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1.1 The future of marketing
Marketing Management (2020)
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Full Length Article
The future of marketing
Roland T. Rust 1
Robert H. Smith School of Business, University of Maryland, 3451 Van Munching Hall, College Park,MD 20742, United States of America
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Article history: First received on June 5, 2019 and was under review for 2 months. Available online 30 August 2019
Guest Editor: Gary L. Lilien
The main thesis of this article is that several long-term trends are reshaping marketing and forcing marketing managers to change radically to keep up. These long-term trends are techno- logical, socioeconomic and geopolitical. Advances in technology, in particular, are having apro- found impact on marketing, resulting in the deepening of customer relationships and the continuous expansion of the service economy. Artificial intelligence, big data, the Internet, and the expansion of networks are creating a revolution in marketing that makes the 1960s- style 4 Ps increasingly obsolete. Compounding the problem for marketers are the socioeco- nomic factors of diversity and inclusion, as well as major geopolitical threats. I explore the na- ture of change, extrapolate marketing practice into the future, and examine the implications for marketing managers, marketing education and academic research in marketing. © 2019 Elsevier B. All rights reserved.
- Introduction
There are three major forces that are changing marketing. These are 1) technological trends, 2) socioeconomic trends, and 3) geopolitical trends. The selection of trends was done on the basisof my experience and judgment as a senior scholar in marketing with a track record of successful prognostication. Of greatest importance, the effects of these trends on marketing are predictable, and point the direction to how marketing must transform itself.
- A history of the future
This is not thefirst attempt to look into the future of marketing. Let usfirst examine a few notable papers that have helped set the stage for our current conceptualization, especially with respectto the impact of technology (Table 1).Capon and Glazer (1987) noted the impact of technology on marketing strategy, which was explored further byBlattberg, Glazer, and Little (1994).Atthe same time, the increasing amount of data made possible by technology resulted in the capability to build mathematical models of marketing phenomena, and catalog empirical generalizations (Bass, 1993;Leeflang & Wittink, 2000). Technology has completely transformed media over the last few decades, as cable TV (Krugman & Rust, 1993) and other personalized technologies led to a relative decline of big media (Krugman & Rust, 1994). The Internet brought the next big change, with many of its profound changes predicted even before the advent of thefirst web browser (Rust & Oliver, 1994). In particular, the Internet and other mod- ern information technologies resulted in deeper customer relationships, facilitating more effective CRM (Winer, 2001)andexpan- sion of the service sector (Rust & Huang, 2014). A truly customer-centered view of marketing (Rust, Moorman, & Bhalla, 2010)is
International Journal of Research in Marketing 37 (2020) 15– 26
E-mail address:rrust@rhsmith.umd
1 Distinguished University Professor and David Bruce Smith Chair in Marketing, and Executive Directorof the Center for Excellence in Service.
doi/10.1016/j.ijresmar.2019.08. 0167-8116/© 2019 Elsevier B. All rights reserved.
Contents lists available atScienceDirect
IJRM
International Journal of Research in Marketing journal homepage:elsevier/locate/ijresmar
the natural result of technology, based on customer equity (Rust, Zeithaml, & Lemon, 2000). I next explore many of these ideas in greater depth, grouping our analysis into the three forces (technological, socioeconomic and geopolitical) listed above. The orga- nization of the paper and a summary of some of its main implications are shown inTable 2.
- Technological trends
The key long-term trends are a) the increasing capability of thefirm to communicate with customers, b) the increasing capa- bility of thefirm to collect and store information about customers, and c) the increasing capability of thefirm to analyze customer information (Rust & Huang, 2014). Today in the 21st century, we have a tendency to think only the latest iPhone is relevant to communication, but we often for- get that the widespread adoption of the original landline telephone greatly improved the ability of the company and the customer to communicate with each other. The advent of the Internet created another leap forward, as the amount of information able to be communicated increased tremendously. The smart phone took this to the next level, as every customer now has the Internet in his/her pocket. The expansion of networks, as typified by developments such as social media, further supercharged communica- tion, and facilitated customer–customer interaction as well as customer–company interaction. A natural result was the increase in the importance of word-of-mouth.
