.
People tend to look at bounce rate as an indicator of whether a page is working, but bounce rate doesn’t always mean something is wrong. Bounce rate means more than just people leaving the page immediately after landing on it. Bounce rate is determined by whether a visitor fires an additional page view or engages with an interactive feature on the page, like a call to action (CTA) or video.
Bounce rate can also be skewed if certain events aren’t tagged properly on the site, which can make this metric useless.
Another example of a metric you can take out of context and use incorrectly is average time on page and site. If the goal of a campaign is to get a visitor to land on a particular page on your site, and then click toward a different site for whatever reason, then key metrics to look at will be different.
The goal in this example is to not necessarily have this person spend that long on the current page or site, so metrics such as time on page, time on site, or pages viewed/visited will be misleading. Metrics that will likely determine success will be an accurate bounce rate percentage and clicks on CTAs.
The goal of the page is to not linger on the page or the site for too long because that would indicate the visitor isn’t taking action to move through the particular goal funnel. This is why time metrics won’t be useful in this scenario. Many times, people will assume that higher-than-average time spent on the page or site would indicate success. But the goal here is to move people along to the next site. So in reality, a higher time spent on site and a lower bounce rate would not be an indicator of success, but instead reveal that CTAs are too far down the page, or that content on the page isn’t convincing enough to lead to a CTA click.
The biggest measure of success here would be viewing the number of CTAs clicked on the page, the rate at which people click a CTA on a page, and whether or not the bounce rate (when correctly tagged) is a smaller percentage than the site average.
These are just a couple of examples that we at Pace have noticed, and we urge anyone starting any sort of campaign or project to establish what the goals of the campaign are to better determine the correct metrics to use.
TL;DR: Not every metric accurately determines the success of a campaign. Figure out what the goal is and then determine what metrics best tell a data story for the particular project or campaign. Not all metrics are the same!