Episode #8

Google Analytics IV: Content Drilldown, Checkout Behavior, and Benchmarking Reports

Today we're going to focus on an advanced Analytics report that's gonna take your understanding of your website visitors to the next level: the content drilldown report. This is a godsend when you have a website whose pages can be classified into categories or templates (e.g. product pages, taxon pages) and you want to understand the relative performance characteristics of each of these categories (as opposed to individual pages within those categories). Then we look at the most important target in the entire field of conversion optimization: your checkout flow - and we will use Google Analytics to figure out which stage is leakiest and most in need of your attention. Lastly we'll visit some benchmarking reports that help you answer the question every website owner has: how do my figures compare to my competition? This can reveal insights - such as the fact that you are missing out on a major marketing channel popular in your industry.

October 18, 2020

Show Notes

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Transcribed by Rugo Obi

I know it seems like a lot, but Google Analytics really is fundamental and If you don't have some mastery over it, it's basically like driving with your lights off in the dark.

And although it can be a bit boring at first, it's very very useful and very quick to master.

I hope that by going through various reports and showing you my workflows with real data, you'll be able to repeat the same sort of process with your own website.


As a prelude to showing you the content drill down report, I'm going to show some aspects of the structure of Oxbridge Notes.

For one, it exists on multiple domains, subdomains. We're on the .co.uk here, but I can go to the Australian one and you can see this is en-au.oxbridgenotes.com, and then the Canadian one is en-ca.oxbridgenotes.com. Okay, let's go back to the UK one first.

On top of that, there is a certain structure to the website. Like if I go over here, I'm in /t/accounting for taxon accounting. And then here at /t/bcl-law.

So basically, this is a template page, and there'll be many examples of (kind of) instantiations of that template, like the economics one. And then if I go in here, I'm viewing a particular product. It's under revision_notes/ and then the product name revision_notes/product_name.

If I go back here, I can open up a different product and there are, you know, maybe 1000 to 2000 products.

And then lastly within each of these revision_notes things there are multiple samples. So I go in here and the URL for the product is there for that particular product and then the URL gets extended with .../samples, and then the name of that particular sample - and there are multiple samples.

That's all the preamble you need.


So here we're in the Content Drilldown report of Google Analytics, you can find that under Behavior > Site Content > Content Drilldown.

What this does is divide your page into multiple "levels", as they call it.

You can see here at the first level, it's the subdomain or domain. So we have oxbridgenotes.co.uk, with www in front, which just means my normal UK site.www.oxbridgenotes.com, then, that's my US site. It accounts for 5% of my traffic, whereas the UK one accounts for 86% of my traffic. Then the Australia site with 5%, the Irish version at 1.6%.

So, what this report does, or what it's strong at, is to broadly sum up where traffic is going.

And this gives me an idea about my relative traffic performance in each of the countries I operate in, in each of my sub-domains and so on.

Now, let's dive in further into the second level, Page path level 2.

And it's easiest to understand this by just looking at the data.

So we have revision_notes/ which corresponded to the particular products I showed you. Like one of these is a revision notes URL, and this captures all the possible revision notes URLs that exist within my website.

So you can see here it's listing 10 at a time here. But in fact there's 1000... 1247. So let me make that 100 and you can check that out.

Before I do that that, actually, I'm going to go back up one level. I need to go back twice because I just changed it from 100 to 10.

Yeah. And so we have /revision_notes/ and then we have the taxon/t/.

And what's useful here is to get an overall picture for what percent of people, you know, maybe land on a particular or end up on a particular page on your website, and this might indicate where to put design budget and so on.

And you also get some other figures like, how much time do they spend on those pages, how often do they exit the website after checking out one of those pages.

It looks like If people arrive on my taxon, or if people arrive on my taxon page, they're very unlikely to leave the website at that point, whereas they're much more likely to leave if they're on one of my product pages. So this is a strong page. I guess it's very transitional, you kind of check out what's on offer.

Let's go one level deeper and look at the possible products again.

So, looking at all the possible products I have under the - you can see up here - the revision_notes level, I see that /law-trusts-and-equity/, accounts for 6.45% of all my traffic.

