We all have a sense that data is valuable and that we should be doing something about it. But what or when? It's a common challenge and a hard question to answer.
This is because the value of data is relative. It depends not only on the technical capabilities to deal with data, but also on the ability to enable business use cases relevant to the stage your company is in. The same data can provide different value as your needs evolve.
This process of discovering and enabling the value of data is what we call the Data Value Journey. Thanks to our collective experiences, we have had the luck of working with some of the most exciting and successful companies in the digital space including Rovio, King, Glassdoor and EA. Each of them has followed their own path to achieve their vision, but we have identified some common patterns and stages that we’d like to share with you.
In the following series of posts, we will be describing in more detail each of these stages and a number of best practices associated with them. Let me give you a quick overview of the topics you will learn about.
A successful journey begins by defining what is your vision for data. This vision will ultimately define how you will transform it into a competitive advantage. It defines the unique value that data will bring to your business.
You are focused on getting your product out the door, and all you really need are some industry standard metrics that are easy to enable such as CPI, CPM, CPC, DAU, MAU, WAU, ARPU, ARPPU, Sessions, Session Time, Retention D1, D7, and many more.
You start wondering what is the underlying driver behind the metrics you are looking at. Why is retention low? Where are users dropping out? What are the most successful features? How to look at users based on behavior? Who are your most valuable users? You’ll need custom events and more importantly custom dimensions to analyze your data and find answers.
Having marketing data in one side, event tracking in another and running custom queries over your application database worked fine for a while. But it’s hard to get the full picture. The data may not be compatible between sources and the overhead of consolidating data manually pushes you to consider dedicating engineering time to bring things together.
With all the data as you want it in front you, and having created enough presentations with fancy charts, you wonder how to take action and use this data to engage with users automatically. How do you deliver a customized user experience? What channels are relevant for engagement? How do you run A/B tests and measure their impact?
You got tired of creating segments and rules that are at most an educated guess. Applying predictive analytics to the user experience can be one of the most effective and powerful tools to maximize the value of your consumers.
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Alex Arias is the CEO and Co-Founder of Omniata, a unified data analytics and user engagement platform. For more than 10 years, Alex has been an entrepreneur and driver of innovation in digital services. It has been 2 years now since he embarked on his own Data Value Journey by co-founding Omniata.