![]() This is where data product management comes in. Of course, for these changes to be effective, the data behind them has to be credible. Product managers are expected to go through this data and make changes in their product design at every step of the development process so that the final product is aligned with customer preferences. Since the primary objective of product management is to develop products and services that are popular among customers, collecting data regarding consumer preferences and market trends is essential in designing any product customers will love. Since developing these data products requires companies to collect and sift through copious amounts of data, they require data product management systems that can handle large amounts of information.īut this doesn’t just mean that data product management only holds relevance in the development of data products. Why does data product management matter?ĭata product management is especially important in today’s world because of the increase in this type of product in the market. Since the development of such data products requires the handling of large amounts of information, traditional product management systems were replaced by product management data systems, which feature the integral role of the data product manager. It analyzes data extracted from the users’ past listening sessions, to curate a list that offers similar songs. The customized playlists created by Spotify is an example of a data product. ![]() So, what exactly is data product management, and how is the job of a data product manager any different from a traditional product manager? What is data product management?ĭata product management is a specialized form of product management that focuses on the collection, organization, retention, and transmission of data within a company to develop a new product.ĭata product management is similar to traditional product management in the sense that all the data collected and shared is utilized for the development of new products.īut while both data product management and traditional product management focus on developing a new product or launching a new service, the key difference lies in the fact that data product management specializes in the development of ‘data products’.ĭata products are products that require an extensive amount of data, analysis, and machine learning techniques throughout their development process. This is where traditional product management has evolved into data product management, with the role of the data product manager at its center. With the rapid digitalization of today’s world, it is no surprise that businesses have had to revise their product management structures.Īs systems governing our everyday lives become automated, it is easier than ever for companies to obtain valuable data regarding their target customer base, current market trends, and future business prospects.īut, with the widespread availability of data, companies require someone who can analyze that data and use those insights to maximize business productivity and profitability.
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