In October 2020, Google started to roll out Google Analytics 4 (GA4), billed as “the future of analytics”. Here, we outline in basic terms some of the differences from Universal Analytics (UA) and next steps you should take to maintian the integrity of your insight.
The current crisis is tough on everyone. I recognise that even in the good times, charities, non-profits, and NGOs can struggle to fund, deliver, and justify their essential work.
We’ve all suffered losses in business, funding, and activity (not to mention the terrible human toll of Covid-19), so I’ve decided to offer some pro bono consultancy to any charities large or small who would like to explore the potential of data analytics.
Following my recent posts on data visualisation and Google Data Studio, I thought I’d share another demo of the potential to visualise data beyond marketing analytics.
Once again, using the fantastic data.world open source platform, I’ve created a project for the COVID-19 crisis, which imports data from an external source. I can then link to this in Google Data Studio, along with a simple SQL query to extract the data I’m interested in.
Data visualisation is all the rage. Some day in the near future, we will be done with spending endless amounts of time producing static reports in Excel, PowerPoint, and Word, instead working with eye-candy dynamic reports such as those provided by Google Data Studio, Microsoft Power BI, Tableau, and many others. These platforms allow diverse data sources to be linked in near real-time to a single report or dashboard, from where users can interact with the data.
Demand for ecommerce reports in Google Analytics seems to be on the rise. Having recently consulted on a full Google Analytics Enhanced Ecommerce implementation, I thought I would share some straightforward, limited-jargon insights into how to best set up Google Analytics ecommerce tracking.