Table 1 Visions of marketing's future.
Authors Publication Primary conclusions Capon & Glazer JM, 1987 Technology as a central factor in determining marketing strategy Bass JMR, 1993 Marketing as a science producing generalizable results Krugman & Rust JAR, 1993 Predicts decline of TV network viewing share as cable TV expands Blattberg, Glazer, Little
Book, 1994 Information technology's increasing impact on marketing
Rust & Oliver JSM, 1994 Pre-dating thefirst web browser, this paper describes the marketing use of an electronic network that resembles the modern Internet Krugman & Rust JA, 1994 Predicts the relative decline of mass media advertising, as a result of new technologies that enable personalization Rust Mktg. Mgmt., 1997
Predicts that the advancement of AI will lead to computers being customers
Rust, Zeithaml, Lemon
Book, 2000 Proposes managing marketing based on customer equity
Leeflang & Wittink IJRM, 2000 Describes how technological advances lead to more marketing modeling opportunities Winer CMR, 2001 Focuses on how the Internet enhances CRM capabilities Rust, Moorman, Bhalla
HBR, 2010 Proposes a truly customer-centered view of marketing, due to technology
Rust & Huang Mktg. Sci., 2014 Explains how information technology grows the service economy
Table 2 Summary of principal trends and their implications.
Trend Implications for practice Implications for education Implications for research 2. Technological trends 2 Expansion of relationships and service
Organize around customers Increased emphasis on relationships and service
Research on how IT improvements drive deeper customer relationships
2 Artificial intelligence Manage AI and HI as a team More emphasis on people skills, less on analytics
New algorithms to serve customers better
2 Big data Personalize, while protecting privacy Train data users, not data creators Adaptive personalization systems, customer reactions to privacy 2 Networks Use networks to scale up learning Classes on complex systems Agent-based models for dynamic systems 3. Socioeconomic trends 3 Discrimination Adopt“group-blind”policies Differentiate discrimination from bigotry
Dynamic models of discrimination effects
3 Inequality of wealth Luxury marketing, marketing to “bottom of pyramid”
Importance of heterogeneity of wealth, not just GDP
Effects of wealth on consumption
- Geopolitical threats 4 Free trade vs. protectionism
Coping with an uncertain international trading environment
Historical study about tariffs How planned economies compete long-term against free-trading economies 4 Seeking the past Move from manufacturing to service Historical study about the shift away from manufacturing
Effect of“propping up”manufacturing
4 Innovation vs. patent trolls
Lobby to create barriers to patent trolls
Study barriers to innovation Optimal government regulation to encourage innovation & discourage trolls 4 Climate change Prepare for massive climate disruptions
Required courses on climate Changing geographic consumption patterns
- As customer relationships become deeper, it becomes essential to manage customers for customer lifetime value (Berger & Nasr, 1998 ;Rust et al., 2000), and manage thefirm to focus on customer equity (Blattberg & Deighton, 1996;Rust et al., 2000;Rust, Lemon, & Zeithaml, 2004). This means extrapolating customer cashflows into the future. Because thoseflows are uncertain, ac- counting practice tends to focus instead on completed current payments. This leads top management and boards of directors to prioritize (certain, immediate) costs over (uncertain, future) revenues, leading to marketing myopia (Mizik & Jacobson, 2007). This marketing myopia may also result in lower compensation for executives who favor customer satisfaction (Huang & Trusov, 2019 ), because satisfaction is reflected mostly in future revenues. One important research project would be to produce better projections of future customer profitability (Rust, Kumar, & Venkatesan, 2011). Another would be to understand better the con- ditions under which top management attaches appropriate weight to future revenues basedon customer relationships (Huang &Trusov,2019).
