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Claire Stewart: Today's LBI idea is to use marketing to help consumers simplify their decision-making process. Our guest today is Ying Zeng, an assistant professor of marketing and a Dean's Faculty Scholar at the Leeds School of Business. She is an expert in inconsistencies and biases in consumer decision-making, especially in digital marketing, strategic decisions, and consumption experience.

Thanks so much for joining us today, Ying.

Ying Zeng: Thank you, Claire, for inviting me to this podcast.

Stewart: Yeah, absolutely. So, how did your interest in consumer decision-making and behavior come about?

Zeng: So, there is an official answer and an unofficial answer to that question. The official answer is that consumer decision-making is extremely important for consumers, for business, and for policymakers. We know that there are many different types of business models. We have business-to-business, we have business-to-consumers, we have platforms connecting different parties together.

But ultimately, the demand is dependent on individual consumers, their decisions collectively. So, it is a very important ultimate channel for us to understand business, to understand demand and supply, to understand how this world of business is working. The unofficial answer is, so there is a joke in our field, meaning that we as consumer experts, we don't study artificial intelligence, we study human stupidity.

So, we are stupid consumers ourselves, and that's why we become interested in this topic. We want to understand why sometimes we overconsume, we buy things that we never use, and sometimes we underconsume. We miss the deals, we stuck in a poorly designed apartment for years without the motivation to upgrade it, even if we have the ability to do that.

In many different things, we make mistakes. So, we want to understand how these mistakes are made and how to mitigate them, how to prevent them.

Stewart: Awesome. So, one of your studies examined how we experience everyday chores and errands. What did you learn about how people feel during a task, especially as they get closer to completing it?

Zeng: This project actually started from a random conversation with my friend. You know, when we are toward the end of a semester, people start to celebrate to some extent. They say, "Great, you must be feeling relaxed more now. You're getting closer to the end." But I actually feel that I'm extremely exhausted when I'm toward the end of a semester, and I cannot say that.

People say, "How are you doing?" You can only say, "I'm good." You cannot say, "I'm exhausted." Right? So, why does that happen? I start to wonder. Is that because I did so many things, or is that because I'm toward the end of the semester? And then we realized that in this paper, there are a lot of different scenarios that are like this.

So, for a traveler, a commuter, when they are on the subway, the closer they are to the destination, the more tired they feel about this trip, even when they have completed the same absolute length of the trip. So, for two travelers, one has a 10-stop trip, the other has a 15-stop trip. At the eighth stop, the person with a shorter trip actually feels worse than the person who has a longer trip.

And then we find that this happens all the time. If you're doing regular workouts, for example, you probably notice that on the treadmill, if you have a 30-minute workout goal, the 25-minute mark is the worst, compared to if you have a 60-minute workout goal.

And we find that that's because people are actually not very sensitive to how much time you have spent on the treadmill, but how much percentage, what is the proportion of this task you have completed. And that's what's causing this exhaustion in this type of everyday chores and errands.

Stewart: Wow. So, do you have any tips of how to feel less drained when completing tasks and getting toward the end of a task?

Zeng: Yes, of course. So, for these types of mundane tasks, the easiest way is to simply combine them together. So, you know, there are controversies over whether we should combine all the chores together on one day, finish them, or if we should spread them out. Our research suggests that it is probably better to combine them together, so you only experience once this draining effect that's at the end of your last task.

Compared to if we spread them out, every time we complete these chores, we will feel this draining moment. So, that could be the easiest way possible.

Stewart: That's helpful to remember. That's good. So, you've also researched something we have all experience with, and that is online reviews. So, how did you approach studying that?

Zeng: That's what comes from my experience as a stupid consumer. I'm always trapped by those things that are very well-rated but with a very low price, and that's an extremely attractive combination to me. But when I buy them, I realize that, okay, its quality is fine, it's not that awful, and that's probably what earns its 4.9 stars.

But actually, it's not as good as what I would expect for something that's 4.9. So, that makes me start to wonder what happens with consumer reviews. Are they lying at all? Or are they somewhat truthful, but they are bad on some aspects? Or are they completely reflecting the quality? So, what's going on with consumer reviews?

And the more I study this, the more I find that online reviews are helpful, but you have to use them in a certain way. You have to recognize the biases behind them, and you have to think about what information they can actually provide, just like many things in our life.

Stewart: So, what did you find out about how people write and interpret ratings?

Zeng: Yeah, that's a great question. So, in two of my research projects, I find that people who write a review are heavily impacted by what's going on in their personal life, in what's going on in the specific reviewer's life. So, for example, if you're rating something on Amazon, and you probably also purchased that on Amazon, you will be heavily impacted by the norm you feel on Amazon.

Like you see every single product there is four-point-something. You never buy something that's three-point-something, and you rarely see something that's three-point-something. That means that you would probably also give a product a very high rating, even though, for example, 4.5 means extraordinary.

