How to fish in the data lake of Analytics

Most Analytics systems act as a lake of data; housing valuable tracked information about customer interaction with an app or a website. This data lake, full or various fish and debris, can be valuable but also messy. Figuring out how to fish your lake of data that has a constant flow of new metrics takes time, but always proves very insightful. As you begin testing methods and seeing what data best influences your ROI, it’s important to realize that no two data lakes are the same.

Every site is unique
Every site is unique and should be treated as such. There can be some parity across industry verticals, but when it comes to analytics, every site should be treated like the snowflake or fingerprint. Be wary of following the “Top 10 things every business must track” lists. While many of the items listed in those comprehensive overviews are important, it’s always essential to look beyond and rather through the lens of your site, your goals, and your customers’ needs.

As there are many differences between sites and therefore ways to track and analyze analytics data, there are still some key overlying tips that are important to consider.

Boosting conversions
Most analytics managers main goal is to increase conversions, whatever those may be. As data comes in, it is helpful to use specific metrics to break down other metrics. For example, it can be helpful to calculate the percentage of visitors that actually hit the point of conversion. This is done by dividing visitors by the number of conversion events. Once that information is calculated, other data points can be applied such as, click path, time on page, referring domains, user segments, etc. By looking at conversions through these various lenses, the most effective paths to conversion begin to come to light.

Rookie mistakes in analytics
With many analytics systems, the first numbers you see on the home screen are those of page views, site visitors, bounce rates, etc. While these numbers are valuable, they should be taking a supporting role to other insights. What’s more important is to look at where those visitors navigate to, which content pieces or products attract them, and what actions they take as they hit those content pieces. By closely looking at this information, you can see where improvements can be made, where customers are being lost, and where optimization efforts can be most useful.

Every analytics discipline should include optimization. Adjust content, add content, and fine tune target audiences based on what you’ve learned in analytics. As your optimization efforts are implemented, you will begin to see what’s really effective, where your time is best spent and truly get to know your visitors. No to mention, the trial and error method of constant optimization almost always results in new and easier ways to guide customers toward conversion.

As you practice fishing your data lake, you will become familiar with the data pieces that hold the most value. This insight will help you reach your customers the best ways that you can and better drive conversions; because no one should feel like they’re drowning in endless calculations of site visitors, page views, and bounce rates.