- With the steady expansion of the service sector, the importing and exporting of service becomes increasinglyimportant (Mishra, Lundstron, & Anand, 2011). Again, technology is playing a transformative role, as advancements in information tech- nology allow even professional services to be exported (e., doctors in India reading electrocardiograms for patients in the US). Research should investigate the conditions that lead a service to be exported or imported. Also, what are the success factors for successful importing and exporting of service?
- We also need research to investigate the skills that will be required of marketingpeople in the fastest growing parts of the ser- vice economy (e., information service). Comparing those skills to the skills thatare required in the declining goods economy, what are the implications for education and training?
- Artificial intelligence
Artificial intelligence (AI), the use of computerized machinery to emulate capabilities once unique to humans, is expected, ac- cording to many experts, to have an even greater impact on business than social media (WeberShandwick, 2016). This section explores the consequences of the AI revolution to marketing, as well as the research opportunities in marketing resulting from AI.
2.2. AI vs. HI When AI takes over a task, human intelligence (HI) is displaced. Loss of tasks for HI inevitably also results in job losses for humans in the jobs that perform those tasks (Huang & Rust, 2018). This has resulted in great concern that AI may result in sig- nificant HI job losses (Frey & Osborne, 2017). We have already seen many physical and/or repetitive tasks assumed by AI. For ex- ample, a modern automobile factory typically involves many AI robots, and far fewer human employees than previously. Telephone automated menus have replaced many customer service employees who used to answer the phone. It has been esti- mated that many human jobs are in peril due to the advance of AI (Ford, 2013). Huang and Rust (2018)note that the development of AI research is proceeding roughly from mechanical to analytical to intu- itive to empathetic. For example, AI is already very good at mechanical and repetitive tasks, but AI has a long way to go to match human empathy. This suggests a series of stages in which AI is replacing HI. A simple formal theoretical model extrapolates these changes into the future (Huang & Rust, 2018). In stage 1, mechanical tasks are assumed by AI, and human jobs that are primarily mechanical decline. We see this, for example, in the decline of manufacturing jobs. In stage 1, HI must emphasize analytics, intu- ition and empathy. In stage 2, which is roughly where we are today, AI beginsto assume analytical tasks. In this stage, HI must emphasize intuition and empathy. In stage 3, intuitive AI becomes good enough to begin to replace intuitive HI. In such a world, HI must then emphasize empathy, resulting in a“feeling economy”(Huang, Rust, & Maksimovic, 2019).
2.2. The feeling economy Marketers (and other business functions as well) are discovering that they spend an increasing amount of their time on inter- personal, empathetic,“feeling”tasks, while AI assumes more of the“thinking”tasks. Empirical analysis using United States govern- ment data confirms that the shift to the feeling economy is already underway (Huang, Rust, & Maksimovic, 2019). That research separates tasks into mechanical, thinking and feeling. Ratings of the importance of thinking tasks are still higher, on average, than those for feeling tasks, suggesting that we are still currently in a“thinking economy,”that values analytical capabilities. The expan- sion of data analytics programs reflects this emphasis. However, the change in task importance from 2006 to 2016 was much greater for feeling tasks than for thinking tasks, suggest- ing that feeling tasks may soon become more important. This conclusion is supported by the fact that average wages for feeling tasks are growing faster than the average wages for thinking tasks. This may be the result of supply and demand, in that organi- zations may befinding it more difficult tofind empathetic employees than analytical ones. The conclusion, drawn from both theory and empirical data, is that we are in the midst of a profound transformation, in which AI competes with HI (and often collaborates with HI (Wilson & Daugherty, 2018)), dramatically changing the skillset that humans need to remain relevant in the workplace. Specifically, empathetic skills will be most important (Huang, Rust, & Maksimovic, 2019 ).
