Analytics Reading List | May 2016

. Posted in: Inspiration
Tags: Reading List

This is the first post in a series of Reading List posts. Part of working with web analytics and conversion optimisation is to keep learning. There are a lot of ways to learn; conferences, books, networking and so on. And then there are people you don’t know. I use Twitter, LinkedIn and even Google+ to follow people that do great stuff within Analytics. And very often, I’ll come across interesting posts or articles with great solutions for different analytical problems. With this series, I want to share what I believe to be some of the best recent articles. And please do send me a suggestion if you think I should read something.

A Comprehensive Guide to Tracking Offline Interactions in Google Analytics:

This is a pretty straightforward tutorial that explains how you can stitch together a complete customer journey from online interactions to offline sales in a store. By using the measurement protocol and saving what you know about your visitors, you’ll be able to get a much better picture of your real ROMI.

Mixing Google Analytics Dimensions and Metrics:

In this post, Krista Seiden, Analytics Advocate with Google, explains why there are some dimensions and metrics that just can’t be combined. It all comes down to the Google Analytics data model and how various dimensions and metrics are either related to users, sessions or interactions.

A Great Analyst’s Best Friends: Skepticism & Wisdom!:

Straight to the point as always, Avinash makes a great point in this post on what makes a great (web) analyst - the ability to be skeptical and always question data in front of you, while knowing when to stop and make a decision based on your (analysed) data.

Google Analytics Mistakes that kill your Analysis & Conversions:

This post sort of ties into Avinash’s view on skepticism and wisdow, but gets more in-depth and hands-on with Google Analytics. What data¬†should you collect, what data should you trust, and how can you avoid misinterpreting your data?