Overreaction to zero-price: Replication Study

What’s next?

The results of the first two studies were surprising, but at the same time very reassuring. In contrast to previous behavioral research showing that consumers overreact to zero-price products, my studies demonstrate that this is not necessarily the case. When the decisions have a real impact on people’s money and the good offered is truly beneficial to them, the reaction to the decrease in price to zero (increase in demand for a zero-price good, decrease in demand for a higher-price good) seems to be explained by people perceiving a drop from 1 Cent to zero as bigger than from 15 to 14 Cents. So maybe consumers are not as ‘irrational’ as previously thought?

If consumers do not overreact to zero-price products when they are truly beneficial to them and have a real impact on their utility, it is unlikely they will do so once those products involve non-monetary costs such as collection of personal data. There is, however, a different puzzling effect that I observed in my data – many participants (35-44%) rejected both offers – they decided to do that task without any help even if it was offered to them for free. This decision had an impact on their payments – those who decided not to use any tools earned less money than those who accepted one of my offers.

This puzzling effect triggered some further questions:

  • Are consumers exposed to free misleading offers, i.e., offers that are advertised as free but impose non-monetary costs on consumers?
  • How prevalent are such offers? Are they easy to distinguish from truly free beneficial offers?
  • Are consumers suspicious about free offers? Does this mistrust lead consumers to reject even truly beneficial free deals?
Overreaction to zero-price: Replication Study

Zero-price effect with digital content

Previous behavioral research has shown that consumers overreact to zero-price offers of goods such as candies or chocolates (Shampanier, Mazar, Ariely (2007)). In these experiments, researchers offered participants two goods. One – a high-value more expensive good, the other one – a low-value cheaper good. Some participants saw both goods offered at a positive price, e.g., 15 and 1 Cent. Other participants saw the high-value good offered at 14 and the low-value good at 0 Cents. Researchers observed that in the group which was offered the low-value good at a zero-price, the demand for the low-value good dramatically increased and for the high-quality good decreased as compared to the group which was offered the goods for 15 and 1 Cent. This effect was surprising, because when the price of the high-value good decreases we should also observe an increase in demand for it, regardless of the price of the low-value good. This combination of an increase in demand for a zero-price low-value good coupled with a decrease in demand for a high-quality good which price decreased by the same amount as the price of a low-value good is called a zero-price effect.

Zero-price effect – the demand for high-value good decreases and for the low-value good increases when the price of both good drops by one Cent.

Later studies have replicated this effect with multicomponent tourism products (i.e., hotel with breakfast; Nicolau and Sellers (2011)), investigated its neural mechanisms (Votinov, Aso, Fukuyama, & Mima, 2016) and tested it with different types of products (i.e., utilitarian v hedonic; Hossain and Saini (2015)). Recent research by Hüttel, Schumann, Mende, Scott, and Wagner (2018) suggests that the zero-price effect might also be observed when zero-price digital content involves non-monetary costs. Using hypothetical scenarios, Hüttel and colleagues showed that the zero-price effect is present also in case of zero-price online services involving non-monetary costs in the form of exposure to advertisements. Importantly, they demonstrated that the lack of a price leads to both – overvaluation of benefits and undervaluation of non-monetary costs.

There are two crucial limitations of these studies. First, they involve goods which may not be necessarily beneficial to consumers. Some consumers may perceive a chocolate as having no or even negative utility to them (e.g., when someone is on a diet). Second, later studies including the one by Hüttel and co-authors relied on hypothetical scenarios, i.e., participants were presented with scenarios describing the details of an offer and were asked to imagine what they would do if they had seen such an offer in reality. Such studies provide valuable knowledge as to consumers’ attitudes or beliefs, yet they do raise a question as to whether consumers’ choices in such hypothetical scenarios reflect their actual decisions when real money is at stake.

The first study I conducted in collaboration with Caroline Goukens from the Maastricht University School of Business and Economics was designed to address these two limitations. In the experiment, participants performed a real-effort task. They were shown a series of matrices with ‘d’ and ‘b’ letters. Their task was to check the boxes next to all letters ‘d’. They were not allowed to check any ‘b’ letter by mistake. They received a bonus for each correctly solved matrix. After performing the task in trial rounds, participants chose whether to use one of the tools offered to them. The tools could help them solve a real-effort task that they performed in the experiment and, thus, earn more money. One tool was cheaper and had only basic features (Basic tool), the other tool was more expensive but also offered additional features (Premium tool). To some participants (Paid treatment), Premium tool was offered for 15 Pence and Basic tool for 1 Pence. To other participants (Free treatment), Premium tool was offered for 14 Pence and Basic tool – for free. This means that in Free treatment both tools were cheaper by 1 Pence compared to the prices of the tools in Paid treatment and one of them (i.e., Basic tool) was offered for free.

Basic tool highlighting incorrectly checked letters ‘b’ and showing how many letters ‘d’ still need to be checked.
Premium tool: highlighting incorrectly checked letters ‘b’ and all letters ‘d’; showing how many letters ‘d’ still need to be checked.

The results of the first study showed that the share of participants deciding for a Premium tool was lower in Free than in Paid treatments, although its price decreased (17% vs 8%). At the same time, the demand for a Basic tool dramatically increased between the Paid and Free treatments (from 28% to 48%).

In the second study, we wanted to test if this effect is robust. Would we observe it with different prices? In addition, we wanted to exclude a straightforward explanation of the results of the first study, i.e., that the decrease in price from 15 to 14 Cents seem smaller to consumers than a decrease from 1 to 0 Cents (concave utility of money). We conducted an experiment in which we assigned participants to four groups. Each group saw a different combination of the prices of Basic and Premium tool.

TreatmentPremium toolBasic tool
15_215 Pence2 Pence
14_114 Pence1 Pence
13_013 PenceFree
10_010 PenceFree
Overview of the treatments in the second study

The results showed that the share of participants deciding for the Basic tool again dramatically increased when its price dropped to zero. Yet, differently from the first study the decrease in demand for the Premium tool was very small an statistically non-significant comparing participants who were offered the Premium tool for 13 Pence with participants who were offered this tool for 14 or 15 Pence. The share of participants offered with the Premium tool for 10 Pence increased suggesting that indeed a zero-price effect observed in the first study can be explained by consumers perceiving a drop in price from 1 to 0 Pence as a bigger decrease than a drop from 15 to 14 or to 13 Pence.

Results of the second study

Both studies (hypotheses, design and planned analyses) were pre-registered on Open Science Framework. There, you can also find a more detailed report of the results.