2.2. Computers as customers If AI assumes tasks that were formerly performed by humans, this implies that AI will be making decisions and even making buying decisions. To some degree, this situation already exists (Dawar & Bendle, 2018). If computerized AI is making important decisions, then it is essential to consider computers as customers (Rust, 1997). To this point, computerized decisions (e., page
rank algorithms) have been simple enough to be fairly successfully reverse engineered (Zhu & Wu, 2011). That is, the marketers have tried tofigure out how the algorithms work. It is already the case, however, that AI algorithms are becoming complex enough that reverse engineering, or even explanation, is increasingly difficult. For example, the decisions of“deep learning”neural networks are often very difficult to understand after the fact (Gunning, 2017). In such a case, it may be better to abandon any hope of reverse engineering AI, and simply evaluate AI's behavior, similar to the behavioralist school of consumer behavior (Rust, 1997).
2.2. The singularity Ray Kurzweil popularized the idea of the singularity, in which AI becomes so proficient that it is generally superior to HI in everything (Kurzweil, 2005). In such a world, how can HI survive? Kurzweil suggests that the winning strategy is for humans to become cyborgs (part human, part machine), and in fact we already see manyearly examples of this, ranging from exoskeletons to computer-brain interfaces (e.,Schalk, McFarland, Hinterberger, Birbaumer, & Wolpaw, 2004). A good question is why AI would want any HI part at all, given that it is less proficient. The only clear advantage that HI would have in such a scenario is thatit is, in fact, human. That is, some people may prefer HI to AI even when HI's performance is worse, just because it is human.
2.2. Research opportunities AI represents a profound transformation of the entire business world, including marketing. As a result, thereare numerous op- portunities for important research in this area.
- AI may eventually devise its own algorithms, but for the time being, the“art”of building AI algorithms still requires human as- sistance. Therefore, afirst, obvious, opportunity for AI research in marketing is to develop better algorithms by which AI can be implemented. This should involve not just machine learning and neural networks, but a widevariety of tools from statistics and computer science. There are already notable examples of this in the marketing literature (Chung, Rust, & Wedel, 2009;Chung, Wedel, & Rust, 2016;Dzyabura & Hauser, 2011;Timoshenko & Hauser, 2019).
- As AI develops, there will be job displacement. We need research that analyzes which marketing jobs are being lost, and which are (for the moment) safe.
- Related to the above, we need to know which skills (especially looking at thinking skills and feeling skills) of marketing man- agers are valued, and how that is changing over time. The expectation is that the shift toward the feeling economy will accel- erate, but this has to be documented.
- The idea of computers as customers needs to be explored much more fully. How can we market effectively to AI as the decision maker?
- We need research to investigate how AI is changing the consumer. With an increasing amount of AI at the consumer's disposal (e., smart phones, virtual assistants, etc.) how does this change consumer decision-making? What kinds of decisions are del- egated to AI, and are there decisions that the consumer is uncomfortable about delegating?
- What happens when AI is better than HI at everything? How can human marketing jobs survive? What will that marketplace look like? To what degree will the economy be dominated by AI and less by humans?
- Big data
In recent years there has been an explosion in the amount of data collected about customers. This is the result of three trends in technology—1) advances in communication technology that enablefirms to maintain closer contact with customers, 2) advances in data storage capability that enable a larger amount of customer data to be stored, and 3) advances in computation speed that enablefirms to analyze customer data in a reasonable time frame (Rust & Huang, 2014). The resulting large customer databases have become known as“big data,”and hiring data scientists has increasingly become a priority.
