Data Product Manager: Everything you need to know about this job

The Data Product Manager is a profession that is increasingly in demand by companies in all sectors. Find out everything you need to know about this profession, and how to train for it. Companies are exploiting data more and more. As a result, they are gradually building their “Data Product” by investing time and money in their software stack. Faced with the importance of data, more and more companies are also choosing to modernize their team structure by entrusting the reins of the project to a Data Product Manager. The role of this professional is to identify problems in the internal use of data and to correct them by working with the Data Science teams. He prioritizes projects and determines the overall vision, to develop an organization’s internal capacity to use data effectively. This is an important role for both startups and established companies. This expert data management product manager can leverage data to help develop new products or improve existing ones. Many e-commerce companies hire a Data Product Manager to help them leverage the data they collect. Through this article, discover the missions, responsibilities, and skills required for this job.

What is a Data Product Manager?

The emergence of the Data Product Manager role dates back to the early 2000s. At that time, companies like LinkedIn, Netflix, and Uber had a problem. Their teams were working with large volumes of data, which was critical to product roadmaps, decision-making, and marketing campaigns. Yet no one was in charge of developing solutions that would enable data analysis at scale and in compliance with regulations. The job of the Data Product Manager was created to determine what data is available, who needs it, where it comes from, what its purpose is, how to simplify the use of that data, and how to ensure compliance. However, the term Data Product Manager can also refer to a product manager who has the distinction of putting data at the heart of his or her work. He designs products and functionalities based on the information provided by the data analysis.

What is a Data Product?

To fully understand the role of a Data Product Manager, it’s best to define the term Data Product. In reality, this term can refer to a wide variety of items such as a Looker dashboard, a Tableau report, an A/B testing platform, or even a multi-layered data platform. Regardless of its nature, a data product should increase the accessibility and democratization of data, accelerate ROI and insight, and save time for data science teams. The Data Product must also be reliable, and its performance must be monitorable in real-time. To adapt to the evolution of the company and its needs, it must also offer scalability. Similarly, the data product must be able to integrate easily with APIs. Other key features are ease of use, security, and compliance to avoid potential data leakage. Finally, a Data Product must follow a strict and pre-planned roadmap for release updates.

What is the role of a Data Product Manager?

A Data Product Manager is responsible for the democratization of data within the company. He must also reduce the time-to-value of data. He designs, builds and manages the cross-functional development of a data platform or a suite of specific tools for multiple users such as data scientists. While the Data Product Manager occupies a similar role to other product managers, he also has specific responsibilities. His or her mission involves data collection and interpretation, design and development of data-driven products, application of various data science techniques, management of engineering processes and data flows, or development of data pipes. The Data Product Manager’s responsibilities focus on data science and statistical analysis. His or her work ensures long-term product performance and enables organizations to evolve in response to changing market conditions.

1. Create new products

The Data Product Manager creates new products. He assembles data and uses it to design successful new products for the current market. For example, Data Product Managers often collect market or consumer behavior data. They also collect survey responses and other data from a wide variety of sources. Once collected, the data is used to come up with new product ideas. After passing various tests, the product ideas go into production. In this way, the Data Product Manager directly influences companies’ decisions on what new products to offer their customers. However, it is important to note that the Data Product Manager does not create the product. He is in charge of the general design of the product, while the coders, manufacturers, and developers create the software.

2. Enhance existing products

In addition, the Data Product Manager improves the existing products in the company’s catalog. To do this, he collects survey responses on existing products to better understand how customers perceive them. This information is then used to improve existing products. Data analysis is used to change the way a product is perceived by the public, to change the marketing around that product, or to change the product’s key features and functionality. In this way, the Data Product Manager enables the company to maximize the profitability of existing products. This helps to increase sales, improve brand image, and increase customer satisfaction.

3. Establish the data infrastructure

In some cases, the Data Product Manager is responsible for establishing the company’s data infrastructure. He or she determines how data is collected, where it is stored, how it is analyzed, and who is authorized to access it. All of these tasks are very mandatory. They help preserve an organization’s data and reduce the risk of it being compromised. This data is used for product development and consumer insight. The Data Product Manager must make strategic decisions when designing data pipes. Moving up the hierarchy, the Data Product Manager is also responsible for training subordinates to maintain the data infrastructure. This ensures the long-term maintenance of the infrastructure.

4. Collect and analyze data for product creation

Collecting and analyzing data is an important part of the Data Product Manager’s job, even after the product is launched. This includes collecting data on product usage, functionality, customer feedback and opinions, and bounce rates. The data is collected through pipelines or data infrastructures. It is then analyzed with different quantitative or qualitative methods. The Data Product Manager interprets the data with the help of statistical tools. The results of the analysis are then used to ensure that the products provide added value to the target audience. This prevents companies from making strategic mistakes while assisting with iterative product design and development.

