More than numbers: how visitor engagement data can be captured and used to amplify your creativity

Tim Stroh, Art Processors, Australia

Abstract

Many museums today know that effective and actionable data is essential to achieving visitation goals—better audience engagement, reaching different and diverse audiences, and increasing attendance. Further, museums and other cultural centers are also facing increasing barriers to audience attraction and retention. The solution to these challenges, and the key to achieving goals for audience engagement, has several parts including a revised understanding of consumer psychology, data and insights, and your creativity. The starting point of being accurate answers to key questions including: What actually is visitor engagement? How can you pragmatically measure it? How can you use data and insights to amplify your creative impact? These and other questions will be addressed in this essential conversation for curators, creators of experiences, and museums. The paper, accompanying presentation, and discussion will cover a three-phase research program designed to generate a better understanding of the consumer market, museum visitors, and their engagement with objects and spaces: 1. A review of current literature on consumer, tourism, and evolutionary psychology, as well as entertainment and neuroaesthetics. 2. Direct research on visitors conducted in late 2019/early 2020 at a major U.S. museum, two Australian museums (one major and one minor), and two additional "leisure entertainment" sites. 3. Current analysis of the single largest data set in existence of museum-visitor movement, dwell time and interactions. Research results and useful takeaways will be shared including: 1. A new model for segmenting the consumer marketplace and visitors that enables practical application and greater predictive accuracy; 2. A description of pragmatic cost-effective tools and methods for capturing engagement data and undertaking analysis; and 3. Methods for using insights to amplify creativity and impact.

Keywords: Engagement, motivational drives, evolutionary psychology, data, visitor experience, segmentation

1. Introduction

The pre-pandemic need of all types of museums to understand how to overcome “the lack of anything new” and to better compete with cinema, sports, and the ever-growing appeal of digital entertainment—all top 5 reasons for not attending (Dilenschneider, 2020)—has become more important than ever. In the post-pandemic world, museums must determine how to (1) increase visitor engagement, (2) appeal to new and more diverse audiences, and (3) optimize overall attendance, patronage, and societal benefits, not only to attract new audiences but to ensure they effectively re-engage their traditional ones.

Problematically, available tools such as Culture Segments and Falk’s Visitor-Identity Model (2009), as well as traditional approaches such as new buildings, “blockbuster” exhibitions, and customer relationship management systems, have proven to be ineffective or inconsistent at best.

Thankfully, there are silver linings to this modern era. Evolutionary psychology and the cognitive neurosciences have overturned Rational Choice Theory (RCT), the very foundation of neoclassical economics, as well as many accepted theories and models from psychology. This research has also laid the groundwork for a new unified theory of behavior that may explain why the existing visitor models used by museums are inconsistent, and the kinds of actions museums can take to secure new visitors and greater engagement.

This research project was conducted to address this clear need for a fact-based, pragmatically useful understanding of how to reach and influence all consumers, measure and improve engagement, and aid museums in achieving their core goals. Rather than describing the cosmetic characteristics of individual visitors, this paper contributes to the field by providing an actionable explanation for why consumers visit and factors that must be considered by museum teams to optimize visitor experience, increase engagement, and attract visitors.

This paper follows a traditional format. First, the questions driving the project are presented followed by a description of the research project components, a review of relevant literature from evolutionary psychology, neuroscience, and engagement with conclusions synthesized from each. This is followed by details of the two research stages, research limitations, and summary conclusions.

2. Research Questions

The stated need and literature review conducted prompt several specific research questions:

  1. How can visitor engagement be measured and influenced?
  2. Why do people choose to attend or not to attend museums? What motivates and influences this choice, or the choice to do something else with leisure time?
  3. How can the growing segment of the market that is not attending cultural institutions be accessed and effectively attracted to visit museums?
  4. How can a visitor’s experience be optimized to ensure museums are able to achieve their objectives? How can we measure, determine what influences, and thus improve engagement and post-visit endorsement behaviors by visitors?

3. Research Design

A two-stage, three-component program was conducted over the course of 2019 and 2020 based on a pragmatic, critical realist and grounded theory approach.

  1. Stage 1A: Multiple iterations of (a) observational research using a “complete observer” method followed by (b) semi-structured interviews. Visitors to several museums and visitor attractions in the United States and Australia were studied. The sample of venues included large museums in Australia and the United States (each venue being confirmed as one of the “most visited” museums in its respective country) as well as medium size and a small museum in Australia. In addition, based on the initial analysis, observations and data were collected at additional leisure activity options in the United States and Australia.
  2. Stage 1B: A traditional literature review was conducted across several focus areas including evolutionary psychology, engagement research, tourism and cultural institution attendance. Additional literature was reviewed from consumer psychology, cognitive neuroscience, and neuroaesthetics.
  3. Stage 2: Data on visitor interaction and behavior in museums as well as publicly accessible data on post-visit behavior was obtained and analyzed. Historical, in situ visitor behavior data captured via mobile device-facilitated visitor experiences was obtained and reviewed. Data was depersonalized and reported on without association to specific venues. Obtaining and analyzing both in situ and publicly accessible data sets were undertaken as a proof of concept validation of the ability to produce a holistic, measured, and cost-effective view of visitor engagement.

4. Literature Review

Advances in evolutionary psychology (EP), behavioral economics (BE), and neuroscience have fundamentally altered our understanding of how and why people behave the way we do and what influences our choices and behaviors. Rational choice theory (RCT) as well as its progeny the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB), both prolifically used in disciplines from psychology to technology acceptance (Davis, 1989; Davis et al, 1989; Ajzen and Fishbein, 1980; Ajzen, 1985; Madden et al, 1992; Venkatesh et a, 2003; Venkatesh and Davis, 2000; Venkatesh and Bala, 2008), have been shown to be, at best, grossly incomplete (Ariely 2008; Kahneman, 2011; Stroh 2017). Even Maslow’s hierarchy of needs (1958), which is still widely used by practitioners, has been shown to be incorrect and is described as “a quaint visual artifact without much contemporary theoretical importance” (Kenrick et al, 2010(a)). From the adoption of new technology (Junglas et al, 2009; Abraham et al, 2013, 2016) and what music we download (Salganik et al, 2006) to the prices we pay for shares on the stock market, these advances in our understanding of what influences decisions have fundamentally and permanently changed whole disciplines (Ariely 2008; Confer et al, 2010; Kahneman, 2011; Stroh 2017). This research also mandates a reconsideration of every other theory or model that is based on an assumption of consumers or visitors as rational agents motivated by personal preferences, self-interest, and price.

