In this post, Kristoffer Olofsson covers some of the benefits of using Custom Definitions in Universal Analytics, as well as have a look at how they are leveraged in practice by startup 'The Beta Family', a crowdsourcing platform for beta testing apps.
In this post Daniel Waisberg describes a dashboard that can be used to measure your most profitable channels, pages and demographics when it comes to AdSense revenue. He also shares a link to download the dashboard using Google Analytics.
By my unofficial count, there are approximately a million ways to segment your users within Google Analytics. One of my favorite segments for predicting future success is looking at the demographics reports, because they allow us to look at the age range and gender of our customers to a great level of accuracy. Learn how to make the most out of it.
This article is a guide to the new Google Analytics Chrome extension: In-Page Analytics. The extension is intended to help its users understand their customers in a better and faster way.
Following a recent post at Online Behavior on Visualizing Google Analytics Data With R I thought I would share my own Shiny application (a free package available for R) for visualising visits, bounce rate etc. from websites.
This article shows how to easily rewrite multiple URLs in Google Analytics with the help of Google Tag Manager (GTM). This solution is life changing for websites that do not have friendly URLs, which makes analyzing customer behavior on websites very cumbersome.
Content experiments for mobile apps can be extremely valuable to a business. We are no longer dependent on long development cycles as soon as we want to test something new. And when we do want to test, we can do so faster, more accurately, and with more certainty to avoid costly mistakes based on hunches. Learn how!
Are you struggling with Google Analytics segments every now and then? Would you like to learn how to use/build them instead of just being overwhelmed with a "best segments" posts? If your answer to these questions is yes, I recommend you read this article very carefully!
This article provides important statistical references and actionable tips in order to run A/B Tests in a professional way. The ideas reflected in this article will help you improve your A/B testing techniques for better decision making and conversion rates.
We've all been there. Everything on surface looks like it's running smoothly. Data is coming in. The 30,000-foot view of your account looks like business as usual. You start upping your analytics game. Maybe you took some training and you're getting your hands dirty asking the tough questions of your data. But how do you know if you can trust your data in the first place?