Jacob Gersen & Joel Steckel, Harvard Law & NYU Stern,
Conference Introduction
Steckel gave a talk on dilution years ago and RT tore him
apart (sorry!); since then, he’s done work with Chris Sprigman to answer some
of the Qs I raised and I was right (not sorry!). Has stayed interested in legal applications
of marketing theory.
Saul Levmore, Chicago Law, Piece Problems: Component
Valuation in Marketing and in Patent and Tort Law
Marketing literature is more interesting than legal literature
here. We have analogous problems in negligence:
if 3 people jointly cause harm, how do you value the harm of each? For patent infringement: how important to the
value of the overall product is one ingredient that was found to infringe? It’s a more interesting problem than it looks
b/c of worries about over- and underdeterrence. Or a case in which someone
patents playing a song on each floor of a parking garage so they can remember
which floor they’re on: if they don’t increase the cost of parking after
implementing this, how do you figure out what the damages are? [He thinks costs saved in not helping people
find their cars.]
Paper discusses how some solutions in some areas transfer
well, and others don’t. B/c the
contribution to the joint tort car accident is a one-off, it may not transfer
well. But valuation is a general problem: figuring out how valuable a third baseman
is to a particular team is actually the same problem, b/c a teammate might be
more or less valuable depending on who else is on the team. The underlying relationship may not be
linear. Our task: we should look to
other fields to see how they do or could solve the problem. Though stresses that doesn’t mean the
solutions elsewhere work there, or would work here.
Q: how do you think about heterogeneity of preferences?
A: in some settings we don’t care: we’re trying to evaluate
a market solution. In others, he hopes it’s not a serious problem b/c mostly we
can look to market solutions or ask individual people (surveying). One possibility: ask people what it was about
the product they like, or ask them to pick among products. People may not be
able to name what they like, but that’s a signal it might not be
important. But he doesn’t yet know what
to do with what happens if only 4 of 50 mention a feature is important to them;
that might help convince a court that it’s not important.
Q: conjoint analysis could be meaningless where other
measurements of damage are better. If you have a broken fridge in a house it
could knock $4000 off the value of the house—but if it can be fixed for $50 that’s
what should happen instead.
A: agrees.
Q: reasonable consumer concept. Good marketers think
precisely the opposite: they segment markets, then go after a segment. The whole
point is the heterogeneity. Groups do
have different valuations for different aspects of products.
A: there’s some doubt, but it’s not as silly as you make it
sound. General approach is to assume that law or the market is aimed at the
reasonable/average consumer; if you know you’re not normal, you should speak
up. Other areas of law think that law
should pick extreme solutions, forcing information out of people who are “normal”—depends
on the costs and benefits of revelation.
Sometimes you might pretend to be normal to avoid the costs of valuation
(e.g., you cut I pick). Usually law is unsympathetic to the non-average person,
e.g., a nuisance claim by a person who can’t stand music and lives near a
church. Law is in part sensitive to the
probability of fraud here.
Q: often sees calculations of actual price compared to
but-for price—but what is the but-for price?
Is it a price that would’ve kept the same market share? A price that would reflect a Nash equilibrium
of a new market without the feature b/c competitors would also have reacted to
the absence of the feature? A price equivalent to average consumer’s WTP for
that attribute/its absence?
A: Law & econ answer: paper talks about this and he
thinks there’s no single right answer.
B2B transactions would be very different from consumers. General reaction: many ways to do it. He wants to identify several different
methods and not tell people in advance which will be used; that prevents
strategic behavior. Uncertainty is a valuable part of the system though we make
believe we’re committed to treating like cases alike.
Q: what happens when it’s not 6 elements but 1000, as in a
cellphone? Then when you do the conjoint analysis it’s down to 6, distorting
the results.
A: when it’s 1000, the chance I could build the cellphone
without it is much greater, so the solution should be: if I’d known the problem
upfront, what would have been my cost to avoid it? That would be the best way
to go about measuring those damages—the beginning rather than the end
consumer. That might also be true when
there are only 3 elements, but it’s more likely w/1000.
Peter Golder, Aaron Yeater, & Mike Schreck, Dartmouth
College, Analysis Group, & Analysis Group, Assessing Trademark Strength
without Surveys
Secondary meaning: in search of a more rigorous way to deal
with the qualitative aspects of an inquiry. Law makes claims about how
consumers perceive product designs that have implications for measurement. Secondary
meaning: “in the minds of the public, the primary significance is to identify
the source of the product rather than the product itself.” Considers evidence that product features were
intended to indicate source and that the firm succeeded in doing this. It’s not just that the design needs to be recognizable
but that it signal the specific purpose of identifying source, and that implies
an intentionality that can be assessed. Wal-Mart: specific assertion about
consumer behavior: predisposition to equate a product design feature with a
source doesn’t exist. The SCt didn’t undertake extensive empirical analysis to
arrive at that conclusion, but it is the rule.