Falk’s Visitor Identity Model (2009) and the Culture Segments framework are two such examples. In practical application, neither consistently delivers predictive accuracy or pragmatically useful insight into how to attract new consumers to museums. While Culture Segments incorporates data on individuals comprising the wider market, Falk’s research is based solely on individuals who have attended a museum (Dawson and Jensen, 2011). More critically, they rely on an assumption that the rational pursuit of personal preference is the foundation of consumer decision making and they are composed of data exclusively on the characteristics and preferences of individuals.  Evolutionary Psychology (EP) and Behavioral Economics (BE) have now disproved this foundation assumption and shown that individual characteristics are, at best, contributors to and not the sole, or even primary, drivers of consumer behavior and choice.

4.1. Literature Review Summary of Evolutionary Psychology

Evolutionary Psychology proposes that “evolution by natural selection is the only known causal process capable of producing complex physiological and psychological mechanisms” (Buss, 1995). More specifically, it posits that our behavior is substantially influenced by, or the product of, evolved psychological mechanisms (EPMs) (Wilson, 1975; Cosmides & Tooby, 1994; Buss, 1995; Confer et al, 2010). EP applies the principles of evolutionary biology to psychological research and theory, and in turn their application to other disciplines.

While Darwin (1859) originally proposed the idea, little legitimate research was conducted until 1975 following E.O. Wilson’s seminal book Sociobiology. At about the same time, Behavioral Economics (BE) emerged. BE, which is largely based on EP, disproved Rational Choice Theory. In doing so, it fueled substantial interest and over the past four decades has firmly established that we are “predictably irrational” (Ariely, 2008; Kahneman, 2011). The consistency and nature of many of the observed biases in our decision-making are increasingly supported by neurological evidence that confirms their origin as evolved characteristics rather than cultural or learned behaviors. The core concepts of EP are now widely accepted across psychology, neuroscience, economics, business management, and marketing to name just a few (Nohria & Groysberg, 2008; Nguyen-Phuong-Mai, 2017; Saad and Gill, 2000; Saad, 2019; Santos and Rosatti, 2015; Kock, 2009).

To overcome the challenges of establishing the evolved origins of traits that have no fossil record, EP uses nomological networks of evidence as a primary tool (Schmitt and Pilchcer, 2004; Saad, 2017). Nomological networks utilize “the weight of systematically accumulated evidence, drawn from a diversity of unrelated streams or disciplines, to establish a coherent body of proof” for an EPM as well as support a hierarchical structure of mid-level theories and associated discrete falsifiable hypothesis based on the EPM (Buss, 1995; Schmitt and Pilshcer, 2004; Saad, 2017). Such networks increasingly include cutting-edge research from neurosciences, phylogenetic evidence or confirmation of cross-species trait expression, genetic evidence, and evidence from a host of other disparate disciplines from economics to anthropology.

In addition to overturning RCT and Maslow’s hierarchy of needs, EP has established there are both highly specialized EPMs and more generalized motivational drives. These EPMs have been shown to influence our behavior and decision-making in a diversity of arenas (Lawrence and Nohria, 2002; Kenrick et al, 2010; Schaller, 2017). Specialized EPM traits detect and respond to specific patterns of stimuli. These include stimuli patterns such as faces, which activate a facial recognition circuit, the sight and sound of our siblings, which trigger the incest inhibition circuit and suppress the potential mate detection circuit, and exposure to an array of visual stimuli or scents that are perceived as attractive and activate a broad variety of mating behaviors from posturing to increased creativity (Rezai, 1996; LeDoux and Self, 2003; Miller, 2000; Griskevicius et al, 2006; Confer et al, 2010; Kenrick et al, 2010).

There are also more generalized EPMs such as our instinctual expectation of fairness and motivational drives such as the drive to pursue status. While there are several proposed sets of motivational drives, including Motivational Drive Theory (Stroh, 2017), the Four Drive model (Lawrence and Nohria, 2002), and the Fundamental Motives framework (Kenrick et al, 2010(a); Griskevicius and Kenrick, 2013; Schaller et al, 2017), all share common elements. These include EPMs that motivate the pursuit of belonging or bonding, status, and relative capability or learning. In addition, there is substantial evidence for drives described as the pursuit of novelty, gossip, play, self-image, parenting, mate retention, mate acquisition, and self-protection. Critically for the museum community, EP research has robustly shown these EPMs influence every type of decision and behavior from schoolyard gossip and product adoption to who in our respective office environments we will assist and our choice of travel and holiday activities (Cummings, 2005; Kock, 2009; Saad, 2017, 2019; Abraham et al, 2016; Pinker, 1997; Griskevicius, 2013; Kock et al, 2018).

Concurrent with the development of EP, new tools and research methods have dramatically expanded the scope and pragmatic applicability of neuroscience research. No longer exclusively the realm of medicine, neuroscience research is being applied to a diversity of fields from information system design to the experience and appreciation of art (Dimoka et al, 2007; Dimoka and Davis, 2008; vom Brocke et al, 2020; Cela-Conde et al, 2013; Pelowsky, 2017; Marin, 2015; Zaidel et al, 2013).

Unlike EP, which is increasingly explaining why people behave the way they do and what motivates behaviors and choices, neuroscience is revealing how, and in some cases proving the why. The volume of relevant research is prolific and includes whole sub-disciplines of immediate pragmatic use to museum practitioners such as neuroaesthetics (Pelowski, 2017; Marin, 2015; Zaidel et al, 2013; Seeley, 2011).

This research has demonstrated the existence of discrete areas of the brain involved in the recognition or appreciation of actual as well as abstracted or representative images — a painting of a landscape as distinct from a photograph of the same scene (Mizokami et al, 2014), diverse and distributed areas of the brain associated with different forms of aesthetic experience (Zaidel et al, 2013), and the sequence of neural activity that occurs leading to the recognition of beauty (Pelowski et al, 2017).

It has also revealed that we not only mimic the expressions we see in the faces of others but the important role this plays in our perception and understanding. When we see someone or an image of someone wincing in pain, we wince. When we see someone smile, we smile. Importantly, this physical mimicking of the facial expressions of others plays a substantial role in our ability to empathize and understand what we see. People treated with Botox literally feel less and understand others less because they can no longer subconsciously physically mimic the emotional expressions they see (Neal and Chartrand, 2011). Engaging sensorimotor areas of the brain increases the reported aesthetic rating of an object, even though the object represents negative experiences such as faces in pain (Ardizzi et al, 2018).

Different types of stimuli trigger surprising collections of neural circuits. Social exclusion, for example, not only triggers areas associated with social behavior but also activates the same areas of the brain that are triggered by physical pain (Libermann, 2013). Stories of social exclusion can also trigger this collection of areas.

