Bad bots bad bots, whatcha gonna do
Common threats to the accuracy of your data are spam, bots and internal traffic.
Detecting spam traffic can be tricky. You’ll often find spam evidence in your referrals, but they can also hide in other reports too. If you come across a language, page title or keyword that looks suspicious, it’s best to err on the side of caution and treat the traffic as spam.
As for bot traffic, there are good bots (like the monitoring, commercial and search engine bots) and bad bots (like impersonators, scrapers, scanners and hackers).
When most people hear “internal traffic,” they usually think of direct internal traffic, but there are other types of internal traffic. Two examples are third party sites and development/staging environments.
With all of these threats, it can be difficult creating accurate filters in Google Analytics. Here’s a nice guide from Carlos Escalera on how to filter different types of data threats.
moz.com | Carlos Escalera | June 12, 2018
Eye Spotify with my little eye
This case study on Spotify is a great example of creating business strategies from data analysis. Spotify realized that the most streamed content in Germany was audiobooks. They could have jumped all in and created a marketing strategy around audiobooks, but what if their hypothesis was wrong? That’s a lot of money wasted on a false lead. Instead, they decided to test their hypothesis. For users based in Germany, they showed half a regular landing page, and the other half a landing page dedicated solely to audiobooks. The result was a 24% increase in their premium subscriptions. Read the rest of Google’s case study to learn more.
analytics.googleblog.com | May 30, 2018
In the context of analytics, an anomaly is any piece of data that doesn’t conform to the expected. In this article, Nikolaj Bowmann Mertz explains the different types of data anomalies and how to implement anomaly detection in Google Analytics.
medium.com | Nikolaj Bomann Mertz | May 25, 2018
Multidimensional Analytics Universe
In a lot of our weekly roundups we feature articles with topic-specific dimensions. In this week’s curated post, we’re featuring an article that explains 13 custom dimensions you can apply to your Google Analytics account.
simoahava.com | Simo Ahava | May 29, 2018