Barriers to secondary meaning: primary meaning of product
design features is to provide functional or aesthetic/ornamental elements.
Extent of advertising for functional benefits of features. Extent of
marketplace crowding and noise with historical or current uses by
competitors/third parties. Duration of existence in market. Inconsistent use of product design features
in the market. Documentary/archival
evidence can be important to these elements.
What else?
RT: I’d add: what else is in use on the product to indicate
source. European concept of the limping mark that is recognized as going with,
e.g., a Kit Kat, but never used to pick candy. Response: in some ways that’s
about materiality. [I agree!]
Comment: visibility/lack of visibility: consumers have
easier/harder times perceiving certain things as marks. Identifiers inside a jacket versus inside
(including observability at the time of purchase, so a standard label on a
jacket may be doing source identification work). How do consumers make categories? If you’re categorizing “birds,” hollow bones
are perfectly predictive but not observable, so that’s not how ordinary people
implement the category “birds.” [I really
like use of category theory though I think we’re still, as here, working out its
implications.]
Standard actions to create and maintain secondary meaning: Look
for internal planning documents about intent to make features source identifying;
look for documents w/clear communication objectives for attempting to establish
secondary meaning and measures progress; company carries out planned
communication (e.g., look for ads); advertising “famous,” “iconic,” “exclusive,”
“unique,” “signature”; aggressively policing asserted marks to protect
exclusivity.
Qs? [Also interestingly,
this framework would be consistent with
Mark Lemley’s
argument that having—and thus allowing/not policing against—parodies should
be a requirement for fame, which would turn into media coverage rather than
competition.]
RT: This is a legal question: the doctrine right now
requires none of this, because the theory is always if there is consumer
confusion then there is something protectable.
So you can have all this and it won’t cover the waterfront unless courts
also say that its absence is dispositive.
There are cases/proceedings finding protection without any of these
things, e.g., the TTAB saying that the University of Wisconsin can fail to
police/“impliedly license” its marks for 70 years and then (re)claim its TM
rights.
Comment: but perhaps it’s just implausible that this creation
of secondary meaning will really happen without the marketers picking up on it
and talking about it internally so there will be documentation.
Marketplace outcomes related to secondary meaning: Complement
to surveys: media provide evidence of success or failure of calling out features
as source identifying. Traditional/social media. Company websites (including past versions).
Online search behavior—if they are source identifiers, consumers should be
trying to search by them at least to some degree [which raises the limping mark
issue again]. Online reviews. % of sales w/product design features. Company
monitors and documents progress towards achieving communication objectives related
to creating or maintaining secondary meaning.
[I like the suggestion, which I’m not sure has shown up in the cases,
that advertising functional features has a separate impact on secondary meaning—it’s
not just that it indicates
functionality; it also tells consumers that they shouldn’t rely on the touted
feature to indicate source.]
The law on what’s required for secondary meaning varies by
circuit. [They categorized intentional
copying by D as an “outcome” but that doesn’t fit in their framework at all. The
missing concept: functionality—if there are good noninfringing reasons to copy,
then copying tells us nothing about secondary meaning. That factor shouldn’t be
in the legal tests, at least without requiring intentional efforts to confuse
in particular and not just to copy, and their framework helps explain why.] If you can luck into secondary meaning, why
would courts care about “look for” advertising?
Cass Sunstein, Harvard Law School, Popcorn: Mandatory
Information Disclosure:
How to value the benefits of information? Pervasive unmet
challenge in policy all over. Principal
focus is on regulatory agencies, but courts and private sector entities are also
trying to value info. Toy/discussion
framework: people might want information for instrumental value—they can know
whether to buy a product, get health care, change their lives. Our primary
approach in the past. There’s also hedonic value: information might make you
happy or sad, and people might be willing to pay to get information that makes
them happy, or willing to pay to avoid information that makes them sad. Cognitive
value: learning may be something that people value. Maybe it’s just curiosity—how
far from the earth to the moon? Or maybe it will reinforce their model of the
world, or maybe it’s intriguing if it undermines their model of the world. Sign issue: the valence of instrumental,
hedonic, cognitive value may be positive or negative. Learning your client is guilty may have
negative value.
Recent data: knowledge is not always preferred. Mesolimbic
reward circuitry selectively treats the opportunity to gain knowledge about
favorable but not favorable outcomes as a reward to be approached. WTP to
receive or avoid knowledge was tied to participants’ expectations about whether
info would be positive or negative. Roughly
1/3 in trials chose ignorance.
