Averages are an analyst’s best frenemy… Easy and quick to calculate, they indicate trends. While averages can sometimes be useful, they can also be treacherous as they often conceal information. The analyst’s job is to flush out this hidden information – to always go a step further, to look beyond the masses, to dig around and find the right insights which will trigger decisions and action… The devil is in the details, and so are the answers to your analytics questions.
Do you use the Analytics Suite but haven’t given Explorer a try yet? Want to learn more about this new tool for data exploration and its features? We’ll share 2 common use cases which illustrate how Explorer can be used to take your data analysis further.
Case #1: Analyse a drop in traffic
You’ve barely finished your morning coffee when you have a look at your reporting, only to discover a brutal drop in traffic. Your line graph has taken a plunge and you need an explanation. If you want to understand – and take action – you need to first investigate. It’s your job, after all! (And they say analysts should devote 50% of their time to analysis. Here’s your chance!).
What should you do?
Here’s what you shouldn’t do: stop there, with no explanation… First, try to identify if your overall traffic has been impacted: is the drop in traffic on just one of your sites, or on several of them? Did it occur on a particular site section, or on a specific page? A problem on a high-traffic page (like your homepage, for example) can have consequences on your overall traffic volumes. Which is why it’s so important to not limit your observations to averages, and instead push your investigation further. Another useful reflex: verify the impacted acquisition channels by checking your traffic sources. The drop can come from a decrease in organic traffic, as well as from a decrease in marketing campaign traffic, or from other factors.
Why use Explorer ?
In this kind of situation, Explorer’s real advantage is the depth of exploration it offers, and the simplicity with which it can display super-precise data. With just 1 report and a few clicks, you have all the information you need to decipher the situation.
The different viewing options available in Explorer, ranging in terms of granularity (overall view, sites and level 2 sites) make it possible to quickly go deeper with your analysis. You can easily compare different analysis periods (by month, by quarter, by year…). And a very useful tip: the drill-down graph displays the top sources, top pages, and even top chapters related to each item in the tables.
Best practice: To be in a position to react quickly if your traffic takes a tumble, set up an alert in the Watcher tool. It’s simple, quick and super efficient.
Case #2: Understand why your bounce rate is high
You’ve just launched your new employee recruiting campaign, complete with all its awesome components: display ads, emailing, PPC ads, and an updated version of your website’s “Careers” page. But you observe a bounce rate that’s relatively high (above 60%). Hmmm… maybe the visitor found the job offer he/she was looking for, and then left right away (the optimist’s explanation). But this could also indicate low interest in your content from this visitor, as generally speaking, a job candidate will do some homework on a company and look at a few pages. So let’s see how we can improve this.
What should you do?
First of all, you must distinguish the bounce rate of your overall site from the bounce rate of individual pages, as there can be significant discrepancies. For example, for a content-heavy site, the bounce rate for the home page might be around 20%, but around 70% for the articles. It’s also important to distinguish bounce rate from exit rate, which takes into account visits that involved several pages (contrary to the bounce rate, which is only calculated using visits that don’t go beyond one single page).
But going back to our example, to understand the bounce rate of your HR campaign, you must segment your analysis. The idea is to analyse the performance of organic traffic sources, and then do the same for your marketing campaign sources. This will tell you where to focus your efforts.
Our first observation: The bounce rate for organic sources is more or less identical to the overall campaign bounce rate (60%+), but much lower for marketing campaign sources (about 35%).
Ok, but a low bounce rate (which is a rather positive sign) doesn’t necessarily mean that conversions are high. It’s now time to see how your different traffic sources are converting. Analyse one of your important conversion pages (for example, the “Submit your CV” page) and then segment on organic traffic sources, then on marketing campaign sources. Compare the proportions of traffic from these sources with the total volume of overall traffic. If you see that marketing campaign sources convert better than organic sources (or vice-versa), it’s worth considering investing a bit more in this channel.
But don’t stop there. Refine your analysis even further. Send your data set to your data mining tool (Data Query, if you use AT Internet’s Analytics Suite). Integrate additional cross-calculations, custom metrics or dimensions. Focus on your email campaigns, for example, and try to identify the geographic location of your visitors, which devices they used, etc… In short, go further!
Why use Explorer?
Explorer’s advantage is clearly the flexibility it offers when it comes to data handling. You can add one (or several) segments directly in the analysis. With one click, you can enable, disable, delete or add segments.
Aside from its depth of analysis, Explorer’s streamlined navigation is also an advantage when leading your investigations. Save time by sending data sets directly to Data Query (data mining tool), with no need to reconfigure your scope and contextual settings. This feature makes it simple to go much further in your analysis without complicating things.
Best practice: Is your segmented analysis of conversions relevant and useful? Do you find it helpful to regularly monitor this performance indicator? Then export it directly to a dashboard, which you can then share with your colleagues via email or direct invitation.
Thanks to Explorer, we see that above all else, an analytics tool should enable us to go beyond simply observing figures. While reporting is evidently necessary, an analyst’s real added value comes from investigating, detecting weak signals, and building on facts to truly understand a situation. Producing recommendations first starts with data exploration and data activation. But to do that, you need to know how to use your analytics tool correctly (and to 100% of its potential!).