There are what would appear to be a variety of innate pre-stored patterns of stimuli that function something like inherited memories. Images of nature and natural stimuli are calming (Chang et al, 2021; Fitzgerald and Danner, 2012). We innately recognize not only that we see a face but a variety of forms such as the shape of the human body (Stroh, 2017) and its relative attractiveness (Tsukiura and Cabeza, 2011; Valuch et al, 2015). In addition, we universally find aesthetically pleasing or repugnant various patterns of stimuli including natural scenery, music, certain smells, and more (Zaidel et al, 2013).

These neural structures specifically influence our perceptions. Our storage of new information is built upon this pre-existing scaffolding. We store information by associating new elements to existing stored patterns (Østby and Østby, 2018). We literally perceive, understand, and remember based on what has been stored previously (Stroh, 2017). As a result, our perceptions are rarely purely objective but rather influenced by all of the interconnected pre-existing patterns that underpin the scaffolding our brain has used to store the new information. This has a broad variety of unintended and seemingly irrational consequences in the modern world (Stroh, 2017). Research by Lera Boroditsky (2011) has shown that how people perceive and describe objects is impacted by the gender pronouns of their native language.

The more related or aligned circuits that are activated by an experience, the more likely we are to be able to recall it (Østby and Østby, 2018). It is known that different neural circuits are involved when viewing a photograph or an object directly than when observing an abstract representation of the object such as a painting. As such, placing an orange next to the painting of an orange may increase the engagement and recollection achieved relative to either in isolation.

In addition, awareness of our relative position and the time when we experience or see something is fundamental to memory and recall (Umbach et al, 2020; Wang et al, 2020). This has substantial pragmatic ramifications for museums. Google Maps-style wayfinding may offer tremendous convenience, but providing it will reduce visitor engagement and recall of their experience in the museum.

We are innately motivated by EPMs to pursue belonging and avoid ostracism, pursue relative status, novelty, and a variety of other outcomes (Anderson et al, 2015; Kenrick et al, 2010(a); Griskevicius and Kenrick, 2013; Schaller et al, 2017; Stroh, 2017; Kock, 2009). Each motivational drive equates to a discrete form of value that is often more important than economic utility. Crafting a visitor experience that increases these forms of value will increase the appeal of the museums relative to other options for leisure activity.

The pursuit of novelty is widely acknowledged in tourism research as a primary motivation for holiday travel (Kock et al, 2018). Park (2017) shows that the drive for status is a hidden motive for knowledge sharing and gossip. Research also shows that social status obtained via posting on social media is a major motivating factor in the selection of tourist destinations (Kock et al, 2018), status motivates “mavenism” (Goldsmith et al 2012), and consumption by non-core consumers elicits pride in more regular consumers (Bellezza and Keinana, 2014). The same motivational drives influence choices to attend or not to attend, as well as boast about or stay quiet about, museums.

These motivational traits and neural circuits are part of a wet system. While discrete, these modules are interconnected and interdependent. So much so it appears there is no universal or explicit hierarchy. Kock et al (2018) state “a key insight from evolutionary psychology is that a specific behavior can be elicited when the respective motive is triggered through cues.” Any circuit activated by external or internal stimuli at the time of a decision, relevant and rational or not, will influence decisions or behaviors (Stroh, 2017; Badcock et al, 2019(a); Badcock et al, 2019(b)). As such, a museum’s ability to create a perception of status or novelty will increase the perceived value of a visit.

EP and neuroscience research have shown that different forms of positive and negative emotional states have differential, and in many cases counterintuitive, effects. In earlier research, the influence of a “positive” and “negative” emotional state was generally considered as being a “positive” or “negative” moderator irrespective of the cause. Research by Ahn and Shin (2015) makes clear that interest, contentment, excitement, and relaxation, while all positive emotional states, have different natures, evolutionary origins, and contextual impacts.

As will be discussed later, the importance of considering the EP lens rather than the basic concept of “positive” or “negative” is also supported by Higgins and Scholer’s (2009) work, which concludes that engagement level and the perceived value of being engaged can be increased by the effort required to overcome obstacles in pursuit of a goal-outcome, obstacles traditionally being considered as explicitly negative moderators.

These are not just biases on specific forms of economic decision-making, though the case for some biases is quite strong. EPMs influence all manner of decisions in all manner of arenas and situations. (Kock et al, 2018; Badcock, 2019(a)&(b); Noel, 2019; Park, 2017; Stroh, 2017)

Most important, EP and BE research have shown that decision-making is more a social process than one that reflects individual preferences (Stroh, 2017; Salganik et al, 2006; Ariely, 2008; Zhang and Glascher, 2020). Any decision that is, or may become publicly viewable, is considered based on a subconscious calculation of its perceived impact on belonging, status, and the likelihood it may be viewed as a challenge by others (Libermann, 2013; Aranson, 1972; Stroh, 2017). Our decisions are a function of what we think our social and peer groups will think of our choices rather than individual personal preference (Salganik et al, 2006; Ariely, 2008; Stroh, 2017). Individual preferences are not the sole or even key determinant. Decision-making for any publicly observable choice, including attendance to a cultural institution, is a reflection of a group decision process.

Collectively, this explains the limited effectiveness of traditional market research focused on individuals, individual preferences, and decisions predicated on rational self-interest. As decisions are the product of a group dynamic, a focus on organic social and peer groups and their interactions around status and novelty would be more effective. Culture Segments, Falk’s Visitor Model, and traditional demographic research describe characteristics of individuals. Irrespective of any other strengths or shortcomings identified with each (Dawson and Jensen, 2011), their focus only on individuals does not reflect the social nature of what motivates people to attend museums or recommend to others they attend.

Just as this has required economists to reconsider what influences investment decisions, business leaders to rethink what prompts product adoption, and marketers to change how they look at consumers, EP and the advances in cognitive neuroscience require that museums and cultural institutions reconsider what they offer, how, and what influences visitors.

4.2 Literature Review of Engagement

Engagement is a relatively new concept both in application and as the subject of academic research. As a result, there are a variety of proposed definitions (Davenport, 2013; Abdul-Ghani et al, 2011; Higgins, 2006; Higgins & Scholer, 2009; Brodie et al, 2011). Broadly speaking, engagement refers to a variety of related concepts drawn from different disciplines including marketing, consumer behavior, digital information systems, e-commerce, and the study of interaction in cultural organizations.

While dominated by e-commerce and marketing, several researchers have focused specifically on engagement in museums. Yalowitz and Bronnenkant (2009) considered a variety of activities by visitors indicating a level of engagement with objects from “walked past exhibit without stopping (stop considered here as 2–3 seconds)” to “stopped, read, engaged with the material and commented to others (pointed, shared through conversation).”

