CXL Mini-Degree in Growth Marketing — Week 2
By: Mary Donné
Tags: Digital Marketing, Digital Marketing Trainng, Growth Marketing, Google Analytics Tips, Growth Hacking

This is my second week taking the CXL Growth Marketing Mini-Degree. You can see my first post here if you haven’t already.

In my previous experience, marketing was traditionally a career of a choice for people who loved writing but were perhaps a little less confident with numbers. Back in the 1990s marketers on the whole weren’t expected to be particularly maths oriented. But that role doesn’t exist any more and growth marketing is totally data based. In fact, having now spent two weeks listening to CXL Founder, Peep Laja, repeating the need to ‘measure, measure, and measure’, it’s become crystal clear to me, if it wasn’t already, that the ability to work with statistics and interpret data is an essential qualification for a growth marketer.

Google Analytics and Statistics

With that in mind, this week, I have been working on the Google Analytics and Statistics modules of the mini-degree. Helpfully, my new-ish blog had not yet been Google Analytics (‘GA’) configured so I was able to walk through the exact steps to do this as set out in the GA module. Now, obviously, I have used GA plenty of times before and I always thought I was pretty competent. This is, however, the first time I have ever spent some time properly sitting back and taking a really deep dive from scratch into it. This was part of the reason that I wanted to do the mini-degree. You can put things together for yourself but there is no substitute for an expert, in this case, Chris Mercer (aka ‘Mercer’), ‘puppy walking’ you through something.

Right from the beginning of these trainings, one thing I really love is that Mercer doesn’t edit out his mistakes. There are one or two occasions when he is talking and then stops and says, ‘oh hang on! I haven’t changed the segment view — what I just said makes no sense!’ Ultimately, this just shows that we are all humans, not machines, and even the experts get a little number-blind sometimes.

The whole GA section of the mini-degree, beginner and intermediate modules, is over 16 hours long — 16! You read that correctly! So it’s very comprehensive. It’s not the easiest module as, let’s be honest, process type trainings are by their nature going to be a little dry and yes, at times, I did find my attention drifting a bit. But Mercer really knows his stuff and is a born teacher. He started by introducing both GA, and explaining how it differs from Google Tag Manager and Google Data Studio. He explained that even if you’re an old-school marketer who is a little shy with numbers, try not to just think of GA in these terms. It’s far more helpful to reframe your thinking to focus on the story behind the measurements. What behaviours is GA showing us? This was absolutely a light bulb moment for me. While I’m reasonably numerate, thinking like this has changed my approach to GA and whereas previously I might just have looked at the statistics and thought, ‘okay, that’s telling me this’, now I am more inclined to think outside the box a little and go further into and around the data to see if I’m correct.

Pic Credit: Stephen Phillips at Unsplash

What I have Learnt about Google Analytics

For me, some great takeaways from this training were:

The Goal Flow Report — I wasn’t familiar with this one. This isn’t a GA table style report that most of us are familiar with, but a way of seeing ‘loop backs’. This is where someone takes a backwards step in your funnel, so they might go the shopping cart, change their mind, and go back to a previous page. It could be quite innocent as perhaps they just want to final check something before purchase. But if it keeps happening then you might want to look more closely at the page they’re looping back from as perhaps there is something there that’s putting them off purchasing. This is something I will absolutely be using in the future.

What does GA actually mean by ‘User’? To GA, a ‘User’ means a client ID. Each browser records a different Client ID so if you visit the same page on your phone, your laptop, your work desktop, and your kid’s tablet, this will record as four different users even though it’s the same person. This is a bit of a problem for marketers as it’s currently quite hard to track individuals. Peep Laja also references the issue in the ‘Running Growth Experiments’ module as it can distort the accuracy of our data measuring.

Mercer explained that Google is aware of this and is working on ways to deal with it e.g. by tracking the log-in that we all use as a user ID rather than the device, but for the moment we just have to accept things the way they are.

Something else which is deceptively simple but really important is to remember to check what your audience is actually buying. Mercer’s example was in the GA test account, the audience was 60/40ish male to female, but once we’d segmented and looked at the purchasing demographics, this changed to 70/30ish female to male. In other words, while our marketing (and the sales products themselves) may well be attractive to men, it is women who are actually putting cash on the table.

This sort of thing is a red herring for any marketer to be mindful of. I know that personally I can have a tendency to look at a source of data which seems pretty clear and make a decision. Ultimately comes back to the aforementioned, ‘measure, measure, and measure again’. We need to keep examining and questioning the data in front of us.

Statistics Fundamentals for Testing

I quite enjoy statistics so I had been looking forward to this module. Incidentally, if you do too, I can recommend David Spiegelhalter’s excellent ‘The Art of Statistics’ which I recently read and which, as it turned out, was a great primer for the Statistics module of the mini-degree.

This section is taught by Ben Labay. Ben introduced the module by referencing his colleague, Matt Gershoff’s blog post thinking about how to measure which cup of coffee from different cafes was hotter. Obviously we can’t measure every single cup of coffee from each cafe every day of the week, so we need to sample and take averages. Any time we want to measure collections of things we need to use statistics. Ben then discussed the concept of standard deviation which I vaguely remembered from an old maths class. I also watched a couple of YouTube videos just make sure I really did understand this properly as it’s going to be important going forward.

In summary, this week has been much tougher than last and I have taken in a lot of information. I’m mindful that with practical things like GA, you do just need to keep putting into practise what you learn otherwise it’s easy to forget it all very quickly. I’m still really enjoying the mini-degree and looking forward to week 3.