Information Economics and Signaling: Why Referral Marketing Works in Markets with Imperfect Information

In university economics, one of the most powerful concepts taught is that of information economics, or the study of how markets operate when buyers and sellers have varying degrees of information about one another and their products. A related concept is signaling theory, developed by Michael Spence, which provides a mechanism for individuals and businesses to convey previously hidden information to buyers and sellers regarding product quality, dependability, and value.

Referral marketing is a current example of how both concepts come together in today's marketplace. Referral software allows a business to reward customers who recommend a product to their friends, coworkers, or family members. While referrals may appear to be a marketing strategy, from an economic perspective they are primarily a response to the ongoing problem of inefficiencies in market information.

Many consumers have difficulty determining product quality prior to making a purchase. The information problem is especially acute for digital services (e.g., cloud storage), financial products (e.g., mortgages), software subscriptions (i.e., subscription-based software), and any other experience goods that reveal their true quality only after use. The term "information asymmetry" describes this situation, in that one party has significantly more information than the other party.

When information asymmetries are substantial, consumers will have uncertainty and search costs associated with their purchasing decisions. Consumers will invest considerable time gathering product reviews, comparing competing products, and evaluating statements made by the businesses. Referrals from family and friends relieve some of the burden on consumers by providing recommendations that typically carry a higher degree of reliability than do advertisements.

The growing economic force that is fueling the rise of referral systems is the demand for trustworthy information. When consumers purchase products through referral systems, they are not simply buying products; they are also seeking confidence in their decisions. According to Nielsen research, 83% of the world's consumers indicate that they have trust in recommendations made by their friends and family, making personal (or "word of mouth") recommendations the single most trusted type of advertisement. The same survey also discovered that 66% of consumers trust online consumer opinions.

Signaling theory helps to explain this trust advantage for businesses that utilize referral systems. A personal recommendation can be viewed as providing a "signal" because the individual making the recommendation has personal experience with the product and will incur a potential loss of reputation if the recommendation is inaccurate. In contrast, paid advertisements have incentives to create an image of the product in a positive manner, thus making personal referrals generally more credible. The social cost associated with providing a personal referral is that the individual providing the referral may incur a loss of social capital if the recommendation is inaccurate.

As a method of proving the value of referrals, online referral marketing software attempts to organize and inspire customers to provide referrals on a continuous and regular basis, rather than relying only on the unstructured "word of mouth" model. The referral software enables businesses to create a "formal" structure that encourages customers to utilize referral linking, codes, or invitations to provide referrals. In addition, the referral software tracks referrals made and rewards customers when their referral leads to a sale or a purchase.

Dropbox is an excellent illustration of the use of referral systems. During the company's early growth period, Dropbox offered special deals for their users who referred their friends to Dropbox. This incentivized customers to act as information intermediaries in the marketplace. As a result, the business used trusted social networks to help relieve uncertainty that new customers may have felt about the reliability and dependability of Dropbox. 

Another example is PayPal, which also offered incentives to customers who referred others during the company’s early expansion phase. For both referral programs, customers and referrers received a reward for completing transactions, which resulted in a system that encouraged people to provide referrals to their friends through their social networks. This marketing strategy helped accelerate the growth of PayPal in a market segment where trust was absolutely critical, because consumers were being asked to begin moving their financial transactions online.

The impact of referral systems isn't limited to marketing; referral systems also shape an industry's structure and, consequently, competitive dynamics. Companies that have successfully built credible referral signals will typically have lower costs of acquiring customers and can achieve faster growth. Owing to the exceedingly powerful nature of referrals, it is not uncommon for strong referral channels to create positive feedback loops of acquiring new customers, thus providing a competitive advantage similar to a network effect.

There is evidence to suggest that customers who are referred to a company may also be economically different than those who are not referred. Research conducted on around 10,000 customers at a German bank found that new referred customers were significantly more loyal than non-referred customers and generated higher profits for the bank with the average value of a referred customer being at least 16% greater than the average value of the equivalent non-referred customer.

The above findings suggest that a referral system not only generates additional sales for businesses, but also helps improve the ability of businesses to create the best possible match between products and consumers. Consumers tend to make product recommendations to individuals who have similar preferences to their own. By doing so, they reduce the likelihood of mismatches between consumers and products that can lead to long-term dissatisfaction. Referral marketing can improve market efficiency by allowing information to flow through trusted social networks rather than relying solely on advertising claims or price signals.