Data Monetisation: The Goldmine Companies Are Sitting On And How They're Digging In
Introduction
What Type of Businesses Are Monetising Their Data?
Data monetisation is experiencing significant growth across diverse sectors. Businesses ranging from retail and healthcare to finance and telecommunications are now recognising and capitalising on the value of their data.
The global data monetisation market, valued at $2.9 billion in 2022, is projected to grow to $7.3 billion by 2027, showcasing a robust Compound Annual Growth Rate (CAGR) of 19.5%. This explosive growth is fueled by the increasing volume of data and the advanced capabilities to analyse and utilise this data effectively.
“Those companies that view data as a strategic asset are the ones that will survive and thrive.” – Cathy O’Neil, a data scientist, author, and founder of ORCAA.
Benefits of Data Monetisation:
Monetising data can yield substantial benefits, impacting various aspects of business operations:
- Enhanced Decision-Making: Data-driven insights enable businesses to make more informed decisions quickly, helping them stay agile in a fast-paced market.
- New Revenue Streams: By identifying and exploiting valuable data, companies can create new revenue streams through direct sales, licencing, or by enhancing existing products with data-driven features. Mastercard generates over $1 billion in revenue annually by selling anonymised transaction data and analytics services to merchants and partners, illustrating the potential for significant financial returns from data assets.
- Improved Customer Experience: Leveraging data to understand customer needs and behaviours leads to more personalised services, improving customer satisfaction and loyalty. Amazon sees about 35% of its revenue from personalised product recommendations, demonstrating the revenue potential of customised customer experiences.
- Operational Efficiency: Data analytics can pinpoint inefficiencies in processes, reduce costs, and streamline operations, leading to greater productivity and profitability. Walmart saved $24 million in just one year by using data analytics to optimise its supply chain and reduce inventory costs.
- Competitive Advantage: Companies that effectively use data to drive their strategies often outperform their less informed competitors, maintaining a competitive edge in their markets.
Case Study Analysis: Uber’s Strategic Use of Data
Uber exemplifies successful data monetisation, utilising vast amounts of data from millions of rides to optimise its pricing and routing. By implementing dynamic pricing, known as surge pricing, Uber adjusts fares in real-time based on demand and supply conditions, maximising profitability and enhancing service reliability.
Case Study Reflection:
“Uber’s data monetisation approach provides a model for others aiming to harness their data’s power, showing how real-time processing can transform service delivery and customer satisfaction,” observes Dr. Emily Sands, Data Science Professor at Stanford University.
Identifying Opportunities to Monetise Your Data:
The key to successful data monetisation lies in pinpointing customer-centric opportunities, whether they’re directly facing consumers or addressing B2B needs. From offering personalised insights to leveraging IoT data for benchmarking, the possibilities are extensive. Collaborating within an ecosystem to establish fraud detection or providing visibility into stock and inventory levels are practical examples of how data can be leveraged for mutual benefit. Adopting a customer-focused approach, particularly one that enables the provision of curated analytics or raw data for enrichment, can significantly enhance the value offered to both businesses and consumers alike.
Potential Barriers to Data Monetisation:
Navigating Challenges in Data Monetisation.
Despite the clear advantages, several barriers can impede a company’s ability to monetise data effectively:
Data Quality and Integration: Disparate data sources and poor data quality can severely limit the effectiveness of monetisation efforts.
- Privacy and Compliance: Regulations such as GDPR and CCPA place strict limits on data usage, requiring robust compliance measures.
- Cultural Resistance: Shifting to a data-driven culture can be challenging in organisations accustomed to traditional decision-making processes.
- Technical Expertise: There is often a gap in necessary skills, as data science and analytics are specialised fields requiring ongoing education and experience.
To Buy or To Build?
When deciding whether to buy or build data monetisation solutions, integrating platforms like Tableau can provide a balanced approach. Tableau is renowned for its rapid deployment capabilities, with users reporting up to 10x faster deployment times compared to other analytics platforms.
It’s used by over 86,000 customer accounts in various industries, demonstrating its scalability from small businesses to large enterprises. The platform’s extensible architecture supports extensive customisation through APIs, web data connectors, and integrations, allowing businesses to tailor solutions precisely to their needs. By adopting Tableau, companies can quickly harness robust analytics capabilities and adapt them as their strategies evolve.
Conclusion
Data monetisation represents a pivotal strategy for businesses aiming to unlock the intrinsic value of their data assets. By understanding the diverse approaches and acknowledging the potential challenges, companies can position themselves to benefit from the vast opportunities that data monetisation presents.
As we look towards the future, the continuous evolution of data analytics and management platforms will undoubtedly play a crucial role in shaping the landscape of data monetisation. Are you prepared to transform your data into a strategic asset that not only enhances operational efficiency but also opens new revenue streams for your business?
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