Technological advancements and social challenges ... - IngentaConnect

Technological advancements and social challenges for one-to-one marketing Danielle Fowler and Dennis Pitta University of Baltimore, Baltimore, Maryland, USA, and

Richard C. Leventhal Ashford University, Clinton, Iowa, USA Abstract Purpose – The purpose of this paper is to investigate the effects of advancements in technology on the practice of one to one marketing. Design/methodology/approach – The paper presents the results of analysis of reported advancements in information technology, social media, and their effects in identifying consumer preferences and consumer identity. Findings – The proliferation of social media, online communities and mobile communication have generated amounts of consumer data of interest to marketers. Simultaneously, technology to collect and analyze the data have improved greatly. The result is insight into the preferences of individual consumers and the ability to implement one-to-one marketing with unprecedented effectiveness. However, countervailing forces exist that attempt to limit the use of that consumer data. Research limitations/implications – One limitation is the reliance on published sources of technological advances. While the information seems representative of state of the art practiced in industry, unpublished, proprietary technology may exist that might re-characterize the potential for information exploitation. Practical implications – Marketers now have many information sources and analytical tools to implement the one-to-one marketing concept and can do so with a higher degree of effectiveness than previously. Originality/value – To date, few, if any, academic studies have been done that link technology, one-to-one marketing and the resistance to incursions on consumer privacy. Keywords Social media, Privacy, Cloud computing, Customer relationships, Mobile applications, One-to-one marketing Paper type General review

Parallel to the technological developments that have refined the implementation and theory of one-to-one marketing, there have been increasing concerns for the encroachment of this approach on consumers’ privacy (Pitta, 1998).

An executive summary for managers and executive readers can be found at the end of this article.

Introduction Peppers and Rogers (1993) popularized the idea of one-toone marketing as the ultimate refinement of market segmentation that promised to yield great customer satisfaction and loyalty and thus provide an unassailable competitive advantage. Using that approach, marketers were supposed to target their offerings so precisely that an individual customer would rate the product or service as “perfect” and consequently minimize concerns about price. A decade ago Peppers and Rogers’ conception was intriguing and logical but implementation was a problem. One issue was learning enough about a particular customer to create a unique product offer. Another was communicating the product’s want satisfiers to the target customer. In less than 20 years, the idea is a reality. The newest iteration of one-toone might well be called “one-to-one marketing 2.0.” It has evolved beyond the original conception to promise even more benefits to marketers and consumers.

One-to-one principles The one-to-one concept was really misnamed. While the goal was to speak to the individual customer with product and service bundles that were somewhat idiosyncratic, the reality was different. The authors recognized that it would be impossible to deal with tens of thousands of customers one at a time in any setting without a costly structural investment in staff. Instead, Peppers and Rogers described the twin processes of one-to-one and mass customization. In reality, the process success required two distinct steps. The first, establishes a one-to-one relationship, which is really an extension of the familiar market segmentation process. To form that relationship, the firm must understand the specific needs of the market segment – ultimately an individual consumer. The requirement includes retaining what was learned and storing additional information for use in the future. The first process requires refining market segmentation dramatically. Instead of moderate to large size segments, oneto-one marketers differentiate and target a focused group of customers with customized products. The next step is to focus on current customers and keep them by enhanced customer service, communication and continued product differentiation. The ultimate objective of customizing a

The current issue and full text archive of this journal is available at www.emeraldinsight.com/0736-3761.htm

Journal of Consumer Marketing 30/6 (2013) 509– 516 q Emerald Group Publishing Limited [ISSN 0736-3761] [DOI 10.1108/JCM-05-2013-0549]

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Technological advancements and social challenges

Journal of Consumer Marketing

Danielle Fowler, Dennis Pitta and Richard C. Leventhal

Volume 30 · Number 6 · 2013 · 509 –516

product/service bundle so carefully that it fits the customer perfectly is the essence of one-to-one marketing (Peppers and Rogers, 1996). The second element is mass customization. Mass customization is really an extension of product differentiation. It recognizes the difficulty of creating a single product for a customer with any level of scalability. Traditionally, product differentiation involved changing the product characteristics to discriminate one firm’s product or products from another’s. The goal is to fit the product to the needs of a target group of customers better. The ultimate goal of mass customization is to link product benefits to the customer’s needs perfectly. This step is difficult to achieve because of the nature and complexity of production as well as the challenge of learning exactly what customers want. True mass customization may be exemplified by the work of a sculptor who creates a mold to cast a work of art on commission with permission to duplicate it. If others want the same design as well, it can be recast using the same mold and the fixed costs can be spread over the production run. Without the ability to sell copies of the artwork to others, the burden of design and production focused on a single item would make productivity low and expense high. Peppers and Rogers (1997) linked forming one-to-one relationships with mass customization. They cautioned that it would require a fundamental change in how the business is organized and run. They highlighted the vital role of information technology which makes one-to-one marketing possible. In order to achieve mass customization, the organization must track large volumes of data well. Insufficiently deep or well organized technological resources prevent one-to-one relationship building. Their work was visionary and predated social media like YouTube which posted its first video on April 23, 2005 (Odden, 2010), or Facebook which was started on February 4, 2004 (ReadWriteWeb, 2009).