So, given that there’s 1247 products, this one is taking a relative lion's share of the traffic.

How might you use that information?

Well, one way is if I'm creating a "related products" pop-up or whatever widget within a page, then I might take these 10 products, as the related ones, and just pop them out.

That'll be kind of a dumb way of doing it rather than dynamically but it will do a pretty good job, given that this accounts for a lot of my traffic. There's probably a high probability that any given user is interested in that stuff.

Another way to use this information would be in online advertising.

They say that in online advertising it's good to be specific. So perhaps if I were targeting the law market, I could say, 'we have great trust and equity notes, land law notes, equity and trust again (it's just a variant of the product) - and great contract law notes'.

And this could be pretty compelling advertising since the average user seems to be looking for something along those lines.

So, imagine you have a multistage checkout on your website, as many websites do. Perhaps you gather email addresses in the first step, and then you let people select their payment option in the next step and so on and so forth.

How do you figure out which step is leakiest in terms of losing you the most conversions?

That's where the Checkout Behavior Analysis report comes in, which is found under Conversions > Ecommerce > Checkout Behavior.

You can see here that, of the 1,619 sessions that added products to cart in this time period, 1,151 made it to the payment state, i.e. 70% of that amount.

And then, 916 actually ended up purchasing. They ended up having transaction data, and this figure is 56% of that figure.

You can also see visualized here the relative drop out at each step. 70% drops out here, 76% drops out here.

You can use this sort of data in order to decide which step in your checkout flow is optimal to optimize. I.e where do you get the biggest bang for your buck?

And considering that the cart step loses more people than the payment step, I would probably optimize there.

And the setup for this report, unfortunately is a little bit complicated in the sense that the Google Analytics documentation is all over the place on this particular topic.

There are basically two aspects here, one is that you go into your View Settings and you find the Ecommerce Settings and then you Add funnel steps here. That's step one, that's the easy part.

The more difficult part is the Google Analytics code you'll need.

And it seems that, depending on what type of Google Analytics code you have, for example gtag or analytics.js or gtag.js, you have slightly different event data you have to send.

For example, I see "checkout_step" : 1 here, whereas in this one I have ’actionField’ : { "step" : 1,... }.

So I would advise you to just consult the latest docs for the kind of Analytics integration you have in order to get this working on your website.


Sometimes it's difficult to know whether or not you have a blind spot in your overall marketing strategy.

Are you missing out on a certain category of traffic or over invested in a certain type or are your bounce rates abnormally high or something like that?

That's where the set of Benchmarking reports come in. They're under Audience > Benchmarking and then there’s Channel > Location >Devices .

We’re looking at the Channels report right here.

So first off, you select your industry vertical. Tere's lots to choose from. I’d say the closest for me is Teaching & Classroom Resources.

Then you select a region, and that has country and also sub regions. So if you’re a very local business, for example, like a pizza restaurant or something like that, then you can compare to within your region.

And then you select the size of your website by daily sessions. Depending on what you choose here, it will make your figures look really good.

For example, if your website is large and you choose to compare against a tiny website, everything will look great.

I'm choosing a range where I'm at the lower end of, but I think it's the most accurate range here.

Now let's have a look at some of the data.

So it's divided into the channel grouping we saw earlier.

And you can see here that I'm very very lopsided in the sense that everything is red. I'm lower than normal, except with SEO where I'm better than normal.

This might indicate to me, for example, that perhaps I should invest more in getting direct traffic or referral traffic or social traffic.

I don't have these marketing arms at all but perhaps this is the blind spot I have.

Another useful thing to look at is Behavior.

How many pages does the average session look at? I'm getting 1.79 versus the average of 4 in Organic, but in other areas I’m quite good.

Like in Social, the sessions are very effective. I'm getting 3.61 instead of 1.94.

This is a strong indicator that I should probably be investing more in social traffic.

Then we have the Avg. Session Duration. I’m doing better than average there but my Bounce Rate is worse than normal, as you can see here.

That’s all I've got for today. See you next week.