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How to Study Consciousness in Consumer Research

Steven Sweldens

RSM Erasmus University & INSEAD

Mirjam A. Tuk

Imperial College Business School & RSM Erasmus University

Mandy Hütter

Eberhard Karls Universität Tübingen

Abstract

Consumer research can benefit greatly from more insight in unconscious processes underlying behavior. Williams and Poehlman’s effort at more clearly conceptualizing consciousness and call for more research provides a welcome stimulus in this regard. At the same time, providing evidence for unconscious causation is fraught with methodological difficulties. We outline why it is vital to uphold standards of evidence for claims regarding unconscious processes, as it is precisely a lack of rigor on this front which has generated a countermovement by researchers sceptical of dual process models in general and unconscious processes in particular. We contend that the sceptics have offered valid causes for concern, which we leverage to formulate six concrete recommendations for future research on consciousness. Researchers should (1) specify the process level at which they claim evidence for unconscious processes, (2) not confuse unconscious influences with unconscious processes, (3) carefully choose between different operational definitions of awareness, (4) maximally satisfy four criteria for awareness measures, and (5) complement measurement with experimental manipulations of awareness. Finally, we recommend to (6) refrain from hard claims about unconscious causation that transcend the limitations of the evidence, recognizing that consciousness is a continuous construct.

Author Note

Steven Sweldens is associate professor of marketing at the Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, 3000 DR Rotterdam, The Netherlands (sweldens@rsm.nl) and distinguished research fellow at INSEAD. Mirjam A. Tuk is assistant professor of marketing at Imperial College Business School, Imperial College London, Exhibition Road, London, SW7 2AZ, UK (m.tuk@imperial.ac.uk) and visiting professor at the Rotterdam School of Management, Erasmus University. Mandy Hütter is junior professor of social psychology at the Eberhard Karls Universität Tübingen, Fachbereich Psychologie, Schleichstr. 4, 72076 Tübingen, Germany (mandy.huetter@uni-tuebingen.de).

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To better understand, aid and protect consumers, it is imperative to have an accurate

understanding of unconscious drivers of behavior. We therefore welcome Williams and

Poehlman’s (2016) effort to stimulate and more clearly conceptualize the study of consciousness

in consumer research. Past research on consciousness has struggled with two major stumbling

blocks. First, it is difficult to provide an accurate definition of consciousness, not least because

we do not really know how the experience of consciousness originates. As a consequence, there

has been much variation in how conscious versus unconscious processing have been defined and

operationalized in past research. We believe Williams and Poehlman (WP) have made important

progress here by restricting the definition of consciousness to awareness, highlighting its

functions and distinguishing it from other features of automaticity. Second, even when

researchers agree on a definition (e.g., “awareness”), it remains difficult to measure accurately.

On both fronts there are elements we feel are still unsatisfactory in WP’s discussion of

consciousness and some accents we would place differently. Mostly these relate to the practical

question of how to study consciousness in consumer research. This comment will broadly

develop the following three interrelated points.

(1) It is vital to uphold and further improve our standards of evidence for unconscious

causation. After all, critical evaluations by some of the most knowledgeable scholars in this field

have revealed grave deficiencies in the evidence that has so far been presented for unconscious

processes, to the extent that they question whether unconscious processes play a significant role

at all in many areas relevant for consumer research (Newell and Shanks 2014).

(2) We believe these criticisms should not be regarded as a threat by researchers studying

unconscious processes but as an opportunity. We outline six concrete recommendations to

improve the quality and communication of evidence for unconscious processes.

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(3) Development of better measures of awareness and other features of automaticity

should be a research priority. However, we also illustrate how the pursuit of better measures of

awareness can run into fundamental problems and a perfect measure of awareness is unlikely to

be developed. Meanwhile, researchers should recognize the limits of the awareness measures

they use, refraining from unwarranted claims given these limitations.