2.3. Standardization vs. personalization The technological advances listed above, and the large customer databases that have resulted from them have inexorably led to smaller segment sizes (Varki & Rust, 1998), and at the extreme have led to segments of size one—also known as personalization. In the manufacturing world, standardization is king (Deming, 1986). Quality in the production of manufactured parts is mea- sured as the extent to which the parts manufactured are exactly the same. This has led to quality movements such as Six Sigma (Harry & Schroeder, 2000), with the very name“Six Sigma”referring to manufacturing tolerances. In service, however, quality is measured as the extent to which customer needs are satisfied, and the heterogeneity of cus- tomers implies that service provided to them should be personalized. The standardization strategy only succeeds to the extent that costs can be reduced. Whereas successful goodsfirms can increase quality and decrease costs simultaneously, through process improvements that reduce manufacturing tolerances and reduce waste (Deming, 1986), successful servicefirms must choose be- tween a high quality, personalization strategy and a low cost, standardization strategy (Anderson, Fornell, & Rust, 1997). With the economy becoming steadily more service-focused over time (Rust & Huang, 2014) this strategic dichotomy is becoming increas- ingly polarized.
2.4. The Internet of Things It isn't just customers who are networking. The Internet of Things (IOT) refers to connections between physical objects, typi- cally with the Internet as a network backbone thefirst article in a major marketing journal on the Internet of things (Ng & Wakenshaw, 2017), and subsequent authors have provided additional insight (e.,Hoffman & Novak, 2018; Novak & Hoffman, 2019;Verhoef et al., 2017). Examples include household appliances that communicate with the factory to order parts or indicate need for repair, and inventory monitors (both in businesses and homes) that can automatically re-order when stocks run low. One central feature of the Internet of Things is that we may consider machines to be both thecustomer and service provider.
2.4. The Internet of Brains A milestone was achieved recently, when researchers successfully connecteda human brain to the Internet, such that informa- tion could be sent both ways (brain to Internet, and Internet to brain) through a physical connection (Wits University, 2017). As multiple brains get hooked up to the Internet at once, this raises the prospect of an Internet of Brains, also referred to as a “brainternet,”in which people can communicate with others directly. For example, one person's memory could be shared with everyone. In addition, a group consciousness could form, in which the network is more than the sum of its parts, similar to what happens in a beehive or anthill. There is also the somewhat scary prospect that such a network might be easier for a central entity (e., dictator) to control. An Internet of Brains would change marketing from focusing on individuals to focusing on the whole, with the probable implication being that marketing becomes moreof a“winner take all.”
2.4. Complex systems Networks tend to be complex systems, in that simple choices and behaviors by individuals mayresult in emergent complex phenomena (Rand, Rust, & Kim, 2018). Modeling the system is not the same thing as modeling its constituent parts individually. One methodology that has become widely used to study the complexity of networks is agent-based models (ABM) (Rand & Rust, 2011 ). That methodology starts from the simple behavior of individual entities, and then catalogs the complex emergent phenom- ena that result. The methodology has already been widely and successfully used to model word-of-mouth networks and new product diffusion (Goldenberg, Libai, & Muller, 2010;Libai, Muller, & Peres, 2013). ABM can model the dynamics of networks that cannot tractably be analyzed using analytical or econometric methods seems ideally suited to investigate the Internet of Things, for example, and might also eventually model the Internet of Brains.
2.4. Research opportunities
- If advertising drives the business model of online companies, and extreme content drives advertising, how should thefirm trade off profits against the social good? How should public policy makers regulate online content forcompanies like YouTube in such a way that the market remains as free as possible, while discouraging the growth of extremism?
- What is the nature of economic loss for closed Internet systems such as China? Commentators have said that a free Internet is vital for economic growth (OECD, 2016), but is that true?
- What marketing efficiencies can result from the Internet of Things? To what degree are consumers willingto entrust the IOT to work for their individual interests? To what point does autonomous action by the IOT increase value tothe customer, and at what point does it become just creepy? What are the tradeoffs between privacy and added utility when the IOT assumes more responsibility?
- What are the dangers posed by an Internet of Brains? Is there a way to design an Internet of Brains such that consumer well- being will be enhanced? What happens when there is a common consciousness or common memory?
- How can ABM best be used to model the IOT? Can ABM be used to model the dynamics of an Internetof Brains?
