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?
If you have a website that is contributing to your business either directly or indirectly, you will probably want to track at least one of these events. Doing so will enable you to make smarter marketing decisions and make a start on a conversion rate optimisation strategy.
Before dismissing your great idea for the next campaign, ad, or website landing page, make sure you don't rely solely on qualitative data. By incorporating current neuroscience studies and other qualitative data to form hypotheses, you can begin testing these hypotheses thoroughly and interpreting the results to maximize your conversion optimization and create your next breakthrough campaign.
In this post you will learn everything you need to know about Google Analytics Cost Data Upload, a feature that allows you to import the extra pieces of data belonging to your non-AdWords paid campaigns into Google Analytics.
In this article Scott Shannon looks at the new demographic and psychographic segments in Google Analytics, and we learn how we can use this information to help inform our marketing and advertising initiatives. Using user segments in conjunction with audience/customer demographics opens up a whole new realm for web analysts and marketers.
This article is a step-by-step guide on how to visualze Google Analytics data using the R programming language, a powerful statistical language. It provides both the the code necessary to do so and the explanations on how to make it work.
This tutorial is a step-by-step guide on how to integrate Fusion Tables and Google Analytics. I present an App Script that gets data using the Google Analytics API and populate it into Fusion Tables.