THE NEED TO UPHOLD STANDARDS OF EVIDENCE

Extraordinary Claims Require Extraordinary Evidence

We agree with WP’s call to ‘rein in consciousness’ and ‘consider consciousness second’

as a way to stimulate new theories and research ideas. WP achieve their second high-level aim to

stimulate consumer researchers to build more conceptual integration into their models by more

deeply considering how neural and physiological processes inaccessible to consciousness are

implicated in consumer behavior (WP, p. 2). Their primary high-level aim, however, is to

enhance conceptual rigor in consumer research. It is precisely on this front that we believe

important qualifications need to be made. As we explain below, a few elements in their article

could have opposite from intended effects if uncritically applied, leading to less-than-desired

levels of rigor in future research.

Threats to rigor could emerge if WP’s call to ‘rein in consciousness’ would be

generalized from the theory generation stage to the theory testing and validation stages (see

Baumeister et al., this issue, for other problems with this heuristic). To their credit, WP

“encourage researchers to rigorously examine the standards of evidence brought to bear when

assessing whether mental processes have conscious or unconscious influences on behavior” (WP,

p. 13). At the same time, however, they endorse the view propagated by Dijksterhuis and

colleagues (2014) and Evans (2014) who argue that the standards of evidence required for

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unconscious processes are often higher than those for conscious processes. Conscious causation,

they claim, is often privileged as a null hypothesis and unconscious processes are unfairly

‘penalized’ as alternative hypothesis, requiring stringent evidence.

In our opinion, in most situations the burden of proof should lie on claims for

unconscious rather than conscious causation. Carl Sagan famously remarked that “extraordinary

claims require extraordinary evidence,” an intuition formalized in Bayesian approaches to

hypothesis testing where the empirical evidence for a hypothesis needs to be weighted by that

hypothesis’ prior level of likelihood. We believe that claims for unconscious causation are more

extraordinary than claims for conscious causation. Consider the following examples.

No researcher interested in judgment and decision making would doubt the claim that

consumers can consciously integrate information and choose between different alternatives by

comparing the extent to which the options’ attributes satisfy the consumer’s purchasing goals.

However, it is far less obvious that consumers would unconsciously continue to integrate

information when their attention is directed elsewhere (see WP’s discussion of consciousness: its

primary function is to integrate information; see Plassmann and Mormann (this issue) for more

elaboration on the role of attention). Furthermore, it would be downright extraordinary if the

choices people make when not even thinking about the alternatives turn out to be superior

compared to when they devote their full attentional and cognitive resources (Dijksterhuis 2004;

Waroquier et al. 2009).

Similarly, no researcher interested in persuasion processes would doubt the fact that

consumers can be influenced by blatant persuasion attempts – a billboard for Coca-Cola® may

feed consumers’ belief that Coca-Cola can satisfy their need for refreshment. However, when

James Vicary claimed in 1957 that subliminal messages could influence movie-goers to consume

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more Coca-Cola and popcorn, it caused an uproar and investigation by the CIA (which exposed

the fraudulent nature of his claims). This illustrates that, from a consumer protection point of

view, unconscious effects will always have graver implications than conscious ones.

Finally, we could list many examples where evidence for unconscious causation is

presented to rule out much less interesting (conscious) causes such as experimental demand

effects. One example is early research on evaluative conditioning (EC). The basic demonstration

of the EC effect – a change in liking of a conditioned stimulus (e.g., brand logo) after repeated

pairing with valenced unconditioned stimuli – would not be all too remarkable if respondents

would be aware of the contingencies between the stimuli and of the researcher’s hypothesis. As a

result, some of the earliest awareness measures were developed to guard precisely against such

trivializing explanations (Allen and Janiszewski, 1989; Allen and Madden, 1985; Page 1974;

Stuart, Shimp and Engle, 1987). Similar concerns could be leveled against demonstrations of

prime-to-behavior effects, mindset effects or identity priming effects. In all such cases it is only

appropriate that the burden of proof lies on the side of unconscious causation.

The Danger in Considering Consciousness Second

We are concerned that a “consider consciousness second” heuristic can lead to a tendency

to uncritically categorize research findings as evidence of ‘unconscious processes.’ Some

references in WP’s treatment show evidence of such a mindset. For example, WP refer (among

others) to the research by Van den Bergh, Dewitte and Warlop (2008) and by Genevsky and

Knutson (2015) as examples of research showing the effect of low-level biological processes and

claim that “processes that occur at low-level, neural, or physiological levels (outside of

consciousness) can account for unique variance in predictive models of behavior” (WP, p. 7).

