As Product Managers, we often find ourselves searching for ways to improve both our products and our processes. One of the keys to success in the product development lifecycle is adopting a data-driven mindset and incorporating it into the culture of your team. By integrating data collection and data analysis into your regular product development process, you will be setting your team and yourself up for success.
Why is Data Important?
Data is important for a myriad of reasons, but it can be boiled down into a simple statement – data makes your product better. Data is a precious commodity in the world of product development and Product Managers should treat it as so.
Whether your data is in the form of a brief comment made by a user or a complex summary of analytics findings, it can provide valuable insights on how to further improve a product. Here are three examples that demonstrate the importance of data.
By using data analytics in product development, Product Managers are able to remove subjectivity and personal biases about what works and what does not. For example, stakeholders might believe that certain product features are beneficial for users, but data analysis may prove otherwise.
Data such as usage metrics provide objective truths about which features are being used and how users are interacting with them. These types of insights should be taken into consideration when evaluating the features of a product.
One of the most evident forms of data in product development is direct feedback from users. As a Product Manager, it is vital to establish channels that allow you to collect and document user feedback because this information will add the qualitative nuances that quantitative data itself cannot.
While numbers can suggest how usage has evolved, user feedback can help tell the story of how and why those numbers changed over time. Together, user feedback coupled with quantitative data provide concrete information on how to adapt, evolve, and accelerate your products or services moving forward.
Data analytics can also be a useful tool in developing product roadmaps. In product management, a roadmap visually defines the evolution of a product over time and the development of various features or epics is planned out into the future. Data analysis serves to inform the business cases that support the timing of each of these features and can help Product Managers understand what needs to be built next and how to incorporate it into a roadmap.
What Kind of Data is Important to Product Management?
There are a variety of different data types that may be valuable to the development of a particular product, but whether that data is applicable or important will completely depend on the product itself. Be sure to consider the product’s purpose and vision, as well as the target users when determining what kind of data to collect for your product. For example, customer-facing applications may benefit more from CX related metrics, whereas back-end applications may benefit more from performance-based metrics.
Customer satisfaction, or CSAT, is a commonly used metric that can provide insights into how happy a customer is with a particular product. Product Managers can use a CSAT score to gauge how users feel about an overall product, as well as individual features of the product. CSAT is also very easy to measure and can be captured through simple surveys, external reviews/ratings, or directly in the application itself.
Usage metrics is a broad term that refers to the various ways that users interact with a product. For example, a web-based application may have a set of usage metrics that includes clicks, views, and time on pages. Furthermore, a mobile application may have usage metrics in the form of downloads, opens, and active users. The important point for Product Managers is to understand what information is important to track and then define the usage metrics that make the most sense for their product.
By making data a critical element of the product management process, Product Managers are more likely to be informed about their product’s performance and its users. It is also important to remember that product development is iterative – you may not have all the data you need right off the bat, and you might even be collecting data that isn’t necessary. That’s okay.
Just be sure to continue evaluating your data and make any changes as needed. At the end of the day, data is a valuable asset for Product Managers, and it will help pave the way to making your product better.
Adam Angelich is a manager at RevGen and serves under the firm’s Digital Enablement practice. He specializes in product management and has deep experience in technical project management as well as overseeing software development for his clients.
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