Asking consumers whether they’d want to know: if they’ll get
Alzheimer’s, whether their partner cheats, year of death, number of calories,
whether there’s heaven (slightly lower percent wants to know whether there’s
hell), predisposition to get cancer. Alzheimer’s:
47% want to know, $107 WTP (average; median is significantly lower). Cancer:
$115, 58%. Spouse cheats: 57%, $121;
Death: 27%, $154; calories, 43%, $49 (annually, contingent on wanting to know);
weekly cost of appliance operation: 60%, $44.
Safety ratings of tires: 67%, GMO, 60% $101, conflict minerals 55, $109,
Online performance of airlines, 57%, $105, GHG emissions from car, 57%, $110. Some
would pay not to receive calorie info, apparently for hedonic reasons.
On yes/no, a lot of heterogeneity out there. Usually around
55-65% even want to know, for typical disclosures. Two categories of not
wanting to know: sometimes it’s bad news, and many people don’t want bad news;
sometimes it is who cares. WTP numbers vary and are usually pretty low.
There are a lot of labels out there: calorie, fuel economy,
energy efficiency, conflict minerals, graphic warnings, country of origin, greenhouse
gass, nutrition, dolphin-safe tuna.
Doing CBA: Four approaches. (1) Benefits not feasibly quantifiable,
so silence is golden (fuel economy labels, conflict minerals). Common but he hates it. Q re actual behavior v. expressed WTP: there’s
limited evidence about this, but people who use calorie labels are likely to
have high self-control whereas people who don’t want calorie labels don’t have
high-self control.
Observation: WTP of those who want to know when they’ll die
is higher even though the percentage is low—preference intensity varies. Payment willingness might be about how likely
it is you’ll get the information some other way.
Comment: hedonic value of information may be one-time
whereas cognitive is persistent.
A: Hedonic damage of knowing the year you will die might be
long-term. More generally, the toy model
here uses a rational actor model, but that’s not complete. People don’t want exposure to info inconsistent
with their political beliefs. But on average people are mistaken in hedonic
forecasting: they aren’t as unhappy with getting inconsistent info as they
thought they’d be, in intensity and duration. Might be present bias or failure
to forecast adaptation.
Q: why ask such self-directed questions? A lot of policy Qs
will be: do you want to know how many people will die in our next war? You might not be WTP to know the capital of
New Zealand, but be WTP for everyone in the country to know that.
A: our labeling Qs are asking about whether you benefit from
a label.
Q: but if you asked “do you want your kids to know the
calories in their food,” the answer might be very different.
A: is that the right Q for info disclosure benefits?
Q: better than saying “do you want to know.”
A: you might want to know the benefits your children get
from that.
Q: research on organizations suggests organizations may have
special difficulties processing information they’re not set up to receive.
Some discussion about the “year you’ll die” question: did
they believe it? Did they think they could “fight” it once they knew? Sunstein
thinks the survey had an implicit “work with me here” message and that people
got it. In Europe, Diet Pepsi is Pepsi
Max—Diet Pepsi was punitive, “good for me.”
That maps onto a lot of an actual driver of responses.
He thinks the data quality of MTurk varies from excellent to
pretty good—if you compare results to nationally representative surveys, they’re
usually pretty close—he wouldn’t expect a huge variation though some percentage
variation wouldn’t be surprising.
Commenters: one had really bad MTurk experience; another has
had varying experiences. Depends on the kinds of Q you ask; these Qs were
interesting and meaningful and some marketing Qs would be less so. Some evidence that MTurkers in some parts of
the world sit in the same rooms and consult on answers.
Q about relationship of answers to how optimistic people are
overall: e.g., date of your child’s death (he thinks learning it would always
be painful, though I don’t know—2115 might be a pretty impressive answer,
albeit an unlikely one). Optimism bias, hedonic
forecasting error, illusion of control—distorting factors. Magnitude of effect
depends on Q.
For policy analysis, we’re trying to look at end states:
e.g., for energy efficiency labels, how much would society gain in reduced
emissions/particulate matter. That doesn’t capture all of the relevant values
if people are made sad by the information.
Got interested in that when calorie labeling was extended to theaters
and he got the response “you ruined popcorn!”
Marketers intuitively understand this—but there’s less understanding of
the relationship b/t instrumental and hedonic or of the malleability of the
hedonic.
Q: relationship between avoidability of info/display and
preferences? E.g., calorie labels that
are impossible to miss [nothing is impossible to miss] versus on the back. Home energy reports: a lot of people don’t like
them even if they will save money with them.
Might suggest that you could respond to heterogeneity by differing
presentation/availability.
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