5. Report on the Data Lifecycle

The Data Management lifecycle is critical for companies that use data frequently. The Data Product Manager is responsible for collecting, storing, organizing, and reporting on how the data is used. He analyzes and monitors large Big Data sets, writes reports or queries, and communicates his findings to company executives. These reports enable executives to make wise decisions about data storage and exploitation. To communicate effectively, the Data Product Manager simplifies the information as much as possible. For this reason, a talent for communication is essential to simplify the most technical concepts for non-technical users.

6. Identify customer needs

The mission of the Data Product Manager is also to understand the audience targeted by his company and consumers in general. He must discern needs and understand what the data he collects reveals about customer intentions and preferences. This is an essential task to enable a company to create products that appeal to its target audience. The Data Product Manager, therefore, does not only manipulate numbers and statistical data but also focuses on the human aspect inherent to any business. This role is therefore essential for any company looking to identify a new audience, improve its existing customer base and brand image, or maximize loyalty and generate long-term relationships.

What are the skills of the Data Product Manager?

The job of Data Product Manager does not require writing code, but it does require technical training. This is because the role requires understanding complex systems and working with highly skilled technicians. The Data Product Manager has skills in data analysis, statistical analysis, and SEO (search engine optimization). They also understand the principles of data management. Communication is also an important skill, to interact with users and customers. This expert must also have leadership skills, to supervise the teams. In general, Data Product Managers have experience in back-end engineering, traditional B2B product management, internal product management, or as Data analysts. Some Data Product Managers work directly with Data Analysts and Data Scientists, while others work with operations teams and software engineers. In a large company, they may even work with executives. Regardless of how reporting is structured, the Data Product Manager makes it easy for all consumers to understand and access the information derived from the data.

Salaries and job opportunities

On average, according to Glassdoor, a Data Product Manager earns more than $110,000 per year in the United States. The salary range is from $71,000 to $175,000 per year. In France, according to Talent.fr, the average annual salary reaches 60,000€. Of course, this salary varies depending on experience, education, geographic location, and skill level. In general, the Product Manager profession is booming. This profession is ranked third in Glassdoor’s top 50 jobs. The role of the Data Product Manager is also benefiting from this boom. According to Zippia, the number of job openings in the U.S. is expected to grow by 8% through 2028 to over 21,800 positions. This makes it an excellent career choice.

Data Product Manager vs Product Manager: what is the difference?

Working with data requires specific skills compared to the traditional product manager job. Rather than working with traditional consumers, this professional works with consumers of data. They are employees, using products that make sense of the company’s data. This data can come from internal or external sources but is exploited internally. In other words, the Data Product Manager is a product manager entirely dedicated to building internal tools or products that exclusively serve internal data consumers.

Data Product Manager vs Data Scientist

The main difference between a Data Product Manager and a Data Scientist is that the latter seeks to extract information from an existing product or data solution. On the other hand, the Data Product Manager aims to help engineers, managers, and business executives to take advantage of data. They look for new alternative uses of data, how to combine it with other datasets, how to ensure its reliability, or which Machine Learning models will be the most appropriate.

The future of the Data Product Manager

At a time when data science teams are becoming increasingly decentralized, new roles are emerging, such as the data governance manager or the analytical engineer. At the same time, the distance between data producers and data users is growing. The demand for data is growing exponentially, as various departments in companies are increasingly dependent on data. The future of the Data Product Manager job will resemble that of a traditional product manager. He will act as a bridge between silos, encouraging teams to collaborate seamlessly. This professional will act as the connection point between data team members, data consumers, and product designers. His/her mission will be to identify user needs, oversee developments, define the vision, prioritize projects and coordinate the various stakeholders. As a result, organizations will stop reacting to data issues and take a proactive stance by developing internal data capabilities to gain a competitive advantage. Data Product Managers will examine the qualities of a good data product, and define their metrics. User satisfaction will be assessed, downtime measured, and relaxation processes documented. The future looks bright for this profession.

How to become a Data Product Manager?

To become a Data Product Manager, it is essential to acquire technical skills. To achieve this, you can choose Liora. All our training courses are distance learning and adopt an innovative Blended Learning approach, combining online learning on a coached platform and Masterclass. Depending on your preferences and availability, you can choose between a Continuing Education and an intensive BootCamp. Our programs are designed to meet the needs of companies and are taught by real Data Science professionals. Among our alumni, 80% have found a job immediately after the training. You know everything about the role of a Data Product Manager. For more information, discover our dossier on the Data Analyst and dossier on the Data Scientist job.