Bypass the massive time investment of a Google Analytics learning curve with three methods for locating the data and insights you need.
Without a degree in data science, the Google Analytics learning curve seems to soar above the heads of professionals seeking its benefits. You’ve installed in the hopes of answering vital questions:
- How many people visit?
- Where do my visitors live?
- Which websites send traffic to my site?
- What marketing tactics drive the most traffic?
- Which pages are most popular?
- How many visitors convert?
But without a practiced eye, it can be difficult to know where to look. Given Google’s particular habit of altering navigation, removing features and renaming reports, you may also find yourself in a frustrating and unwieldy time investment.
Here are a few reliable methods to find what you’re looking for in Google Analytics without losing your mind.
Search Rather Than Browse
It’s possible to peck your way through the navigation tree, but it’s not recommended.
For one thing, Google alters its navigation roughly every six months in a messy game of musical chairs — brand new reports enter the scene while others are transferred to different sections.
Perhaps the most frustrating, and least intuitive, intervention is the renaming of reports and metrics that professionals have already internalized as fact.
How do you make the best of a resource that can never seem to be pinned down? Consider the two ways in which you can search Google Analytics:
Google is, after all, the master search engine. The left-hand search bar is best used to find report themes (i.e. “location,” “mobile device” or “source”), and one to two-word search queries will surface the most relevant reports for those searches.
The second method to find what you’re looking for is emergent in its newness: Analytics Intelligence. Ask any question about your data in plain English and Google Analytics machine learning algorithm will try to answer your question. For example, you can ask: “How many users did we have last week?”
The quality of the answer will depend upon the quality of the data you’ve collected, but it attempts to locate an exact data point to match your query.
Google consistently retools and tests features, and this AI tool has improved in accuracy and usability in recent months.
Create Advanced Segments
Have you been curious which of your online marketing campaigns (anything from local search to social media marketing) are the most successful in terms of driving traffic and conversions to your website? To find the answer, you’ll need to locate and create advanced segments.
Clear, direct search queries will surface the best results:
- “How much organic traffic did my site get in October?”
More complex questions require a conditional segment:
- “How many organic visitors who landed on X page went on to buy more than $100 of product?”
Add a new segment to compare against All Users.
Create a naming system for search purposes later.
Fill out the Advanced section.
After finishing this segment, you have the ability to use it in the Google Analytics UI and Google Data Studio.
Leave the Google Analytics UI
Why would you free your data from Google Analytics?
Typically, you can avoid data sampling by leaving the platform. Sampling occurs so that reports can be presented to you faster, but if you’re exporting weekly or monthly metrics to clients or simply pulling a select few metrics at each sitting, you can access unsampled data more often and more easily.
The other benefit is essentially aesthetic. You can more easily build your data stories and visualization of the data without the limits of stock program defaults.
One way to do this is to export to Excel in order to use pivot tables. Why not relocate the data in an environment in which you’re comfortable?
The .csv format is tried and true, and mostly compatible.
For beginners and Google Analytics pros alike, these three methods will hopefully help you bypass the weighty time investment of finding the two things you want most: data and clear insight.