Brodie et al (2011) provide a simple, generic, and yet relatively complete definition: “Engagement is perceived as involvement with, and commitment to, a consumption experience.”  They have also produced one of the more comprehensive definitions specifically crafted for generalized use in a variety of contexts:

“Customer [or visitor] engagement (CE) is a psychological state that occurs by virtue of interactive, co-creative customer experiences with a focal agent/object (e.g., a brand) in focal service relationships. It occurs under a specific set of context-dependent conditions generating differing CE levels; and exists as a dynamic, iterative process within service relationships that co-create value. CE plays a central role in a nomological network governing service relationships in which other relational concepts (e.g., involvement, loyalty) are antecedents and/or consequences in iterative CE processes. It is a multidimensional concept subject to a context- and/or stakeholder-specific expression of relevant cognitive, emotional and/or behavioral dimensions.”

While the debate continues regarding a generalized definition that works across arenas, nearly all proposed definitions share elements having comparable roles within the conceptual representation. These shared elements are readily and directly applicable for museums:

  1. A customer or visitor and their psychological state
  2. The nature of that psychological state occurring to differing degrees as a result of
  3. Attention to a focal agent/object (e.g., a brand, product, etc.)

Further, that the psychological state of engagement:

  1. Is demonstrated by interactions (with an experience, experience element, or environment such as conscious action to select and click a link, the choice to stand and focus attention on something, etc.)
  2. The result of a dynamic and iterative process not limited by a single set of stimuli and associated response
  3. Occurs within a specific set of context-dependent conditions and within a broader relationship context in which other relational concepts and influences (e.g., involvement, loyalty, willingness to engage in specific activities, contribute feedback or make public commentary, awareness, pre-existing knowledge) are antecedents and/or consequences
  4. Is a multidimensional concept subject to a context and/or stakeholder-specific expression of relevant cognitive, emotional and/or behavioral dimensions

In addition to efforts to define the phenomena, research has extended to understanding what influences engagement and how engagement impacts other phenomena.

Contrary to the traditional focus on dwell time (Castro et al, 2016), research has shown that time spent by individuals is at best an indicator. Strong engagement can occur despite very brief investments of time and extended time does not necessarily mean high levels of engagement (Taheri et al, 2014).

New technologies have also changed how engagement can be measured in museums. Historically, time proximate, observed stopping, and self-reported data were the only measurable variables. Each of these is accompanied by some degree of subjective or measurement error. Today, however, capturing actions that definitively indicate engagement and a wealth of other data are default capabilities of enhanced experience offerings from creative technology companies like Art Processors (www.artprocessors.net.au).

Importantly, it is clear that the more simplistic concepts of engagement are lacking. All engagement occurs within a broader relationship context and must be considered holistically. These wider contexts are dynamic and the interactions that produce engagement are an iterative and multi-dimensional process incorporating cognitive, emotional, and behavioral parameters (Brodie et al, 2011). A behavioral change can be an outcome as described in commercial research but is also part of the defining phenomena (Brodie et al, 2011). Just as our subconscious mimicry of facial expressions corresponding to emotions is part of what allows us to understand what we see, our behavior is a dimension of what results in engagement.

Engagement plays a central role within the larger network of interactions forming a relationship between a consumer visitor and an organization, which in turn impacts levels of engagement. This relationship is composed of and influenced by all interactions from an initial interaction with a website through to coffee in the café and exiting through the gift shop. As such, engagement must be considered concurrently at a variety of stages of interaction from that of a single focal object (e.g. an artwork, interactive exhibit, architectural feature, vista) through to the gallery or exhibition level and outward to engagement by the museum experience or relationship as a whole. “The engagement process may be viewed as a series of aggregated engagement states” (Dunham et al, 1993; Zhou et al, 1999 – taken from Brodie et al, 2011).

Engagement is also interconnected with our concept of value. “Regulatory engagement theory proposes that value is a motivational force of attraction to, or repulsion from, something, and that strength of engagement contributes to value intensity independent of hedonic and other sources of value direction” (Higgins, 2006; Higgins and Scholer, 2009). Engagement influences perceived value and can be influenced by a pre-existing perception of a goal-object’s value. Social Exchange Theory identifies interactions that are composed of both tangible and intangible elements including the value of social interaction, social approval, emotional reward, pride, and more. While independent, these concepts of value and engagement can not be pragmatically separated. Engagement is influenced by value and has been specifically shown to be increased by the perceived “social” appropriateness (e.g. social bonding benefit, compliance with social norms) of the method used to achieve a goal-outcome. Engagement is influenced by the process and the motivation as well as the outcome or end-state emotional response in the moment (Higgins & Scholer, 2009).  “Strength of engagement in goal pursuit contributes directly to the value intensity of the goal object (a goal-object value intensification effect). The different sources of engagement strength contribute different experiential qualities to the goal pursuit activity (a goal-pursuit, activity experience effect). And, forces influencing value direction +/- and value intensity are independent” (Higgins & Scholer, 2009).

Taheri et al (2014) have also made clear that engagement is influenced by prior knowledge, recreational motivation, and an individual’s omnivore-univore nature (e.g. do they like many different things or do they prefer a single type of activity).

Higgins and Scholer (2009) have shown that value and engagement can be increased by the effort of overcoming a challenge to achieving an objective. Importantly, increased value and engagement come from the person putting in effort not the existence of a challenge or obstacle. So museums must keep in mind that simply adding challenges won’t increase engagement or the perceived value of an experience. Adding obstacles or challenges that visitors put effort into overcoming, however, will. As such, in practical application challenges, tasks, or features that are aligned with the experience, fun, or offer sufficient value in the form of novelty, status, or opportunities for mastery to be participated in will increase engagement and perceived value. Effective gamification is an example of such an approach.

The process and experience of pursuing a goal or which generates engagement may be valued for various reasons. The motivation and process also influence the perceived value of the target goal-object (Higgins and Scholer, 2009). In the case of museums, engagement can be driven by (1) prior knowledge (familiarity, expertise including knowledge and skill and past experience of the site), (2) multiple intrinsic motivations (self-expression, self-actualization, self-image, group attraction, enjoyment, satisfaction, recreation, and person enrichment), and (3) cultural capital (social origins and the accumulation of cultural practices, tastes, education) (Taheri et al, 2014). “The process can be valued because it is socially prescribed and satisfies some social norm, because it is effective or efficient, or because it fulfills multiple goals” (e.g. a focal goal and one or more other goals)(Higgins and Scholer, 2009). Going to the movies or the museum on a date makes sense in this light as they provide entertainment value, opportunities to socialize, and shared experiences, which are a requirement for bonding.

