”Content of the job is more important than wage”

“Debt reduction trumps financial growth”

“Life is more important than money”

All three above statements are sentenced I could well imagine someone utter in an intelligent discussion. All the statements have one other thing in common: they’re pretty much meaningless.

It’s clear that we can – and often do – make such statements. In itself, there’s nothing wrong about saying that A is more important than B. For example, “the math exam is more important than the history exam” is a perfectly legit way of relating your lack of interest in what happened in the 30 Years’ War. But when it comes to talking about what you want, and how you should distribute your resources, importance statements are meaningless without numbers.

The third case is perhaps the most common one. Presumably the idea is to say that we should never sacrifice human life to gain financially. Of course, that’s flat out wrong. Even if you agreed with that in principle, in practice you’re trading off human life for welfare all the time. When you go to work, you risk getting killed in an accident on the way, but have a chance of getting paid. Buying things from the grocery means someone has risked themselves picking, packing and producing the items – if you really valued their health, you’d grow your own potatoes. In healthcare, we recognize that some treatments are too expensive to offer – the money is better used for other welfare-increasing things, like building roads for instance. Life can be traded for welfare, ie. money.

The first case also seems clear in intent: you want to have a meaningful job, instead of a becoming a cubicle hamster for a faceless corporation, no matter the wage differential. However, it’s surely not true that meaning of the job is infinitely more important. Would you rather help the homeless for free, or be a hamster for 10 million per hour?

The problem with importance without numbers is that they are hinting at tradeoffs, but grossly misrepresenting what we’re willing to accept. The choice examples involve tradeoffs, and tradeoffs are impossible if one goal is always more important than another. This causes an infinite tradeoff rate, causing you to favor a teeny-tiny probability of loss of life over the GDP of the whole world. Doesn’t sound too reasonable, does it? In fact, Keeney (1992, p.147) calls the lack of attention to range “the most common critical mistake”.

Naturally, we can always say that the examples are ridiculous, surely no one is thinking about such tradeoffs when they say life is more important than money, surely they’re thinking in terms of “sensible situations”. In a sense, I agree. Unfortunately, one’s ridiculous example is another’s plausible one. If you don’t say anything about the range of life and money that you’re talking about, I can’t know what you’re trying to say. It’s just much easier to say it explicitly: life is more important than money, for amounts smaller than 1000 euros, say.

Even this gets us into problems, because now if I originally have a choice problem involving 3000 euros and chance of death, you’d be willing to make some kind of tradeoff. But if I subdivide the issue into three problems, now suddenly human life always wins. If you think about utility functions, you can see how this can quickly become a problem. But the situation is still better than not having any ranges at all. Even better would be to assign a tradeoff ration that’s high but not infinite. 

A concept that comes up pretty often in decision research is the one of aspiration levels. They are meant to reflect some kind of preference levels, meaning levels of attributes that the decision maker would like to have in an ideal situation. The idea behind the concept is that such levels can guide both the decision maker and the analyst to look for portions of the alternative space that’s relevant – better to search close to the optimal levels.

Now that’s nice and all, but for practical purposes I think an inverse concept is perhaps even more useful. By inverse I mean rejection levels. Or, as I like to call them, what-the-hell-I’m-absolutely-not-willing-to-accept-that levels. The idea is simple enough: rejection levels signify the worst attribute levels you’re willing to accept. A value worse than that means you’ll discard it immediately and look elsewhere.

The benefit is that if you have many alternatives, rejection levels can be used to make the search space smaller very fast. Imagine you’re buying a bike, and there are two criteria: cost and quality. You probably have some aspiration levels – the ideal bike. That’s reflected in the upper left corner (low price, terrific quality). But that only tells us the portion of the search space with the best alternative, but unfortunately very likely a non-existing one. Looking at the picture below, it’s clear there’s still a lot of search space remaining.

The trick with rejection levels is that you need to set them before looking at the options. A bike can be bought without issues, but any more complex decision and trouble arises. For example, house buying is of considerable difficulty in itself. And what marketers know is that if the house makes a good first impression, you’re likely to start coming up with reasons for why that house was just so lovely, convenient, and so on. As a result, people tend to exceed their budget after falling in heavy with a single house.

To avoid this, rejection levels are a great technique. If the price goes above the rejection level, you can confidently say thanks, but no thanks and just move on. By making the rejection decisions with a rule that you’ve committed to beforehand is much, much easier than mulling over each and every option you come across.

So, back in September I wrote about one basic bias: context-dependent preferences. At its core, context-dependent preferences mean that consumer choices are based on relative value, instead of absolute value. So, instead of assessing which option is best on its own, we tend to look at which option is the best, relative to others in the choice set. With strategic selection of the items, a marketer can thus heavily drive us to choose a middle option that sits between a cheap and an expensive one. This is known as the compromise effect.

Now, Simonson is saying that the compromise effect isn’t real anymore! I picked up his claim from his talk at TEDxBayArea. Here’s the video:

So, Simonson has replicated with Taly Reich his previous experiment that showed the existence of the compromise effect. He shows that the new study was pretty similar to the old one, and that the compromise effect just wasn’t there. Unfortunately, since the study hasn’t been published yet, we just have to take Simonson’s word of this. But let’s do that, and see what the implications are.

