5 Minute Intro to Data Monetization
Updated: May 28
What is Data Monetization?
Data Monetization is the process of generating measurable economic benefits from available data sources through analytics. It involves identifying and marketing data or data-based products to create monetary value. With more organizations becoming data-driven and executives recognizing the inherent value of data, there is a steady adoption of the practice to help support critical areas like revenue generation, customer retention, and reducing costs. The benefits of data monetization are felt both internally and externally.
Provisioning of trusted data for analytics
Improving business insights
Gaining a competitive edge
Reducing customer attrition/increasing lifetime value
Increasing operational efficiencies
Differentiated/Improvised product experience
Enriched customer experience
Augmented market position
Improved vendor/partner collaboration
New business models
Despite the promise, monetizing data through analytics is not easy. Internally implementing data and analytics efforts of any kind are notoriously tricky for several reasons (See: The 7 Common Challenges of Fielding Internal Analytics Teams). To succeed, companies need vision, planning, and execution, along with a multi-faceted team of data analysts, data engineers, product managers, domain experts, and application developers.
But having all mentioned above means very little without the most critical component: a robust, transparent data and analytics infrastructure that is tuned to meet the requirements of the target users.
Why Data & Analytics Infrastructures Are The Foundation For Delivering on Data Monetization
The efficacy and returns of a Data Monetization effort are massively dependent on the strength of data & analytics infrastructures. These infrastructures are the foundation that supports all other data-driven business efforts, including data monetization. The most robust and useful infrastructures all share one common characteristic: transparency. This transparency emerges once necessary data from multiple, disconnected data sources is brought together into a single, comprehensive view. Without this comprehensive view, the teams that manage these infrastructures cannot organize, direct, or optimize data.
Given the growing complexity of modern data infrastructures, it's likely that teams are dealing with significant transparency issues. Fortunately, emerging technology and data platforms like Process Tempo are assisting organizations in overcoming these issues and rapidly establishing foundational transparency. In addition, they are helping to support critical business processes and a number of go-to data monetization strategies.
Top Data Monetization Strategies:
Asset Sales: Generating additional revenue based on provision/sale of data or from granted access to data. Here, businesses need transparency into what potential data can be sold - and what data absolutely shouldn’t be.
Business Process Improvement: Value from data is created through improvement or optimization of internal business processes. Clarity into processes helps highlight inefficiencies so teams can find corrections or suitable alternatives, specifically around reducing costs, either directly or indirectly.
Data Democratization: Delivering data analytics internally across the organization to employees to enhance intelligence decision-making across the board. With transparency into systems, it's easier to direct timely, contextual, and usable data to employees. In addition, going through this process also helps to significantly improve data quality.
Product/Service Innovation: Extending the existing range of offerings to customers with new products or services based on data.
Product/Service Optimization: Optimizing existing products or services by utilizing data.
Data Insights Sale: Selling information or knowledge derived through any processed step of insights making (analytics, visualization, etc.) based on data.
Contextualization: Using context-based data to generate economic benefits.
Individualization: Using customer-linked data to individualize certain aspects of a company’s value proposition on an individual basis.
Customer 360: leveraging data to create and maintain lasting relationships with customers.
Not sure which strategy is the best for you? See our top recommendations
1. Data Democratization
Once an organization establishes data democratization, data monetization tends to follow automatically. We recommend working toward data democratization first as it can provide immeasurable short and long-term benefits for the business overall, not just in data monetization.
However, delivering data to employees how and when they need it has been a constant struggle for analytics teams. The ever-increasing demand for analytics-based insight generates a growing backlog of unmet deliverables, resulting in teams being unable to keep up with analytics requests and deadlines. It can take days, weeks, or even months to accommodate individual data requests. By the time reports are received, data can be outdated, in the incorrect format, or completely unusable. These bottlenecks can be corrected by implementing self-service analytics, an area that has made impressive strides as of late. Business users are seeing more user-friendly data platforms emerge like Process Tempo that are better tuned to their needs and less technical skillsets, allowing them to easily access and report on contextual data in a timely fashion. Armed with usable, accurate, and contextual data, employees can capitalize on opportunities as they arise and contribute toward the data monetization objective.
2. Customer 360
The same technology and approach to enabling self-service analytics also apply to enabling the Customer 360 effort. Both involve bringing multiple data sources together and distributing impactful, accessible data to users.
With Customer 360, teams are powered with in-depth knowledge of their customers and understand how all applicable information interrelates. This information ranges from the customer journey, churn avoidance, loyalty, cross-selling, customer sentiment, and identifying common relationships between products, transactions, locations, and devices.
The more informed the organization is about its customers, the better it can improve customer loyalty, lower average churn rates, identify potential customers, and expand its market share.
The efficacy and returns of a Data Monetization effort are massively dependent on the state of an organization’s data & analytics infrastructure. Strong infrastructures are the backbone of data monetization and require the right blend of technology and best practices. By implementing modern, next-gen technology like Process Tempo (and capitalizing on Analytics as a Service), organizations can achieve greater transparency into their systems and their data, directing it to where it’s needed most in their cost-saving, revenue-generating efforts.
Process Tempo is a hybrid cloud, data management & analytics platform that breaks down silos to allow people, processes, and technologies to seamlessly work together. The platform supports a secure, governed, scalable, and high-performance environment for analysts and data scientists while serving as the foundation to deliver insights to all employees. It helps to deliver markedly fast, actionable, and accurate insights, easily incorporates a semantic data layer to curate and recommend information from across the organization, and makes every employee a first-class citizen in contributing insights and feedback to make the organization smarter over time.
Analytics as a Service from Process Tempo is an analytics solution that helps your entire team make intelligent and profitable decisions by leveraging your data without a heavy, upfront investment. By choosing an efficient, fast, and cost-effective path to insights, we can help you beat your competitors in today’s data-driven, competitive digital economy. With Process Tempo as your Managed Service Provider, stakeholders can focus on achieving sustainable and predictable profitable growth. Ready to get started with a Managed Analytics Service? Read more about Process Tempo's Approach to Managed Analytics or schedule an introductory session.