WHY THIS BOOK?
As I was watching a movie online just before US presidential election last year, the website displayed an advertisement every ten minutes. Since I had not paid anyone for watching the movie and am used to watching commercials on television, it should not have been unusual to see a commercial every ten minutes or so. The website, however, showed me the same commercial over and over. After about the eighth time, I felt sorry for the poor advertiser (someone advertising for Mitt Romney as presidential candidate) because the effectiveness of the ad had long since dissipated and, instead, an annoyance factor had crept in. I was facing a real-time decision engine that was rigid and was placing an advertisement without any count or analysis of saturation factor. As an aside, I lived in a “swing state” for the fall 2012 US presidential elections, so it is possible the advertising agency for the candidate had decided to saturate the advertisements at my location. I must confess, I am not very politically aligned with either party. However, I do have a curiosity about marketing analytics and how political candidates market themselves. So, I decided to respond to the Obama campaign to compare the two. I was amazed to see a level of personalization in the campaign. Unlike the push campaign from Romney, the Obama campaign team worked hard to collect and document my personal political preferences, and knew how to target his responses personally to me in emails. His 2012 campaign is a grand example of marketing analytics driven by big data, and was studied in detail, even by the Republican Party. The campaign used an interesting mix of big data analytics with many connection points with the voters. The campaign drew heavily on big data analytics to drive email campaigns, television spot purchases, and even in scheduling President Clinton’s visits to battleground counties.1 To compare, I have since subscribed to a couple of other political campaigns, including one for the Tea Party. In most cases, the campaigns are using emails to push what they always did with junk mail, that is, a set of standard messages.
So much for political marketing, how are the consumer marketers dealing with big data driven collaboration with their customers? Figure 1.1 shows a caricature of how someone may initiate their social medial interaction. How would a marketer sense customer need for information and respond accordingly? Let me go back to the advertising on the website, where I was watching the movie. How could the website offer advertisements during breaks, which I would find relevant? For example, the site was well aware of the movie genre I had accessed during several visits to the site. An analysis of this genre could have placed me in several viewing segments. In fact, the same website offers me movie recommendations, which are based on prior viewing habits. The viewing segments could be of tremendous value to the advertisers in advertising decisions. After watching the movie for a while and repeatedly viewing the same advertisement, I decided to take a break from watching the movie to searching for a food processor as a gift to my son. When I returned to the movie, I again faced the same advertisement. I had secretly hoped that my food processor search would conveniently trigger an advertisement for a good food processor to help me in my purchase. By sensing and analyzing my previous web searches, marketers could have offered me appropriate information or promotions, thereby increasing the advertisement relevance for me. This book will show you how a marketer can sense a customer’s needs and respond in real time
Figure 1.1 How was your first marketing exposure to the Social Media? with a campaign that focuses on customer needs and offers a customized campaign for a solution that will meet the need.
As an evangelist for big data analytics, I have been in front of audiences with different levels of maturity and excitement about big data availability and use. These audiences have raised a number of good questions about big data and its impact on marketing, which inspired me to document the brainstorming and ideas discussed in response to those questions. This book covers a set of fundamental questions you may have at the back of your minds. As I have watched the changes that have taken place over the last 35 years, the questions below have reflected my own curiosity about big data. Certainly, the field is rapidly evolving, and I have done my best to highlight the maturity in our collective understanding of the field, which impacts the certainty of our responses.
What has changed marketers’ communication with their prospects and customers? In the early 1980s, in my first year of immigration to the United States, I found in my mailbox a big envelope from American Family Publishers (AFP) with my name printed in a 72-point font, “Arvind Sathi, you have won a ten million dollar a jackpot, you only need to subscribe to the magazines listed here.” I was intrigued that the marketing systems had caught up with me so fast and that they could spell my name correctly, find my address, and offer a chance to win money. However, despite AFP’s attempt at personalization, other people around me received identical packages, and it was ironic that AFP offered the same magazines to everyone! While AFP learned to spell my name and research my address, they did not have a customized set of magazines for my needs. For the big $10,000,000 sweepstakes in 1985, New York state employee Lillian Countryman calculated the odds of winning. Players of the AFP sweepstakes had a 1 in 200,000,000 chance.2 As B-school graduate students, a group of us had a healthy debate regarding how to make such offers appealing to consumers, and we concluded that customization of a magazine list was a better way to attract customers, as opposed to offers for an elusive jackpot. We also realized that the cost of customization at that time was prohibitive, as AFP had no easy way of collecting micro-segmentation information about their target customers. Although the modus operandi has not changed for a number of marketers, there are subtle changes in the wind. Consumers continue to receive a large collection of junk postal mails and emails, but they now have filters for most of it. Based on the breadcrumbs available from consumers, savvy marketers are increasingly fine-tuning their targeting. I am currently in the process of buying a new house. I am amazed to find a new set of catalogs offering me outdoor furniture. While I discard most of the junk mail, I find myself studying these catalogs, marveling at the marketing process at Frontgate for appropriately targeting me as a recipient for their catalog. Many catalog marketers are able to establish a dialogue with their customers, to offer additional information related to items in a catalog, where the customer has shown interest. How do these marketers sense and respond to specific customer needs, and what type of attention are they able to attract from their customers? What are the analytics capabilities that enable these marketers to be so focused and conversational with their customers?
