Getting Started With Analytics

Your Analytics Tool Should Get You to Product-Market Fit

Your analytics tool should enable you to get all the way from your first visits to product-market fit. If it can’t, you should change tools.

Easy Metrics may lead to Vanity Metrics

There’s a wave of tools being sold that are hitting the notes of “privacy-friendly” and “easy.”

Privacy-friendly is, in isolation, a good thing, but it can also lead you astray if your users care about privacy much less than you. Unfortunately, Privacy-friendly tools make design decisions that constrain what information they can give you.

As an analytics practitioner, I’m happy to be seeing interest in good UX for analytics. However, if all a tool shows you is visits and pages and referring domains, that’s not giving you sufficient wisdom to act. Without sufficient information, all you have as a result are vanity metrics.

You deserve more

You deserve to understand usage of each of your features. Specifically, you should be able to correlate them with customers at specific points in the lifecycle, which means your tool should be able to understand when your customer first arrived. Were they on your site yesterday? A week ago? A month ago? A year ago?

You deserve to know how well your messaging is working. For example, that means your tool should display to you conversions downstream of an acquisition channel or a landing page. (The “downstream” bit, which involves persisting values throughout sessions, can be a tricky point for privacy-forward tools.)

You deserve to know how well your marketing campaigns work, paid or non-paid. Put another way, your campaign parameter(s) should work all the way from the first arrival to the first payment.

You deserve to know when app failures get in the way of people giving you money (or causing them to churn). You should be able to send error events in a custom variable and respond to individual users with apologies or discount codes. Additionally, you should be able to read these error events from a very fast API, to know if errors are spiking.

You deserve power

The new wave of small, light, privacy-forward tools is very new, and some of them will continue to add to their feature sets (while prioritizing a pleasant UX). That’s great, but I believe they are not yet ready for prime time.

I have tools that I recommend. But, regardless of which tools you choose, consider prioritizing power as a key differentiator.

You will likely need it to reach product-market fit.

Interested in analyzing your way to product-market fit?

My book, Analytics for Indies, will show you how to set up three market-leading analytics tools just like they’re used by billion dollar e-commerce and SaaS companies. And it takes less than a day to set it all up, using the easy step-by-step guide in the book.

Sign up now for four free tips to get started. I’ll also throw in a free cheat sheet that tells you which tools to use.

Getting Started With Analytics

The 6 events that will complete your analytics

It’s a frequent question, asked in a variety of ways. Here are two:

  • How do you measure user engagement?
  • What user events should I be capturing?

I’ve been making events happen in large businesses like PlayStation and Rakuten since 2012. I estimate I’ve had a hand in over 1 trillion events being sent.

Even at high scale, events boil down into about 6 types. I’ll give a quick runthrough of each and a small taste of their benefits.

Let’s dive right in:

The Page View

The page view is the most basic unit of app analytics tracking. It’s incredibly versatile.

In almost every analytics tool, this is what you get by dropping in the standard snippet of code. The ROI of dropping in that code is huge given how many benefits there are and how little effort it takes.

Let me divide up some benefits into pre- and post-conversion.

Before conversion

Prior to conversion, when you’re looking at content viewed by prospective customers, you can see a few things quickly.

  • You can see where customers are landing, and where they most commonly navigate to next. That tells you what pages are valuable.
  • Even without any additional events, you can look at the number of people who reach your checkout/signup page, and even how many people have purchase confirmations or start using your app, and get a rough conversion rate with no additional effort.

After conversion

After signup, you want to focus on what your newly onboarding customers are doing.

  • What proportion of customers proceed to do something important right away to get value out of your product?
  • How many fall out of the funnel right there instead?
  • Do any customers come back later and do that important thing?
  • Are there patterns in where users navigate? Are they missing content that’s really important to their success with your product?

Just looking back up at those sets of bullets, that’s a lot of goodness to get out of the humble Page View.

The Purchase

As the wise Amy Hoy writes, “stay close to the money.”

The Purchase event lets you do that.

But wait, I hear you say. Can’t I get this from Stripe?

In some cases, yes. When you want to examine your MRR or ARPU, I definitely recommend looking at Stripe or Baremetrics. In fact, I’ve written before about the difference between Stripe/Baremetrics and Google Analytics for revenue metrics.

