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Alberto IncisaProduct and Growth at June

04 Apr 22

What Is a Data Product Manager & What Is Their Role?

Product data management is a vital aspect of the modern software development pipeline, and the role of a data product manager handles the collection and handling of data in a product.

In the past, a data product manager existed mainly to facilitate the efficient movement of data around an organization. A secondary role was to consider the data security aspects of handling customers’ personal information.

However, now, in the era of Big Data, the smart use of data analytics in marketing and software development can open exciting new opportunities for business growth. The tech industry is increasingly geared towards the collection and processing of data, with the volume of data/information created expected to exceed 181 zettabytes by 2025.

That’s why the role of a data product manager is more important than ever. What is a Data Product Manager? What is their role? How does the role of a DPM fit into the rest of a product development team?

The best friend of a data product manager is a good product analytics platform. June.so gives the discerning DPM an overview of user engagement, retention, and feature adoption – allowing software teams to develop products that people love to use! In this article, we’ll explore what a data product manager is, and list all the responsibilities of this increasingly vital role in SaaS product development.

What is Product Data Management?

Before exploring the lucrative role of a data product manager, let’s first introduce you to the world of product data management.

Product data management – or PDM – is the continued use of software to manage and collect product data that can be used to grow or improve an existing product or to help create a great software product that users love.

By using product data, we can develop products that are more functional, meet the needs of our users more closely and grow faster than ever.

It is broadly defined by the use of data to inform product design, enhance user experiences and improve the profitability of SaaS products. This discipline ties neatly into the introduction and continued growth of Big Data.

Introducing: Big Data

Ask anyone in the tech industry what is Big Data and you’ll get a myriad of different answers. Some say it’s the future of software development, others say it’s a marketing buzzword for eager startups.

What do we say? We define Big Data as the belief that complex banks of information can allow us to build anything and improve every aspect of our lives. More specifically, big data refers to the use of predictive analytics and user behavior analytics to better understand the way our users interact with software products, adding value to products along the way.

The art of the craft is understanding which sources of data are relevant and which information is just noise. It’s the role of product data management to spot business trends and apply that to accelerate business growth.

Big Data is concerned with the “three V’s” – as defined by Gartner’s Doug Laney in 2001:

  • Volume: Collecting data from a variety of sources, and lots of it!
  • Velocity: Data needs to be processed as fast as possible. Old data is worthless.
  • Variety: There are many types of data available. Each type offers new clues, opportunities, and paths for growing your SaaS product.

Two further V’s have emerged over the years:

  • Value: How much value can be extracted out of data? How can the use of data and data analysis methods add value to your SaaS business?
  • Veracity: Put simply, is this data true? How can it be verified? How much can you rely on it? What are the implications of this data turning out to be false or skewed?

Why is all of this relevant? A data product manager should keep all of the above concepts in mind when conducting their work. Failing to do so leaves value on the table – or worse – leads to ill-informed use of data, information, and statistics.

What is a Data Product Manager?

Given the untapped value of collecting and using data, SaaS companies quickly learned that they needed a product manager for data – hence the role of a data product manager was formed. What is a Data Product Manager?

A Data Product Manager – or a data PM – is the person responsible for overseeing how data is used within a company. These people are the go-to management personnel for all things data. They are expected to know how the company is tracking data, where it comes from, and how it is being used.

It can seem quite strange to call a data PM a product manager. It’s simple in practice: it encourages data to be seen as a product within a firm – and with the value it can bring, it deserves the same resources and oversight as any other SaaS product developed by your company.

On a wider scale, a data product manager is encouraged to ‘sell’ data science to everyone involved in an organization. Some call this responsibility “evangelism”. Data PMs will routinely liaise with upper-level management, stakeholders, clients, the press, and customers on how data is transforming the organization and improving the products and the user experience people love.

What background should a Data Product Manager have?

A data product manager is predominately a data science role. As they are the expert on how data should be handled, collected and processed, a good data PM will need to have a qualification in data science or statistics.

At the very least, they need qualifications in Mathematics and industry experience working with and creating value from data. They should be proficient in research, AI and Machine Learning, analytics, and product management.

Why are Data Product Managers needed?

Companies around the world are opening their eyes to the fruits of data analytics. An executive survey from New Vantage Partners found that a whopping 99% of firms are reporting at least some investment in data in AI.