Collectively, this research makes clear that engagement must be considered holistically. Measuring object-level engagement is a starting point, but engagement must also be considered at multiple levels including for the whole of an experience.

Fundamentally both engagement and EP research make clear the need to think differently about the concept of value as it relates to experiential offerings.

Historically, a thing has been considered valuable if it fulfills a need or is useful (taken from Higgins, 2007 – Gibson, 1979; Weiner, 1972; Woodworth & Schlosberg, 1954) or delivers hedonic pleasure (e.g. Bentham, 1988/1781). Needs and pleasurable experiences having been determined by rational self-interest and the pursuit of personal preferences, utilitarian gain, security, food and shelter, or a personal goal.

While substantial research exists on biases and moderators that influence the economic value ascribed to a thing or experiences, the inability of these efforts to generate a replacement to RCT is at least in part a result of a fundamental need to reconsider and redefine how we think about what results in a perception of value.

Regulatory Engagement Theory (Higgins, 2006) “proposes that value is a motivational force of attraction to or repulsion from something.” This broader definition and a consideration of all of the forces or motivations that attract or repulse visitors is critical to museum success.

EPMs explain the diversity of these motivations and associated attraction to and repulsion from various relative outcomes for members of the organic groups an individual recognizes they are part of. Conscious and rationally determined utility or economic value, as well as individual preferences, need to be re-conceptualized as one of a family of forms of value that are not universally exchangeable or reducible to a shared monetary form. Each form of value appears to be the product of discrete neural circuits that influence a perception of value whenever the circuits are active and in turn influence resultant behaviors based on a dynamic interplay between individual EPM expression, context-specific perception of social impact, individual preference, and only in some cases conscious reasoning.

5. Onsite observation and semi-structured interview research

Observations of museum and leisure activity audiences were undertaken based on a grounded theory approach. Initial observations were made prior to the literature review with later observations and interviews informed by both the earlier rounds of each and early analysis of reviewed literature.

A pure observation method was initially adopted. Observations were first made at a non-cultural tourist destination (an observation deck), an outdoor tourist destination (city square), and a major museum in a large Australian city. This was followed by semi-structured interviews at the tourist destination, additional pure observations of visitors at the initial museum, and observations at two additional museums. The three museums included top tier, “most visited” museums in Australia and the USA as well as a small but well-known museum in Australia. Semi-structured interviews were then conducted at the large Australian museum. Based on the analysis of these results, observations were then also made at additional tourist and leisure activity destinations including two stage theaters, two movie theaters, two sporting events, and ten restaurants.

Observational data was strictly limited to what could be easily, objectively, and consistently observed or deduced about visitors from their appearance and behavior. Observable characteristics included a very general approximation of age (young child, older child, young adult, post-children adult, older adult, retirement-age adult), superficial gender, if they were by themselves or with others, as well as the nature of the group they were in if self-evident (e.g. families with children, romantic couples). In addition, at museums, the relative pace of movement (fast movers and slow movers) was noted.

Observations were made at multiple different times during the day and on different days of the week including both weekdays and weekends. In the museums, observations were made both while walking around and from fixed positions maintained for 2 or more hours. Finally, at each of the large Australian and large US museums, while observing from fixed positions, photographs were taken at 5-minute intervals and subsequently referenced as a basic check to ensure the veracity of recorded data.

What was immediately clear from these observations:

  1. The vast majority of people observed were part of discernible groups. There were very few lone individuals. Across the three initial sites, less than 1% of observed individuals were present on their own across more than a 1,000 individuals in hundreds of discernible groups. Groups were so prevalent that group size and nature quickly became the primary recorded observation.
  2. Some of the observed groups had clearly defined types with different objectives and behaviors. For example, atomic families and groups of mothers with young children (mother’s groups) attending together were readily identifiable and common at museums. These groups were clearly more focused on social discourse than on the museum’s content relative to other group types. Romantic couples, both recently initiated and long-standing composed of both young and old members, were also prolific. A substantial number of couples were observed drawing attention to objects as a basis for discussion but did not appear to be didactically interested in the objects. The museum appeared to purely provide a context for and the objects were used as a pretext for social interaction.
  3. The role of the museum as a provider of venue and context for facilitating some combination of social interaction and an entertaining leisure activity was also evident for many other group types (friendship groups, pairs of adult couples who may or may not have been romantic couples). Behaviors and movement suggested that their presence was less about the objects on display and more about the nature of the venue and the social activity the museum facilitated. Clearly romantic couples (determined by physical behavior), groups consisting of several individual parents and their young children (so-called “mother’s groups”), and many groups of adults were in attendance and moved through the venue as a space to conduct their primary objective of social interaction. The venue and its objects were simply a pleasant environment within which to conduct that activity and only occasionally were sufficiently engaging to stop a relatively steady rate of movement.

After an initial round of observations, semi-structured interviews were conducted by a team of two at the tourist location. One researcher would engage subjects in dialogue while the other would take notes. After each interview, additional notes were recorded based on a brief discussion between the researchers about the observed conversation. While it was expressly stated to visitors that the discussion’s intent was for research purposes, substantial effort was made to ensure a pleasant and open discussion and avoid any sense of a survey or list of questions and answers to be obtained. Discussions were initiated with a question about the nature of the visitor in context such as “Tell us a little about your group?” Discussions were then maintained until answers to target questions were stated or an opportunity presented itself to naturally introduce the specific questions without directly revealing what elements of the discussion were the focus of the research. Specific information captured for all discussions included the nature of the visiting group, what prompted the day’s visit, was an activity undertaken prior to visiting this site, and if there was an activity planned for after this site.

While not universally captured, discussions generally also covered a group’s favorite comparable activities and why they were liked above other such experiences.

More than 50 interviews were conducted across four days. Based on observations and common themes within the first ten interviews, an additional element was added to the required data to be captured for the remaining 40 discussions: “Was the activity entirely unplanned, part of a specific plan created for the day, or was there a loose or ad hoc plan?”

These discussions and questions allowed all visiting groups to be readily categorized by the nature of the group, their prompting objectives for the day’s activities, and the nature of the plan or expectations for the day.

This method was repeated at the large Australian museum. Semi-structured interviews were conducted with 158 individuals in 62 groups.

Our goal was to verify the nature of observed groups, the nature and degree of structure for a group’s activities before and after, as well as the prompting objective for the groups’ decisions to attend the museum, respective motivations, and the decision processes associated with the groups’ activities.

The most common prompting objectives identified included (1) a desire to socialize with friends or a date, (2) the need for an activity to provide and undertake with a visitor from out of town, (3) an activity to undertake with “the kids” who were not at school (on vacation, on the weekend), and (4) a desire (inferred) to have something to talk about or boast about to friends.

