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Stop putting your data tracking on the back burner!

Updated: Mar 16



We’ve all been there before - You’re already two sprints behind, you’ve promised your customers revolutionary features that are “just around the corner”, and your CEO wants to make back the money sunk into development as soon as possible. The launch is imminent, and your team’s not ready to board the rocket yet. Not ideal! 😬


So you think to yourself:


Where’s the dead weight? What can I push until after production?
Oh wait …💡 Let’s push back the data tracking. We’ll ship now, get some basic GA data for a while and catch up on the setup in a few weeks time. No one will notice!”

But are you really better off by doing this? We’ve spoken to dozens on PMs, and *spoilers* - you’re really, really not. Here’s why:


Loss of data 📉


To get the obvious out of the way: if you’re not tracking data, you’re not gonna have data!


Put differently, the longer you postpone your tracking, the more time you spend making decisions blindly. But what we’ve seen happen is that even after companies think they finished their tracking weeks later, they often find that their data is incomplete. In the middle of bug fixes and other post-launch priorities, their developer might’ve forgotten or misunderstood requirements, or the PM might’ve lost sight of small but crucial detail. Once they finally tracked all they wanted to track initially (definitely, 100%, for sure), they may discover that the data they’re interpreting does not fully make sense, and requires more granular tracking to fully understand.


Simply put, what is supposed to be a quick detour in your data tracking journey can throw you off course completely, leading to weeks or months of unreliable data and unsound decision making.


Poor documentation 🗋📓


Hey, can we quickly add some properties for this button I totally forgot about?

When your developer receives a Friday afternoon text like this, it’s no wonder that some of your post-hoc changes may not be neatly reflected in your tightly laid-out tracking plan. A lack of documentation can then lead to problems of their own: you may have limited awareness of the workload and deadlines your developer needs to follow, new team members coming in may not know what's been done or what hasn't, and tensions may arise between technical and non-technical employees. We've seen the results of this all too often: no tracking conventions, double tracking and no comprehensive quality assurance.


Lack of accountability 🤔


Let’s be honest - data tracking isn’t always sexy, and your developers are always going to prioritize shipping features over tracking setup. If that is true in the design stage, it is even more true after shipping, when real customers are encountering real problems with your products - problems your developer needs to fix.


By consistently pushing your data tracking post-launch, you are allowing it to slip further and further down the list of priorities. In an era of Big Data and data-driven companies, the last thing we want to signal is "data tracking is not that important to us”. It’s a bad habit rooted in convenience, and the constraints of your business won’t magically go away - It’s time to push your thumb deep on that swollen wound!


So what can YOU do?


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1. Write. It. Down. ✍️


Good tracking plans can make or break your tracking strategy. There are plenty of resources on creating one (e.g. here and here), and we're working on an article diving in in greater detail ourselves. In general, you can consider these 4 Cs:


Clear: Make sure your developer always knows exactly what elements you want to track, where they're located and how to identify them, so there's no confusion.


Comprehensive: Go through the entire customer journey and make sure you are tracking data at every important touchpoint. Anything you forget to include here can delay your understanding for weeks until you discover and fix the problem.


Conventions: Setting and following conventions ensure that you don't track the same interaction twice under slightly different names, and that your developer never has to come back and ask for information such as missing or poorly placed tags or labels. You may also consider a data library where you index your events or a best practice document.


Consistency: A perfect tracking plan without proper follow-through is worthless. Make sure you take the time to go back and note down any changes or status updates that might affect your tracking plan. Set 20 minutes aside every couple of weeks to double-check that nothing has changed without documentation.



2. No tracking = No Shipping 🙅‍♂️


Make it a habit to never ship without tracking. We've seen it become a slippery slope, where companies promise themselves to correct at the next release, only to fall back into old habits. People love good data but hate the setup, so without discipline, it's unavoidable.


And it’s such a shame too - using data to optimize your product can have a tremendous bang for the buck, yet companies choose to consistently bench the star player in their toolset based on convenience. It might be a pain at first, but you don’t have to do it all at once. Make data tracking a consistent priority, you will see your releases become much tidier with practice, and your long term prospects grow!


3. Make It a Team Activity 🙏


Like it or not, data tracking has a diverse array of stakeholders that either rely on the data or need to provide their expertise for successful implementation. Most commonly, the process involves the leadership team, product managers, business or data analysts and developers. Companies must therefore strike the balance between no one being truly accountable for data tracking, on one hand, and having too many cooks in the kitchen, on the other.


Thus, it’s important for product managers to ask the right questions, but have a clear understanding of what is feasible from the developer’s point of view. The developer, in term, needs to gain an intimate understanding of the customer journey and the uses of the data collected, something a simple excel sheet often won’t provide. Likewise, data analysts should strive to understand the needs of product managers and marketers and help them become self-sufficient, so that neither party becomes a burden to each other.


This all means that your team must adopt a collaborative culture and put in place processes for all hand offs to be successful. Having clear steps and dedicated channels (e.g. Slack, Jira, Notion) is a good step forward, but better still is to strive to have one source of truth that is accessible to all team members. A great such place is Figma, which provides a clear understanding of how your website should flow from the consumer POV, and makes collaboration tools widely available for your team.


Last but not least, make it easy! 😎


We know it's easier said than done, so try to make things easier for yourself! We know just how messy data tracking can be, so we built a tool that allows you to define your tracking, send it to Jira and monitor implementation, all without ever leaving Figma! You get to do the entire set-up and catch any mistakes, all before pushing to production.

Pro Tip: We’re giving away a bunch of pre-release perks, so check it out asap below!
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