to identify consumers with the highest lifetime customer value, they can try to maximize the profitability of their efforts (Zeithaml et al., 2001; Rust et al., 2004). Identifying those who will never purchase their products, allows companies to stop spending money and effort trying to win them over. They simply will not purchase. Analogously, learning which customers are non-profitable allows companies to stop serving them and concentrate on those that are. It is also important to learn who are the loyal customers. More important, it is vital to learn who are highly satisfied brand ambassadors, those customers who represent the brand and promulgate its value. Brand ambassadors represent the best prospects for company success and should be one of the company’s most valued assets. Companies must treat them appropriately to keep their business and their friends’ business sustainably. Social media and the spread of internet connectivity have provided a window into customers’ lives. Today, the information available can be like a tsunami. With users flocking to social media or using free e-mail services like Gmail, companies already learn a flood of information. Typical information items a firm can obtain include e-mail address, lists of favored e-mail contacts (who form another database sometimes termed friends of friends), topics discussed online, subjects the user searches, and others. Evidence suggests that G-mail, in particular, has maximized its potential for information collection. One needs only to see the ease at which users can offer a free G-mail account to friends. Moreover, the service offers great value in terms of storage. Google provides ever expandable storage that is held indefinitely. As of March 1, 2011 it offered over 7 GB of free storage to each user. One other clue is the information panel on the right side of the G-mail screen. It is populated by likely matches to the content of a person’s e-mail message. If one types the name of a retired comedian, London Lee, the ads which appear will somehow be linked to “London.” They may be for vacations to the UK, souvenirs from London, or for the food item, London broil. The matches are not exact but are still valuable for an advertiser, which explains how Gmail can continue to offer free storage and free accounts. Over time, the suggestions seem to be more focused which would enhance selectivity and be more valuable to advertisers.

Implementing one-to-one marketing One-to-one practitioners have provided provocative, insightful, useful, and visionary approaches to marketing. Although the effort requires a shift in direction, developing relationships with customers is fundamentally straightforward. Many companies have been able to reorient their focus successfully (Peppers and Rogers, 1997). In the past, companies made two mistakes in approaching one-toone relationships with their customers. First, they tended to overestimate the amount of change needed to begin the process. Second, they underestimated the degree of enterprise integration required. It requires more than integration within the marketing group. It requires a wholehearted commitment and philosophy dedicated to knowing each consumer and treating each one as the company’s complete focus (Pitta, 1998). Implementing one-to-one requires four basic steps that span the range from gathering information to putting it to use.

Differentiate individual customers Customers have different needs from the firm, and from each other. Moreover, they have different preferences and values from the organization. While lifetime customer value may help determine how much time and investment marketers should allocate to a customer, knowing specific needs determines how successful an organization can be. Knowing a customer’s needs represents the key to keeping and to growing that customer’s business. Knowing how those wants and needs change over time is also important in keeping both consumers and industrial customers satisfied. Developments in technology and social media have made it possible to know customers intimately. The G-mail example demonstrates the empirical results that Google gains every day with every user. As consumers examine their mail, ad links appear in a panel. If a consumer opens one, the choice will be recorded and serve to refine his or her portrait. The picture can become quite nuanced to allow highly specific targeting.

Identify customers Companies must know their customers in terms that are relevant. Thus, they must be able to learn which are the heavy, medium, light and non-users of products, and who has the highest lifetime customer value. When companies are able 510




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Interact with each customer

leading to effective mass customization have reduced the challenge for marketers somewhat (Anderson, 1997). Nevertheless, the potential success of agility still depends on high quality information.

Interacting with customers is another one-to-one marketing fundamental. Every contact or touch point with a customer represents the opportunity to learn more about his or her needs, and value to the organization, as well as to shape customer expectations. At the beginning of one-to-one, direct contact was possible and astute marketers prepared carefully to learn the maximum possible about the individual. Sometimes it was possible to use direct questions. In other cases, consumers made choices from which the firm could infer customer preferences. Traditionally, marketers had to rely on memory and paper records. For example, the local butcher shop owner learned his customers’ preferences and remembered them. Alternatively, the shopkeeper might use cards to store the data but the system was quite personalized. When one-to-one was initially implemented, more sophisticated information technology guided the customer interaction. Databases allowed chain locations to understand a specific customer’s needs by accessing the customer profile. Thus information technology allowed scalability that was not possible when using human memory or written records accessed by humans. Hotel chains led the way with profiles that were accessed in advance of a customer’s stay. The specific hotel then could provide accommodations just as the person preferred. The effect of getting a room with a view, built in Internet connection, a welcoming basket of fruit, or a mini-bar stocked with specific items helped cement the relationship with the customer. Today, the range of interactions and the possibility for unobtrusiveness is greater. Information technology allows easier collection and storage of relevant data. One example is affiliate sharing of information across businesses. In many ways, Amazon has become a platform, on which users can use their Amazon account to buy products from other companies such as Target, who use the Fulfillment By Amazon service to handle inbound, outbound and inventory services. Customers can use their existing profile, which holds credit card details, shipping address and other details. In this way the most dominant single-company profiles (Amazon, Facebook, Apple, and Google) have gained more utility, and the companies have access to much more data about their customers.

