Data as an Input: Returns to Scale in the Information Economy

Companies grow from data, with consumer data generating services and ideas for new goods and services.  With almost all of our data having moved online, there are services to protect and package this data, analyze this data, refine this data, and return to us recommendations for goods and services based on our data.  Theoretically, our lives can be improved and streamlined by letting companies have access to our data.  The ability for data to be used as an input (resource) in the creation of services has created a demand for it.  Now, tech companies seek our data so it can be either used by those companies or packaged and sold to other firms for profit, which is known as data brokering.

Data Accumulation and Natural Monopolies

Websites collect our data all the time, ranging from our searches for products and services to buy to social media posts we make.  Over time, this data accumulation allows the website owners to begin making inferences about us as consumers or factors of labor.  For example, after a year of grocery searches and purchases through an app, the app owner has a good idea of our desires and needs as a consumer.  This helps the app tailor ads and promotions to us as individuals, likely increasing our demand (and quantity of purchases).

In the long run, companies that collect more of our data and are able to tailor desirable goods and services toward us have increasing advantages in sales.  This can lead to less successful firms exiting the market, unable to compete with data powerhouses that can effectively tailor individualized promotions to online customers.  Consumers will quickly come to expect tailored online shopping experiences, disadvantaging firms that cannot provide that experience.  This will especially harm small businesses, which are less likely to be able to afford access to online tools, such as AI platforms, that can turn customer data into individualized offerings.

Increasing Returns to Scale Creates Barrier to Entry

The high barrier to entry of being able to process customer data into concrete individualized ads, promotions, or offerings can create natural monopolies.  New firms cannot match the expected customer service of existing firms, creating a lack of competition.  Among existing firms, the accumulation of data results in increasing returns to scale as these companies can provide better services without spending more on physical resources.  The increasing returns to scale comes from efficiency: firms with massive amounts of customer data can more quickly and easily determine new offerings that will sell without having to create focus groups, pay for market research, etc.

Monopoly or Oligopoly?  Non-Rivalrous Data Can Help Multiple Firms

Some large retailers that sell a wide range of items, such as consumer products and groceries, operate in multiple markets and may prevent the rise of a true monopoly from accumulation of data and its resulting increasing returns to scale.  Consumers are likely to frequent a supermarket chain and a multi-purpose retailer like Walmart or Target, providing both types of stores their data.  As long as a large firm is somewhat differentiated from its rivals, it may survive as a niche monopoly if it can streamline its offerings.  For example, customers may provide Walmart lots of browsing and consumption data only for certain lower-cost items while providing Target similar data for higher-cost items.  

In order to remain efficient and profitable, similar oligopolists may become more different over time and avoid competing on items where a rival has more data to create individualized offerings.  This streamlining may be possible through online ordering, allowing customers to get the items they need from different sellers with the same efficiency as previously getting all items from one large retailer.  However, some limits to this efficiency exist as consumers come to value their time and transportation costs more than price savings - consumers will continue to put some premium on convenience and only having to make one order pickup.

Helping All Firms: Open Data and Widespread Productivity Gains

Firms’ collection of customer data is valuable and creates marketing and market research advantages.  However, smaller firms may be able to access consumer data from other open sources, such as social media posts and Google Reviews.  This requires processing ability, but this will likely grow less expensive over time.  Free-use and open source AI platforms may be used effectively by small firms, especially in smaller markets, to analyze consumer data and remain profitable.

Policy Dilemma Over Large Companies Trying to Limit Free Data Analysis

Monopolists and oligopolists who crunch volumes of customer data internally may lobby AI companies to put all of their services behind paywalls to prevent small firms from easily accessing those capabilities.  This is especially true if these large companies pay those same companies for more advanced packages of the same service.  “It’s unfair that we pay you for data analysis of our ten million customers while our small rivals can get the same analysis of their customers for free,” the oligopolist’s lawyers would say.

This could create legal and government policy challenges, with accusations of anti-competitive behavior if large firms try to force AI behind paywalls.  Is it fair for small companies to get to use freemium versions of AI if large companies have too much data to use those same free versions?  On the other hand, can courts consider data analysis as a resource to which all companies should have equal access?  There are many types of data analysis, and many methods of analyzing data.  Companies have operated for centuries without digital data analysis, and it would be difficult to prove that such ability is necessary to remain competitive.

The Classic Response: Nonprice Competition to Remain Competitive

Small firms that cannot afford mass data analysis to streamline operations can likely rely on nonprice competition to remain competitive.  Friendly customer service, charm, and innovative advertising can help small firms retain customers, even at a higher price point, from the increased efficiency of larger rivals.  Some customers may even prefer the non-tailored aspect of shopping at a smaller firm due to it feeling safer and more organic.  Online shopping from a large firm may come to feel almost exploitative when consumers know that every ad and promotion is tailored specifically to their individual profile.  Whether it’s nostalgia or a fear of invasion of privacy, a significant portion of customers will likely remain loyal to smaller, brick-and-mortar stores for at least some of their purchases.