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Do You Think Your Decision to Buy Was Rational?

Do You Think Your Decision to Buy Was Rational?

Rohini Daraboina and Ripinka Patil

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Journal of Marketing Research Scholarly Insights are produced in partnership with the AMA Doctoral Students SIG – a shared interest network for Marketing PhD students across the world.

Imagine your friend suggests that the latest iWatch is a great purchase that you should consider. When you visit the store to purchase it, what questions do you think you will ask the store associate?  Will you ask about the product features?  Can you be influenced to look for more positive or more negative information based on the prior information you received? How can marketers use the information that they provide to consumers to their advantage? These questions served as an inspiration for the authors Kinshuk Jerath and Qitian Ren for their article “Consumer Rational (In)Attention to Favorable and Unfavorable Product Information, and Firm Information Design.”

Consumer big data provides marketers with information about every touchpoint in a consumer’s journey, including the feedback after the actual purchase. Using artificial intelligence, marketers conduct multiple analyses to provide targeted information to consumers regarding various facts about the product, like its pricing, attributes, and other information that can enable a consumer to make an effective decision. Marketers also have the responsibility of providing factual yet persuasive information that results in a beneficial transaction to both consumers and the firms. The authors have found that strategically placing the information in ways that resonate with consumers’ own beliefs, such that it confirms both the positive and negative information they have about a product, may result in more purchases. Contrary to intuitive belief, the authors suggest that providing negative information about the product along with its positives thus becomes advantageous to the firms. The authors build a mathematical model that illustrates the benefits of providing these two types of information for both marketers and consumers.


The authors have found that strategically placing the information in ways that resonate with consumers’ own beliefs, such that it confirms both the positive and negative information they have about a product, may result in more purchases.

The authors construct their framework based on “rational inattention theory,” which states that when information processing is costly, consumers optimally process only a part of it. Using this as the theoretical basis for the model, the authors provide a mathematical solution that optimizes the consumers’ attention allocation toward both favorable and unfavorable product information. Research in psychology has found that people tend to focus on information that affirms their beliefs (confirmation bias), and the authors show that this may occur for consumers when information processing is costly. Also, the authors show that marketers may benefit from both favorable and unfavorable product information, challenging the intuition that sellers cannot profit from negative information of the product. The negative information becomes essential to consumers especially when deciding the fit of the product to their needs, and if a sufficient amount of negative information is not available, then consumers may not even start their search process.

Q: The application of mathematical modeling using confirmation bias is very interesting. What aspects of the modeling did you enjoy the most? Why?

A: We had an open-ended research question that motivated us. We wanted to understand what information consumers seek when they are making purchase decisions. I think the enjoyable part was the emergence of the phenomenon known as confirmation bias as the result of optimal consumer information processing behavior. This confirmation bias can be a reason why the firm should provide unfavorable information about the product: if you as a consumer know that the firm gives only positive information and will never give me any negatives about the product, you are likely to feel that you will not be able to make a confident decision using this information. If you feel that the information given is not going to help you make a decision, you might not search for any information at all. In addition, if you don’t search for information, you will not be confident about buying the product. Therefore, the availability of negative or unfavorable information can induce purchases. 

Q: What types of websites in your opinion would benefit from the information design? Are there any websites that are exempt from this framework? Was there any particular website you were thinking of when developing this research?

A: The framework would be applicable to most e-commerce websites.  When consumers have a product in mind, they seek information. They can visit e-commerce websites like Amazon, where they can find the product ratings and can sort by the star rating. When you click on the 5-star link you will see all the 5-star reviews, or you click on the one-star link, and you see all the one-star reviews. I was doing the same to see what unfavorable information was there on Amazon. Essentially, e-commerce websites like Amazon were used as a frame of reference where primarily information gathering is important. However, if it is a discussion forum, where the objective of the website or the person who runs the forum is just to provide information and it is not easy to sort this information as positive or negative, then this model is less relevant. Some examples include Wikipedia or Quora. 

Q: The current framework studies many interesting concepts like confirmation bias, attention allocation, the valence of information. What would you say were some of the challenges you faced while developing this research?

A: There were many challenges. We wanted a strong theoretical foundation that would be supported by data. One reason I like this paper is that it starts off with the idea that consumers are rational, but it ends up showing that they can do things that might appear irrational, like confirmatory search or confirmation bias. Most people know and understand that consumers are not fully rational, right? If you take a rational consumer, they incur a reasonable cost, like the cost of thinking or the cost of processing information, then you can see the behavior as predicted by our framework. This action is essentially rational but appears irrational. Putting it all together in a framework that is theoretically solid, intuitive, and yet technically solvable was a challenge, but it was rewarding.

Q: How would you think information design would change with respect to using AI devices. What are some of the aspects to think about in this scenario?

A: It depends on how it is used. One aspect is that you can use AI systems on the fly. I think AI can cut both ways. For example, a person could be looking at certain information and the AI  makes suggestions which is the next best piece of information, helping the consumer make a good decision. However, you could also have  it the other way around where the consumer has seen certain information and AI gives them a different piece of information or makes it easier to search, increasing the chance that they end up buying the product. AI is a big tool that firms can use for consumers’ benefit. In order to be used for consumers’ rather than just for the firms’ benefit, there must be some regulations around that.

Q: Visuals and graphics form a large portion of website information. What are your thoughts about including visual information? How would this change the framework?

A: Visuals can really help with attributes that otherwise can be difficult to understand. Think of a car. Visually I can decide, I like red more than blue. Visuals can help a lot in conveying information when it is about softer match attributes or information on horizontal attributes. Information on vertical attributes is often information that can be digitally conveyed well in text or in some other numerical format. Visual information is a very good complement to textual information. Even complicated information can be given visually to make it is easier to understand. Sometimes it can be “in place of” textual information and sometimes it can be “complementary.”

Q. We were also curious to know how marketers can avoid negative perceptions arising from information management.

A: This is a big debate going on in privacy circles, which is all about information. Consumers are worried that there is a lot of information that marketers have. It’s a very important issue and it is a matter of trust. I trust some websites more than others. It’s about reputation. Coming back to this paper and talking about favorable and unfavorable information, there should be some of both. First of all, as a marketer, you should be giving different kinds of information and not make it too difficult to understand or find information. This also helps with reducing negative perceptions. Over time a firm will build the reputation of being fair. Marketers should not make finding unfavorable information especially hard. They can always highlight the positive things, but I think marketers should make unfavorable information readily available as well.

Read the full article:

Jerath Kinshuk, and Qitian Ren (2021), “Consumer Rational (In)Attention to Favorable and Unfavorable Product Information, and Firm Information Design,” Journal of Marketing Research. 58 (2), 343–62. doi:10.1177/0022243720977830

Rohini Daraboina is a doctoral student in marketing at University of Memphis.

Ripinka Patil is a doctoral student in marketing at Louisiana State University, USA.