His main point is that the compromise effect doesn’t surface because modern technology helps us estimate absolute value instead of relative value. Twenty years ago, we would proxy quality with attributes such as brand, country of production and so on. These days, we have access to a host of online services that look at the product quality. Some of them directly assess products, while others provide just customer reviews. Irrespective of the way of assessment, both are pretty decent ways of assessing quality.

So what does it mean? Well, Simonson comes up with a list of commonly believed statements about marketing that he proceeds to debunk:

1.       A company’s brand is more important today than it has ever been

Quite a few people say that precisely because there’s so much information out there, branding is even more important today. Because of information overload, consumers can either process all the information, or ignore the information and rely on brands. However, Simonson argues that we can combine the approaches: quickly glance at reviews to assess quality. Brands will still exist – for example as status markers – but they will not be effective proxies for quality.

2.       Nurturing customer loyalty is the best investment

Customer loyalty is usually thought to be a sound investment. Satisfied customers will buy your products again, and thus loyalty will act as a barrier against competitor. Simonson thinks this is less likely to be true now. He claims that each product is evaluated on its own: he’s not going to buy a Toyota just because he liked the previous car. I think the example is correct, but the lesson’s not. Sure, when you buy a big pure product, you’ll evaluate the attributes with care. But with smaller purchases, brand surely matter. I seem unable to find the paper, but I remember reading that when buying groceries, customers tend to go for the products they usually buy (classic System 1 way of action – status quo).

3.       Market research can predict what consumers will want

Simonson says that since our choices are these days driven much by social media and we rely on opinions of others, then market research should focus on that part, instead of looking at wants and preferences today to predict the future. Simonson argues that the prior wants are really bad predictors – what matters are the sentiments in the social environment.

All in all, I think Simonsons ideas are pretty thought-provoking. There’s a lot riding on the replication failure of just one experiment, which seems a pretty shaky justification for a new theory. However, it is just one TED Talk, so I hope there’s more to it. Apparently, Simonson has also written a book about this. Well, that’s one more book for my pile of books to read...

You wander around at the store and see a nice looking pair of speakers. You plug in you iPhone and test them out, rocking it out to your favorite tunes. The speakers are very enticing already, but you decide to test out the next, slightly more expensive set just to be sure. Comparing the sounds, the more expensive set sounds just so much clearer, with better bass punch, too… Oh, it’s just so much better! Walking out from the store with a pair of speakers that are way better than your needs, you’ve just exhibited a prime example of context-dependent preferences.

In its simplicity, this bias may sound like an old truth. Sure, our preferences are changed by the context, so what? Unfortunately, in its simplicity lies the problem: this bias has the potential to affect us in almost any situation involving comparisons. And in the modern information era - with comparisons just a few taps away – well, that’s just about any situation. So what’s the bias? To be concise, the point is that choices are affected by changing the choice set, for example by adding new irrelevant alternatives. In effect, this can mean than whereas you this time preferred the high-grade speakers, adding a third middle option might have pushed you to choose the most cheapest, lowest quality ones instead. I’ll explain the theory with the help of a few images, borrowed from Tversky’s and Simonson’s paper.

If you look at the figure above, it shows three products that are quite different. Product Z is high in quality (attribute 2) but unattractive due to high price (ie. low on “affordability”, attribute 1). Product X, on the other hand, is very cheap but low quality. Product Y is somewhere in between.

The worrying part in the context-dependency is that our choices between options can be largely influenced by adding or removing options. For example, if we start with products X and Z and then add Y, by strategically placing it our choices can be heavily influenced. If Y is placed like in the next figure, a large proportion of decision makers will tend to switch to preferring Z, despite preferring X when they just had a choice between X and Z. Let’s look at a figure that shows this better.

The reason for the bias is that quality (attribute 2) now seems much more important after seeing that Y has a lot of that, too. X, on the other hand, is still cheap but looks much worse in terms of quality. After all, you don't want to get the lowest quality option. Depending on the setup, this will either lead to picking Y (which is not a bias, since you couldn't choose that initially) or picking X (which is, if you preferred Z initially). If you want to see the equations that clarify how the placement logic works, they are in the Tversky and Simonson’s paper. In addition, the same effect with a different example is very nicely explained here in Dan Ariely's lecture.

The gist of the issue is this: context-dependency means that with some set of options, we would choose X over Z, whereas a change in the option set – for example adding Y – may nudge us to choose Z instead. What you see influences you heavily.

So what’s the problem in preferring X in some situation and Z in another? Well, the problem is twofold. First of all, if our choices are affected by options we don’t even pick in the end – so they should be irrelevant – it can be argued that our sense of what we actually want is problematically limited. Admittedly, this is a big concern in its own right. A bigger issue is the fact that often we don’t get to pick the options we see. What this means is that our choices can be influenced by marketers and other people who have the power to set up the choice situation.

Thankfully, I think there’s a remedy. Contextual choice works in both ways, so you can use it to your advantage, too. When considering what you’d prefer, you can play out the situation by creating different alternatives – even irrelevant ones –and reconsider your choice. This kind of thinking will not only make you less susceptible to choosing on a whim as you consider things more carefully, thinking about other alternatives may give ideas on what’s actually possible in the situation and what you actually value.