One-to-one marketing 2.0 The sea change in information availability and access has driven one-to-one beyond its initial conceptualization. In the 1990s the vision was to isolate valuable customers who could be scrutinized and satisfied. The terms one-to-one and mass customization represented more of a wish than a realizable goal. True, practitioners adapted existing technology to profile their customers and try to predict their purchases. However, they were hampered by the rather rudimentary state of their tools compared to those available now. Moreover, even discerning who customers might be was dwarfed by the difficulty of interacting with them. In reality, retailers trying to form one-to-one relationships had two choices. They either had to wait for customers to approach them or advertise to entice new customers into their stores. Once contact was made, even anonymous customers visiting the store could be identified if they used a credit card to make a purchase. Retailers went further to offer newsletters and non-promotional informational items to entice a customer to reveal his or her name, address and other contact information. Still, the process was rudimentary and resisted automation. Today, the term one-to-one marketing 2.0 is more the product of the revolution in data availability than improvements in the basic concept. To their credit, Peppers and Rogers conceptualized a robust process to get closer to the consumer, to build barriers to dissolving the relationship and to increase satisfaction to the point that consumers do not consider walking away. The new sources of information provide a wider variety of data, might possibly reduce the cost of data collection, speed the collection process, and allow more multidimensional influence. Curiously, there are few recent marketing references to the one-to-one or mass customization topics in the academic literature. However, practitioners seem to be applying the principles in ever increasing numbers.

The nexus of forces: big data, mobility, social media and the cloud

Customize products for each customer This logical step of producing and delivering a product customized to an individual customer is the most difficult principle to put into practice. Its difficulty lies in successful completion of the previous three steps. Knowing enough to design a product is valuable, but being flexible enough to manufacture it as designed may not be possible. In addition, some firms facing foreign competition have decided to focus on efficiency to gain higher quality. That may result in fewer choices. The higher quality may be a benefit, but sacrificing a good fit with customer preferences is a problem. Indeed, customization creates a firm’s biggest competitive advantage. It forces an individual to invest time and energy specifying his needs to a firm. To go elsewhere requires a similar investment to share the same knowledge with another vendor. This creates a barrier to exit from the first firm. In addition, there is a risk that products from the next vendor might not be as satisfying as products from the first (Pitta, 1998). Significant developments in the field of agile product development

A rather recent development that underscores the power of information to satisfy consumers is the revolution in big data (Savitz, 2012; Woyke, 2012). Traditionally, companies have collected information about their customers, competitors, and relevant trends in their environments. Data was expensive and difficult to collect, and the source of data tended to be byproducts of existing relationship with consumers (e.g. in CRMs). As an increasingly large amount of data is available both online and throughout an organization, however, that siloed and limited data view is expanding rapidly. Big data Rather than simply having access to analytics on your own website traffic, organizations now have tools that let them collect and analyze data from all over the internet and beyond, from social media stalwarts like Twitter and Facebook and blogs/vlogs, to phone apps like Angry Birds or Foursquare, to “anonymous” search histories, to the quickly growing 511




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“internet of things” like the sensors you walk past in a mall that can track which path you take when shopping, and where you are mostly likely to stop. “Big data” now includes information such as voice data you leave at a call center, the TV shows you watch with your DVR, the time you spend in online game or entertainment environments like Xbox live, all in addition to Clickstream data from the web – data not tractable to conventional analytics, but for those organizations who understand them, enablers of new products and services and rapid organizational change (Davenport et al., 2012). With this massive increase in data to be mined has come ever more powerful analytical tools and methods. Google famously was able to predict the movement of the Avian flu (H1N1) in 2009 better than the Centers for Disease Control, by testing many different predictive models over their massive search data until they found the best candidates (Ginsberg et al., 2009). Another famous name, Amazon.com, is one of the masters at data analysis for customer relationship management and retailing. Yet big data is only one of four converging technological trends impacting business. Howard et al. (2012) describe these as a “nexus of forces” that define the convergence and mutual reinforcement of four interdependent trends: . social interaction; . mobility; . cloud computing; and . information (such as big data).

