liveBook · Manning

Monetization

As explained in Data for All

The process of converting data into economic value, revenue, or other financial benefit.

When you use a free map or search service, what happens to the data you leave behind? Monetization means turning data into economic value. That value may go to the company collecting it, or—in a proposed alternative—to the person who generated it. section 2.2.1 section 3.5.6

Location services show the current imbalance. A service can help you find a route while selling access to collected location data. Other companies may combine and share that data, while you receive no payment for contributing it. Advertising offers another route to value: Google and Facebook earn substantial revenue from services people use without paying money. section 2.2.1 section 3.5.6

A proposed model puts more choices in your hands:

  • Set terms for particular data and uses, including a price, permitted dates, and companies you prefer or exclude. section 3.5.6
  • Allow, restrict, or revoke access; choose not to charge when sharing supports a goal you value. section 3.5.1
  • Consider value beyond a single payment. Data can be reused, combined with other data, and directed toward different objectives. section 8.7 section 8.10

Price can express a preference

Suppose you want to support sustainable farming but object to an airline’s environmental impact. You might offer the farmers free access to your data while charging the airline much more. The example treats monetization as a choice about both money and who may use your data—not as a requirement to sell to everyone. section 3.5.1

Tools that make these choices simple are presented as a future possibility, not an established way for everyone to earn a data dividend. For now, managing access is described as disjointed and time-consuming. Understanding who benefits from your data is a useful first step toward deciding what terms you would want. section 1.6 section 6.9

How Data for All covers it

How deep it goes
Explains pricing and access choices with scenarios, while deferring a deep treatment of data economics.
Examples
Uses paid location-data access, advertising revenue, and different prices for airlines and sustainable farmers.
What it assumes
Starts with familiar free services and everyday data creation rather than assuming knowledge of data economics.
What you can do after
Evaluate/understand who gains from your data and what access, payment, or nonfinancial terms you might prefer.
How it connects
Connects monetization to data ownership, access rights, data licensing, advertising revenue, and data intermediaries.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Data for All. The section links point to the parts of the book it draws on.