Further observations were made at other leisure and tourist activity sites including 2 stage theatres, 2 movie theatres, 2 sporting events, and 10 restaurants in the USA (LA and NY) and Australia (Melbourne). These observations were consistent with earlier observations and conclusions. Virtually all people were observed as members of discernible groups. Group types were also consistent.

Additional interviews were planned but were prevented by the COVID-19 pandemic.

Conclusions from all observations and interviews were consistent and included:

  1. Groups attend museums and undertake leisure and tourist activities that compete with museums as groups not, or only very rarely, as individuals.
  2. Groups are motivated to undertake the leisure activity by a shared prompting objective.
  3. The museum, or competing activity, is selected based on the suitability of the activity to satisfy the prompting objective, an interaction between group members regarding the choice of the destination as an option, and its perceived novelty value, how conducive it is to the desired social interaction (e.g. social value), the potential for the activity or destination to confer status or storytelling value, as well as the specific interest to any individual participants.
  4. While not universally discussed in the semi-structured interviews, the observed near-exclusive attendance by groups of people and many specific comments by subjects, supports the conclusion of EP research that the decision process associated with attendance at museums is a social or group function not the reflection of individual member’s personal preferences or a conscious consideration of the economic or didactic “value.” While didactic value was raised by some subjects (generally parents of children), in light of the EP research, it is equally reasonable to attribute this to a subconscious judgment of how others in the parent’s social or peer groups would judge the activity. Various discussions involved statements clearly aligned with the EP research regarding the primary motivations for the individual decisions of group members being a desire to belong and opportunities to socialize (“something cool to do with friends”), novelty (“we hadn’t been before”), and status in the form of something to boast about (“I wanted a photo in front of the Warhol to show my friends”).

Given this and the EP research, museums would be well served to consider the market as a collection of types of organic pairs and groups rather than of individuals. Further, that these groups can be most effectively segmented by considering their prompting objective. In short, it’s not solely or even primarily about the individual “love of art / love of [subject]” but rather the desire of groups to share experiences or tell stories. Rather than a negative, this is an opportunity to increase the general level of art or subject appreciation in the community by providing experiences conducive to these forms of value sought by groups and thus greater interaction with the museum and its content.

Equally important, it is clear that a museum’s competition is not other museums but other leisure activities that appeal to these different types of groups and forms of value as well as satisfy the prompting objectives and forms of planning or expectation setting for a day. A didactic perspective can add value, enhance status, and potentially enhance self-identity, but a pure focus on the traditional view of a museum’s “purpose” is likely to result in continued erosion in attendance and an inability to attract new visitors which require attracting groups making a collective decision.

Given the EP and tourism research showing an innate drive for novelty and the interplay of self-identity and pre-existing stored patterns of memory with engagement, it is also clear that offering visitors a choice of different experiences with content relevant to the individual given their socio-cultural background as well as experiences that regularly change and thus provide novelty value on each visit would be a beneficial approach for museums.

The primary motivation for all decisions, however, appears to be making decisions that others will admire not ridicule.

6.  Stage 2 – Verifying the ability to measure engagement at multiple levels including post-visit impact

Having established a pragmatically useful definition for engagement and an understanding of what motivates visitors, stage 2 was conducted to validate that:

  1. Engagement can be readily and cost-effectively measured at each level including:
    1. object engagement,
    2. contextual level such as room or gallery, and
    3. at the relationship or whole of experience level, which is most important for determining both social impact and a museum’s ability to influence the decision processes of the different types of organic groups that comprise the market.
  2. Such measures of engagement reflect changes to the visitor experience made by a museum; and
  3. Thus confirm that action to directly improve engagement at the various levels, generate public endorsement and thus would attract new audiences by influencing the social decision processes of the various organic peer and social groups that represent the entirety of the market.

Data was reviewed from multiple sources. First, Art Processors is a commercial enterprise that crafts enhanced visitor experiences as well as providing necessary systems to deliver cinematic, narrative, location-aware experiences linking together objects and digital content across individual exhibits or the entirety of a museum.

The company has relationships and provides systems to a broad variety of museums of various types and sizes around the world. At most of these museums, Art Processors has provided enhanced visitor experiences, associated mobile applications, touch tables, and for many, complete exhibit design.

These enhanced visitor experiences are generally universally and freely available to visitors as a downloadable app or via a mobile device provided on-site. Uptake ranges from a low of 12% to a high of 98%.

Enhanced experiences include the ability for consumer visitors to voluntarily take a number of actions that represent freely chosen conscious interaction with specific objects. Interactions, which definitively indicate interaction with an object, include accessing additional information on a specific object, activating rich media or augmented reality associated with an object, favoriting, liking, or disliking an object, or making a comment specific to an object, was extracted.

In addition, to facilitate the experiences, the system utilizes the relative position of the device to objects and thus has a record of the movement of devices as a generalized proxy for visitors as well as the time spent proximate to objects and in rooms or locations. This data, as well as data on the dates of publishing events representing changes to the experiences by museums, was reviewed. Overall, this provided a view of millions of discrete museum visits and many hundred publishing events over many years.

In addition, data was obtained from a variety of public online sources. This data consisted of consumer reviews, social media posts, and a tally of the associated unique number of accounts making social media posts specific to museums for which in situ visitor interaction data was also available.

To assess object-level engagement, a normalized value was calculated for each object based on definitive interactions with the object, distinct blocks of content viewed (relevant to the object), in app viewing time, time spent proximate to an object, and time spent in the room of the object by individual sessions representing discrete visits to the museum. These values were weighted to reflect the certainty of their representation of engagement with an object and normalized to provide a consistent and reliable engagement score.

The rolling weekly average engagement score for a representative object is shown in figure 1. The variable horizontal data line is the engagement score of the sample object. The vertical straight lines are the dates of publishing events to the enhanced experience (e.g. new audio, text, tabs of information, etc).

Figure 1. Object engagement score

Rolling average engagement score for an object as well as publish events impacting resultant engagement score.

As can be seen, the first and second publishing events are correlated with significant positive increases in the object’s engagement score. There is also a noticeable dip and subsequent return in the engagement score in the second half of the chart. It was confirmed that this corresponded to the closure and reopening of one of two access paths to the gallery space containing the object. Figure 1 is representative of 271 objects that showed a significant change in scores during the period reviewed taken from the total set of objects for which engagement scores were calculated.