connecting the search data with other public information, specifically by matching a rating profile to the internet movie database (IMDb.com). The research demonstrated that rating just six obscure movies out of the top 500 could identify a Netflix user 84 percent of the time (Howard et al., 2012). Facebook privacy is arguably the most difficult to maintain. With the ability of others to tag and post photos, even those without Facebook accounts can be subject to facial recognition analysis and have their activities exposed. These cases are notable for their age: 2006 is an age away in internet terms. Google now (as of early 2013) has seen 30 trillion URLs online, crawls 20 billion sites per day processing 24 petabytes of data to handle 3 billion searches (a petabyte is 1015 or 1,000,000,000,000,000 bytes). Similarly, Facebook generates 130 terabytes in data per day in logs (another 400 terabytes in images); and Yahoo runs 42,000 Hadoop nodes to cope with 200 petabytes of data (Hadoop is a Java-based programming framework that supports the processing of large data sets in a distributed computing environment). Twitter took three years to see the milestone of 1 billion tweets – this now happens weekly. Governments also collect data: in the USA the NSA is reputed to store 1.6 billion e-mails/phone calls a day, and the FCC has 400 different registered data collection initiatives. Does size matter? Howard et al. (2012) argue that it does – that existing privacy solutions such as “notice and consent” work when the potential use of the data collected is known, but that this is rarely the case with big data – it is important precisely because it reveals uses/solutions/products not yet identified. Google can hardly contact millions of search users (if they could find them, itself a task violating their privacy) to ask them retroactively for permission to use their search histories in predicting the next flu outbreak. Asking users to agree to any possible future use of data at the time of collection is similarly problematic. While organizations can point to things like their data governance policies (which often use concepts like the responsibility matrix of “responsible, accountable, consulted and informed (RACI)”, this is still an untested area. While previous privacy breaches like the Netflix and AOL cases have not lasted long in public consciousness, it is possible that a new event could catalyze a stronger reaction, or that overall sensitivity could rise over time. Microsoft, for instance, is presently running an ad campaign (“Scroogled”) against Google that emphasizes the extent to which Google shares consumer data with third parties, generally without their awareness (Harrison, 2013).

The forces combine to empower individuals as they interact with each other and their information through well-designed ubiquitous technology. The upside is that companies can know more about customers and their preferences than ever before. That information allows one-to-one marketing to reach its ultimate potential. The downside is the uncertainty associated with privacy and trust. Privacy is important to consumers, and can strongly affect purchasing choices and brand image. This is because privacy is an antecedent to trust: if consumers do not trust that their information is “safe” they will decline to provide any more of it, whether it is an updated address, the transaction data of a sale, or their “like” profile. Privacy is of course subjective: European norms on individual privacy tend to be higher than the USA, for example. There have also been plenty of cases where online data has proven not to be “private” that have not stopped the proliferation of data. The mechanism individuals often assume will provide them privacy is anonymity, which is neither the same thing as privacy, nor something that can be guaranteed when dealing with online information. Notable cases include that of AOL and Netflix. In the AOL case, 20 million search queries from over 650,000 users were released for researchers to analyze. The data had been stripped of identifying marks such as IP addresses and user names, and yet the NY Times took only days to identify user 4417749 as Thelma Arnold, a 62 year old widow from Lilburn, Georgia. The Netflix case was similar: in 2006 they released 100 million rental records from half a million customers as part of a competition to crowdsource an improved film recommendation system. Again, a user was identified; a mother and closeted lesbian in the US Midwest, who subsequently sued Netflix. Researchers discovered later that the identity had been re-identified by

The cloud A second technological influence with respect to one-to-one marketing is cloud computing. While the idea is now well established, it is not the cloud platform that is inherently useful, but rather the integration that is beginning to take place. Companies like Google, Microsoft, Amazon and Apple are working hard to create ecosystems that consumers will want to inhabit: from storing their e-mail and music collections to enabling video calls (Skype) to sharing files, consumers have central IDs that are becoming much stronger links to their online behaviors, enabling consumer tracking at an unprecedented rate. Instead of a PC login, Microsoft now encourages Windows 8 users to log in with their Microsoft Live ID. Apps bought from the app store live side by side on their work desktops (and their phones) with the company 512




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office suite. When they go home at night they may login to the Xbox network with the same ID, and be able to access the same apps and files as at work. Microsoft can now look for patterns: perhaps customers who suddenly spend hours gaming in the middle of the night when they used to game during the early evening, and start accessing their e-mail from a tablet instead of their phone have recently had a new baby.