However, not enough data products are creating enough returns – with only 29.2% reporting that they achieved the “transformational business outcomes” the Big Data paradigm promised. In 2022, it is extremely difficult for tech firms to become “data-driven”.

What’s missing? It can be argued that the top-down product development model helps fill the gaps in our modern data pipeline, ensuring all aspects of SaaS development use data to extract value.

  • Data Product Managers better consider how data can help reach business outcomes and improve its impact on business growth as a whole. There is too often a lack of clarity data products are meant to achieve for a company, and how it should be properly used. Data PMs are responsible for developing a roadmap of how all products within a SaaS firm can benefit from data, and will know exactly how to execute this.
  • A data PM will follow any source of information throughout its lifecycle. They are responsible for monitoring how it is collected, stored and where data products need to go to be used most effectively. Without a dedicated data science specialist, the effectiveness of data can be lost and bad practices of handling data could be rampant.
  • Data Product Managers must set a high standard of data literacy throughout the SaaS firm. This means training other product managers, executive management and clients on how to read, communicate and use data effectively.

Data PMs can be seen as those responsible for organizing data and its usage.

Does the marketing team need to run some reports on product data for its next campaign? They’ll ask the data product manager.

Perhaps a product manager is developing a new product strategy and needs some persona research to better identify a target audience. A data PM will be able to assist.

Thereby, a data PM encourages the use of data science as a product within an organization.

How does a Data Product Manager compare to a traditional Product Manager?

It’s easier here to start with the similarities. The strengths of product management is the relentless focus on business objectives, outcomes and instilling the requirement to consider the users’ needs. Where a traditional product manager is conducting the development of a SaaS product and ensuring it meets the above criteria, a data product manager does the same but for the use of data.

For a data PM, data analytics is the product. They are responsible for ensuring that data science is being used to meet business outcomes and that it is being used safely (adhering to data protection legislation).

By developing data products that other aspects of the organization can use, a data PM can help influence the way data science is used in every SaaS product your company develops.

For example, a data product manager may create a database of real-time user metrics for easy analysis. They will then help other product managers use the reports and findings from this data product to improve the UX and usability of other products.

How does a Data Product Manager use Big Data?

Returning to the principles of Big Data, let’s see how a data product manager can help an organization adhere to its principles to become “data-driven”.

  • Volume: A data PM is adept at handling large, complex data sources and will be able to facilitate the processing of large data sets with ease.
  • Velocity: Data PMs love fast data sources like from product analytics platforms like June, and so they facilitate near real-time access to data products for use across an organization.
  • Variety: Knowing what data is out there, in what format, and how to access it is key to becoming a truly data-driven company. Data product managers enable SaaS firms to take advantage of data-rich solutions like user analytics, GPS, IoT data, and more.
  • Value: Data PMs are laser-focused on business objectives and outcomes. They know exactly how data can be used to add value to an organization, and will be able to adeptly communicate its benefits to management and stakeholders.
  • Veracity: As a data science expert, data PMs will be able to tell when a data source is untrustworthy. They’ll be able to spot irregular patterns that are tell-tale signs that something may be wrong with a data set. They will be able to reduce the risk of bad or old data.

By encouraging the continued use of data within an organization, a data product manager helps everyone – from management, other product managers, stakeholders and more – to make better decisions and to use data-driven methods to improve their products.

June.so: Smart product analytics for a smart data product manager

The most important tool a data PM can have in their arsenal is a good product analytics platform. This gives them real-time access to a wide array of data on user engagement, user retention, feature adoption, and more.

Without an analytics tool, the collection of user data can be tedious – taking much of a data PM’s time, energy, and budget. June.so can automate this process, allowing SaaS businesses to use analytics to extract as much value as possible out of data and create products they know users will love.

You can automate retention tracking by connecting your segment account to June. Acquired by Twilio, Segment is a platform for collating your customer usage data into one easy-to-access place. With Segment, you can automatically collect user metrics from hundreds of software tools like Google Analytics and Stripe. With June, you can easily generate attractive and functional engagement and retention graphs and reports.

Get started today at June.so and access beautiful product analytics for B2B SaaS companies. It’s now time to unlock the power of data-driven development.

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