Whereas we certainly agree that this research is inspiring, effects of low-level biological or

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physiological factors do not necessarily occur outside of consciousness. For example, Van den

Bergh and colleagues demonstrate that men seek more immediate rewards after confrontation

with sexually arousing cues. Participants were certainly very aware of the arousing stimuli,

might have been aware of their own elevated arousal levels, and maybe even of the fact that

physiological arousal could influence their decision making.

Similarly, Genevsky and Knutson (2015) demonstrated that consumers’ affective

responses to photographs accompanying microloan requests are an important predictor of

market-level microlending decisions. Their research showed that neural imaging data of brain

areas involved in affective responses improve prediction accuracy over and above participants’

self-reported affective responses – interpreted by WP as evidence for an unconscious effect of

affective responses. However, it is unclear whether the additional variance explained by brain

activity data reflects an unconscious process. It could possibly reflect another consciously

accessible feature of the photographs that was not measured (e.g., the extent to which they are

considered self-relevant). Importantly, neither Genevsky and Knutson (2015) nor Van den Bergh

and colleagues (2008) made claims about the (un)conscious nature of the effects they identified.

To assume all too easily that these effects are unconsciously generated, simply because

physiological factors are involved, demonstrates the dangers of taking the “consider

consciousness second” adage too far. In their treatment of these articles, WP allowed

unconscious causation to take the spot of the ‘null hypothesis,’ that is, a hypothesis for which no

evidence is required. Taking evidence for unconscious processes for granted will not improve

research in this domain. Instead, as we illustrate below, such lack of rigor is precisely what

fueled researchers’ skepticism about unconscious influences.

Why the Case against Unconscious Processes Merits Attention

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While there is no doubt that vast amounts of human mental processing occur

unconsciously (e.g., the integration of sensory information), there are also a few areas in human

cognition where there is much more debate and disagreement about whether unconscious

processes play a significant role. Specifically, in recent years a few influential articles were

published questioning seemingly abundant evidence for unconscious processes as (1) underlying

human associative learning (Mitchell, De Houwer, and Lovibond 2009; Shanks 2010), and (2)

playing a significant role as direct, independent and proximal causes of human judgment and

decision making (Kruglanski and Gigerenzer 2011; Newell and Shanks 2014).

How can these scholars arrive at such sweeping conclusions in the face of hundreds of

scientific articles claiming evidence for unconscious processes in learning, behavior and decision

making? As we shall see below, they identified a number of serious limitations common to much

of the evidence for unconscious processes, based on which they put into doubt the entire

literature. Proponents of unconscious processes have argued that Shanks and colleagues are

overly radical and dismissive of large bodies of literature (Dijksterhuis et al. 2014), or apply

unfair standards of evidence to unconscious processes (Evans 2014). As a consequence, it can be

tempting to dismiss Shanks’ criteria for good awareness measures as arising from a perspective

that puts consciousness central (WP, p. 13).

Shanks and colleagues might have been overly radical in their conclusions, yet we also

believe it would be a mistake not to take their substantive concerns seriously. Instead, we argue

that for our science to progress, we need to regard their (and other) criticisms as an opportunity

to, first, improve the design of studies and measures of unconscious processes, and, second,

guide authors and reviewers in more carefully interpreting empirical evidence.

FROM CRITICISM TO PROGRESS

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We believe that criticisms raised against evidence for unconscious processes usually fall

into one of the following four brackets: not specifying the part of a process assumed to operate

unconsciously, confusing distal causes with unconscious processes, failing to clearly

conceptualize and operationalize awareness, and using inappropriate measures of awareness.

Each type warrants consideration and implies concrete recommendations to improve consumer

research on consciousness.

Awareness of What? The Importance of Specifying Awareness at the Process Level

Awareness (or lack of it) can take place at different processing levels. These levels can be

stimuli, cognitive processes, behaviors, and relations between all of these. For example,

Chartrand (2005) describes the case of unconscious goal priming where one could be unaware of

the goal prime itself, of the thought process generated by the goal prime, or of the behavior

displayed as a result. Similarly, for judgment and decision tasks, Newell and Shanks (2014) use

the lens model (Brunswik 1952) to illustrate that one needs to distinguish awareness of decision

criteria, of cues and their validities, as well as of cue utilization and the resulting judgments.