to protect consumers from unwanted contacts. The option did not offer blanket protection. Charities and religious organizations were exempt as well as marketers with whom the consumer had a business relationship. Strictly speaking, the rules did not really address privacy. They enhanced a consumer’s right to be left alone. In principle, telemarketers could, if they desired, collect data on consumers they could not contact. Some found a loophole in the rules. Resourceful marketers developed a strategy for establishing relationships with customers. They offered free premiums or product via mail and provided a telephone response method, only a telephone response. If the customer called and requested the item, the company would comply; collecting the telephone number as well as the mailing address. Simultaneously, it established a business relationship with the customer allowing it to use the information collected, legally, to contact the customer, again, legally. Similarly, as with telemarketing, consumer groups and watchdog agencies are creating an outcry for protection. As marketers embraced new technology and requested more, consumer activists warned against the inherent threats to privacy and agencies of the US government acted to restrict their reach. In December 2010, the Federal Trade Commission prompted the creation of a “do-not-track” system that would restrict access to consumer preference information. Shortly afterwards the Obama administration backed an online “privacy bill of rights” aimed at datagathering companies (Thurm, 2011). In the developer world, browser makers responded to the demand for online privacy by building in additional privacy tools. Internet Explorer 9, for instance, released on March 15, 2011, includes two significant new privacy features: tracking protection lists (TPLs) and a do not track (DNT) header that allows users to request that websites not track them. A countervailing force reacted to the perceived threat. The prestigious Competitive Enterprise Institute (CEI) has been staunchly against government regulation of the industry. Wayne Crews, Vice President for Policy and Director of Technology Studies at CEI has testified before the US Congress warning against unneeded and damaging regulation (Crews, 2008). In a recent press release, CEI described the proposed legislation as ill-advised in today’s uncertain economic environment. Echoing other evaluations of government intervention, CEI warned against a “politically defined do not track regime [that] risks undermining targeted advertising, impeding business transactions that occur between strangers, and stifling mobile ecosystems that are barely out of the cradle.” If consumers are encouraged to optout of what CEI describes as for the most part beneficial information collection, the industry will wither and the jobs it creates will disappear; certainly not attractive in the current economy. Moreover, the industry is developing its own privacy protection standards that will make government imposed restrictions unnecessary. Criticizing the “privacy purists,” CEI states that “the right to use information acquired through voluntary transactions is no less important than the right to decide whether to disclose information in the first place” (Competitive Enterprise Institute, 2011). Given the debate on both sides of the issue, it is uncertain whether the bill will pass into law but even so, a regulatory agency might easily draft a “rule” it can apply that accomplishes the same end.

Mobility The cloud integration effect is amplified by the trend to mobility. As more and more people take personal devices into the workplace (the BYOD: Bring Your Own Device trend), the line between personal activity and business activity blurs. While the IT management view of BYOD is divided – company e-mail on personal phones brings liability issues, headaches with security, privacy and confidentiality, backup issues and so on, it often produces new and innovative business practices (sales teams showing a client a new interactive video presentation or real time business intelligence data about a product they are trying to sell, or the artist who can now accept credit card payments for her work at art festivals using nothing but her phone and Square). The amount and variety of data flowing through mobile devices is accelerating faster than in any other sphere. Social media Social interaction networks continue to grow, and as with the cloud and mobility trends, offer one-to-one marketing opportunities by virtue of the convergence and integration of social ecosystems. Sites like YouTube, Twitter and Facebook are becoming a standard part of communication and have changed the way that people live (Godin, 2005). Howard et al. argue that social technologies both drive and depend on the other three Nexus forces: (1) Social provides an important need for mobility. Accessing social networks is one of the primary uses of mobile devices and social interactions have much more value when they are possible wherever the user is located. (2) Social depends on cloud for scale and access. Social networks benefit from scale, the kind of scale that is really only practical through cloud deployment. (3) Social feeds and depends on deep analysis. Social interactions provide a rich source of information about connections, preferences and intentions. As social networks get larger, participants need better tools to be able to manage the growing number of interactions, which drives the need for deeper social analytics (Howard et al., 2012). Individually, the four nexus forces of technology are disruptive and innovative. Collectively they are revolutionary in their power to bring about business and societal change.

The push for privacy Few would argue that consumers do not deserve the right to have their personal information held closely. For example, recent concerns in the health care industry have led to laws preserving patient privacy. There are other examples that serve as analogs to the online data gathering situation. In the past, when telephone marketers (telemarketers) used new technology that preventing consumers from ending a call by hanging up the phone, it created such a level of consumer outrage that the US government created a do not call option 513




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How did it happen and where is it headed?

stores send him customized messages. In the movie, they appear to be aural and are heard clearly by the audience. For ordinary consumers passing the same stores, one might imagine that they would hear and respond to an offer they liked. This scenario is possible today, with the use of RFID tags or with geolocation data. While RFID tags are typically “killed” at the point of sale, due to strongly voiced privacy concerns (particularly in Europe), active tags could indicate to businesses in the mall the products a person is wearing or carrying. Targeted ads could then be sent to their phones as they walk through the mall. Less sophisticated “opt-in” versions exist as apps now: for instance, LivingSocial’s mobile app “Instant Deals” feature allows you to look at your phone and see which nearby businesses offer LivingSocial members special pricing. All you have to do to get the deal is to visit the business and show your phone to the store. The scenario is appealing to marketers and is just one form of offer customization and communication possible when based on a sophisticated one-to-one consumer profile. The question remains whether actions by governments to restrict data gathering will be imposed. If they are, the restrictions might allow a loophole like that in the current “do not call list.” Alternatively, they may be more draconian and restrict data gathering severely. One might speculate that marketers will meet the challenge, and succeed. However, the link between One-to-one Marketing 2.0 and data gathering technology will be changed, with possible negative effects on marketers, and in terms of richness of choice, on consumers.

