Francis explores how companies can unlock new revenue streams by transforming overlooked digital byproducts—like clickstreams and sensor logs—into valuable assets. From personalizing services to creating anonymized data products, this piece offers a strategic roadmap to turn “data exhaust” into high-margin growth.
“Every click, transaction, and digital footprint your customers leave behind is a monetization opportunity—if you know where to look”
What Is Data Exhaust?
Data exhaust refers to the passive, secondary data generated through routine digital interactions—often captured incidentally. This includes clickstreams (the sequence of actions a user takes on a website), IoT sensor logs from smart devices, location records from mobile apps, and metadata from transactions or system events. While this data isn’t part of a company’s core operations, it accumulates rapidly and contains deep insights into customer behaviour, usage patterns, and operational trends.
Yet, what many firms discard as digital noise can be transformed into a strategic asset. Take Mastercard as a leading example: in 2024, the company generated $10.83 billion—over a third of its total revenue—from its Value-Added Services and Solutions segment. This includes anonymized analytics and insights derived from 125+ billion purchase transactions, which are sold to advertisers, retailers, and policymakers. Once considered an operational byproduct, this data exhaust now fuels a growing, high-margin revenue stream—demonstrating the massive, untapped potential hiding in plain sight.
Why This Matters – Data Exhaust as a Critical Asset
In today’s data-driven economy, data exhaust is emerging as a powerful yet underutilized strategic asset. While most organizations analyse only a small portion of their data, research shows that 80% of the most innovative firms actively leverage data for business gains. Industries like banking, financial services, and telecom are leading the way—using aggregated and anonymized data exhaust to enhance customer experience, optimize operations, and support strategic decisions like urban planning.
The potential is massive: the global data monetization market is projected to grow from $375.97 billion in 2025 to $1,632.57 billion by 2034, at a CAGR of 17.72% during the forecast period. As companies invest heavily in data infrastructure—Microsoft is planning to spend $80bn in 2025—unlocking value from data exhaust is not just an opportunity, but a competitive imperative.
Why Companies Fail to Utilize Data Exhaust
Despite its value, many companies struggle to monetize data exhaust due to structural, technological, and strategic barriers:
Overcoming these challenges requires organizational alignment, investment in AI-driven analytics, and consulting expertise to build scalable, compliant monetization models.
How Can You Unlock Revenue from Data Exhaust?
- Enhance Core Business with Data-Driven Insights
Use behavioural and usage data to improve products and personalize services. For example:
- Insurance: Progressive’s “Snapshot” program uses smartphone telematics to reward safe drivers and now accounts for over 20% of its direct-channel revenue.
- Agriculture: John Deere transformed data from its equipment into a “Precision Farming” subscription service, shifting from one-time sales to recurring revenue.
- Retail: Amazon leverages browsing logs and purchase history to personalize offers and recommendations, significantly reducing customer churn and boosting sales.
Estimates show that the right personalization strategy can lift revenues by 10–15%, and that data-driven operational changes yield 10–25% performance improvements. Treating data exhaust as fuel for R&D and marketing can deliver immediate ROI.
- Package and Sell Anonymized Data Products
Companies can sell insights derived from aggregated, anonymized client data. For instance:
- Financial services: Mastercard’s Data & Services division sells over 25 products based on 125+ billion purchase transactions, enabling ad targeting and market research.
- Telecom: A Fortune 500 telecom used tower and subscriber data to launch a data marketplace, serving city planners and retailers.
These data products are high margin, require little incremental cost, and comply with privacy laws when properly handled.
- Innovate Business Models and Services
Data exhaust can enable new offerings and business models:
- Aviation: Rolls-Royce uses jet engine data to offer “power-by-the-hour” maintenance contracts.
- Healthcare: Propeller Health uses sensor data to guide asthma patients, cutting emergency events by 50%—a value proposition that justifies premium pricing.
- Software: One firm monetized telemetry data to detect license misuse, generating $4M in additional revenue.
- Banking: Aggregated transaction data is used for spend analytics and fraud detection tools offered to clients.
By turning data into IP and services, firms unlock new revenue streams and premium pricing opportunities.
How Data Missteps Derail companies: Risks and Repercussions
Industry leaders are increasingly monetizing data exhaust. However, the risks of mismanagement are just as real:
- Silos and lack of coordination can result in initiatives like GM’s OnStar, which faced regulatory scrutiny for sharing driver behaviour data without explicit consent, causing reputational damage and operational restrictions.
- Privacy concerns and inadequate governance were evident when a fitness app’s public heatmap inadvertently exposed sensitive military locations, highlighting the dangers of poor data handling.
- Leadership mindset and insufficient transparency contributed to backlash against a smart speaker brand that used user recordings to train AI without consent, eroding trust and attracting regulatory pressure.
- Lack of a clear monetization strategy led some firms to build costly data lakes that yielded no returns, ending in write-offs and stalled projects.
Successful leaders treat data exhaust as a strategic asset—balancing innovation with governance, transparency, and clear business value.
Action Plan for C-Suite Leaders
To harness data exhaust effectively, executives must take immediate, structured steps:
- Audit and classify data exhaust: Identify all customer and usage data (e.g., web logs, sensor data) that could unlock value.
- Implement governance and privacy safeguards: Anonymize data and comply with regulations. Use data catalogues, encryption, and transparent privacy policies.
- Pilot analytics projects: Form cross-functional teams to test monetization use cases. Start with small wins—like customer journey analytics or personalized offers—and scale success.
- Develop data products and partnerships: Create dashboards or reports for external use. Collaborate with ecosystem partners or join data marketplaces.
- Measure, iterate, scale: Track KPIs such as new revenue, cost savings, and retention impact. Refine the business case and expand successful pilots.
To achieve this, the key enabler is investing in technology and talent by building modern data infrastructure—such as data lakes and real-time analytics—and hiring specialists in AI, data science, and data privacy
Conclusion
Data exhaust is not digital waste—it’s an untapped strategic asset. As data generation surges, the gap widens between firms that act and those that fall behind. C-suite leaders must reframe their mindset: data exhaust must become a core pillar of innovation. The tools and talent are available. What’s needed is urgency. Turning “waste” into wealth could define the winners of the data-first economy.
Francis Morais
Francis is a consulting intern at Avalon Consulting, currently pursuing his MBA at IIM Indore. With over 4 years of experience in manufacturing operations at Flowserve Sanmar, he has led initiatives across process engineering, Lean Six Sigma implementation, and cross-functional efficiency improvement. His work has contributed to significant gains in productivity, quality, and lead time reduction. Francis holds a bachelor’s degree in mechanical engineering from St. Joseph’s College of Engineering, Chennai, and brings a strong blend of analytical rigor and hands-on leadership to problem-solving in dynamic business environments.