Next, engagement at a room or gallery level was considered. The score is a weighted average of duration in the space, duration in-app whilst in the space, number of tabs or views engaged within the experience in the space, and the number of interactions while in the space. This was then normalized for the number of objects in the space. So all other values being equal, a space with fewer objects would have a higher score compared to one with more objects (assuming duration, tabs engaged, number interactions, etc. were equal for the spaces).

In Figure 2, the variable horizontal data line again represents the rolling average engagement score calculated for a space as a whole. The vertical grey lines are publishing events.

Figure 2. Gallery space engagement score

Rolling average of the engagement score calculated for a gallery or space.

Publishing events in mid-September 2018, February 2019, and March 2019 each produced positive impacts on the engagement achieved by the room. The drop off in February 2020 is attributable to differential access associated with changed conditions caused by the COVID-19 pandemic as is data ceasing in March 2020.

As with Figure 1, the space level engagement score shown in Figure 2 is representative of scores calculated and assessed for 84 total spaces.

Finally, data from publicly accessible sources on public comments made by visitors was assessed. Data was collected from “customer review” websites and social media. Given the EP research indicating that subconscious consideration of what others will think of our choices is a primary influence on our decision processes, public comments are seen as the most definitive and accurate indicator of engagement by the museum as a whole. Importantly, the number of social media followers/friends and “likes” were rejected as a useful measure of engagement for several reasons. First, followers or friends, while indicative of some acceptance by the market, are generally largely inactive in advocating to others about an organization. These measures do not inform the museum of engagement induced by a visitation over time. In addition, neither “likes” or following relationships are as public and influential on other members of a peer or social group as direct, posted, publicly-made comments. As such, publicly commenting on a visit is seen as the ultimate indicator of engagement achieved by a museum relationship as a whole.

Finally, both likes and followers are substantially influenced by variables other than the engagement created by exhibits. To utilize this information, given the radically different volumes of visitors and marketing budgets different museums have, a method was developed to capture posts definitively attributable to a museum or exhibition, identify the number of discrete individuals or accounts making those comments, weight posts that may or may not be attributable to a museum based on the proportion of the appearance of keywords from posts made on-site by individuals who could be identified as tourists by the home country of their account, these values were normalized by the number of annual visitors to the museum, and other factors confirmed as influencing the total number of posts associated with a museum including (but not limited to) such factors as the operating budget, the population of watershed area of the museum, tourist volumes to city the museum is in, etc.

A Visitor Promoter Score thus calculated allows for the overall engagement achieved by different museums to be objectively compared to each other and for overall engagement achieved to be measured.

Figure 3 shows “reviews” posted over time for a specific museum, the publish or launch dates, and the period over which enhanced experiences were made available to the public.

Figure 3A. Online reviews

(Figure 3A shows 5 stars ratings only across several online services. Please see Figure 3B in appendices for all ratings. Pre-MOS is the period immediately prior to the publishing of the initial enhanced experience. Pilot, Ex.1, Ex.2 and Ex.3 show when and the period over which the enhanced experiences were available to the visiting public.)

As can be seen, the addition of the enhanced experiences and subsequent publishing of new experiences in support of new exhibits is correlated with an increase in the public reviews posted by visitors. In addition, the VPS calculated for this museum over the time increased from 10.4 to 17.4. To put this in context, the VPS was calculated for a total of 7 museums including 2 of the most visited museums in the US, 2 of the most visited museums in Australia, 2 medium-sized and 1 small museum. VPS scores for these museums ranged from a low of 2 to a high of 27 (please see appendices for further details). As such, the above increase in VPS correlated to the addition of an enhanced visitor experience and subsequent publishing events is clearly significant.

What is clear from this analysis of data is that engagement can be readily measured and engagement scores calculated for objects, galleries, and museums holistically. Further, these scores directly reflect changes to the context and specifics of the experience. As a result, museum curators and experience designers can take specific actions to increase visitor engagement at each experiential level of object, room, crafted journey or tour, and venue. Further, post-visit impact and public endorsement, the forces most likely to prompt others to visit, can also be cost-effectively measured and influenced by changes to exhibitions and experience elements.

7. Limitations and future research

As with most research, this project and its various components have a variety of limitations and generate substantial opportunities for further research. Increasing the sample sizes of semi-structured interviews as well as the number and diversity of sites at which interviews are conducted would add further value and veracity (noting that the number of interviews and sites was larger than for many studies featuring visitors, which are limited to only 1 or 2 sites). The sample size of observed visitors was substantial across all locations and types of entities. However, observations at non-museum sites could not be followed up with semi-structured interviews to gain further insight into group types, prompting objectives, and the role of specific EPM motivational drives. Additional semi-structured interviews were also planned for the additional museum sites in Australia and the United States that were prevented by the COVID-19 pandemic.

A more robust assessment of the questions and format of the semi-structured interviews would also be an important further step to ensure objective data collection, determine the potential socio-cultural influences, eliminate bias introduced by the questions or researchers, etc.

Online reviews posted by visitors as well as social media posts are known to be influenced by a broad variety of factors from changes to the quality of food and coffee, positive or negative service experiences, and even changes in the surrounding traffic conditions making access to or parking at a museum or location more difficult. While all these factors are appropriately incorporated into the holistic whole of venue consideration of engagement, additional research must be conducted to control for and determine the discrete impact of these different factors to inform optimal decision making about how to optimize object level, exhibition level, and whole of relationship level engagement and to understand their impact on attracting more diverse and new audiences.

This research has shown engagement as indicated by post-visit public commentary can be measured, calculated, and influenced by the museums and curators’ decisions in relation to objects, enhanced experience elements, and exhibitions, the exact impact of different factors requires additional research to determine. In this case, while the associated increase in public commentary reflected in this data may be correlation rather than the result of a causal relationship to the exhibit and publishing events, the earlier stage research showing a direct impact on engagement at the object and room or gallery level makes clear that changes to publishing events and the nature of the visitor’s experience can reasonably be interpreted as impacting whole of relationship engagement. Nonetheless, further research is required to validate the specific causal relationship and determine the specific characteristics which determine influence.

All data collected on the interactions and movements of individual visitors is obtained without any awareness of the nature of the individuals such as personal identification or traditional demographic data. Nonetheless, that data, as well as the data on objects, exhibits, and publishing events from museums can not be made public. Additional research allowing an analysis of engagement data such that differential behavior by different types of individuals would be valuable. Further, while the described methods are sufficiently clear to allow near replication, space does not permit comprehensive details on methods of normalizing and a thorough review of methods and data. True replicability requires publicly available data. As such, it would be my hope that further research may be conducted and made available which includes such access.