Like most good marketing ideas, if there is potential for profit in one, someone will try to develop it. Marketers realized the potential and soon identified the technology needed to get the right information. As a result, there has been a great investment in companies that make programs that track data (Thurm, 2011). Since 2007, venture firms as a group have invested $4.7 billion in 356 online-ad firms (Thurm, 2011). In 2010, the amount increased 29 percent over 2009 to more than $1.1 billion. The level of investment may be a bit too high with predictions of an industry shakeout. However, the level of investment is set against a background of the privacy concerns and possible government moves noted above. Data tracking companies are going ahead with their operations. Notably, the Wall Street Journal investigative report has revealed that the top 50 US websites collectively installed thousands of “cookies” and other tracking technologies on people’s computers in 2010. One goal was to build sophisticated profiles of people based on their personal activities and to track them in real time (Thurm, 2011). Despite the revelations venture capitalists continue to invest. Several reasons exist. First, start-up costs are relatively modest. For a few million dollars, a company can experiment to see if there is potential. If the test is successful, the organization can seek more funding. If not, the loss will be manageable. Another reason is the size and growth of the internet advertising market: it is $26 billion-a-year and growing. Americans, arguably in one of the most connected societies in the world, now spend 28 percent of their media time online. At the same time, internet media spending is much lower, totaling only 13 percent of total ad spending (Thurm, 2011). Examining the nature of data gathering startups that are getting much of the investment reveals that their goal is to target individual consumers. That level of selectivity is attractive to advertisers who hope to target only those individuals who will respond to their ads. The consequence is a trend by practitioners to look for experts who can refine where to run ads, verify which specific users have seen the ad and help target ads to individuals. There is also an established literature looking at consumer/ user behavior online, including on social networking sites. Several studies have shown that while the dangers of putting too much personal information online have received a great deal of attention in the media in recent times (Lewis et al., 2008), and that users of such sites actively manage their privacy (Utz and Kra¨mer, 2009) at the same time they place detailed personal information on their profiles. This phenomenon has been described as the privacy paradox (Barnes, 2006).

References Anderson, D.M. (1997), Agile Product Development for Mass Customization, Irwin Professional Publishing, Chicago, IL. Barnes, S.B. (2006), “A privacy paradox: social networking in the United States”, First Monday, Vol. 11 No. 9, available at: http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/ fm/article/view/1394/1312 (accessed 19 March 2011). Competitive Enterprise Institute (2011), “Congress should reject privacy-killing do not track mandate: ‘do not regulate’ a superior approach to privacy protection”, March 16, Competitive Enterprise Institute, Washington, DC. Crews, W. (2008), “Privacy implications of online advertising”, (Vice President for Policy/Director of Technology Studies Competitive Enterprise Institute), Testimony before the Committee on Commerce, United States Senate – Privacy Implications of Online Advertising, July 9. Davenport, T.H., Barth, P. and Bean, R. (2012), “How ‘big data’ is different”, Sloan Management Review Magazine, Vol. 54 No. 1, pp. 43-46. Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S. and Brilliant, L. (2009), “Detecting influenza epidemics using search engine query data”, Nature, Vol. 457, pp. 1012-1014, 19 February, published online 19 November 2008; corrected 19 February 2009. Godin, S. (2005), “All marketers are liars”, Sales & Service Excellence, Vol. 5 No. 7, pp. 1-2. Harrison, L. (2013), “Update: Microsoft renews its ‘scroogled’ ads, claims they’re working”, KQED, April 9, 2013, available at: http://blogs.kqed.org/newsfix/2013/04/ 09/microsoft-refocuses-scroogled-attack-ads-on-android/ Howard, C., Plummer, D.C., Genovese, Y., Mann, J., Willis, D.A. and Smith, D.M. (2012), “The nexus of forces: social, mobile, cloud and information”, Gartner, Inc. Report G00234840, 14 June 2012, available at: www.

Implications for marketing Previously, we posed the question, “Now just imagine if a marketer could only access that data. What kind of advantage would that convey?” The answer is not unlike the situation portrayed in the Tom Cruise movie, Minority Report. Arguably, that movie may haunt consumers but we marketers see promise and potential. One of the scenes shows the hero trying to evade surveillance. He moves through a crowded shopping mall until technology identifies him via facial recognition. He is then offered specials deals by each shop he passes. They seem to be customized for him and his buying preferences. Somehow the 514




