PRICE Lab: An Investigation of Consumers’ Capabilities with Complex Products
Authors:   ESRI, Lunn Pete , Bohacek Marek , Somerville Jason , Ní Choisdealbha Áine , McGowan Féidhlim 
Published: January 2025

Executive Summary
This report describes a series of experiments carried out by PRICE Lab, a research programme at the Economic and Social Research Institute (ESRI) jointly funded by the Central Bank of Ireland, the Commission for Energy Regulation, the Competition and Consumer Protection Commission and the Commission for Communications Regulation. The experiments were conducted with samples of Irish consumers aged 18-70 years and were designed to answer the following general research question: At what point do products become too complex for consumers to choose accurately between the good ones and the bad ones?

BACKGROUND AND METHODS
PRICE Lab represents a departure from traditional methods employed for economic research in Ireland. It belongs to the rapidly expanding area of ‘behavioural economics’, which is the application of psychological insights to economic analysis. In recent years, behavioural economics has developed novel methods and generated many new findings, especially in relation to the choices made by consumers. These scientific advances have implications both for economics and for policy. They suggest that consumers often do not make decisions in the way that economists have traditionally assumed. The findings show that consumers have limited capacity for attending to and processing information and that they are prone to systematic biases, all of which may lead to disadvantageous choices. In short, consumers may make costly mistakes. Research has indeed documented that in several key consumer markets, including financial services, utilities and telecommunications, many consumers struggle to choose the best products for themselves. It is often argued that these markets involve ‘complex’ products. The obvious question that arises is whether consumer policy can be used to help them to make better choices when faced with complex products. Policies are more likely to be successful where they are informed by an accurate understanding of how real consumers make decisions between products. To provide evidence for consumer policy, PRICE Lab has developed a method for measuring the accuracy with which consumers make choices, using techniques adapted from the scientific study of human perception. The method allows researchers to measure how reliably consumers can distinguish a good deal from a bad one. A good deal is defined here as one where the product is more valuable than the price paid. In other words, it offers good value for money or, in the jargon of economics, offers the consumer a ‘surplus’. Conversely, a bad deal offers poor value for money, providing no (or a negative) surplus. PRICE Lab’s main experimental method, which we call the ‘Surplus Identification’ (S-ID) task, allows researchers to measure how accurately consumers can spot a surplus and whether they are prone to systematic biases. Most importantly, the S-ID task can be used to study how the accuracy of consumers’ decisions changes as the type of product changes. For the experiments we report here, samples of consumers arrived at the ESRI one at a time and spent approximately one hour doing the S-ID task with different kinds of products, which were displayed on a computer screen. They had to learn to judge the value of one or more products against prices and were then tested for accuracy. As well as people’s intrinsic motivation to do well when their performance on a task like this is tested, we provided an incentive: one in every ten consumers who attended PRICE Lab won a prize, based on their performance. Across a series of these experiments, we were able to test how the accuracy of consumers’ decisions was affected by the number and nature of the product’s characteristics, or ‘attributes’, which they had to take into account in order to distinguish good deals from bad ones. In other words, we were able to study what exactly makes for a ‘complex’ product, in the sense that consumers find it difficult to choose good deals.

