Data Collection

How to use the (UTM) Campaign URL Builder

The Campaign URL Builder for Google Analytics is a free tool. It lets you build URLs by appending certain parameters to your existing landing page URLs. In turn, this lets you track inbound traffic from marketing campaigns in Google Analytics on a detailed level. Ultimately, you’re better equipped to analyse the performance of campaigns. And you’re able to do so on a per marketing channel basis.

Let’s say you’re running a Winter 2016 Sale. You promote it on Facebook and in your email newsletter. By using the Campaign URL Builder, you’re able to track visits, behavior and conversions related to that campaign. And you’re able to examine it on marketing channel as well and see how the campaign is performing on Facebook vs. the newsletter. Continue reading

Data Quality

Fix Duplicate Ecommerce Transactions in Google Analytics

A relatively common issue with ecommerce tracking in Google Analytics is that transactions are often counted more than once. This is not really caused by an error in Google Analytics. Rather it’s a problem in the ecommerce platforms and the tracking implementations. For the most part, Google Analytics will trust that you send valid and correct data. So it doesn’t try to correct anything. But just like it’s possible (but not allowed) to log PII (Personally Identifiable Information) in Analytics such as email addresses, it’s also possible to log the same transaction multiple times. Basically, Google Analytics will not fix duplicate ecommerce transactions for you – you’ll have to DIY.

The problems with duplicate ecommerce transactions are obvious. For one, you’ll simply be seeing too many transactions. And this will affect your ecommerce conversion rate, your sales quantity and your revenue totals as well. Your average order value will also be higher than it is in reality. You can’t trust this kind of data, and if you can’t trust your data, you risk making bad decisions. In this post, I’ll show how to find out if you have a problem in the first place, why the problem is there and how to fix it.  Continue reading

Data Analysis

How to find Dead Pages in Google Analytics

Once in a while, I need to identify so-called dead pages on a website – that is, pages with no pageviews. Usually, this is necessary when migrating a website to a new CMS. In that case, it’s useful to know if there are pages that can be safely deleted/omitted (just remember proper redirects). A similar use case is when cleaning up a website in order to remove unnecessary content. However, since Google Analytics only track pages that are visited, it’s not possible to find dead pages in Google Analytics alone since those pages will not show up in any reports.

But it’s actually still possible to find dead pages in Google Analytics if Analytics is combined with something else. The basic approach is simply to have a complete list of pages on the website. Then compare that list to the logged pages in Google Analytics. All pages that are not found in Google Analytics are dead pages. Depending on your selected time frame of course. Continue reading


4 important skills of great web analysts

The data analysts and web analysts of today are not just required to do reporting and relay data in simple charts and tables. True web analysis is about answering business critical questions and come up with intelligent answers. It’s about delivering real value based on insights derived from data. And it has a lot to do with recommending specific actions or to qualify discussions and planning in marketing and sales. I’ve thought about the most important skills of great web analysts for some time. I’m not done thinking, but this post contains some of what I’ve come up with so far.

Compared to web analysts 10 years ago, it’s now an entirely different skill set that’s required. The days where a web analyst was just the person who could navigate the reports in Google Analytics are gone. But what makes a great web analytics today? Well, a lot of different skills do – but in my mind, these are some of the general requirements:

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Data Collection, Data Quality

Track Real Time on Page for Bounces and Exits with GTM

The Time on Page metric is probably one of the most misunderstood metrics in Google Analytics. Google Analytics measures the time on page for each page, but can only do so by measuring the elapsed time between two interactions. The first interaction is the timestamp of the initial pageview, and the second interaction is usually the timestamp for the next pageview (or an event). So for sessions with just one pageview (i.e. bounces) there’s just one timestamp. In those cases, Google Analytics is unable to measure the time on page. As such, for the time spent on a page for bouncing sessions and on exit pages there’s simply no data. (there’s no ‘last’ timestamp on exit pages either). The real time on page is therefore likely higher than what your reports are telling you.

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R with Google Analytics Edition | Reading List

So lately, I’ve been learning to use R with Google Analytics using R Studio. I’m just a couple of weeks in, but so far it has proven just amazing. By combining R with the Google Analytics Core Reporting API, it’s possible to do analysis, calculations and statistics much faster and deeper than using the Google Analytics interface or even add-ons to import Google Analytics data into Excel. Since R is script based, all analyses are automatically documented – and they’re easily reusable. Throw in the built-in plot functions (or the ggplot2 package) to build a wide range of visual representations of data, and you got an extremely powerful data analysis tool. However, what I’ve found is that – compared to Google Analytics – it’s more difficult to find good information, tips and learning material online. So I thought I’d share some of the articles I have come across. Continue reading