Why is analytics so damn expensive?

Jan 24, 2018

The nature of the modern internet, especially the consumer internet, is that we expect software to be free or inexpensive. Free email, search, video entertainment, news, social media. All of this is free. As consumers we inevitably bring this mindset into our online business dealings. Even if we build and sell software ourselves we still love a free software service. Enter Google Analytics (GA).

There’s ~1.2 billion websites acrosss the internet. Over half of them use GA to monitor the health of their website or web app. GA is the number one installed analytics tool not because it’s the best but because it’s free[1]. We love free shit.

GA properly used and maintained is powerful, there’s no denying that. But the developer instrumentation and maintenance it needs is staggering and costs a bomb. Yet a $0 price tag blinds many of us. When we see a similar tool or service that’s paid-for our brains instantly think “DAMN, why so expensive!?”

We love free shit.

Free software with a $0 price tag doesn’t mean you save money or have the best solution. It means you didn’t need to shell money out there and then. Instead, you pay with it in other, hidden ways.

The number one reason free analytics turns out to be expensive and frustrating is the sheer amount of expensive time that needs to go into setting it up to properly understand user behaviour.

$0 doesn’t mean it’s free

Analytics seems simple. Place your tracking code on every page of your website/app and from that point onwards your dashboard populates with such riveting data as page views, page-load times, users, session duration, bounce rate, user location, and device. This is surface data. If all you want is an overview of traffic, website performance, and popular content then this stock data is great.

But… what about when you want to understand user interactions and behaviour on a deeper level than page views? Well, for many analytics tools, that’s when things start getting serious.

To go deeper user behaviour needs to be broken down into single events[2]. For example, a user journey with multiple interactions needs each interaction defined as a single event. Each created event has its own tracking code that needs to be injected into your website. A simple website can have anything in the region 5-20 unique events. A web app can have substantially more.

Whenever you want to change or add events tracking code is involved. Want to track clicks on a call to action at the end of a new blog post? New event and tracking code. Added a new sign up flow? New events and more code please. This design is archaic.

Here’s the worst part. You think this is saving you money because the tool is ‘free’.

Contrast this to a tool that tracks every user interation with a single piece of tracking code. You only ever need to add one line of tracking code to you website or app. To add new events you simply record them with a visual recorder. It’d look something like this:

A video walkthrough of using Prodlytic

We’ve written a whole blog on this subject because, frankly, analytics is complicated when it shouldn’t be.

Counterintuitive: save money by spending money

It seems to go against the very fabric of the universe that you can save money by spending money. But when it comes to understanding how people use your app and making the right decisions to enhance their experience, it really does pay to have analytics that’s built for the job.

[1] Of course there is an element of brand recognition here too. It works in Google’s favour that they dominate the consumer and business web. You can also purchase a yearly contract for Google Analytics for $150,000 😬

[2] An event is an interaction with your website or app. For example, clicking a sign up button, watching a video, or downloading something.



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