Google are pushing hard for website owners to adopt Enhanced Conversions – also referred to as “hashed first-party data”. This post outlines the implications of using this, its impact on customer trust, and the alternatives for data collection.
An interesting discussion was developing on LinkedIn by a fellow data author Brent Dykes: Data-Driven vs. Data-Informed, and I wanted to contribute to it here also. A more philosophical post from me.
Since GTM introduced an automatic way of tracking scroll depth in Google Analytics, there has been a proliferation of this tracking. In this post I explain why you should avoid such “noise” and avoid the cost implications.
Now and then I tease myself by trying to predict the future, and so in preparation for this years’ attempt I found myself reading the recent Forrester Prediction 2019: Business Insights report.
Part of my job involves the audit of Google Analytics setups in order to establish the quality of the data collected. This video story brings together some of the extraordinary findings of this work. It’s a study of 75 enterprise websites using Google Analytics.
Universal Analytics collects and stores visitor IP addresses by default. These are used to provide geolocation information about your visitor – such as which city, country, continent visitors connect from. In the new GA4 however, no IP addresses are stored. That’s a big change in approach. In this post, I investigate what impact that will have on your data.
In this post I discuss why surveys often end up being a silent brand killer that also produce skewed data, as well as how to increase survey participation without damaging your brand….
If you have a transactional site, then of course you will want your transactional and product data as measured by Google Analytics, to match the real sales numbers that your back-end system collects. However in reality, these never exactly match due to a number of issues.
I continuously come up against smart people with responsibility for data who remain waaaay too focused on data points, rather than the business they support. A good example of this is the confusion that is stirred up when discussing KPIs…
ClickZ is a great learning resource. Even for expert readers their articles are well researched and informative - they simulate thought and further...
The question of data trust is what I see as the biggest issue facing the digital analytics industry at present. Why? Because it is so easy to collect junk data online. And businesses will not act on data unless they have trust in it. Is this scenario true? Take part in the Trust Survey.
This is Part ONE of a three post series. In this post I discuss what digital data is accurate (and what is not) from a publisher’s point of view.