We see this happening in the software industry. Startups outcompete legacy players by building the things people want and need, not necessarily because they know what to build from the start but by quickly iterating through the process of building, shipping, measuring and tweaking. Just imagine someone delivering seven times more things in a day than you do over a week. I mean, how would you even compete with someone like this?
This is a big thing happening as we speak, and we see velocity is everything. It all boils down to how fast we are at understanding what customers need and want in our products. We see Netflix who are all about hyper personalization and we see Amazon talking about customer obsession and user centricity. Any tech company out there will face this challenge, and we want to turn this into our competitive advantage as well.
Leveraging behavioral data – how it is done
To accomplish this there are three things the best companies do. They collect user behavior data, they define relevant metrics for their field, and they apply quantitative research. These are the key things companies accomplish when leveraging behavioral data.
To do this, and as we know it, understanding users’ behavior quickly becomes complex. Our response to this is product insights, where we want to provide guidance, tooling and competence to successfully leverage user behavior data.
First things first, user behavior has to be tracked. This requires some type of tracking tool that amasses all data we want to analyze.
Secondly, to turn the amassed data into valuable insights, we require metric frameworks. What constitutes an active user, and what is your task success or retention metric?
Thirdly, nothing works without communicating and operationalizing your insights. Visualizing insights and your relevant metrics is therefore key to making an impact into companies’ ways of working.
Lastly, we want to of course scale our experimentation efforts, which is what this is all about. Applying scientific methods and using the defined metrics to evaluate which of these experiments were truly a success.
These four areas are all necessary and also dependent on each other, which means that for each one to function, it must be complemented by the three others.
The state of product insights
We firmly believe that empowering our teams with product insights will help ensure us to build the best products on the planet. Our mission is to provide world-class product insights capabilities and support for all Visma teams, customers, and stakeholders to utilise user behaviour. 30 Visma products to date are putting their trust in this framework, and we can already see disruptive changes in people’s ways of working.
Each team can just invest a few hours to a few days, and receive high quality datasets, reports, and metric frameworks to understand what users are doing in their products. The most value comes when your teams analyse the data themselves, with their domain knowledge, and with your users and customers in mind. The Product Insights platform lays the foundation for that. Want to know more? Reach out directly to Brian Ye (email@example.com), Product Insights Lead at Visma who can go into more detail into what this is.