Specifying the process level where an unconscious effect takes place is highly important

for both practical and theoretical reasons. Practically, it is crucial to know which part of a

process operates outside of awareness to design effective countermeasures to protect consumers

(Chartrand 2005). Theoretically, demonstrations of unconscious influences can range from trivial

to crucial in their theoretical contribution, depending on the process level. In the realm of EC, for

example, the debate on ‘awareness’ has been raging for decades (for a review, see Sweldens,

Corneille, and Yzerbyt 2014). One reason why the subject generates so much attention is due to

its theoretical relevance: since researchers concluded that classical (Pavlovian) conditioning

effects in humans are generally not established without participants’ conscious knowledge of

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contingencies between conditioned and unconditioned stimuli (Brewer 1974; Lovibond and

Shanks 2002), demonstrations of unaware associative learning were almost exclusively restricted

to EC effects. As a result, the whole premise that humans would be able to learn associations

between stimuli unconsciously came to rest on EC demonstrations. However, not all

demonstrations of “unaware EC effects” should be considered equally important.

Consider, for example, a researcher who first runs an EC procedure in which a

conditioned stimulus (e.g., a brand logo) is paired with positive affective stimuli (e.g., gorgeous

visuals). Next, the researcher runs an indirect measure of attitudes (e.g., an evaluative priming

task), demonstrating that the brand logo has acquired positive valence, without participants’

awareness that their attitude towards the brand is being assessed. While such a demonstration of

“unaware EC” is useful to dispel experimental demand explanations for the phenomenon, it

would do little to convince scholars that unaware association formation between stimuli

occurred. The relevant question is rather whether the EC effect was established without

participants’ awareness of the contingency between conditioned stimulus and the valence of the

unconditioned stimulus at the time of learning. To this date, such demonstrations remain elusive

(Hütter et al. 2012; Stahl, Haaf, and Corneille 2016; Sweldens et al. 2014). The point is that

evidence for unawareness at one level (e.g., of one’s behavioral or attitudinal response) would be

evaluated very differently from evidence for unawareness at another level (e.g., of the relation

between stimuli). Hence, our first recommendation is the following:

R1: Analyze the process of the phenomenon of interest and be specific about the

process level(s) at which you claim an unconscious influence is taking place.

Confusing Distal with Proximal Causes or Unconscious Influences with Unconscious

Thought Processes

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There is no doubt that consumers are often not aware of all the factors that contributed to

their choices or behavior. However, there lies a danger in confusing distal causal factors of

which consumers might not be aware with the operation of unconscious thought processes

influencing behavior or decision making. As an example, Newell and Shanks (2014, p. 5) discuss

an experiment by Nisbett and Wilson (1977) which formed an early cornerstone in the evidence

for unconscious influences on behavior. The experiment shows that consumers prefer the right-

most option in a list of identical consumer products (e.g., socks), while when probed for their

reasoning, they do not mention or even flatly deny being influenced by the position of the items.

Newell and Shanks argue that this finding can be mediated by an entirely conscious decision

making strategy during which options are sequentially sampled and consumers apply a heuristic

like “if the current item is no worse than the previous item, I’ll prefer the current item.” As long

as identical items are sampled from left to right, consumers will end up with the right-most

option. Newell and Shanks argue that Nisbett and Wilson confused a distal cause (serial position)

with a proximal one (consumers’ decision strategy), so that they argued in favor of unconscious

processes on false premises. Hence, there is a distinction between (distal) factors that have an

influence outside of awareness versus unconscious thought processes as conceptualized in dual

process theories (e.g., System 1; Kahneman and Frederick 2002). There is no debate on the

existence of the former, but much more uncertainty and difficulty in demonstrating the latter.

