What Many Companies Get Wrong About Product Analytics
A word of caution before you explore your product data for valuable insights.
Often, companies slip up even before they implement
a product analytics solution.
Product analytics tools diverge in how they track user actions. While some tools collect all data from every user interaction with your product (autocapture), other tools require you to be more selective about which data you want to collect before implementation. Autocapture solutions usually work best for small teams with limited resources, where only a handful of people will use the tool. Where companies get into trouble, is testing an autocapture tool outside those boundaries.
Mishandling Your Data
In about 80-85% of the product analytics projects we work on, we’ve seen clients cling to event naming schemas that are far too granular, independent of autocapture. This can waste time and create confusion. In the same way, failing to address data formatting or identity resolution can lead many companies astray.
Lack of Organizational Alignment
Ideally, every product analytics discussion should focus on the needs of your customers. And since every team in your company serves your customers, any time you talk about your product analytics strategy, you should include members from every team. Bottom line: your product analytics strategy cannot be effective unless it has buy-in from senior stakeholders.
Approaching a New Paradigm With an Outdated Mindset
Many companies see product analytics as an efficient way to collect user actions. But really, product analytics is a method for analyzing users’ behavior. Since the input for your product analytics tool is data created by users as they get value from your product, the output is context. And you can use that context as the foundation for better, data-driven decisions.