Socioeconomic trends
Diversity and inclusion
Unlike thefield of Economics, which tends to study social issues from an aggregate point of view, thefield of Marketing pays considerable attention to the heterogeneity of the population. Marketing tends to focus on the effects of social issues on individual consumers. Two important issues that call out for further study are discrimination and the inequality of wealth.
3.1. Discrimination Discrimination is likely to become even more of an issue in the future, because the increasingly widespread migration of people from the less-developed countries to the more-developed countries ensures that the more-developed countries will be sure to have an“under class”for many years, and the immigrants are likely to be more diverse. For example, the United States is currently facing substantial immigration pressure from Latin America, and Europe is trying tofigure out how to assimilate Muslims from the Middle East and Northern Africa. Given the population projectionsfor Africa, people emigrating from that continent are likely to be numerous in all of the developed economies in the coming years (Nathale, Münz, & Migali, 2018). Research has shown that in the short run it may be optimal for a rationalcompany to discriminate in service against consumers who come from groups that are on average less profitable, even if those consumers are of equal quality, and exhibit equivalent objective quality measures (Aigner & Cain, 1977;Phelps, 1972;Ukanwa & Rust, 2019), even if thefirm has no irrational bigotry.
In the long run, thesefindings can reverse (Ukanwa & Rust, 2019). The Ukanwa and Rust work shows that the long-term unprofitability of discrimination depends on an improving quality trend forless advantaged groups—something we generally ob- serve empirically (Goldin, 2014).
3.1. Inequality of wealth Inequality of wealth has been shown to lead to social instability, and also to slower economic growth (Cingano, 2014). From the standpoint of marketing, inequality of wealth implies different opportunities for different wealth levels. At the high end, in- equality of wealth implies that the luxury market becomes important. For example, if we know that 1% of the population has more than 30% of the wealth, as we see in Germany (Vermeulen, 2016), then that 1% needs to be carefully targeted and nurtured. On the other end of the continuum, the“bottom of the pyramid”is also important (Prahalad, 2012). Although the profitpercus- tomer is less, there are so many people in that category that the total profit potential is still large. Income inequality also tends to result in a decline of the middle class. While the middle class is still growing rapidly in someparts of the world (e., China and India) (Sheth, 2011), the middle class is declining in wealthy economies like the United States (Krause & Sawhill, 2018).
3.1. Research opportunities
How should service be designed, in such a way that discrimination is minimized, and long-term profit is maximized?
What government regulations will protect consumers from discrimination, with limited damage to corporate profits?
What characteristics cause minority groups to assimilate faster, and close the income and wealth gaps more rapidly?
What is the most effective way to market to thenouveau richein developing countries? Is their consumer behavior different from the wealthy in more-developed countries?
How can we most effectively market to the bottom of the pyramid? How does access to smart phones (sometimes direct, some- times indirect) make the poorer consumers behave differently from poor consumers in the past?
How should marketers market to Muslims? What changes are necessary to appeal to this growingsegment?
- Geopolitical trends
Marketing is the driver of the economy, which means that macrogeopoliticalissues that affect the economy also have a major effect on marketing. Government policies can have a large impact on suchissues as free trade vs. protectionism, support for de- clining industries, judicial threats to innovation, and climate change.
- Free trade vs. protectionism
International marketing is strongly influenced by the international trade environment, and especially free trade agreements, protectionism, and tariffs. Following the failure of the Smoot–Hawley tariffs of the Great Depression (Irwin, 2017), the world's most advanced economies have moved toward free trade over the last 75years. Currently, the Trump administration's tariff intro- ductions, along with moves toward de-unification in Europe such as Brexit, have disrupted global trade. This impacts not just in- ternational sales, but also the supply chain, asfirms that manufacture across national boundaries, such as most of the car companies, need unencumbered movement across those boundaries. For example, a car that is manufactured in the US may use parts that were produced in Mexico. International marketing is roiled when pricing (and therefore demand) is altered in unfore- seen ways.