It might seem obvious that factors influencing our decisions outside of awareness are a

different matter altogether from unconscious processing. And yet the two are easily confused. In

WP’s article, for example, the difference is never made explicit. WP refer to dozens of

unconscious influences to make the case that consciousness should be nudged toward the

background, “allowing low-level neural, physiological, and other unconscious influences on

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behavior to share the stage” (p. 8, italics added). One could wonder if unconscious influences per

se really need more of a stage in consumer research. Is not most of the research we do (or

publish) highlighting an influence that was not obvious to us as consumer researchers at the

outset, and therefore probably even less transparent to consumers? Consumers are likely not

aware of how the decision context affects their choices (Simonson 1989), of how mood

influences their reasoning (Labroo and Patrick 2009), or of how merely deliberating an option

already increases loss aversion (Carmon, Wertenbroch, and Zeelenberg 2003). Or consider some

of the endocrinological research highlighted by WP, for example, the finding that consumers’

risk-taking can be predicted by their prenatal testosterone levels (Stenstrom et al. 2011).

Although consumers could hardly be aware of this influence, this is an indication of a cause so

distal (strictly, only a correlation) that it has little bearing on unconscious processing, but is

likely mediated by personality development.

In sum, we need to realize that demonstrations of unconscious influences (even

endocrinological or neurophysiological ones) do not necessarily offer evidence for the existence

of unconscious processing as conceptualized in dual process theories. To pretend that they do

will only generate more confusion. Hence, our second recommendation is straightforward:

R2: Do not confuse unconscious influences with unconscious processing.

What is Awareness? From Definition to Operationalization.

WP equate consciousness with awareness, thereby distinguishing it from other features of

automaticity. Yet, defining consciousness as awareness presumes we have a clear understanding

of what awareness means without referring to consciousness. Unfortunately, consciousness and

awareness are often equated and used interchangeably (Moors and De Houwer 2006; Reingold

and Merikle 1988). Consumer researchers often speak of “conscious awareness” as if one term

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clarifies or qualifies the other (e.g., Chartrand 2005; Chartrand et al. 2008; Dalton and Huang

2014; Forehand and Perkins 2005). WP similarly use awareness to define consciousness on the

one hand, but regularly mention “conscious awareness,” or relate the concept back to

consciousness when discussing “consciously accessible thoughts,” highlighting the circularity in

definitions (Fiedler and Hütter 2014). Awareness is often referred to as a state of subjective

experience, defined for example as “introspective access to mental processes or mental contents”

(Gawronski and Bodenhausen 2014, p. 194). Yet, operational definitions which link the construct

to measurement are more useful than (rather philosophical because empirically inaccessible)

definitions in terms of subjective experiences.

When awareness is operationalized via measurement, one can distinguish between

subjective, objective and metacognitive operational definitions of awareness (Timmermans and

Cleeremans 2015). Subjective operational definitions depend on participants reporting the

contents of their thought processes in self-report measures. The limitation of subjective

operationalizations is that self-reports are potentially influenced by other processes, such as

consumers’ verbal skills, their interpretation of the question, and compliance. Objective

operational definitions depend on participants utilizing their internal knowledge in performance

measures (e.g., tasks that require participants to select a stimulus previously seen out of an array

of stimuli). A drawback to such measures is that performance may also reflect familiarity or

implicit memory (Hütter et al. 2012; Jacoby 1991). A third operational definition of awareness

draws on the metacognitive insight in the accuracy of the verbal report or one’s performance.

This definition is implemented in measures of confidence or betting tasks that assess the degree

to which consumers trust their knowledge (Persaud, McLeod, and Cowey 2007). The drawback

of this definition is that metacognitive acuity may be fuelled by both explicit knowledge and

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intuitive feelings, of which consumers might be aware or unaware, and that consumers differ in

their tendency to rely on these signals (Epstein et al. 1996).

It is also possible to operationalize awareness via experimental manipulation (e.g., via

subliminal presentations or with secondary tasks distracting attention). As we shall see below,

both measurement and experimental approaches come with different limitations. Given this

conceptual confusion and the multitude of operational definitions, we recommend to start with a

theoretically motivated, operational definition of awareness. Researchers tackling awareness

should be asking themselves whether they want to investigate whether participants know

(measured subjectively or objectively) or whether they know that they know (metacognitive

acuity). Awareness measures or manipulations should maximally correspond to this definition.

