If you are new to web analytics or have recently updated your software, you might feel like you are drowning in data. But don’t worry, we’re here to help.
The first thing to say is this: too much data is a nice problem to have. It wasn’t so long ago that marketers had to resort to some fairly arcane, unreliable methods to estimate their sites’ performance. Today, you have your pick of hundreds of qualitative and quantitative measures that can help you target your marketing much more effectively.
And this is the key: targeting. When you first get a new piece of analysis software, it can be tempting to collect everything, just in case it becomes useful at some point. This approach is likely to lead to you being quickly overwhelmed by data, and overlooking important metrics in the flood of numbers.
In this guide, we’ll show you how to build a web analytics strategy that keeps you focused on your goals, that produce reliable and useful information, and that allows you to spot trends easily.
The first and most important principle of effective web analytics is to design an analytics strategy that is integrated with your business goals. These can be simple, such as increasing your social media followers, or complex, like total dominance of a particular market. The key is to make sure that these goals are measurable.
Often, this comes down to finding one or two metrics that genuinely inform your ongoing marketing decisions. In the same way that the best password management apps reduce the complexity of making and remembering passwords into using just one, you can often reduce dozens of raw metrics into one measure.
This could be, for instance, the number of customers who sign up for your newsletter or download a report. Knowing exactly the path they have taken through your website to get there can be interesting, of course, but only insofar as it helps you to achieve your primary goal.
This principle is linked to another. You should be aware of the issues surrounding web analytics and data privacy, and recognize that today your customers genuinely care what data you are collecting on them, and what you are doing with. In short, just because you can collect a piece of data doesn’t mean that you should.
Targeting your data collection in this way is an enormous help when it comes to avoiding data overwhelm, because you have far less data to wade through when it comes to making your analysis.
The next stage in building a web analytics process is to think carefully about your “data schema”. This is a phrase that can be intimidating to those new to data-driven marketing, but in practice, it means something quite simple: your data should be organized in a logical way.
Most businesses take the following approach. All of their web analytics data is organized by UID, the unique number that identifies each customer visiting your site. Though you can collect more general information on the number of visitors to a particular page, each view should be linked to a UID in order that you can (if necessary) look at the “journey” of individual customers.
Alongside each UID is also the metadata, such as the location of the user, and perhaps demographic information about them. Collecting and organizing data in this way suggests a natural model for both analyzing it and storing it: a “tree” structure in which each user account (or session) can be broken down according to a number of key metrics.
Alongside your data schema should also be processed for managing the reliability of the data you are collecting. You should build into these processes mechanisms for managing duplicates, finding and adding missing information, and highlighting where data may be out of date. That’s because the only thing worse than too much data is too much incorrect data!
Finally, you can use the work you have done in identifying and collecting your data to feed directly into the way that you present it. If your business goals are clear, and if your data is organized in a logical way, then the way you present your findings should be clear enough because you know what’s important for your business.
Using web design software tools to help visualize data is quickly becoming a popular way of doing this. There are plenty of visualization tools available, and the one you choose depends on your specific needs. However, it’s also important to make sure that all key team members have access to these tools, so they can use them to inform their own work.
Visualization is perhaps the most powerful tool available when it comes to combating data overwhelm because you can take complex data structures and present them in a way that instantly highlights the goals you have identified. If done correctly, visualization can also help to identify areas in which you need to improve your messaging or work on the functionality of your site.
The Bottom Line
Though web analytics, software offers among the biggest ROIs small businesses can make, the sheer power of this software means that it is easy to become overwhelmed by the data you are collecting.
The key, as we’ve discussed above, is to be clear about what you want to achieve. Technical solutions, like web analysis, are tools that can be used to achieve specific goals. No web analysis software, not even the best around, is going to replace the value of strategic business planning and intelligent tactical decision-making.
Instead, look to web analytics as a targeted system for finding the answers to specific questions: carefully think about what you need to know, structure this data rationally, and present it visually. That way, instead of wading through endless spreadsheets, all the important information you need at your fingertips.