1) Are the 2nd and 3rd layers free or do they cost?
2) Do you know the official nomenclature of these layer products so that I can google how to implement them?
Thank you.
The first level they mention is out-of-the-box, no setup Google Analytics. You install the site code and you get metrics. You don't need to be a developer or have any real skills to accomplish this. It is essentially low-effort, low-return.
The 2nd and 3rd layers do not require an investment in Google, but they do require an investment in people. You'll need someone who understands the Google Analytics API, the Measurement Protocol, how the script collects and sorts data, who can install, configure and implement Google Tag Manager, and who has at least an intermediate understanding of HTML/CSS/JS.
There is no nomenclature apart from the aspects of Google Analytics I described above, but you can read more about them here: https://developers.google.com/analytics/
1.: No - but you need people understanding your business and GA as well as being able to implement additional tracking events via Google Tagmager (for example) to be able to answer questions like: What percentage of our users came via paid social media advertising, viewed a product, added it to the shopping cart, but abandoned the checkout. And how many of them are newsletter recipients so that we might be able to send them a reminder, that they have items in their shopping cart.
2.: No official nomenclature - just deeper data analyst's knowledge to ask the business people the right questions, develop an understanding of what to measure, talk to the developers to have them help provide (if necessary) additional info in a dataLayer structure and implement the necessary tracking events in the tagmanager.
After that said analyst needs to build the necessary dashboards/reports so that management/business can have the initial questions answered.
Data/Web Analytics in a nutshell (and described way reduced).
#2 - custom GA events implemented via Google Tag Manager triggers. only takes a few hours to learn.
#3 - once you identify a few particular funnels you want to dive deep into, just skip GA altogether and use an all-purpose recording tool like Hotjar that'll let you automatically record entire user journeys starting or ending at some page. go through those with your UX team/person and look for potentially confusing interactions. takes like 5 min to set up, several days to collect data, and then a good UX person to interpret likely pain points that your users are running into. it's really hard to do a good funnel analysis in Google Analytics. Hotjar, or to some degree Facebook Insights, make that analysis a lot easier because they're GUI-driven and monitor the DOM visually, not code-and-config based like GA
I feel like your questions were answered - pretty much the answer I'd give.
1) The only cost is cost of a person who has a deep understanding of Google Analytics. Google Analytics courses are hours long but they only teach you the first layer. 2nd and 3rd come with experience - I've been working with GA for about 4 years and there are still things that surprise me, caveats that we sometimes forget about. Quick example: Beginners will quite often select 2 dates (separately), get number of users from those 2 dates, add them together and say: that's the number of users we had in those 2 dates. But if you selected those 2 dates together, you'd see a lower number. Why? Because a user who visited in both periods would count as 2 if looking at separate dates, but only as 1 if looking together.
2) There isn't anything official but there's lots of blog posts - from great people like Simo Ahava and Julius Fedorovicius. If you're just starting out, I'd recommend sitting down and writing questions you want answering. Default GA implementation will not give you answers to all your questions - they had to create a product that works OK for most, so it doesn't answer specific business questions. The greatest problem with people saying Google Analytics doesn't give them the data they need is they don't start with the question. Examples of tracking I recently implemented because I taught the team to ask questions WHEN they change/implement something: -Are users printing the pages? Tracking is set up to track when they use browsers print button. -Do we have any searches on page that return no results? Do we have searches that return too many results? -How accurate are our results - which position of the result do they normally click on.
Those questions you wouldn't answer with basic setup. By setting up custom event tracking, we can answer them.
Lastly, on the most advanced setup (keep in mind you might not actually need it) - new version of Google Analytics offers free integration with Big Query. This means you get to analyse the data using SQL.
For me, a much better approach would be my own analytics, tailored to my product using simple sql statements.
For example how many of my users are tracking mainly dividends vs tracking their portfolio? To get such data I would have to invest more time into setting the right firebase analytics flags than just creating a BI Dashboard that uses one sql query under the hood.
Are there best practices to follow? I just have a table with: id, id of thing being accessed, user email, time, event enum, and notes.
It works well enough, and I have a python script to query the table and aggregate and print graph or print the results. But it would be great if there was some "bring your own data" dashboard that would let me view the time series w/ things like filters
Sounds like Grafana
I hope you get good traction!
