Neuroeconomics and Shopping: Don’t Ask the Person, Ask the Brain

There’s a saying in neuroscience: “Don’t ask the person, ask the brain!” What does this mean in practice? And how does it affect the way we shop? Colin Camerer, a behavioral economist at the California Institute of Technology (Caltech), dives into his research on this question.

“Hypothetical bias” (AKA cheap talk) is the difference between what people SAY they'll do and what they ACTUALLY do. For example, in a survey, 70% of people might say they'll buy a product—even if only 45% actually do.

Camerer and his colleagues use brain imaging and eye-tracking to account for hypothetical bias and predict real-life shopping behavior.

This video is based on the following papers:

Differences in Behavior and Brain Activity During Hypothetical and Real Choices by Colin Camerer and Dean Mobbs. https://pubmed.ncbi.nlm.nih.gov/27979604/

When the eyes say buy: visual fixations during hypothetical consumer choice improve prediction of actual purchases by Taisuke Imai, Min Jeong Kang & Colin F. Camerer. https://link.springer.com/article/10.1007/s40881-019-00071-3

More of Colin Camerer’s work: https://camerergroup.caltech.edu/

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- [Colin] We have a saying
in neuroscience sometimes:

"Don't ask the person,
ask the brain,"

because the brain activity
may be something that's less

than fully conscious.

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My research is about behavioral
economics and neuroeconomics.

And behavioral economics is using
ideas from psychology

and other social sciences
to make economics

a little bit more lifelike
and fit human behavior.

The neuroeconomics part
is that we actually try to see

what's happening in the brain

when people are making
economic decisions.

Hypothetical bias is a term
for when you ask somebody

whether they're going to something,
but there's no actual consequences,

like a lot of surveys:
"Are you going to vote?"

"Will you buy
this new product we have?"

You tend to get a kind
of upward "yes" bias.

People are more likely to say,
"Yeah, I'd think I'd buy it,"

or, "Oh yeah, I'm planning to vote."

The hypothetical bias can
be pretty high,

and it can be also retrospective.

So if you ask people did they vote,

70% say yes and really
the answer was 45%.

One application is
in things like marketing.

A lot of new products fail,
and one reason they fail

is because when
they test market it,

a lot of people said,
"Yes, I'd buy it,"

who weren't going to buy it.

One thing that people
have been chasing

in different fields in economics
and psychology is

how can we measure the size
of this bias and adjust for it.

So that if 70% of the people say
they're going to buy a new product,

we know that
the real number is 45%.

We did a couple of studies using
brain imaging to say

is there a kind of signature
in the brain of when

somebody says,
"Yes, I would buy it,"

but when they really have
to choose, they say no.

So we showed them pictures
of different goods,

and the first part
of the experiment, we asked them,

"Would you pay $27
for this backpack, yes or no?"

That's the hypothetical part,
and then we kind of surprised them

when they come out of the scanner
and we say to them,

"Oh by the way, now we're going
to actually have you decide

to spend money
so we're going to give you $50."

If you want to buy the backpack
for $27, we're going to take it

out of your 50, so that now
they have to make real decisions,

and then we study
in the brain imaging,

could we tell what areas
were saying yes,

but actually would later say no
compared to the areas that said,

"Yes, I think I'll buy it,"
and, yes, they really did buy it.

And we found both more activity
in certain regions associated

with valuation and then activity
in different regions,

which were somewhat predictive
of when a yes was going to turn

into, "Well, not really."

In some other studies
on hypothetical bias,

we used eye tracking,
which is a computerized way

of seeing what you're looking at
for how long.

It also measures pupil dilation.

When you're aroused
by something that you like,

or possibly you're scared,
the pupil dilates a little bit.

So we used that method
and then another method

using mouse movements.

And so we found
that the mouse tracking

and the eye tracking
actually could give us an idea

of when people would say, "Yes,
I'm going to buy this product,"

but then they really didn't
when they had skin in the game

and had to buy it.

The quicker a person moves a mouse
to a box to click on something,

the more they like it.

It's like a fast trajectory,
"I really like this."

A slow meandering trajectory is,
"Well, I don't know. I'm not sure."

The motor activity in the mouse is
actually an index in economic value

as well as some other things,
like indecision.

We live in a kind of golden age
of social science

in which we can measure things
in lots and lots of different ways.

So one thing we've just begun

that I think it's going
to be really, really fun

is in order to study habit
and a bunch of other things.

We bought a smart vending machine,
and a smart vending machine

is basically a vending machine
in the back

and a giant iPad in the front.

So you could program the iPad
to show whatever you want.

For example, if somebody buys
habitually and you raise the price

by a few percent,
do they just ignore that

because they're not
even looking at the price?

Eventually, we'd like also
to be able to use webcam cameras

to record so when I say
somebody is not looking at the price,

I really mean they
are not looking at the price

because the camera looked
at where their eyes were looking.

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