- Seeking the past
As the economy of every developed nation moves away from manufacturing and toward service (Rust & Huang, 2014) many manufacturing jobs are lost. That shift is part of a century-long trend thatpoliticians are helpless to affect. That, however, does not stop“populist”politicians from claiming that they will save the manufacturing jobs, oreven the agricultural jobs. However, those jobs are not coming back. Some poorer countries may benefit from manufacturing in the short-run, but as GDP improves, manufacturing becomes too expensive because of wage increases, and needs to be either automated or off-shored. We have seen this play out in mainland China in recent years, as the Chinese economy has advanced. Many items formerly manufactured in China are now manufactured in cheaper countries such as Bangladesh orVietnam. From the standpoint of marketing, the em- phasis needs to move away from goods-based concepts such as the 4 Ps, and toward a conception of marketing that is more re- lationship- and service-based (Rust & Huang, 2014).
- Innovation vs. patent trolls
A free economy works best when innovation is encouraged. This means thatinventors must be able to profit from their inven- tions (e., there should be a working patent system, and theft of intellectual property should be prohibited). Unfortunately, we have seen the rise of non-innovators (“patent trolls”) who seek to shake down the real innovators by“protecting”overly broad patents that have no real value in themselves. This may be discouraging innovation, as, for example, the number of entrepreneurial startups seems to be declining in the United States (Appel, Farre-Mensa, & Simintzi, 2019). For the system to work properly, there
- Take advantage of the inequality of wealth. Extreme wealth inequality provides marketing opportunities. The“bottom of the pyr- amid”should be considered an important market, due to the sheer number of potential customers the opposite side of the wealth distribution is an unprecedented number of very rich people. This ensures that luxury marketing will be an important area of emphasis.
- Avoid seeking the past. Companies should seek to deemphasize their exposure to the manufacturing economy, whichis a shrink- ing part (percentage-wise) of the total economy. Companies should accept that the future economy will be global, service-dom- inated, driven by information, increasingly automated, and will demand abandoning business models and practices that used to be successful and profitable.
- Implications for marketing education
The implications for management, as listed above, change how students shouldbe prepared for a marketing career. Here are some of the major changes that will be required in marketing education:
- Focus curriculum on service rather than goods class and textbook marketing examples should be from the service sector rather than the goods sector, because that is the lion's share of the economy. Conceptualizations such asthe 4 Ps, which focus on transactional sales of physical goods, should be replaced by conceptualizations thathave a relational basis, and focus on service.
- Emphasize STEM skills less, and people skills more the Feeling Economy approaches, AI will assume many of the tasks that cur- rently involve STEM skills. This means that the skills that will be in most demand are people skills such as empathy and com- munication skills. This should be the focus both in curriculum and in admissions.
- Phase in AI as an instructor, AI is used only for mechanical and repetitive instructional tasks, but as AI continues to advance, and develops better analytical and intuitive skills, the opportunity willarise for AI to assume higher-level instructional responsibilities. This may eventually mean a much smaller faculty, as much of the instructional work is done by machine.
- Put more attention on complex, dynamic systems a service world driven by long-term relationships, in a connected environ- ment that includes not just the Internet, but also IOT, the marketing managers of the future will need to be able to understand complex, dynamic systems. The economic concept of staticequilibriumwill give way to understanding dynamicdisequilibrium. Techniques such as agent-based models and other computationally intensive approaches, will be necessary to understand the complexity of such systems.
- Implications for academic research
As the marketing environment changes, many opportunities for research will emerge. Some of the most important and fastest- growing topics are the following:
- Develop new AI algorithms for marketing decisions. Deep learning is in vogue right now as a method for developing analytical AI, but AI's capabilities should not be restricted to any one methodology. Training with vast amounts of data is feasible sometimes, but other approaches that require less data and more understanding are likely to emerge in the future. General intelligence AI, although not yet well-developed, will be a game changer, and fast Bayesian statistical methods, that utilize prior knowledge as well as new data, also have excellent promise (e.,Chung et al., 2009;Chung et al., 2016).