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gartner.com/resources/234800/234840/the_nexus_of_ forces_social_m_234840.pdf Lewis, K., Kaufman, J. and Christakis, N. (2008), “The taste for privacy: an analysis of college student privacy settings in an online social network”, Journal of Computer-Mediated Communication, Vol. 14 No. 1, pp. 79-100. Odden, L. (2010), “YouTube was born five years ago and now it’s the fifth largest website in the world”, Search Engine Watch, February 6, available at: http://blog.searchengine watch.com/100206-173401 (accessed 14 March 2011). Peppers, D. and Rogers, M. (1993), The One to One Future: Building Relationships One Customer at a Time, Currency/ Doubleday, New York, NY. Peppers, D. and Rogers, M. (1996), “How do you use them?”, Forbes, 3 June, pp. 132-135. Peppers, D. and Rogers, M. (1997), Enterprise One to One, Currency/Doubleday, New York, NY. Pitta, D.A. (1998), “Marketing one-to-one and its dependence on knowledge discovery in databases”, Journal of Consumer Marketing, Vol. 15 No. 5, pp. 468-480. ReadWriteWeb (2009), “Did Mark Zuckerberg’s inspiration for Facebook come before Harvard?”, ReadWriteWeb, May 10, available at: www.readwriteweb.com/archives/mark_ zuckerberg_inspiration_for_Facebook_before_harvard.php (accessed 9 March 2011). Rust, R., Zeithaml, V. and Lemon, K. (2004), “Customercentered brand management”, Harvard Business Review, Vol. 82 No. 9, pp. 110-118. Savitz, E. (2012), “The big value in big data: seeing customer buying patterns”, Forbes, 25 September, p. 36. Thurm, S. (2011), “Online trackers rake in funding”, The Wall Street Journal, February 25. Utz, S. and Kra¨mer, N. (2009), “The privacy paradox on social network sites revisited: the role of individual characteristics and group norms”, Cyberpsychology: Journal of Psychosocial Research on Cyberspace, Vol. 3 No. 2. Woyke, E. (2012), “BigData within reach”, Inc., Vol. 34 No. 9, pp. 94-96. Zeithaml, V.A., Rust, R.T. and Lemon, K.N. (2001), “The customer pyramid: creating and serving profitable customers”, California Management Review, Vol. 43 No. 4, p. 118.

Xu, H., Teo, H.H., Tan, B.C.Y. and Agarwal, R. (2009), “The role of push-pull technology in privacy calculus: the case of location-based services”, Journal of Management Information Systems, Vol. 26 No. 3, pp. 135-173.

About the authors Dr Danielle Fowler is an Associate Professor in the Department of Information Systems and Decision Science at the University of Baltimore. Dr Dennis Pitta is a Professor in the Department of Marketing and Entrepreneurship at the University of Baltimore. Dennis Pitta is the corresponding author and can be contacted at: [email protected] Dr Richard C. Leventhal is a Professor in the College of Business and Professional Studies at Ashford University.

Executive summary and implications for managers and executives This summary has been provided to allow managers and executives a rapid appreciation of the content of the article. Those with a particular interest in the topic covered may then read the article in toto to take advantage of the more comprehensive description of the research undertaken and its results to get the full benefit of the material present. The notion of one-to-one marketing was undeniably revolutionary when first mooted. Marketers became eager at the prospect of taking segmentation to an extreme whereby products and services might be customized for the individual customer. However, enthusiasm was tempered by challenges such as gaining sufficient information to create the perfect match. In reality, true one-to-one marketing was unattainable. Aiming to provide distinctive offerings to huge numbers of people would never work without massive investment is staff. The real nature of the concept was therefore more a hybrid between one-to-one principles and those of mass customization. The process is described as having two separate stages, the first being to create a one-to-one relationship. Understanding specific consumer needs is the objective during this step, which essentially extends the usual process of market segmentation. A major difference here though is the emphasis on serving a significantly smaller segment than the norm. Having identified and targeted such customers, firms need to communicate, provide superior customer service and ongoing product differentiation in order to satisfy and retain them. Mass customization is the second step where the objective is to create products with attributes that perfectly meet the needs of target customers. Production complexities ensure that this would be no easy task though. Compounding the challenge was the difficulty of establishing precisely what each customer would want. Advocates of fusing one-to-one marketing with mass customization acknowledged that some transformation would be needed with respect to how companies operate. Top of the agenda is having the information technology capabilities need to accurately process considerable amounts of data. Developing one-to-one relationships would be seriously hindered by inadequacies or weak organization in this area. Many firms recognize the need for a shift in focus in order to successfully implement one-to-one. Others have seemingly

Further Reading Angwin, J. and Steel, E. (2011), “Web’s hot new commodity: privacy”, Wall Street Journal, Monday, February 28, pp. A1-A16. Be´langer, F. and Crossler, R.E. (2011), “Privacy in the digital age: a review of information privacy research in information systems”, MIS Quarterly, Vol. 35 No. 4, pp. 1017-1042. Mayer-Schonberger, V. and Cukier, K. (2013), Big Data: A Revolution That Will Transform How We Live, Work, and Think, Eamon Dolan/Houghton Mifflin Harcourt, Geneva, IL. Noyes, K. (2010), “Why Android app security is better than for the iPhone”, PCWorld, August 6, available at: www. pcworld.com/businesscenter/article/202758/why_android_ app_security_is_better_than_for_the_iphone.html Smith, H., Dinev, T. and Xu, H. (2011), “Information privacy research: an interdisciplinary review”, MIS Quarterly, Vol. 35 No. 4, pp. 980-1016. Valentino-DeVries, J. (2010), “What settings to look for”, TheWall Street Journal, December 19, available at: http:// blogs.wsj.com/digits/2010/12/19/what-settings-to-look-forin-apps/ 515




