Scalable data governance

Your teams gain more when you have high quality data as they can build more immersive user experience and iterate faster with more confidence. Monetization teams can build queries that don’t have heavy workarounds and help to make cross functional decisions more informed and faster. Marketing teams will be able to improve their advertising efforts and inspire users to take action by sending personalized messages based on user traits and behaviours.

However, a lot of companies still find data mistakes more often than not. Things like an event implemented as OrdreCompleted instead of Order Completed will have you expending valuable time cleaning your data set so they are easier to use.

Achieving a state of high quality data stakeholders trust as a company is no easy feat but it is doable. Your company will need to combine alignment, validation and enforcement perfectly.

This lesson shares how you can collect data that is high quality and scalable.

Align your team around a standardized tracking plan.

Any company looking to collect high quality data must create tracking plans or implementation specs that align its business objectives with the events it tracks and its metrics.

You use your tracking plan to create a standardized method of data collection across your website and app. It can be a project management tool and a reference document which contains the following key information:

What events and properties you should track
Justification for tracking these events
Where to track the events in your app or code base

If you have these three items in your tracking plan, your product engineer can add your events in the correct places in your code base.

Validate your data before it hits production

Whenever changes are made to your code you must QA before you send them off to production, the same thing does for instrumenting events because one small error on an important event like lead captured can make your business lose a lot of money. As soon as your tracking plan is created, set and implemented, the next thing to do is ensure that dirty data never gets in there. To make sure this never happens you’ll have to create a method used to validate new tracking events before they are added to your codebase. If a new event fails to match with your tracking plan, it should be spotted and fixed before it is added to your production app.

Enforce your tracking plan.

To take collecting high quality data to the next level, you have to find a way to make sure dirty data never gets into your monetization and marketing tools. Doing this is hardly ever easy though, you can enforce management by creating a data “data governance council” that manages the whole process. Their responsibilities will include:

Developing the tracking plan
Deciding the core set of data points to be used by all teams and creating a strict event-naming framework.
Okay events that should be removed/added/updated to each channel or product.

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Choosing the right data

Next lesson:

lesson 6

The anatomy of a .track()’ call

Being able to maintain a clean and easy to use consistent naming convention is great but being able to send a ‘.track()’ call is even better as it can step up your monetization efforts enormously. It helps you create funnels and understand cohorts as you explore your data. You’ll also leave a smaller code footprint when using a tracking plan which is easier to maintain.