What Is a Data Product Manager?
A data product manager (PM) focuses on product data management, which is the process of collecting, organizing, storing, and sharing data within an organization.
Data product managers are responsible for finding ways to leverage data flow throughout an entire product lifecycle (not just the design stage), and they use that data to build and perfect a feature or product.
According to the educational organization Udacity, “the primary function of a data product manager is to balance the strategy, governance, and implementation of anything data-related, and facilitate the conversations between all impacted stakeholders—executives, engineers, analysts, other product teams, and external customers—who consume the data.”
Recognized as the data authority within an organization, a data PM chooses and maintains a product’s product data management software and has a broad understanding of machine learning algorithms, AI, and all things technical.
How Does a Data Product Manager Differ from a Traditional PM?
Data, of course, is important to any product manager because it informs essential product activities like setting OKRs and KPIs and creating the product roadmap. However, being data-driven doesn’t officially make a PM a data PM.
Ellen Merryweather of the Product School blog writes: “Data is an integral part of Product Management, as it is with all aspects of product. You may have seen the job title ‘Data Product Manager’ and thought ‘well, aren’t all Product Managers…Data Product Managers?’ It’s a common misconception, but being a data-driven Product Manager doesn’t necessarily make you a Data Product Manager.”
For a data PM, data-driven insights play a central role in all decisions and efforts in building a new product or feature. This deep dive into data is the key differentiator between a data PM and a traditional PM.
To a data PM, data is the product.
How Does a Data Product Manager Use Data?
Data product managers use data to define goals for data that align with the broader organizational vision. They also use data to:
- Define key metrics to track success or prioritize features
- Translate requirements of large data initiatives into smaller actionable items
- Champion data literacy within the organization and drive adoption rates
- Conduct market assessments, user interviews, and testing
- Map out data personas and consumer profiles
- Perform A/B testing
- Set OKRs and KPIs
- Make objective arguments to influence stakeholders
- Track usage to identify opportunities for improvement
This video shows you how to create a data-driven roadmap.
Why Does a Product Team Need a Data Product Manager?
Successful products are driven by data. Adding a data PM to a product team can reduce the burden of data management across individual contributors. This can lead to breaking down silos between teams by centralizing data sets and insights. Additionally, operationalizing data becomes far more consistent, accessible, and less prone to errors.
More than that, however, data PMs unlock possibilities and opportunities for long-term success. Trey Causey, senior manager of Data Science at Indeed, writes:
“Data is at the core of product development; not only in the post-hoc analysis of usage metrics and A/B tests. The continual intake and exhaust of data is determining how products behave and what new classes of products are possible. Machine learning models automatically adapt products to users’ preferences, make recommendations about next actions, and suggest future features and products. Data product managers understand this and incorporate it into their products.”
Appointing a designated data expert at the helm of product data management helps organizations build and perfect features or products.
Related terms: Objectives and Key Results (OKRs), Key Performance Indicator (KPI), Prioritization, Retention, Impact Mapping, A/B Test, Beta Test, Roadmap.