In my work at PlayStation, I frequently get asked why the same metric isn’t identical between two tools.
There are always precise technical reasons why they aren’t – for example, revenue may not be the same in two systems because each one calculates exchange rates slightly differently.
That’s not what this article is about.
More importantly, I don’t mind these differences and you shouldn’t either.
Instead, use multiple tools and leverage each one for what it’s best for.
For the purposes of this post, I’ll use a simple example. Let’s suppose I have an indie software business, and I currently have Google Analytics and Baremetrics hooked up.
Why you should care: seeing money from all angles
If I want to get a complete picture of my revenue, I should be using at least two tools. Maybe even more.
But getting back to our example…
Baremetrics shows me really big-picture metrics, like MRR (monthly recurring revenue).
My overall MRR metric is super important. It’s a single metric that shows the size and health of my business. You gain a lot of knowledge from the single number. It’s fitting that MRR is the headline number attached to any business on communities like Indie Hackers.
Google Analytics would struggle to show me MRR, because GA only gets data that’s sent from a user browsing my app. So if a subscription quietly renews and my user isn’t around to send me a “subscription renewed” event, GA can’t “see” that happen.
Kind of like a tree falling in the woods: GA can’t “hear” it, so it didn’t happen.
It’s possible to get GA to show this information, but it doesn’t make logical sense to put the time or effort in to do it when you already have a tool that can reflect the “primary source” data. (That would be all of the subscriptions and their individual charges, all sitting conveniently at Stripe, and fed in to Baremetrics.)
Google Analytics shows me unique things too, though.
Likewise, there are things that GA does see that Baremetrics doesn’t, because GA is measuring what your visitor is doing in their browser.
To turn the comparison around, Baremetrics could show me the conversion rate of each marketing channel. (For example, comparing the value of ads on each of Twitter, Instagram and Reddit.) But it would be a ton of extra work compared to GA. GA has that data on hand thanks to referring information, and a couple more bits of information that are easy to set in code to send.
So, it’s pretty easy to argue that I need both as an indie software business owner.
This GA-vs-Baremetrics distinction can be generalized to a wide variety of the metrics you may want to see in your day to day operation.
When to use Google Analytics
Google Analytics is best suited to understanding users in aggregate, relating to their activity on your site or in your app. Use GA to answer questions like:
- How many visitors does my site have?
- What is the proportionality of visitors from the places where I’ve done marketing?
- How many signups (or how much revenue) comes from each of my marketing channels? Are visits from one channel more valuable than others?
- What patterns of navigating my site are the most common? From which pages do users leave more frequently?
- From where in a funnel are users most likely to leave?
- What is the device distribution of my visitors?
There’s a lot more that GA can answer, but I have to stop that bullet list somewhere.
When to use Baremetrics (or Stripe Dashboard)
Baremetrics (or, for a starter utility that’s free, the Stripe Dashboard) is well-suited for questions that look at your business’s money flows from a very high level (almost like a 21st-century version of business accounting):
- What’s my MRR right now, and what was it last month?
- How much is one user worth? (What’s my ARPU?)
- What’s my churn right now, and what was it last month?
There are more tools and more use cases
In my upcoming e-book, Analytics for Indies, you’ll see more use cases. For example, still other tools aside from these two might let you:
- See an individual user’s stream of events (useful for detecting technical problems, UX problems, or fraud)
- Attach geography to the stream of events (useful for detecting account sharing)
- Create a collection of users meeting a certain condition
- Compare collections of users, or message one cohort with highly targeted information (such as pointing out an as-yet-unused feature during an onboarding period)
If you’re an independent software owner who wants to have well-rounded analytics and quickly, you’ll want the e-book.
The goal for this book is to take you from “not sure what to do” to “done” in a couple hours, with future-friendly analytics data capture all set up.
Sign up now to be notified when the book releases, and get a free email course with four quick wins and a freebie cheat sheet that tells you what tools to use. The only way to get the cheat sheet is to sign up!