FINDINGS
Overall, across all ten experiments described in this report, we found that consumers’ judgements of the value of products against prices were surprisingly inaccurate. Even when the product was simple, meaning that it consisted of just one clearly perceptible attribute (e.g. the product was worth more when it was larger), consumers required a surplus of around 16-26 per cent of the total price range in order to be able to judge accurately that a deal was a good one rather than a bad one. Put another way, when most people have to map a characteristic of a product onto a range of prices, they are able to distinguish at best between five and seven levels of value (e.g. five levels might be thought of as equivalent to ‘very bad’, ‘bad’, ‘average’, ‘good’, ‘very good’). Furthermore, we found that judgements of products against prices were not only imprecise, but systematically biased. Consumers generally overestimated what products at the top end of the range were worth and underestimated what products at the bottom end of the range were worth, typically by as much as 10-15 per cent and sometimes more. We then systematically increased the complexity of the products, first by adding more attributes, so that the consumers had to take into account, two, three, then four different characteristics of the product simultaneously. One product might be good on attribute A, not so good on attribute B and available at just above the xii | PRICE Lab: An Investigation of Consumers’ Capabilities with Complex Products average price; another might be very good on A, middling on B, but relatively expensive. Each time the consumer’s task was to judge whether the deal was good or bad. We would then add complexity by introducing attribute C, then attribute D, and so on. Thus, consumers had to negotiate multiple trade-offs. Performance deteriorated quite rapidly once multiple attributes were in play. Even the best performers could not integrate all of the product information efficiently – they became substantially more likely to make mistakes. Once people had to consider four product characteristics simultaneously, all of which contributed equally to the monetary value of the product, a surplus of more than half the price range was required for them to identify a good deal reliably. This was a fundamental finding of the present experiments: once consumers had to take into account more than two or three different factors simultaneously their ability to distinguish good and bad deals became strikingly imprecise. This finding therefore offered a clear answer to our primary research question: a product might be considered ‘complex’ once consumers must take into account more than two or three factors simultaneously in order to judge whether a deal is good or bad. Most of the experiments conducted after we obtained these strong initial findings were designed to test whether consumers could improve on this level of performance, perhaps for certain types of products or with sufficient practice, or whether the performance limits uncovered were likely to apply across many different types of product. An examination of individual differences revealed that some people were significantly better than others at judging good deals from bad ones. However the differences were not large in comparison to the overall effects recorded; everyone tested struggled once there were more than two or three product attributes to contend with. People with high levels of numeracy and educational attainment performed slightly better than those without, but the improvement was small. We also found that both the high level of imprecision and systematic bias were not reduced substantially by giving people substantial practice and opportunities to learn – any improvements were slow and incremental. A series of experiments was also designed to test whether consumers’ capability was different depending on the type of product attribute. In our initial experiments the characteristics of the products were all visual (e.g., size, fineness of texture, etc.). We then performed similar experiments where the relevant product information was supplied as numbers (e.g., percentages, amounts) or in categories (e.g., Type A, Rating D, Brand X), to see whether performance might improve. This question is important, as most financial and contractual information is supplied to consumers in a numeric or categorical form. The results showed clearly that the type of product information did not matter for the level of imprecision and bias in consumers’ decisions – the results were essentially the same whether the product attributes were visual, numeric or categorical. What continued to drive performance was how many characteristics the consumer had to judge simultaneously. Thus, our findings were not the result of people failing to perceive or take in information accurately. Rather, the limiting factor in consumers’ capability was how many different factors they had to weigh against each other at the same time. In most of our experiments the characteristics of the product and its monetary value were related by a one-to-one mapping; each extra unit of an attribute added the same amount of monetary value. In other words, the relationships were all linear. Because other findings in behavioural economics suggest that consumers might struggle more with non-linear relationships, we designed experiments to test them. For example, the monetary value of a product might increase more when the amount of one attribute moves from very low to low, than when it moves from high to very high. We found that this made no difference to either the imprecision or bias in consumers’ decisions provided that the relationship was monotonic (i.e. the direction of the relationship was consistent, so that more or less of the attribute always meant more or less monetary value respectively). When the relationship involved a turning point (i.e. more of the attribute meant higher monetary value but only up to a certain point, after which more of the attribute meant less value) consumers’ judgements were more imprecise still. Finally, we tested whether familiarity with the type of product improved performance. In most of the experiments we intentionally used products that were new to the experimental participants. This was done to ensure experimental control and so that we could monitor learning. In the final experiment reported here, we used two familiar products (Dublin houses and residential broadband packages) and tested whether consumers could distinguish good deals from bad deals any better among these familiar products than they could among products that they had never seen before, but which had the same number and type of attributes and price range. We found that consumers’ performance was the same for these familiar products as for unfamiliar ones. Again, what primarily determined the amount of imprecision and bias in consumers’ judgments was the number of attributes that they had to balance against each other, regardless of whether these were familiar or novel.