Hence:

R3: Consider the different types of operational definitions when choosing your

awareness measure or manipulation. Recognize the constraints of each type of

operationalization.

Operationalization via Measurement: Four Criteria for Measures of Awareness

Shanks and colleagues have proposed a set of four criteria for measures of awareness:

reliability, relevance, immediacy, and sensitivity (Lovibond and Shanks 2002; Newell and

Shanks 2014; Shanks and St John 1994). Together they form perhaps the greatest reason for

these authors’ skepticism of the literature on unconscious processes, as few if any articles have

used awareness measures satisfying all of these criteria. We recommend researchers interested in

studying awareness to consult the original publications for more in-depth discussion of the

different criteria. Here we will exemplify these criteria by considering the use of funneled

debriefing protocols, one of the most frequently used methods to assess awareness of a priming

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procedure (e.g., Chartrand et al. 2008; Dalton and Huang 2014; Fitzsimons, Chartrand, and

Fitzsimons 2008; Laran, Janiszewski, and Salerno 2016; Sweldens, van Osselaer, and

Janiszewski 2010; Tuk et al. 2009; Wheeler and Berger 2007). Typically, a series of questions of

increasing specificity is presented, ranging, for example, from “please guess the real purpose of

the study,” over “did you see a connection between the first and second part of this session,” to

“did you see a connection between the words in the first task? If so, which one?”

Despite their intuitive appeal, funneled debriefing procedures often fail on multiple

criteria for awareness measures. The first issue to consider is that of reliability, which concerns

the reproducibility and independence of noise in the measure. Open-ended questions typically

score low on reliability as participants differ widely in their eloquence and motivation to answer

truthfully and thoughtfully. Reliability (how the question is answered) ties immediately into

relevance, or what information is being probed by the question. The relevance criterion dictates

that awareness measures should test participants’ knowledge of precisely the information that an

aware participant would rely on when responding to the key behavioral (or attitudinal) measure

of the study. Many of the questions in a funneled debriefing procedure are often not well targeted

at the most relevant dimension(s). Note that to achieve “relevance” in the question format, the

researcher should first consider the operational definition (R3) and the process level at which

s/he aims to demonstrate unawareness (R1, R2). To demonstrate, for example, that a goal

priming effect occurs without awareness of the primed construct, questions should be targeted on

that construct. Say the priming manipulation consists of a lexical decision task featuring self-

control related words (e.g., Laran et al., 2016, Study 1). The awareness check should then assess

whether participants were aware that the task contained self-control related words. Instead, a

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funneled debriefing procedure is usually restricted to vague questions like “did you notice the

words were related?” or “did your responses in one task influence those in another task?”

The third issue is that of immediacy, which in Newell and Shanks’ (2014) description

prescribes that the awareness check should happen as closely as possible to the target behavior.

We believe this should be qualified: again researchers need to consider R1 to R3 before

determining what would be the appropriate level of ‘immediacy.’ In a goal priming setting, for

example, if one aims to demonstrate that the effects are caused without awareness of the primed

construct, the awareness measure should follow the primed construct immediately. If, on the

other hand, one aims to demonstrate that the behavior occurs without awareness of the thought

process, the measure can occur closer to the behavior. The problem with funneled debriefing

procedures is that they are typically collected at the very end of an experiment. This is

problematic because the human brain has an unparalleled ability to forget: according to some

estimates, 90% of the information that is not transmitted to long-term memory disappears from

short-term memory within 20 seconds (Rubin and Wenzel 1996). Hence, measures collected at

the end of an experiment are at risk of severely underestimating actual levels of awareness and

could thus easily provide spurious evidence for unconscious effects.

The final issue is that of sensitivity, which specifies that awareness measures should be at

least of equal sensitivity as the behavioral measures they speak to. This too can be a problem

with funneled debriefing procedures which normally consist of roughly coded open-ended

questions, while behavior is often measured to the millisecond (e.g., in an evaluative priming

measure) or consists of forced choice measures (e.g., when participants choose between a healthy

and unhealthy option). Now imagine that research participants would like to minimize the effort

they spend on the experiment (not too far-fetched an assumption). Every participant of this kind

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would provide completely registered data on the key dependent measures (e.g., evaluative

priming, forced choice, etc.), but would be free to skip through the funneled debriefing part as

fast as s/he could. Disturbingly, the less effort participants decide to invest on the debriefing

procedure, the greater their chances of being classified as ‘unaware.’

