The Impact of Data Commercialization Strategies on Business Revenue: Six Innovative Approaches

Introduction

In the digital era, companies are increasingly recognizing the significance of digital data for their business growth and identifying new opportunities for data gathering and analytics. Leveraging valuable data has become essential for enhancing operations and overall business performance. Although companies are adept at structured data collection and analysis, many fail to explore the creative and commercial aspects of data utilization fully. This essay explores six inspiring ways for companies to monetize their data, supported by real-life case studies.

1. Selling Insights to Customers

Companies can aggregate and enrich existing data, transforming it into valuable insights for sale to customers. Reports, online dashboards, and indexes can be bundled with existing offerings, increasing the bundle's perceived value. Additionally, incorporating machine learning applications into user interfaces allows for real-time creation of new insights during customer interactions.

Illustration: Oikotie.fi, a Finnish job portal, commercialized its data by providing B2B customers with performance comparisons of their job ads against industry peers. This data empowered recruiters to optimize their advertising strategies while generating new revenues for the job board.

2. Empowering the Sales Force with Data

Data can be a potent tool for sales organizations to maximize their performance. By equipping the sales force with rich customer data, companies can identify customer pain points, improve presentations, and enhance customer service. Salespeople play a pivotal role in establishing the company as a data leader, reinforcing the value proposition to customers.

Illustration: Kone, a Finnish elevator and escalator company, empowers its sales force with comprehensive device data, enabling them to provide customers with valuable insights on device conditions, leading to additional sales of maintenance services and spare parts.

3. Data Utilization in Marketing and Advertising

Data on consumer behavior can be leveraged to optimize marketing and advertising efforts. Companies can either optimize their own marketing using internal data or sell data to other firms for their marketing purposes.

Illustration: Foursquare, a location-based service app, sells its data to retailers for optimizing outdoor advertising and online marketing, aligning with people's navigation routes. Media companies collect digital data on consumers' interests and sell it to online advertisers, allowing them to target specific audiences effectively.

4. Selling Data within the Industry Value Chain

Rather than considering data as a proprietary asset, companies can capitalize on sharing data within their industry's value chain. Data can be sold to suppliers, vendors, retailers, and other partners, both up and down the value chain, to optimize operations and cooperation.

Illustration: In the pharmaceutical value chain, Finnish distributor Tamro sells data on drug purchases to local pharmacies, enabling them to enhance sales and optimize drug display and stock. Tamro also sells data to drug manufacturers for pricing strategies.

5. Selling Data to Players Outside the Industry

Exploring opportunities outside the company's industry or value chain can reveal potential buyers interested in economic activity, consumer behavior, and other relevant data.

Illustration: Legislative changes in the EU have compelled retail banks like Nordea and Danske Bank to share account and payment data, creating opportunities for fintech and other companies to develop digital services based on consumer banking data.

6. Data-Driven Company Valuation

Viewing data as a valuable asset in the company's balance sheet can lead to the sale of the entire company to a buyer seeking access to valuable data for business growth or improvement.

Illustration: Acquisitions such as Facebook's purchase of WhatsApp and Microsoft's acquisition of Minecraft were influenced significantly by the data possessed by the companies, as it held immense value for the acquiring companies' business plans.

Conclusion

Data commercialization is an extensive and promising opportunity for businesses worldwide. By embracing innovative approaches and partnerships, companies can capitalize on their data assets to drive growth and profitability. Legal considerations and consumer privacy must be prioritized, with companies closely monitoring legislative changes. With advances in machine learning, the future holds great potential for companies that skillfully harness data exploitation and make data a core pillar of their business strategies, yielding substantial revenues and competitive advantages.

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