How the Best Product Managers Market their Best-selling Products
This guide is written to empower data product managers who are intent on optimizing adoption and commercial outcomes, not just delivery. It will be most productive for teams that already have data assets in place and are looking to implement a scalable, revenue-generating approach to data productization.
The best product managers do not simply “publish” data. They market it using a deliberate, customer-centric process focused on discovery, adoption, and long-term value realization. The best product managers treat a data product as not just a singular spreadsheet, or static dataset, but rather as one or more data assets that deliver a value proposition to a defined target market.
The following playbook outlines how product managers can most effectively execute a marketing strategy that drives faster time-to-value for consumers, and by extension, commercial success for their business.
Anticipate Consumer Needs
Raw data Assets such as tables, notebooks, or files form the foundation of data products. Value is created by assembling these assets into products that are designed to solve specific problems. A single Asset can be reused across multiple data products, each serving a different audience or use case. For example, the same underlying dataset might be repackaged as:
A Python-based dataset for data scientists, consumed in a collaborative notebook environment
A curated BI dashboard for marketing executives, placed in a no-code, visualization tool
Effective data product management involves identifying which combinations of value proposition and target market are worth pursuing, and then tailoring the product’s packaging, positioning and permissions accordingly.
Packaging refers to how a data product is described, branded, and positioned on the Marketplace. It is not merely a documentation task, or a box to tick prior to publishing. It is the primary marketing mechanism whereby if leveraged fully, will compellingly articulate the specific problem the data solves and the outcome it enables.
Typically speaking, the less experienced, lower performing product managers tend to market their products based on what they contain. For example, “Toronto Retail Transaction Table”, or “Customer Churn Dataset.” While this is true, this positioning and surface-level description does little to help consumers understand the value that the product delivers. Best-selling product managers will position and make clear whether their product:
Reduces the time spent manually gathering or preparing data
Enables real-time decision-making rather than day-old or week-old reporting
Automates processes that previously required human judgment
If the consumer can be made sure of these value levers upfront, they are more likely to spend money to achieve them. In addition to proactively presenting the problems and outcomes enabled, a well-marketed product will anticipate its target consumer’s needs, and the questions they will ask prior to subscription. For example,
What is this data, and where did it come from?
How frequently is it updated, and how reliable is it?
What can it be used for, and what are the access limitations on its use?
Who do I contact if I have questions or run into issues?
Product cards determine how a product presents itself on the Marketplace, and are a powerful tool to answer these questions most directly and immediately. By providing answers across both the Product card and page, the objective is to make the product as self-service as possible. Beyond metadata and written descriptions, best-selling product managers may also embed dashboards directly into these product pages. This creates an “unboxing” experience in which potential consumers can evaluate the value of the product to their use case before subscribing. This immediate validation reduces uncertainty, increases the likelihood of adoption and accelerates consumers to move from browsing to buying.
After all, if every consumer requires a one-on-one orientation or ad hoc email exchange, the product will struggle to scale. Given this, the effective marketing of a data product requires a clear understanding of who the product is for.
Integrated Go-To-Market Strategy
To get the best sense of their consumers, their value drivers and prospective questions, in order to get ahead of them and accelerate time-to-value, the best product managers do not solely rely on written requirements or feature requests. They observe consumers in the context of their broader business and working environments to uncover pain points and unmet needs.
For example, a data scientist who works primarily in Python notebooks will have very different expectations from a business analyst who operates in Power Bi. Product managers must analyze their ideal customer profile (ICP) across several dimensions, including:
Their technical expertise
Preferred Bi tools, interfaces and sharing mechanisms
The decisions or outputs that consumer will be responsible for
The formats that the underlying data assets are in
The security, privacy, or compliance constraints that must apply
The context that is needed for the data product to be deemed useful
How easy is it for the intended user to work with the product independently
These factors not only determine how a product should be packaged, positioned, and permissioned, but allow for the product to align with how the intended consumer actually works. Even the most well-marketed products will disappoint commercially if they fail to do so.
Adoption and Retention
Once a data product is available on the Marketplace, success is defined by sustained usage and realized value, not by launch alone. By understanding and accommodating for the factors stated above, product managers can lower the barrier to entry and drive adoption by enabling:
Self-service filtering, querying, and evaluation of data
Data customization without engineering involvement
Flexible, no-code data pipelines for sharing
Consumption in the Bi tools and interfaces that consumers users prefer
If a consumer can understand the product quickly and get started on their use case without assistance, the product is more likely to become part of their regular workflow, which in turn supports retention. It is the combination of strategic positioning and proactive packaging that removes friction from discovering, accessing and consuming data products. The final piece in the puzzle, for product managers to market their best-selling products, is permissioning.
Scaling and Expansion
Top product managers scale their impact by expanding the reach of their most successful products. As has been made clear, they take responsibility for commercial outcomes, not just the technical delivery leading to ‘publish.’ Permissioning is a commercial lever in that it is not only a security mechanism, but a way of sustaining business logic. Using Subscription plans, product managers can manage access at scale by defining:
Who is allowed to access the product
Under what conditions access is granted
How long access is maintained
The price for which access is gained
Importantly, permissioning does not need to result in product sprawl. A common pitfall in data product management is creating multiple near-identical products to serve different segments or use cases. For example, a single product manager might have entirely separate products for “Consumer Trends: Europe”, “Consumer Trends: Asia”, and so on, crowding the marketplace offering and degrading the consumer’s discovery experience. An overpopulated, confusing marketplace for consumers reduces the likelihood of their data consumption, and by extension, the revenue-generating prospects and operational overhead of the producer. A more scalable approach is to treat permissioning as a function of the subscription, not the product itself.
By applying different Subscription plans against a single core data product, producers can create multiple variants of access without duplicating the underlying asset. Full access, region-specific access, or role-based access can be facilitated through Subscription plans that enforce row- and column-level restrictions. This allows product managers to support multiple ICPs using one product, improving governance and commercial clarity at the same time.
Consumers immediately understand exactly what they are provisioned to based on their subscription, while producers retain control over how data is consumed. When combined with strong placement and clear packaging, subscription-based permissioning completes the equation: products are easy to find, easy to understand, and easy to access appropriately.
Summary
Commercially successful data products are defined by intentional marketing, clear value propositions, and thoughtfully designed access. The best product managers treat their marketing strategy as an integral part of the product itself. They position for discovery, package for understanding, and permission for growth. When done well, data products evolve from static assets into scalable products that users trust, adopt, and are willing to pay for.
Success Checklist
- Positioning based on consumer needs makes the discoverable by the right audience
- Packaging communicates value, use cases, and constraints without explanation
- Product pages are written for intended consumers, not internal teams
- Previews and product cards allow consumers to assess relevance before subscribing
- Data ownership, quality and update frequency are clear and trusted
- Permissioning enables different types of consumption, and different types of consumers
- Feedback and usage inform iteration and improvement for scaling and expansion