The problems can be further aggravated when researchers do not properly account for the

consequences of measurement error in the way they combine measures of awareness and

performance on a different criterion (e.g., attitudes, purchase intentions, reaction times) to draw

inferences about unconscious processes. For example, when participants are selected based on an

extreme score on one measure (i.e., selecting those scoring very low on an awareness measure),

it is a statistical regularity that they will score closer to the average on a different measure (i.e., a

performance measure). Such a “regression to the mean” bias is sufficient to generate spurious

evidence for unconscious processes (Shanks 2016). Considering the various ways in which

measures of awareness have fallen short of their target, it is understandable why some scholars

doubt whether evidence presented for unconscious processes stands up to closer scrutiny. Hence:

R4: Make sure the awareness measure satisfies the criteria of reliability, sensitivity,

relevance, and immediacy to the best of your ability. Beware of spurious inferences

due to measurement error.

Operationalization via Experimental Manipulation

The manifold problems associated with measurement of awareness have prompted calls

to rely more on operationalization of awareness via experimental manipulation (Gawronski and

Walther 2012; Shanks 2016). Popular approaches to ensure information has been presented

‘without awareness’ include presenting critical information in a hidden format, for example by

mixing target words in between filler items in scrambled sentence tasks or word search puzzles

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(e.g., Laran et al. 2016; Tuk et al. 2009) or by presenting information subliminally (e.g.,

Chartrand et al. 2008; Dedonder et al., 2014; Fitzsimons et al. 2008; Galli and Gorn 2011; Stahl

et al. 2016).

Experimental approaches can have important advantages over pure measurement

approaches. Notably, random allocation of participants to ‘unaware’ versus ‘aware’ conditions

prevents regression to the mean effects on other variables, which occur when this allocation is

based on measurement (Shanks 2016). Nevertheless, manipulations of awareness still need to be

accompanied by sensitive measures to offer convincing evidence for unconscious processes.

Otherwise, it could not be excluded that (a subset of) participants can somehow still detect the

presented information and drive a spurious ‘unconscious’ effect. For example, one problem with

subliminal presentations is the inter-individual variation in detection thresholds. Hence,

subliminal presentations should always be accompanied by sensitive measures of detection

thresholds, so potentially aware participants can be excluded or the presentation times can be

individually adjusted (Holender 1986). Such combined approaches are still rare in consumer

research; we would like to highlight Galli and Gorn (2011) as a commendable example in this

regard. Note that one additional advantage of combining experimental manipulation with

measurement of awareness is that the manipulation provides a direct test of the sensitivity of the

measurement. Hence:

R5: The strongest approaches combine experimental manipulation with sensitive

measurement of awareness.

While a combined approach can in principle offer strong evidence for unconscious

processes, it should be noted that failures to find evidence (i.e., null effects) for unconscious

processes via subliminal presentations need to be interpreted with caution. We agree with WP

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and Evans (2014) that this might be a case where unfair standards of evidence are imposed on

demonstrations of unconscious thought processes. Bargh and Morsella (2008, p. 74) expressed

this concern most clearly: “We […] oppose the cognitive psychology equation of the

unconscious with subliminal information processing […]. Subliminal stimuli do not occur

naturally—they are by definition too weak or brief to enter conscious awareness. Thus, it is

unfair to measure the capability of the unconscious in terms of how well it processes subliminal

stimuli because unconscious (like conscious) processes evolved to deal and respond to naturally

occurring (regular strength) stimuli; assessing the unconscious in terms of processing subliminal

stimuli is analogous to evaluating the intelligence of a fish based on its behavior out of water.

And as one might expect, the operational definition of the unconscious in terms of subliminal

information processing has in fact led to the conclusion of the field that the unconscious is, well,

rather dumb.”