And if every product is extraordinary, there's no such thing as extraordinary. But if you're reading, for example, a book on Goodreads, you will notice that most books you see on Goodreads are two-point-something, three-point-something, or four-point-something. That means books have different qualities and people have different perceptions of them, and you will feel better when you give a book a three-star, for example, because you don't like it that much, but you don't hate it.

So, this type of norm heavily impacts how people express their attitudes and rate something. So, if you just take these ratings at their face value, you just think that four stars on Amazon is the same as four stars on Goodreads. That could heavily bias your decision. The other thing that I noticed that's super important for people when they rate something is the price. Why is that? It's because when I am the consumer, I pay something to get the product, and that pain of payment is very salient in my mind. I am the person who's spending that money. But for someone who's buying something, they won't realize that the rater actually thinks about the price when they rate this product.

They will only take that rating as if it's about the quality itself. There's nothing to do with the price. So, that means people are double-penalizing products that are high-priced. So, they think about, okay, the rating is only influenced by the quality, so it's not penalized with its high price.

And then I notice the high price, it means that I should discount it even more. And that is something people might make a mistake. But the mistake is mostly on the low-price product side. People would mistakenly believe that something that's low-price and high-rating is the best combination, which is the mistake that I mentioned earlier that I often make.

Now I realize this bias existing, I might favor products with a mediocre rating of, let say, 4.2, but it used to be a high-price product, and now it's at a discount. That could be the best combination compared to something that's extremely cheap but with extremely high ratings.

Stewart: Interesting. So, has this really changed the way that you shop and the way that you look at consumer reviews?

[Zeng: Yeah, of course. So, I'm now more expertised with consumer reviews. There are several tips I use. First, if there is a communication site or a review site, I use that site. I don't trust transaction sites that much now. So, if I choose a restaurant, I probably won't use, for example, OpenTable to choose that. I probably will use Google Maps.

If I choose a book, I probably won't just rely on the Amazon rating, and I probably will rely on the Goodreads rating. If I choose a movie, I probably won't use Fandango rating, just take it as it is. I probably would go to Rotten Tomatoes or IMDb for that. For products that do not have such type of open review sites, for example, if I'm going to buy a vacuum, I probably want to go to a third-party site like Consumer Reports to look at their reviews rather than relying on the ratings, simply on the ratings on Amazon.

And I also look at the review texts, which gives me more information. And I'm also aware of the price thing, which I mentioned earlier. So, it makes my decision become complicated but increases the quality of my decisions.

Stewart: Nice. So, you've become a super shopper, really, after all of this.

Zeng: A super and tired shopper, yes.

Stewart: Yeah, I believe it. How do you see AI impacting shopping decisions and consumer behavior?

Zeng: This is, I think, a perfect question to follow up from our earlier conversation. If you're very tired with shopping, you probably want to take shortcuts, and that's just human. One shortcut people take is using branding information, brands. People have brands that they trust, and they don't think about other things like price, like other consumer reviews, like the product specifications.

There are other shortcuts people use. For example, simply relying on ratings. That's another shortcut that starts when the reputation system establishes. Now we have another shortcut that we can also customize for our own needs, which is AI. So, if you are someone who cares, who has all these principles when you select a product, AI can be a tool to help you reduce these cognitive burdens.

And I can only speak about this at this current time period, because we do not know how AI will develop in the future and how that might become another shortcut that ultimately leads to bad decisions. For example, there's very recent research in our field showing that people start to use ChatGPT to help them make decisions for shopping, and they ask ChatGPT to help them compare the models, to compare different needs they have for a complicated product.

But right now, people are mostly relying on AI for complicated decisions, for products they are not familiar with. For example, I'm not super familiar with the different specifications for a computer. I probably will ask GPT to help me do that. But people are still heavily relying on search engines for simple products.

If I'm buying a dress, I probably want to just go to a search engine, just browse it, look for whatever fits what I like. Or if I'm buying some simple office supplies, search engines are still where I'm going. So, what I would like to summarize about AI's impact is, first, it's start to impact people's behavior, just like any other shortcuts people used to take.

And second, right now its impact is limited and more within the complicated shopping decisions domain. But in the future, they may become more customized. It might learn my preferences better, it might know me better, it might have more resources to help me simplify my decisions. That can become a very powerful tool, but it can also, meanwhile, become some problematic shortcuts, just like every other shortcut we used to take.

Stewart: Awesome. So, you provided some great information for consumers to be smarter, but for executives and marketers that are reading your research, what is the biggest misconception that businesses have about how consumers make decisions?

Zeng: One idea I really want to transmit from my own research is, do not overestimate how sophisticated your consumers are. Consumers are lazy. Consumers are not that intelligent. I am lazy. I am stupid. I am a consumer. So, for business and for marketers, the key part for us to design a successful product or to design something that consumers love is to help them simplify their decisions.

