For many global companies, the business of data monetization yields an even more pragmatic and efficient route to sustaining competitive advantage. Bolstered by the efficiencies of modern-day analytical frameworks and technologies, today’s data monetization play adopts a more strategic approach where planning, organizing and implementing sound tactical strategies amongst other things take center stage.
Data as a Dynamic and Ever Evolving Entity
The first step in formulating a data monetization strategy is realizing that data, very much like the organizational framework of a corporation, is dynamic and ever-changing. This fluid and dynamic nature of data requires a commensurately flexible strategy that is adaptable enough to help the corporation spot the value and economic signals contained in data even as it evolves.
The effort put into the development of such a strategy is well and truly justified. As a corporate asset, aside from acting singly to bolster competitive advantage, this strategy has the inherent ability to improve and maximize the competitive advantage delivered by an enterprise’s strategic value creation faucets. To do this, however, it needs to be synergized with all aspects of the enterprise.
Deriving Financial Returns
Screening data in the manner outlined above helps delineate its inherent value and possible monetization channel. Ultimately however, the actual monetization plan is executed as;
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A return on advantage model where data and the insights it provides is used to improve competitive advantage
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A premium service model, where data is precision engineered into data products for the end consumer
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A differentiator model where the end goal is to use data as a proprietary value creation asset for retaining consumers and strengthening loyalty
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A syndication model where processed data is auctioned off to third parties who exploit it on their own
As is apparent from these models, the success of any monetization campaign is hinged on how efficiently an enterprise is able to define and mobilize the value of its data to the willing market.
Efficient Value Definition and Market Mobilization Strategies Drive Better Monetization
In today’s IoT powered ecosystem it’s easy for enterprises to fall into the rabbit hole of churning through vast amounts of data pursuant to maintaining wide scale inclusivity. This ‘jack of all trades’ approach sets enterprises on a course where they basically exploit low-risk low return channels while expunging significantly huge resources. A better strategy would be to classify data at its point of origin and asses its distinct value proposition to derive a foresight of what value it commands and to whom it commands it within the context of the resources necessary to repurpose it into a market fit. Note that although tech infrastructure plays a significant role in this classification process, it should never be treated as the limiting factor. Organizations must learn to work with the most available solution until the best solution becomes available.
Overall to guarantee the success of any monetization drive enterprises must shift their strategic focus from business intelligence and technological optimization to developing a dynamic, adaptable and pragmatic mechanism for defining data value and purposing it into a market fit.
With the help of Data Meaning,you could reposition your data to bolster your company’s revenue stream while prospering competitive advantage and operational efficiency. Read our full Case Study or visit us at datameaning.com to learn more about us and also email us at info@datameaning.com to begin a conversation about your Data Monetization strategy!