THE WAY AHEAD

Perfection is not attainable, but if we chase perfection, we can catch excellence - Vince Lombardi

Perfect Measures or Manipulations of Awareness Do Not Exist

We hope our recommendations can be helpful to researchers studying consciousness. At

the same time, it should be noted that none of these recommendations is easily satisfied, let alone

all of them together. At the risk of discouraging researchers, we note that the criteria by Shanks

and colleagues are not even the only ones to be satisfied by awareness measures. A particularly

difficult issue is the extent to which the measures exhaustively and exclusively measure

awareness, in the sense that the measure should reflect all possible sources of awareness and not

be influenced by unaware processes (Reingold and Merikle 1988). Since Jacoby’s (1991)

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seminal paper on process dissociation, it has been recognized that these criteria are never

satisfied, as no measure is ever process-pure.

We are grateful for WP’s discussion of our work on process dissociation procedures as an

important step forward (WP, p. 13). Twenty-five years after their introduction, process

dissociation procedures are still at the vanguard of research on consciousness. One reason why

they are often superior to other approaches is that by design they combine manipulation and

measurement into one procedure. Yet, process dissociation approaches come with their own

assumptions and limitations, most notably the strong assumption that conscious and unconscious

processes contribute equally in different conditions (Hütter and Klauer 2016). Therefore

parameter estimates obtained by process dissociation procedures cannot be taken at face value

either, but (like other measures) need to be complemented with additional experimental

manipulations. For example, parameter estimates for conscious and unconscious processes need

to be validated by manipulations of variables assumed to impact these processes differently (e.g.,

cognitive capacity, motivation or attention; Hütter et al. 2012; Hütter and Sweldens, 2016;

Mierop, Hütter, and Corneille, 2016).

Consciousness as a Continuum

The previous sections highlight that it is nearly impossible to design a perfect measure of

awareness. How can consumer researchers deal with this important constraint? Shall we stop

investigating the role of consciousness? We would like to promote a more optimistic view and

find inspiration in the perspective on consciousness as a continuum, highlighted by Plassmann

and Mormann (this issue). We fully agree with these authors that consciousness need not be an

all-or-none phenomenon. Furthermore, we believe that many problems and ensuing criticism in

this field emerged from the fact that researchers often applied a dichotomous perspective on

20

consciousness to their theories and empirical evidence, while the awareness measures they used

are ill-suited to substantiate dichotomous claims (especially where it concerns the strictly

‘unconscious’ nature of an effect). However, the imperfections in awareness measures are much

less problematic if consciousness is treated as a continuous construct and researchers refrain

from hard claims regarding the unconscious nature of an effect. Instead, in most cases the

measures would be able to validly support claims that ‘effects are less consciously mediated’ or

‘characterized by lower levels of awareness’ in some conditions compared with others.

R6: Hard claims that a process is unconscious are difficult to support, given the

limitations of awareness measures. Softer claims that processes are ‘more’ or ‘less’

consciously mediated can be more validly entertained.

CONCLUSION

Despite the difficulties involved in the study of consciousness, we cannot agree more

with WP that the role of consciousness has crucial theoretical and practical implications for

consumer behavior. The last few decades have brought about important conceptual and

methodological advancements which we should embrace and continue to develop (e.g., process

dissociation procedures, item-based analyses and hierarchical models, convenient eye-tracking

equipment, the neuroscience toolbox). At the same time, it is crucial to be aware of the

difficulties in studying consciousness. Researchers should try their best to apply or develop the

best possible measures, yet at the same time be aware of and explicit about the limitations of the

measure they use. They should not make claims that transcend the empirical evidence,

acknowledging the limitations they encountered from R1-R4. Conversely, reviewers and editors

should value advancements in this challenging field which acknowledge, but not necessarily

overcome, these limitations in a single paper.

21

In closing, we would like to note that several of our comments are not restricted to the

investigation of awareness. Awareness is just one of several features of automaticity that may or

may not co-occur. As rightly pointed out by WP, even if a process occurs without awareness, it

cannot automatically be assumed that this process would also be uncontrollable or independent

of processing resources. These features need to be investigated separately. The same conceptual

and methodological rigor that we promoted in this commentary needs to be applied to other

features of automaticity to gain a more complete understanding of consumer behavior.

22

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