How consumers feed the data economy ... Industries extract value from the data swamp

What are the different uses by which enterprises extract value from consumer data? Advertising was the first application. Since then, the monetization of consumer data has spread to many other domains. A recent overview shows the use of consumer data across a wide range of businesses.


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Advertising


Advertising is the earliest and possibly still the most dominant use of consumer data collected from Internet services. Initially, the data fed traditional advertising channels, such as broadcast TV and print ads. With the growth of consumer Internet services, digital advertising is growing rapidly. Going beyond targeting ads at large demographics, digital ads are increasingly customized to target individuals.


In 2019, $129B of digital ad spending represented 54% of total media ad spending, with an expected increase to 67% in 2023. In the process, digital advertising has given rise to a gigantic ecosystem of marketing technology companies.





Price discrimination of goods and services


Consumer data is used for price discrimination, charging different prices to different consumers. In some cases, price variations based on data are related directly to the goods or services sold. For instance, by letting insurance companies monitor their driving habits, consumers may receive discounts on their coverage. Health insurance premiums may be reduced based on data about physical activity. Home insurance may be lowered based on monitoring equipment in the home. In these applications, the data collection and the resulting price changes are visible to consumers.


In other cases, though, price discrimination is invisible and unrelated to the goods or services sold. Using algorithms to determine consumers’ willingness to pay for certain products mostly increases the prices, and increases the sellers' profits. In the UK, an investigation has been started to determine whether the use of AI in pricing hurts consumers. This kind of price discrimination, often used with consumer goods and services such as insurance or loans, is not always illegal. However, this largely invisible price discrimination can be unfair, for instance, by making decisions based on race or gender. In some cases, the discrimination may be subtle, such as targeting junk food ads at black and Hispanic kids. In pretty much all cases, this price discrimination is to consumers’ disadvantage.


Service Denial


Going beyond price discrimination, denial of jobs or services such as loans may make some enterprises more profitable. However, in many cases it results in cost and disadvantage to consumers. For instance, 90% of employers are analyzing applicants’ social media during employment decisions. Some of this data may be relevant. But as the amount and diversity of data used by AI algorithms increases, much of it likely is not. AI algorithms tend to be opaque, and bias is pervasive and difficult to prove and prevent.

Product and service improvements


Product and service improvements are decidedly beneficial uses of consumer data, for both consumers and enterprises. They result in better, more efficient, and safer products. They range from more focused search results and easier-to-use e-mail to smart thermostats and wearables that give health warnings. Data also enable personalized products that are more useful and fit better into consumers’ lifestyles. Monitoring social media about comments on products can have beneficial safety benefits. For instance, social media monitoring has given early warnings of adverse drug reactions. The benefits of these types of data uses are hard to overestimate.

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