But there are a ton of other ways you need to examine your revenue. In those cases, you benefit from having (at least some) transactions in your analytics tools:

  • Which campaigns lead to trials/subscriptions more often?
  • What kind of feature usage correlates with converting from trial to paid?
  • Do users who churn have something in common?
  • What errors or app failures are costing me money?

These questions all have in common the need for analytics data, such as tagging marketing campaigns individually, capturing feature usage, or capturing errors.

The Campaign

A campaign code lets you organize all your inbound traffic, so that you can categorize (and understand) all your efforts to gain traffic.

Tiny technical sidebar: in code, campaigns don’t get their own event. They are properties added to existing events, particularly Page Views and purchase events.

Suppose you have four major ongoing efforts to gain traffic:

  • An email list
  • Facebook ads
  • Reddit non-paid posting (e.g. your own posts/comments, starting a community subreddit, etc.)
  • Reddit paid ads

If you use campaign codes on all of the links from those efforts back to your app, you can then slice and dice all of them to know what’s most valuable, and when and where.

It may seem like a lot of work, but it lets you answer really valuable questions like:

  • Which efforts drive the most eyeballs and awareness?
  • Which efforts drive conversion most effectively?
  • Among my paid ads, which service is more economical?

User Interactions

In the classical analytics world, lots of people call this “clicks” – what are people clicking on and interacting with on the screen?

At PlayStation we started calling them User Interactions because most of the time, our customers don’t use mice.

More importantly, this is a totally standard event that lets you see what happens on the page. If you have a submittable form and a video trailer, you can find out which one your users interact with more often.

And by combining this event with the Purchase event I from above, you can find out if one is more valuable to conversion than the other.


Error events can be a life-saver, even if you already have infrastructure monitoring in place.

If there’s an error that faces the user, that’s a great time to send an event with it.

This lets you do three super important things:

  • When a customer is logged in, you can know who is experiencing a problem, so you can proactively reach out to them.
  • If your visitor is a prospective customer, you can find out if/when there’s something blocking them from giving you money
  • If your tool has real-time support, you can monitor this metric and be aware of increasing problems. (Shout out to fellow indie creation GAInsights for linking that monitoring to your Slack instance!)

Everything else

I admit, it’s a bit of a cop-out to have a listicle of 6 event types and have the last one be a catchall.

But importantly, every app is different. Here’s a short preview of other things you might want to capture, if your app has them:

  • Have streaming video or audio? You can capture a heartbeat event every 30-60 seconds to know how much of your content is being consumed
  • Have social networking features? You can expand the definition of User Interaction to include adding friends, following people, publishing posts, or hitting the Share button
  • Is your app all about long-form text? Do you have those cool super-long, story-driven landing pages? You can capture scroll depth to know how much of a story is being read
  • Do you have an e-commerce app? You should absolutely capture the e-commerce classics: adding something to the cart, every checkout step, payment method management. Also, store searches and promo code usage will let you into people’s heads so that you know what they want and what triggers a buying decision.

Where might your app’s magic be? Use these events to find out.

How about a step-by-step walkthrough to go 0-to-100 in half a day?

My book, Analytics for Indies, is exactly that guide.

Each one of the event types I’ve written about in this post gets its own chapter, with code samples that can go straight into your app.

Sign up now for four free tips to get started. I’ll also throw in a free cheat sheet that tells you which tools to use.

Getting Started With Analytics

The Metrics You SHOULD NOT Use

Analytics systems make a delightful amount of data available quickly. Unfortunately, that may lead you astray and burn lots of your time as the owner of a small software business.

Here are some common issues I’ve seen among communities like Indie Hackers, and while onboarding users in my work at PlayStation, and how to handle them so they give you the insight you really need.

Don’t look at Total Visitors or Total Visits. Split them into New vs Customers Instead.

Let’s start with the biggest, highest-level, most visible, most KPI-able metric that you could see: your total visitors (or total sessions, for that matter).

Consider that your business gets some customers and starts making a little money. Your number of Total Visitors is steadily climbing. In this example, is your business healthy? 

I can tell you one thing for sure: you don’t know. 

Total Visitors could be capturing your increase in customers. Or it could also be capturing an increasing number of visitors who aren’t converting, which signals that you have problems with your landing pages and that this is bad for your business.

Put another way, the metric could be giving you good news or bad news, and you don’t know which.

That problem is worsened for Total Visits, because there’s one more variable in the equation: how frequently do your paying customers visit?

