“Data Monetization”

(Nihilent’s experts, Nihilent, 2019)

“It’s no longer just about business know-how and instinct. Advanced Analytics (AA) may seem like a daunting challenge, but applying the right model, innovation can be data-driven”.

Co-managers remodel their business models by driving innovation and monetizing their data. By monetizing their data, they can find avenues for additional revenue streams from data. If you want to achieve a successful data monetization, you have to formalize your vision and refine your marketplace niche. There are some examples below with their consumer benefit and business impact: a) In the financial services industry, selling credit transactions to merchants or payment networks, consumers benefit from transaction information for precision marketing; fraud detection and credit risk management.  This leads to lower customer-acquisition lifetime value per customer, reduces revenue and improves profitability of credit products. b) In the manufacturing industry, offering condition-based or preventive, maintenance based on monitoring of embedded sensor data (IOT). Continuity of business leads to minimizing unplanned downtime. Innovation must be data-driven. This can be achieved by applying AA, which provides: 1) Deep insights into customer behavior, operational efficiency, and business models. 2) Cognitive services such as sentiment analysis, voice to text translation, and vision recognition. 3) Automating decision-making based on sound business rules derived from historical data. Nihilent has developed a recurring process that you can adopt to move forward with AA initiatives. Both human interventions and automated, Machine-Learning driven processes can be integrated to improve the results. Nihilent can translate your vision into your next great innovation, by developing your data offering and approach to monetize your data to generate new revenue streams.

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