- Monitor the advance of AI in marketing. As AI advances in marketing, where does it provide the most value, and how is that changing over time? Does the use of AI in marketing provide a competitive advantage?
- How do consumers use AI? Businesses aren't the only users of AI. Consumers use AI, too, through such vehicles asAlexa and Siri. How does this affect the way consumers behave?
- Move toward computationally intensive research methods. The price of computation and data storage is declining rapidly, which (from a cost of inputs argument) implies greater use of computationally intensive methods. We can expect simulation-based approaches such as agent-based models, to become more important, and analytical modelingto become less important.
- Develop methods to understand computers as customers. Traditionally the way to do this has been to discover (or reverse engi- neer) the algorithms employed. As AI algorithms become more opaque (as is already happening with deep learning), the algo- rithms are probably better understood through regularities in their behavior, as is currently typically studied inconsumer behavior.
- How do frontline workers team up most effectively with AI? With AI/HI teams becoming more commonplace, we need to under- stand when this teamwork operates effectively, and when it doesn't.
- How does the Feeling Economy affect marketing? As human workers focus more on feeling, what are the implications for how marketing works?
- Which jobs are being (or will be) lost to AI the soonest? We need longitudinal data analysis to see the effects of AI on work tasks and jobs, and to project job trends into the future (e.,Huang & Rust, 2018).
- How can we balance personalizationvs?What information management methods can be employed to maximize the de- gree of personalization, while limiting the loss of privacy?
- Develop adaptive personalization systems personalization systems change the offering(s), over the course of a customer relationship, to personalize better over time. Although some applications of adaptive personalization systems currently exist
(e.,Chung et al., 2009;Chung et al., 2016), there are many potential applications, with most arising from long-term use of in- formation services.
- Understand the Internet of Things are many possible topics to explore, including how people interact with IOT (people to machine), how non-human elements of the IOT interact with each other (machine to machine), and how to optimally build an IOT system.
- Prevent automated discrimination has been shown that AI methods can discriminate against certain groups, even if there is no bigotry or intent to discriminate (e.,Ukanwa & Rust, 2019). Methods need to be developed that can identify such discrimina- tion, and avoid it.
- Research the“bottom of the pyramid”.The world contains a large number of poor people, and marketing needs tofigure out how better to serve their needs.
- Research the luxury market opposite of the bottom of the pyramid is the very rich. Although the numbers are relatively few, the total importance to the economy is substantial. Thus, we need to know how to market effectively in the luxury market.
- Summary
In many ways, the future of marketing will seem discontinuous with the present. Such advances as artificial intelligence, the Internet of Things, and huge leaps in computation and data analysis, will lead to a marketing environment 50 years from now that few would recognize today. Marketing practice, marketing education, and marketing academic research will all be trans- formed to an unprecedented degree. It is the most fun time ever to be a marketing scholar.
Acknowledgments
I would especially like to thank Ming-Hui Huang, with whom I have explored the implications of technology on service in a series of papers and books. Special mention also should go to Gaurav Bhalla, Tuck Siong Chung, PK Kannan, Kay Lemon, Max Maksimovic, Chris Moorman, Rich Oliver, Bill Rand, Kalinda Ukanwa, Jacqueline van Beuningen, Sajeev Varki, Michel Wedel, Valarie Zeithaml, and all of the other research colleagues with whom I have explored these topics. Thanks also to Gary Lilien, Eitan Muller, and attendees at the EMAC Conference for many useful ideas and suggestions. I would also like to thank the authors, editors and reviewers who I have learned so much from over the years.
References
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1.1 The future of marketing
Course: Marketing Management (2020)
University: Hebron University
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