I have an account but have not invested yet...
As the most dominant player in the market, they could do this (and to a certain extent still can). But for how long?
So, clean cut seems like a good idea.
GA3 and GA4 are so different, it isn't like the US and Russia, it is Earth and Jupiter (not in terms of impact or size, but just vastly different).
Like a toothbrush and a table. Vastly different.
it allows you to understand what drives revenue and measure the exact MRR you get from a blog post, churned users you get from an ad campaign, etc.
here is an example dashboard: https://hockeystack.com/live-demo/dashboard-preview/Content%...
But using this solution would mean loading third-party JavaScript with third-party trackers. Which for many reasons is a complete non-starter. I'm quite happy to have a site with zero third-party scripts/trackers.
So, call me when I can send the events myself from my code :-)
How well would a new cookieless search engine hosted in the EU do charging $99 a month to use when Google/Bing exist?
it's unifying the whole customer journey with no code "while" being cookieless and hosting in the EU
I respect your opinion, but please also check out how much tools like Amplitude or Heap cost
^^^ This !
If its free, then you are the product.
I'm sure all that analytics data is a veritable goldmine for Google.
I pulled Google off all our web properties three years ago (it was originally put there by the web designers) and no amount of blog hype will ever convince me to put it back.
I built a mobile compatible website (after previously believing my product was a strictly desktop/laptop only product).
I translated my site into Portuguese, since the majority of my users were from there, and many of those users were acting like they didn't understand the site (written on English).
Those two things were probably together a 20% revenue uplift. Worth having Google analytics.
The usual story is that I should care about traffic and bounce rates, because of short attention spans and potential customers getting bored or not finding what they needed — but seriously, if you are about to start using inventory control and production control software that will make your life easier and that you intend to use for years, attention span is not a problem.
The metrics I do care about are signups, churn, and everything else that is money-related. But those I can (and do) measure myself.
Note that I am not saying that analytics are totally useless, just that they aren't useful for me.
If you apply that thinking to other areas it doesn't make as much sense e.g. 'I don't care if my site takes 2 minutes to load. I don't get paid for how fast my site loads. I get paid by customers who subscribe and pay for using my software because it brings them value.'
Like sure, that's not what you are directly paid for but it doesn't necessarily mean the data can't help you increase signups.
If you think of it in ML terms - that's extra data that would likely increase a theoretical model's accuracy as it's not fully covered by your other (more important) metrics. Except in this case the model is you and it's possible the extra work isn't worth it for the benefit which could be tiny.
I use adsense for that. It counts page views which is what i need. GA seemed to me like something full of marketing buzzwords for which i really really dont care
I wrote code for traffic source attribution and used it to find out that my money spent on super-targeted LinkedIn, Facebook and Google ads resulted in precisely $0 revenue, so I stopped advertising and the code is now rusty.
I wrote code for A/B testing (this is something you really want to have integrated with your site) using the multi-armed bandit approach and used it to find out that with low traffic of a B2B SaaS it takes months to reach conclusions. That is still sometimes used, but not a whole lot, and only because the multi-armed bandit approach with Thompson sampling is nice enough to prioritize "better" options over time, so you can leave it running safely without baby-sitting it the whole time.
Overall the problem with a B2B SaaS is that unless you are already huge, the amount of good actionable data that you can work with is small. It's much better to spend the effort on making a product that people will want to use, e.g. talk to your customers.
Properly instrumented code allows this as a side-benefit.
The main benefit of properly instrumented code being that it makes debugging a breeze.
Why are people using client side (even more, 3rd party) code for this? The server knows it, you can get it from the logs.
Google Analytics or its competitors take a few minutes to set up. Recreating that whole stack to feature parity would take forever.
Those page view numbers do have a relationship to my business. But it's like measuring traffic on a highway when your store is next to it. The numbers will be somewhat related, but not actionable in any way.
I guess it makes sense if you get paid by page views (ad-supported sites?). But I have a B2B SaaS and I get paid by subscriptions. I rarely care about any of the metrics that GA shows, and I found that many of them are bogus anyway. I could probably wrestle GA into measuring what I need, but why bother, there are easier ways to handle that.
A nice side benefit is that I'm not participating in the global people-tracking business and I'm not subjecting my users/customers to that.