8. Conclusion and Contributions

This research paper clearly supports several high-value conclusions:

  1. The volume and richness of EP research directly relevant to museums suggest it should be standard reading for curators, marketers, and museum staff of all types.
  2. We need to re-conceptualize how we think about the market. Rather than thinking it is composed of individuals with relevant characteristics, it is composed of organic groups seeking to satisfy some prompting objective. These groups make a selection from competing options based on its suitability for satisfying that prompting objective and the composite of value it offers as defined by EPM motivational drives.
  3. Engagement, including holistic or whole of relationship engagement, can be easily and cost-effectively measured at all levels.
  4. Given the social or group nature of our decision processes as revealed by EP research, public commentary by others will be the most effective way to attract visitors. As such, while dependent on engagement at more granular levels, Visitor Promoter Score (VPS) as a measure of whole of relationship engagement should be a primary focus for museums.
  5. We need to re-conceptualize how we think about value. Value is not simply defined by price point or convenience but reflects a collection of unique relative outcomes we are motivated to pursue including novelty, social belonging, status, gossip, and more. Substantial value can be offered to visitors through novel changing experiences, a choice to select an experience relevant to their perspective, and by giving them a story to boast about to their social groups. Offering such a combination of forms of value will maximize public commentary and appeal to the widest possible audience.
  6. Engagement of all types reflects changes to visitor experiences made by museums, for good and bad, at all levels. Publishing events associated with enhanced visitor experiences impacted engagement scores for objects and galleries as did changes to access conditions. Further, changes in exhibitions and the addition of enhanced visitor experiences impacted or is correlated with whole of relationship level engagement and Visitor Promoter Score (VPS). As such, regular iterative changes to the visitor experience and experimentation represent a certain path to improved overall results and achieving museum objectives. It provides a guaranteed path to achieving museums’ core objectives through experimentation, iterative enhancement, and the offering of choice.

 

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Appendices

Samples of Data Collected

Tabulation of Semi-Structured Interviews at Museum

Total museum visitors engaged 158
Tourist group or family 41%
Something to do with an out of town visitor 7%
Dating Couples / Couples 27%
Novel venue for group socialising/ dialogue / Friendship Group social activity 13%
Spending time before event (social gathering) 4%
Work meeting (at museum cafe) 4%
Calming location / break from work 3%
Art as therapy <1%
Total 100%

 

Part of a Plan 65%
Part of Specific Plan 14%
Part of simple / flexible plan 51%
Just Museum / No Plan for other activities 35%

 

Made explicit unprompted statement indicating a form of value:
Something to boast about (Status) 6%
Want more changing exhibits (Novelty) 3%

 

Observation Data Theaters, sporting events, restaurants

Individuals Couples Friend Groups Families w/Kids/
Movies 1 0 4 3 0
Movies 1 1 6 6 3
Stage Theater Book of Mormon and Shakespeare in the Park – 100% couples or adult groups

 

Sporting events

Individual Pairs Friend Group (adults) Families Large Groups 6+
Melbourne Cricket Ground (AFL match) 4 17 4 6 4
4 34 18 27 24
Note: Observations were made by being early and observing as people first took their seats.  Observations were stopped once it was crowded as it became impossible to effectively observe behavior and if individuals or all members of groups were definitely part of the observed group. Sample could therefore reflect that individuals come later.
Tennis – Estimated 0 10 10 5 5
Note: detailed notes not transcribed. The key observation, however, is that no individuals were observed and groups of types as predicted were observed.

 

Restaurants

Single Pairs Family w/ children 3+ Friends / Group 3+ Larger Group No Children 6+
LA 1 4 3 2 0 Sushi (monday)
LA 2 1 1 0 0 Persian (tues)
LA 3 5 5 1 0 Mexican
LA 4 7 0 7 2 Sushi Hollywood (Friday)
NY 1 9 4 6 5 Middle eastern hosted dinner (Friday)
NY 2 2 2 1 1 (Thurs)(Harlem BBQ)
Melb 1 5 3 2 1 y14 (Friday)
Melb 2 4 4 1 1 Indian
Melb 3 1 7 3 3 1 Baia di vino (Thursday night)
Melb 4 2 2 2 Thai (Friday)
Total 1 46 27 25 11
Avg. Individuals per 1 2 4 4 6
Total headcount 1 92 108 100 66 367
Individuals entering for take away were not counted at any location.

Only diners at tables were counted. At restaurants with a bar, people at the bar (who appeared to be couples or friendship groups) were not counted. It is likely that there were some individuals at some locations in this context. Also, no hotel or fast food restaurants were sampled.

Figure 3B – All Online reviews

Online ratings of a single museum in context of new experiences

 

Visitor Promoter Score – Holistic Relationship Level Engagement

Pre-enhanced experience Month 1 Experience #1 Month 1 Experience #2 End of Experience #2 Experience #3
Visitor Promoter Score (VPS1) 10.4 16.1 16.6 16.8 17.4

 

Figure 4 – Average Visitor Promoter Score for Seven Museums over 12 Months

Figure 4 Sample of visitor promoter scores across types of museums

 

Average VPS for Seven Sample Museums over 12 month period
Top 5 Large US Museum 11
Top 20 Large US Museum 5
Very Large Aus Museum 2
Medium Aus Museum 16
Medium Aus Museum 27
Large Aus Museum 10
Small Aus Museum 22

 

Paper Details & Author statement

Title

More than numbers: how visitor engagement data can be captured and used to amplify your creativity

 

Author Information:
Authors: Tim Stroh
Affiliations: Art Processors Pty. Ltd.

Royal Melbourne Institute of Technology (RMIT) Melbourne Australia

Corresponding author: Tim Stroh
Email: tim.stroh@artprocessors.net

timothy.stroh@student.rmit.edu.au

LinkedIn: linkedin.com/in/timstroh
ORCiDs 0000-0002-3955-0267
Author Declaration: I confirm that no other persons satisfy the criteria for authorship.
Conflict of interest statement: Portions of this research were funded by and the author is an employee of Art Processors Pty Ltd. The author has previously published on the topic of evolved psychological mechanisms (EPMs) and has a book commercially available on the subject of EPMs. This research was conducted independently of the author’s Ph.D. program.
Author Bio: Tim Stroh is a successful serial entrepreneur, senior innovation executive, Ph.D. candidate in the School of Management at RMIT in Melbourne Australia, and head of product strategy for Art Processors.

Key words – Visitor engagement, engagement, evolutionary psychology, motivational drives, museum visitors

 


Cite as:
Stroh, Tim. "More than numbers: how visitor engagement data can be captured and used to amplify your creativity." MW21: MW 2021. Published January 20, 2021. Consulted .
https://mw21.museweb.net/paper/more-than-numbers-how-visitor-engagement-data-can-be-captured-and-used-to-amplify-your-creativity/