Make it obviously suitable for your target consumer. Do not hide the information. Do not assume they will simply infer it. Do not assume your consumer will read your 30-page, single-spaced product information. They won't. So, highlight the most important part for your consumer, help them simplify their decision, and make sure that your strongest comparative advantage is salient enough for consumers who only need to spend one second can understand.

That would be a great, very powerful and effective marketing tool for businesses to consider.

Stewart: Great. So, one of the other areas that you've researched is risk. So, what do you see as the connection between that and consumer behavior?

Zeng: Yeah. I would like to mention what makes me start to think about risk. So, if you think about this word, risk, people think about something negative. People think about losing money, for example. People think about worse health. People think about smoking. People think about taking risky activities. People think about riding a motorcycle without wearing a helmet, things like that. But when we think about real-world products that we describe as risky, by risky, we mean that it might bring people with benefit, whether it's hedonic or it's utilitarian, it's emotional, or it's functional, but it might add cost of something else, then things become different.

So, in my very early research on risk, I find that during COVID, for people who were severely impacted by COVID, they are more likely to take risks. They prefer risky things more. And it's weird because when you think about COVID, you probably think about fear. You think about staying home. You think about getting sick. Why would that be related to risk? Because risk is something that people tend to think about fear when thinking about risk. And then we find that that's because these people who were severely impacted, they're more bored, they're more restricted, and they really want some stimulating activities, something exciting.

So, risky things are actually something that tends to be exciting because of the uncertainty component associated with that and that potential reward. And then we can think about, in the marketplace, what are typical types of risky activities? A lot of entertainments are risky activity. Like skiing is actually a risky activity. And skydiving is another risky activity. Even for things like mystery boxes, Labubu, is also one type of, sort of, risky activity. You might just spend money buying something you hate. They're ugly. They're not something you really want. But people like that. It's the rewarding. It's that exciting component.

So, that's what we're trying to study, like, the exciting component of risky products, of products that are associated with risk, is actually very important for certain segments of our consumers. Consumers who are bored, consumers who are seeking stimulation, consumers who are looking for another lifestyle, who are stuck in mundane everyday activities and want to have some change.

Those consumers, risk is actually a good thing for them, and designing a product that has this component of risk, of uncertainty, of resolving an uncertainty, can be something important to our consumers.

Stewart: Awesome. So, before we let you go, what's currently piquing your interest when it comes to consumer behaviors or trends, personally or professionally?

Zeng: Yeah. So, I like to study two types of topics. One type of topic is something we call immortal. So, it's something that's deeply ingrained in human nature that lasts forever. It does not change with time, does not change with culture, does not change with context. And there are many things like this. So, one project I'm currently studying on is consumer attribution.

When there is a service failure, for example, who do you blame? Do you blame yourself? Do you blame the business? Do you blame someone else? Or do you think it just happens, you blame the luck? So, these types of topics are something what we call as immortal. There is a fundamental human principle underlying that, and that guides us in different types of consumer decisions and behaviors.

And the other type of research project that I find super interesting is what you describe as trends. So, I like to briefly discuss the three distinctions between fads, fashion, and classics. So, what I said "immortal" is something like classics. It is there forever. It's there since ancient Greeks, for example.

And a fad is something that has been super popular. Everybody talks about that, but it quickly decays. Nobody talks about it a year later, for example. Everyone can think of one example. There's actually a fun anecdote I have from a colleague who shares that they have this case competition every year for their business administration students.

What they find is every year there is a key trend. Everybody studies the same topic. But across different years, the topics change so much. So, in year one, everybody studies blockchain. In year two, everybody studied metaverse. But nobody studied blockchain for two or three or four years. So, that is what we call, as for example, fads that disappear very quickly.

That's not something that I like to study, but I like to study fashion, meaning that it's something popular for a couple of years or even a couple of decades. It's something used to become something cutting edge and then start to become the foundation of human society, and then it actually nurtures new things to come up.

So, reputation systems or consumer review systems used to be this type of fashion. When they first started, it was something new to everybody. And then they started to nurture this whole business of peer-to-peer business, this digital marketing business, all kinds of things. And now I think artificial intelligence is probably the next trend because it has all the features of what we call general-purpose technologies.

It has this feature of potentially nurturing new industries, potentially nurturing new ideas, and it has this feature of potentially having this feedback loop of reinforcing itself. So, I'm currently thinking about studying things that are either a fashion, now, I could be wrong, but I would judge this as fashion, or as a classic that has been lasting forever.

Stewart: Awesome. Well, I've loved speaking with you today, and I know that I will definitely be looking at consumer reviews differently and being a better shopper now, so I thank you so much for your time. This has been a fascinating conversation, and I really appreciate you joining us, so thank you so much, Ying.

Zeng: Thank you so much, Claire.

Stewart: Thank you again for listening to Leeds Business Insights. Make sure you're one of the first to hear every episode by subscribing to the show wherever you get your podcasts. The Leeds Business Insights Podcast is a production of the Leeds School of Business and produced by University FM. We'll see you next time.