The one metric you are watching really should be separated into two

  • Your website’s new visitors
  • Visits by existing customers

Having those two numbers side by side is going to be more convenient for you to quickly get back to work on your business. Here’s why:

  • Looking at the number of new visitors will tell you at a glance how your traffic acquisition efforts are working. Is the number going up? Great! At any conversion rate above zero, that will probably equate to growth for you.
  • Looking at the number of visits by existing customers will tell you a sort of combination of how many customers you have, and how sticky your app is. Is the number going up? Great, you have growth! Is it going down? You probably have a churn issue.

The above samples explain the actual goal of analytics. It isn’t to make a dazzling amount of numbers or visualizations appear. It’s to get the information you need as quickly as possible to run your business. 

Don’t look at your conversion rate as a percentage of Total Visitors. Base it on Non-Customers Instead.

If we’re segmenting our visitors overall, we want to do the same for our conversion rate.

Too many people create a quick calculated metric that looks like:

Signups / Total Visits

But this is problematic, because if you have growth you’ll accidentally create the illusion that your conversion rate is falling.

Huh? Isn’t that crazy?

Another way to express the above metric would be:

Signups / (Visits by Non-Customers + Visits by Customers)

Note that “visits by customers” is in the denominator. When you gain more customers, overall denominator for your conversion gets bigger, and your conversion rate artificially falls.

We actually want to know how well your site is turning non-customers into customers. So let’s focus on them, and restate our conversion rate as:

Signups / Visits by Non-Customers

This is a number that you can watch over time. Even when your customer base grows over time, your conversion rate can be used to look specifically at how well your introductory content is creating new customers out of new visitors.

Don’t Monitor Page Views as a KPI

In the early days of the Internet, we counted “hits” to a page or site as a sign of its popularity. We intuitively knew that more hits was better.

Back when the Internet was almost entirely static HTML content, that was fine.

Now that we have SaaS apps, it’s hard to draw meaning from Page Views going up.

Let’s play a tiny game. Any of the following scenarios could result in Page Views increasing. As you read through the list, sort each scenario into “good news” or “bad news”:

  • You’re on the front page of Hacker News
  • Users are encountering a fatal error and they’re refreshing the page repeatedly
  • You acquired 100 customers this week
  • Your ads started running
  • You rolled out a new feature that is a multi-page process

Did that get tougher as it went on? Perhaps you answered a couple with “I don’t know” or “it depends”?

That ambiguity is exactly why you shouldn’t use Page Views in isolation.

There could be a case where looking at page views of a certain subset of your content may make sense. But the lesson here is that as a rule, you should start from the broad question of “what do you want to know?”. From there, you can back your way into a metric that specifically illustrates the case in question.

Don’t monitor Bounce Rate as a KPI

Bounce Rate is another metric that hasn’t aged well.

If you’re unfamiliar, Bounce Rate is the percentage of people who leave after a single page view.

This was fine back in Web 1.0 when pages weren’t super interactive.

Google Analytics’s bounce rate documentation explains the problem. As soon as your page sends a second call to the tracking server for any reason, the visit is no longer a bounce.

As a result, for most people Bounce Rate is perpetually deflated.

For example, any of these things could quickly send a second call, if they’re instrumented:

  • Page scroll depth plugins
  • Video playback
  • A form submission or button click
  • Moving to another section of a single-page application (SPA)

In short, the technology isn’t doing what we intuitively think it should do.

(Side note: Google Analytics isn’t the only tool that has this tricky definition.)

There is one place where it’s OK to use Bounce Rate: you might consider monitoring the bounce rate strictly from your landing pages.

Bounce Rate is, by its definition, a metric that leans toward being used at the “top of the funnel” – that is, when someone is a new potential customer and doesn’t deeply know you or your product yet. (It wouldn’t make sense to look at the bounce rate from your loyal customers, right?)

So you could use Bounce Rate when looking just at the content that’s used as your landing pages. That gives you a reliable number to watch over time and try to improve.

Look at this instead

It’s my book, Analytics for Indies.

(Real subtle plug there, right? Hey – you’ve read this far – I’m optimistic this book will be of interest to you.)

Your business deserves clear and consistent metrics that are quick and easy to check, so you can get back to running your business.

Each chapter has one event of tracking that you can install to take you all the way to tracking that’s on par with billion-dollar e-commerce sites. With each chapter you’ll get one key metric to watch in your dashboards.

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!