How is marketing research changing with big data and related technological forces? Marketers have been among of the most sophisticated users of social research and have invested a fair amount into gathering data from their customers. In the past, the limiting factor was the number of observations collected for marketing research. National surveys were hard to collect and required a massive investment of time and resources. In addition, surveys collected past recollection of customer choices as reported by the customers. The data was only as good as the sampling technique and size. It relied heavily on the survey administrator’s ability to ask questions, and respondent’s ability to recollect history. Now the floodgates are gradually opening, as what was formerly the wastebasket in corporate information technology (IT) departments and consumer personal computers (PCs) is becoming a gold mine for marketers and market data traders. Big data analysts are lining up with buckets, gathering all the bits they can find anywhere to collect and analyze past events. What do these bit buckets offer to marketers?
How are these new sources of data and advanced techniques for analytics changing the way we conduct research and analyze research data?
What do I do to the decades of investments in marketing partnerships, processes, skills, and technologies? Is it revolutionary or evolutionary change? Marketing received its due share of resources and investments over several decades. In addition, a number of external organizations helped marketers buy the data and the instruments for communications—for example, the prime-time television viewership data. Marketing processes were built to take advantage of the available resources, with a razor-sharp focus on optimizing a set of measurable key performance indicators (KPIs). In any large Fortune 50 organization, there are hundreds of skilled resources, as well as a large number of computing resources dedicated to marketing analytics or sources of data, which feed marketers with the required source information. Over the last decade, we have witnessed the development of a new marketplace. On the one hand, it is changing our current processes and organizations. On the other hand, it is challenging some of the fundamental principles and removing many hard constraints. Instead of buying advertisement space in advance, much of the online advertising spots are being claimed through auction platforms. A new breed of analysts has emerged with a new set of technologies for big data analytics. With a myriad of cloud-based data sources, and third parties offering social media interactions with customers, how do we change our partnerships, processes, skill sets, technology mix, and our decade of investment in marketing science tools and techniques? How do these factors change marketing research, advertising, pricing, and product management organizations? It seems like each evolution of technology seeks a replacement for everything we have achieved to date. How would a marketer continue to evolve these processes as new marketing data vendors show up with clouds and big data?
Is big data a big hype created by a handful of social media companies that will fizzle once customers and marketers understand the privacy implications? What is the longevity of this wave and is there a crash coming? In every presentation I have given, I find a couple of skeptics, someone who is ready to challenge the big data tsunami. How about the new sources of data? Is that not adding a lot of lies from which is hard to extract any additional truth? And how about customer trust? Are we likely to lose our customer base as we eavesdrop on their behavior? What happens if consumers get tired of it and stop using the engines that drive big data? What the skeptics address mostly are the well-known, and well-publicized areas of concern. The market is still maturing and a fair number of processes have yet to be discovered and properly regulated. When the marketers discovered short messaging service (SMS) on the mobile phone, there was a plethora of advertising initiated using SMS. However, the Telecom Consumer Protection Act in the United States and similar laws in many Asian countries have issued new guidelines that impose restrictions on telemarketers using SMS for messaging3 and require explicit opt-in.4 Marketers must conform to these regulations or pay hefty fines. The guidelines give us a glimpse of how regulations will help consumers use technology without runaway misuse. In addition, there is a much greater number of bit buckets, which can be used without sparking any controversial issues. Also, there are ways to use the data, which is fairly legitimate and respectful of consumer privacy concerns. The market has yet to fully mature, as marketers evolve ways to effectively interact with customers using new technologies.
I do not want to understand big data. Can someone explain what it does to marketing? Almost every other book I have read gets to the techniques of big data too fast, without delving into marketing analytics. While there are significant technological advancements, the real changes are sociological and organizational. They are reflected in the hefty market valuations for the new information providers. The organizational relationships are rapidly changing. Consumers have figured out how to fast-forward through the push marketing and avoid any messaging they do not want. Telecom organizations are finding they are at the epicenter of shopping and content viewing, and are very interested in the monetization of their data to retailers. Auto manufacturers are rapidly designing connected cars, which should be aptly renamed “mobile devices.” Insurers would like to offer insurance based on what we eat and how we drive our cars. I am grateful to my editor for pushing me hard to write this book for the marketers and not for the technologists. The lenses this book has applied are those of marketers. The focus is on how changes to the consumers and the environment are shifting the basic function of marketing, and how the analytics will reshape how we market to these consumers.
How about business-to-business (B2B) marketing? Most discussions are about consumer markets. Is there anything changing about B2B marketing? How can big data be applied to B2B marketing? Also, how is big data shared across industries? Corporate marketing is going through its own silent revolution. Marketers and customers are changing how they interact with each other. Social media is radically altering how professionals interact. Industrial research has many more avenues for data gathering. YouTube is rapidly emerging as the platform for corporate messaging and product demonstrations. Blogs are increasingly being used as ways to research ideas or to initiate and promote product buzz. A fair amount of IT marketing is directed to corporate customers. How do corporate marketers keep track of their customers, their needs, competitive activities, and major changes?