POLICY IMPLICATIONS
There is a menu of consumer polices designed to assist consumers in negotiating complex products. A review, including international examples, is given in the main body of the report. The primary aim is often to simplify the consumer’s task. Potential policies, versions of which already exist in various forms and which cover a spectrum of interventionist strength, might include: the provision and endorsement of independent, transparent price comparison websites and other choice engines (e.g. mobile applications, decision software); the provision of high quality independent consumer advice; ‘mandated simplification’, whereby regulations stipulate that providers must present product information in a simplified and standardised format specifically determined by regulation; and more strident interventions such as devising and enforcing prescriptive rules and regulations in relation to permissible product descriptions, product features or price structures. The present findings have implications for such policies. However, while the experimental findings have implications for policy, it needs to be borne in mind that the evidence supplied here is only one factor in determining whether any given intervention in markets is likely to be beneficial. The findings imply that consumers are likely to struggle to choose well in markets with products consisting of multiple important attributes that must all be factored in when making a choice. Interventions that reduce this kind of complexity for consumers may therefore be beneficial, but nothing in the present research addresses the potential costs of such interventions, or how providers are likely to respond to them. The findings are also general in nature and are intended to give insights into consumer choices across markets. There are likely to be additional factors specific to certain markets that need to be considered in any analysis of the costs and benefits of a potential policy change. Most importantly, the policy implications discussed here are not specific to Ireland or to any particular product market. Furthermore, they should not be read as criticisms of existing regulatory regimes, which already go to some lengths in assisting consumers to deal with complex products. Ireland currently has extensive regulations designed to protect consumers, both in general and in specific markets, descriptions of which can be found in Section 9.1 of the main report. Nevertheless, the experiments described here do offer relevant guidance for future policy designs. For instance, they imply that while policies that make it easier for consumers to switch providers may be necessary to encourage active consumers, they may not be sufficient, especially in markets where products are complex. In order for consumers to benefit, policies that help them to identify better deals reliably may also be required, given the scale of inaccuracy in consumers’ decisions that we record in this report when products have multiple important attributes. Where policies are designed to assist consumer decisions, the present findings imply quite severe limits in relation to the volume of information consumers can simultaneously take into account. Good impartial Executive Summary | xv consumer advice may limit the volume of information and focus on ensuring that the most important product attributes are recognised by consumers. The findings also have implications for the role of competition. While consumers may obtain substantial potential benefits from competition, their capabilities when faced with more complex products are likely to reduce such benefits. Pressure from competition requires sufficient numbers of consumers to spot and exploit better value offerings. Given our results, providers with larger market shares may face incentives to increase the complexity of products in an effort to dampen competitive pressure and generate more market power. Where marketing or pricing practices result in prices or attributes with multiple components, our findings imply that consumer choices are likely to become less accurate. Policymakers must of course be careful in determining whether such practices amount to legitimate innovations with potential consumer benefit. Yet there is a genuine danger that spurious complexity can be generated that confuses consumers and protects market power. The results described here provide backing for the promotion and/or provision by policymakers of high-quality independent choice engines, including but not limited to price comparison sites, especially in circumstances where the number of relevant product attributes is high. A longer discussion of the potential benefits and caveats associated with such policies is contained in the main body of the report. Mandated simplification policies are gaining in popularity internationally. Examples include limiting the number of tariffs a single energy company can offer or standardising health insurance products, both of which are designed to simplify the comparisons between prices and/or product attributes. The present research has some implications for what might make a good mandate. Consumer decisions are likely to be improved where a mandate brings to the consumer’s attention the most important product attributes at the point of decision. The present results offer guidance with respect to how many key attributes consumers are able simultaneously to trade off, with implications for the design of standardised disclosures. While bearing in mind the potential for imposing costs, the results also suggest benefits to compulsory ‘meta-attributes’ (such as APRs, energy ratings, total costs, etc.), which may help consumers to integrate otherwise separate sources of information.
FUTURE RESEARCH The experiments described here were designed to produce findings that generalise across multiple product markets. However, in addition to the results outlined in this report, the work has resulted in new experimental methods that can be applied to more specific consumer policy issues. This is possible because the methods generate experimental measures of the accuracy of consumers’ decision-making. As such, they can be adapted to assess the quality of consumers’ decisions in relation to specific products, pricing and marketing practices. Work is underway in PRICE Lab that applies these methods to issues in specific markets, including those for personal loans, energy and mobile phones.