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Data Democratization and Monetization, Explained

Mike Lampa

If your organization has been focused on digital transformation or data-driven decision making over the last several years, you’ve probably been hearing a lot about data monetization and democratization.

Both are valuable approaches to leveraging the unrealized value of your data and analytics products. While they’re closely related, each has its own specific objectives, strategies and considerations. You can choose to do either or both.

But if you’re not yet clear on what data monetization and democratization can do for your organization — or even what the terms mean — no worries. We’ve got you covered.

In this article, we’ll look at data monetization and democratization in detail — including definitions, benefits, examples, and a few cautions — with the goal of inspiring you with ideas to get the biggest bang for your data analytics buck.

Understanding Data Monetization

Data monetization generates revenue. It maximizes the financial value and return on your investment in data and analytics products through creating products and/or services that can be sold or licensed to external customers, suppliers, customers, or partners. The audiences for these types of products include any external stakeholders in your customer/supplier ecosystem who have a need and are willing to pay for access to valuable data-driven analytic products or insights.

Monetization’s main focus is generating profits, optimizing pricing strategy, and maximizing ROI of data and analytics product development.

Examples of data monetization include:

  • Working with partners to increase efficiencies, as in managing and optimizing supply chains
  • Enabling new market opportunities and better customer service throughout your customer/supplier ecosystem
  • Creating analytics products focused on buying behavior, consumer preferences, and more
  • Selling insights to third parties as subscriptions or as part of consulting offers

Generating Value Through Data Monetization

Monetization usually involves a B2B model where data analytic products are sold as a value-add service either as part of a core offering or as add-on standalone products.

These products allow you to differentiate your organization with unique, high-value solutions that enable your customers and suppliers to address their specific market needs, solve pressing problems, and explore new opportunities through the use of actionable insights.

Keep in mind that organizations must take care to ensure data privacy and to protect customer data when developing products. If you use a B2C model, data, privacy, and protection require control down to the individual consumer level.

Data and Analytics Monetization Strategies

Planning your data monetization strategies involves defining your pricing structures to ensure you generate your financial targets from analytics products. With this goal in mind, you may decide to offer:

  • One-time purchases
  • Ongoing subscriptions
  • Consumption- or usage-based models
  • Tiered pricing

or some combination.

Access to each of these products should be restricted to paying customers or require licensing agreements to protect IP and ensure exclusive access to data assets.

Embracing Data Democratization

The goal of data democratization is to break down data and structural silos within organizations or communities. It enables broader access to data and empowers a wider range of eligible users, making data and insights available to individual employees, teams, and departments through self-service analytics.

The target audience is typically the organization’s internal business and technology users who can benefit from data-driven insights to:

  • Make faster, more informed decisions
  • Drive innovation
  • Enable achievement of strategic initiatives
  • Grow the top line through market expansion, revenue, and growth
  • Improve the bottom line by minimizing costs, improving operational efficiency, etc.

Depending on users’ data and analytics skills and sophistication, democratization tools can include dashboards, data warehouses, BI tools, and more.

Examples of data democratization include:

  • Helping marketing teams to create more engaging content and higher-converting campaigns
  • Empowering customer success teams to deliver better customer experiences and support
  • Allowing engineering and product teams to build products customers want and to know when to wind down outdated ones
  • Enabling executives to evaluate business performance and make better decisions on future investment strategies

Generating Value Through Data Democratization

Democratization empowers data-savvy business users with secure access to quality data and analytic products and provides easy-to-use tools and platforms. The goal is to enable stakeholders to explore and analyze data independently, at scale, without heavy reliance on data specialists, who are typically constrained. It’s a user-centric, self-service approach that empowers internal users.

While democratization may not have a direct revenue-generation focus, it does contribute to improved organizational performance in many areas. Better data-driven decision making helps reduce costs, boost revenue growth, improve the customer experience and much more.

The primary focus of democratization is to promote open access, encourage collaboration, and remove unnecessary barriers to data and analytics throughout organizations.

Still, governance oversight is critical. The right access controls are needed to ensure data privacy, regulatory compliance, and the ethical use of data and analytics.

In the end, data democratization empowers business users, improves data literacy across the organization, and fosters a data-driven decision-making culture.

Phasing Out Data and Analytics Products

All products will eventually need to be decommissioned, and the end of life stage requires careful planning and execution. Products that reach their end of life but aren’t yet phased out risk becoming liabilities instead of assets.

So how will you know when it’s time?

Conduct periodic assessments to evaluate each product’s performance, relevance, and market demand. Establish clear criteria and indicators to identify when a product is showing signs that it is approaching or has reached its end-of-life stage. Consider factors like actual usage trends (revenue and profitability), customer feedback, competitive product launches, technological advancements and overall market shifts and trends.

Once you’ve determined the time is right, there are several steps you’ll take, starting with:

  1. Proactively communicate with customers who are still using the product. Notify them well in advance about its retirement, providing clear timelines and transition plans. Learn about your customers’ needs and gain an understanding of the impacts decommissioning will have. Offer guidance on alternative solutions and migration paths to the next generation product offering to minimize disruption and support their smooth transition to other products or services.
  2. Implement a sunset period during which the decommissioned product remains operational but is no longer actively marketed, enhanced, or supported. This allows customers to continue using the product while they plan and execute the transition to alternative solutions. During the sunset period, provide a level of support and maintenance that is commensurate to your customers’ collective needs.
  3. Be deliberate about capturing and documenting the knowledge and expertise associated with the decommissioned product. This includes technical documentation, best practices, and lessons learned. Preserve this knowledge for future reference, internal training, or potential reuse in other products or services.
  4. Review and address all legal or contractual obligations you may have related to product phase-out.

Thoughts on Choosing Your Strategy

Monetization is usually a more complex undertaking because of the need to protect data integrity. As a result, it requires more investment. It’s possible to democratize data and analytics products without directly monetizing them if you’re looking for a place to start.

While the direct goal of democratization is not to generate revenue, you can realize measurable benefits that contribute to the overall success of your organization.

On the other hand, if you decide to monetize data products without full democratization, make sure that you carefully align your pricing and access strategies with your overall business objectives and with your customer expectations.

Finding the right balance between the two is a strategic decision that should be continually assessed based on your organization’s circumstances and priorities.

What’s Your Next Step?

Hopefully you now have a greater appreciation for how data monetization and democratization could benefit your organization, or even ideas you’re considering implementing.

If you’re ready to learn more, check out How to Get Started with Data Democratization & Monetization. And of course, you can always reach out our Data & Analytics team if you have any specific questions.