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on a one-to-one basis. Marketers lost touch with their customers in the era of one-size-fits-all mass optimization. Customers became survey responders and focus group participants; it was all about products and channels. However, the need for customer-centric marketing has always been there, it just wasn't practical and cost effective to practice. Digital transformation including web, email, mobile, social, location technologies combined with technologies to store, process, and extract information has significantly changed what is practical and cost effective.

      Predictive marketing is the approach that restores that personal touch by bringing that human sensibility into our digital and offline lives, by focusing on the consumers individually to understand what they did and what they will do next. Predictive analytics, based on machine-learning algorithms, offers enormous leverage to marketers trying to make sense of these actions. Rather than replacing human decision making, machine learning and complex algorithms could help people amplify their intelligence and deal with problems on a much larger scale, something like giving a bulldozer to people used to digging with a shovel.

      I saw the opportunity to solve a problem that a growing number of companies were struggling with, and I decided to disrupt the status quo and solve this problem. In 2006, I founded AgilOne, to bring the power of big data and predictive analytics to everyday marketers with an easy-to-use, yet powerful, cloud-based software platform.

      AgilOne was initially bootstrapped for the first 5 years, then backed by top tier VC firms including Sequoia Capital, Mayfield Fund, Tenaya Capital, and Next World Capital. We are helping more than 150 brands in retail, B2B, Internet, media, publishing, and education deliver relevant experiences across channels. Through complete and accurate customer profiles, predictive insights, and built-in life cycle marketing campaigns, marketers boost customer loyalty and increase customer lifetime value.

      In my spare time, I claim to be an accomplished potter of 28 years, having studied at Rhode Island School of Design under Lawrence Bush during my years at Brown. A native of Turkey, I now live in Los Gatos with my wife Burcak and two daughters, Ayse and Leyla. As I write this introduction, my daughter Ayse, who is a freshman at Castilleja School in Palo Alto, is reading an article about predictive marketing for her math class, which shows how predictive marketing will become mainstream for the next generation.

Dominique Levin

      I credit my education, a combination of engineering school, design school, and business school for my left-brain–right-brain approach to marketing: I have a master's of science (Cum Laude) in industrial design engineering from Delft University in The Netherlands and a master's of business administration (with Distinction) from Harvard University. I recommend all marketers to marry human creativity with technology learning in order to deliver value to customers. Over the past 20 years I have run marketing at companies large and small, on four different continents, targeting businesses and consumers. Above all, I was an early convert to the importance of customer data.

      In 1994 I took my first marketing job: a summer internship in Cusco, Peru. I drove around in a pickup truck to visit local farmers and tally how many would join a local cooperative to process fruits into marmalades and liquors. For my next job, at Philips Consumer Electronics, I was asked to find a way to sell more electronics to girls and women. I mingled with teenagers at local high schools to collect data. Philips launched a product called KidCom, an electronic organizer for girls, and proto-typed TeenCom, a two-way paging device for teenagers. My boss on this project was Tony Fadell, who later became the father of the iPod and iPhone, and who went on to found NEST. In 1997, I relocated to Tokyo, Japan, to work for Nippon Telegraph and Telephone (NTT). All employees at NTT, whether in product or finance, worked one weekend in the company store to meet and serve customers. I recommend such “meet the customer” program to any company as no numbers can totally replace meeting customers face to face.

      In 2000, I moved to Silicon Valley and ran marketing for my first big data company, LogLogic – later acquired by TIBCO Software. For the first time I had access to lots of customer data in digital form. Log files are like the digital video cameras of the Internet. At LogLogic we used this log data to monitor security, but it also opened my eyes to the possibilities of using similar data to better understand and serve customers.

      I went on to work for several other technology companies, including Fundly and Totango, focusing on building highly data-driven marketing organizations. Fundly helps non-profits use social media to raise money. We used data to automate the process from self-service sign-up to fundraising success. Totango offered a predictive marketing solution that monitors customer behavior to identify both promising and struggling customers. In both cases data and predictions helped to accelerate customer acquisition and increase customer lifetime value, while lowering the cost of sales.

      I met Omer in my role as CMO at Agilone, where I got to work with thousands of marketers just like you to figure out how they can best use customer data to delight customers. Omer and I are united in our data-driven and customer-centric approach to marketing. Data and humanistic experiences go hand-in-hand. Our passion for customers has led us to this book.

      In my spare time, I love to travel with my husband and three children and experience people, places, and cultures around the world. I play ice hockey to blow off steam and was once a member of the Dutch national team. I love to work with entrepreneurs and help them make their dreams a reality.

      Acknowledgments

      This book was significantly enhanced by the efforts of Anne Puyt, Barbara Von Euw, Rinat Shimshi, Dhruv Bhargava, Carrie Koy, Joe Mancini, Angela Sanfilippo, Hac Phan, and Francis Brero, who not only work tirelessly every day to help companies be successful with predictive marketing, but who also went above and beyond the call of duty to add their experiences, examples, and wisdom to the manuscript.

      We also want to thank visionary CEOs and CMOs who were early adopters of the predictive marketing approach, specifically John Seabreeze, VP Marketing at Billy Casper Golf; Joe McDonald, SVP Sales and Marketing of Stargas, Eoin Comerford, CEO of Moosejaw; Levent Cakiroglu, CEO of Arcelik; Ersin Akarlilar, CEO of Mavi; Adam Shaffer, EVP Marketing of TigerDirect.

      Additionally, Omer's personal success, the success of AgilOne, and the concepts in this book would not have become a reality without the help from Bonnie Bartoli, Peter Godfrey, and his “adopted sons and daughter” Ozer Unat, Dhruv Bhargava, Oyku Akca, Anselme LeVan, Louis Lecat, Ryan Willette, and Francis Brero.

      We would also like to thank our families:

      Omer would also very much like to thank his wife Dr. Burcak Artun, always believing and encouraging him for challenging the status quo and being patient with his busy schedule.

      Dominique thanks her husband, Eilam, and children Liv, Yanai, and Milo, for their encouragement during the writing process. Similarly, she would like to thank her AgilOne marketing superstars, Chris Field, Johnson Kang, Kessawan Lelanaphaparn, and Angela Sanfilippo for being so independent and professional so she could focus on the book at times.

      Part 1

      A Complete Predictive Marketing Primer

Chapter 1

      Big Data and Predictive Analytics Are Now Easily Accessible to All Marketers

      Predictive marketing is the evolution of relationship marketing defined and practiced by many direct marketers in the last few decades. Predictive marketing is not a technology, but an approach or a philosophy. Predictive marketing uses predictive analytics as a way to deliver more relevant and meaningful customer experiences, at all customer touch points, throughout the customer life cycle, boosting customer loyalty and revenues.

      The rise of predictive marketing is fueled by three factors: (1) customers are demanding a more personal, integrated approach as they interact with marketing and sales through many channels, (2) early adopters show that predictive marketing delivers enormous value, and (3) new technologies are available to capture new and existing sources of customer data, to recognize patterns, and to make it easier than ever to use customer data at the intersection of the physical and digital worlds.

      Predictive analytics is a set of tools and algorithms used to make predictive marketing possible. It is an umbrella term that covers a variety of mathematical and statistical techniques to recognize patterns in data or make predictions

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