What’s a data product? And how do they help revolutionize product development?

Across all companies, data is the backbone of successful product development. Data enables you to gather insights about your users’ behavior, helps you better understand your customers’ needs and pain points, and ultimately equips you with the know-how to build innovative, relevant products in today’s overcrowded market. 

But data is also key to powering your products, too. From algorithm-driven recommendation systems to personalized content delivery, the data within your tools and applications is critical to helping you offer unmatched value to your end user.

In this blog, we’ll dive deep into the world of data products and draw on a recent discussion with Eric Weber, Senior Director of Data Science at StichFix.

We’ll explore: 

• What is a data product? And who is a data product owner? 

• What are the benefits of a data product in your product development process?

• The role of AI in product innovation

What is a data product? And who is a data product owner?

A data product is a fusion of data science and product development. The product uses data insights to create and deliver tangible value to end users. 

According to Eric, “a data product is where data adds key differentiator capability from which the target customer benefits.” 

To understand if a product within your organization is a data product or not, Eric suggests that you start with two critical aspects: what makes this product a differentiator, and for whom? To do this, you can start by asking the below questions:

• Is data the key differentiator in this product? 

• Who benefits from this data product, both internally and externally? 

• How does it create tangible value for your end users?

Data products can be diverse and range significantly from one another. Using examples from Stitchfix, Eric helps bring the concept of data products to life.  

“We use ChatGPT to write our product descriptions. We have tens of thousands of differentiated products, and it's simply not scalable for us to write our product descriptions, “ says Eric. “We also have a homegrown experimentation platform which enables us to do experimentation at a level of complexity that would just not be available from third-party solutions.”

“We have something called a Client Time Series Model, which drives all of our recommendations that we make within the product. We also have a lot of executive dashboards that help us understand the functioning and health of the business. These are just a few of our data products, amongst many.” 

Because the concept of data products is relatively new, many of them are currently unowned within an organization. This presents an opportunity for a new kind of role: a Data Product Manager.

A Data Product Manager solely focuses on products that are centered around data-driven capabilities and insights. Their main responsibility is to identify and develop data-driven products that add measurable value and serve as key differentiators for the target customers, whether internal or external.

The benefits of data products for your product development process 

Data products offer many benefits for organizations. Here are a few of them:

1. Enables personalization at scale: By harnessing customer data and behavioral insights, organizations can create tailored offerings, recommendations, and campaigns that resonate with different users. This might be suggesting personalized product recommendations, curating content based on user interests, or delivering targeted marketing messages.

2. Streamlines stages of your product development process: From ideation to launch, data products enable Product Managers and teams to make informed decisions based on real-time market trends, user feedback, and performance metrics. This iterative and data-driven approach accelerates the product development process and increases the chances of delivering successful products that align with customer needs.

3. Encourages iterative prototyping: By leveraging data-driven insights, data product teams can rapidly prototype and test new ideas, features, and concepts. This iterative approach allows organizations to gather real-time user feedback, identify improvement areas, and fine-tune their products for optimal performance. 

4. Drives data-backed decision-making: Data products can provide comprehensive data analytics, market trends, customer behavior patterns, and other essential metrics that inform strategic planning and resource allocation. By leveraging data in decision-making processes, organizations can minimize uncertainties and increase the likelihood of successful outcomes.

The role of AI in product innovation

Today’s companies are exploring how AI can help them innovate and develop products at a faster rate, especially around large language model tools like ChatGPT. Eric believes AI will continue to transform the way product teams think and work.

“AI creates this ability for more people in a company to act as product builders,” says Eric. “I think one of the biggest opportunities is to say, okay, what is my idea, and can I take this idea to something functional?"

With the help of AI, the line between the traditional role of specialized Engineers and Data Scientists is being blurred with general Product Managers. Now, elements like the framework, code base, front-end design, and the rough draft phase of product development are more accessible. This enables a broader range of employees to participate more actively in the ideation and prototyping stages.

AI also empowers Product Managers to make data-backed decisions more granularly than before. Rather than relying solely on high-level macro insights, Product Managers can zoom in and evaluate the smallest pieces of the customer experience. This is magnified by tools like Heap, which can provide an intelligent data science layer that helps you gain a total 360-degree view of your user behavior. 

By understanding customer behavior and engagement on a micro-level, Product Managers can identify opportunities for improvement and align product features with customer needs. Eric says, "It can be very tempting when you're building a model just to toss everything in... starting from the ground up and justifying why you're adding each aspect of data into the product becomes critical."

Looking into the future, Product Managers should assess how AI can improve the current product experience, focusing on small pieces of the customer journey to determine how AI can alter and improve these aspects. AI may also challenge traditional product definitions, which Eric says may lead to integrating AI capabilities into other product offerings or even creating entirely new product categories. 

"What does it eliminate the need for? What does it create the need for? And I think pushing on that boundary is super fascinating for me," says Eric.

Conclusion

As the landscape continues to evolve, Data Product Managers play a crucial role in identifying and developing data-driven products that add value to target customers. They create differentiation through data-driven insights and ensure products deliver measurable value to both internal and external users.

For organizations, data products help to personalize offerings at scale, streamline the product development process, encourage iterative prototyping, and drive data-backed decision-making. And with AI as a driving force, product teams will continue to break down barriers between traditional roles, allowing more people within the organization to contribute to data product ideation and prototyping.

Want to learn more about the power of data products? Go watch our on-demand webinar now!