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overestimated the degree to change demanded by the process or have failed to appreciate that the necessary integration of focus needs to be company-wide. The responsibility of acquiring extensive knowledge about each customer extends well beyond the marketing function. Four basic steps of implementation have been identified and include: (1) Identification of customers. The purpose here is to classify customers according to their usage levels. Ascertain who provides the greatest value means that attention can be focused on loyal customers and brand ambassadors rather than on people who are reluctant to buy. With the advent of social media, this task has become less daunting. Firms can easily access such as email addresses, areas of interest, discussion topics and subject searches. (2) Differentiation of individual customers. Intimate knowledge of customers is now more possible than ever thanks to social media platforms. Firms must remain aware that preferences, needs and desires will evolve over time. (3) Interaction with each customer. This is a core principle of one-to-one marketing. Organizations need to appreciate that every contact made with a customer is a priceless learning opportunity in terms of identifying their requirements and the value each individual provides. Technology has simplified this task considerably and data is now much easier to store and access. The practice of affiliate companies sharing information is testimony to this fact. (4) Customization of offerings to each client. Successful execution of the previous three steps is vital if this objective is to be achieved. Manufacturing flexibility will likewise make a difference. Some organizations facing competition aim at superior efficiency and quality but greater difficulty in providing uniqueness for individual customers is one unwelcome consequence. Being able to customize can provide a significant competitive edge, so businesses should take care about decisions that may jeopardize this. If a firm can meet a customer’s preferences, they will be reluctant to go elsewhere because switching to another company will mean repeating the investment in time and energy in order to specify their needs.

correspondingly huge increase in tools enabling firms to analyze this data and take knowledge acquisition about customers to previously unscaled heights. (2) The cloud. According to the authors, integration is the prime asset of cloud computing. Major organizations like Google, Amazon, Microsoft and Apple are creating ecosystems that permit consumers to engage with various services and activities using one central log-in. Any significant patterns can thus be identified by the firms. (3) Mobility. Integration has additional relevance given the explosion in availability and usage of mobile devices. Rapid growth is partly attributable to the range of data these devices can accommodate. (4) Social media. Such networks continue to expand and provide substantial information about consumer “connections, preferences and intentions”. Researchers point out that exploiting the interactions requires companies to develop more sophisticated tools for analysis. Technology enables marketers to access more consumer data than ever before. However, this comes at the expense of heightened concerns about privacy and trust. People naturally demand reassurances that businesses will seek consent and use their information responsibly. But giving consumers notice about data usage is not always possible. The real significance of big data is its potential to point marketers towards novel solutions previously unidentified. High profile violations have not helped and pressure for tighter legislation has risen accordingly. One outcome is web browser builders including new privacy features relating to data tracking. Concern that such developments could be politicized has aroused protests in the USA from the Competitive Enterprise Institute (CEI). Its argument is that enforcing do not track (DNT) measures will stifle targeted advertising and jeopardize business, jobs and choice for customers. Self-policing by the marketing industry is deemed more preferable than government intervention. More controversial is CEI’s claim that firms should be free to use information obtained from “voluntary transactions”. Academics also note the “privacy paradox” whereby consumers take great care with personal details when making online transactions, while including such information on their social networking profiles. Investment in online-advertising firms continues to grow. Data gathering organizations are enticing marketers with the objective of enabling highly targeted advertising that is also cost-effective. Companies are becoming more sophisticated in the quest to customize their offerings. For instance, Fowler et al. mention the possibility of businesses using active RFID tags to identify the products shopping mall visitors are wearing or carrying. Such knowledge would then enable relevant advertisements to be sent to the phones of these people. However, this controversial idea illustrates the challenge facing marketers to secure vital consumer data without inviting further concerns over privacy.

The basic concept of one-to-one marketing has largely remained unaltered. Technology enabling more comprehensive access to consumer data is where the revolutionary aspect of what Fowler et al. term “one-to-one marketing 2.0” lies. Consequently, firms are now able to take the initiative instead of relying on advertising or customers making contact to secure information. Other possible benefits include the potential for speedier data collection and lower costs. Business access to consumer information has been greatly aided by what one scholar has termed a “nexus of forces” consisting of different technological trends which converge and thus increase in potency. These trends are: (1) Big data. Companies now have the tools and means to acquire data from a wide variety of online and offline activities like social media platforms, search histories, voice data and information from such as gaming activities like Xbox live. There has been a

(A pre´cis of the article “Technological advancements and social challenges for one-to-one marketing”. Supplied by Marketing Consultants for Emerald.)

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