Targeting Revenue Leaders for a New Product

Historically, when targeting potential adopters of a new product, firms have tended to focus first on people with disproportional effect on others, often labeled “opinion leaders.” The authors highlight the benefit of targeting customers with high lifetime value (CLV), or “revenue leaders.” The authors argue that targeting revenue leaders can create high value both by accelerating adoption among these customers and because of the higher-than-average value that revenue leaders generate by affecting other customers with similarly high CLV. The latter phenomenon is driven by network assortativity, whereby people's social networks tend to be composed of others who are similar to themselves. Analyzing an agent-based model of a seeding program for a new product, the authors contrast revenue leader seeding with opinion leader seeding and compare the factors that influence the effectiveness of each. They show that the distribution of CLV in the population and the seed size play a major role in determining which seeding approach is preferable, and they discuss the managerial implications of these findings.

[1]  C. Heath,et al.  Where Consumers Diverge from Others: Identity Signaling and Product Domains , 2007 .

[2]  Jacob Goldenberg,et al.  Riding the Saddle: How Cross-Market Communications Can Create a Major Slump in Sales , 2002 .

[3]  Russell S. Winer,et al.  Interactive marketing goes multichannel , 2005 .

[4]  Ruth N. Bolton,et al.  Customer-to-Customer Interactions: Broadening the Scope of Word of Mouth Research , 2010 .

[5]  V. Kumar,et al.  Expanding the Role of Marketing: From Customer Equity to Market Capitalization , 2009 .

[6]  Éva Tardos,et al.  Maximizing the Spread of Influence through a Social Network , 2015, Theory Comput..

[7]  Donald R. Lehmann,et al.  When giving some away makes sense to jump-start the diffusion process , 2006 .

[8]  M. Newman,et al.  Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  William Rand,et al.  Agent-Based Modeling in Marketing: Guidelines for Rigor , 2011 .

[10]  Robert A. Peterson,et al.  Customer Base Analysis: An Industrial Purchase Process Application , 1994 .

[11]  E. Muller,et al.  Decomposing the Value of Word-of-Mouth Seeding Programs: Acceleration vs. Expansion , 2012 .

[12]  Katherine N. Lemon,et al.  What Is the True Value of a Lost Customer? , 2003 .

[13]  V. Mittal,et al.  Geographic Patterns in Customer Service and Satisfaction: An Empirical Investigation , 2004 .

[14]  Dominique M. Hanssens,et al.  Modeling Customer Lifetime Value , 2006 .

[15]  Sunil Gupta,et al.  Customer Metrics and Their Impact on Financial Performance , 2006 .

[16]  Tammo H. A. Bijmolt,et al.  Will It Spread or Not? The Effects of Social Influences and Network Topology on Innovation Diffusion , 2010 .

[17]  Sinan Aral,et al.  Identifying Influential and Susceptible Members of Social Networks , 2012, Science.

[18]  P. Marsden Seed to spread: how seeding trials ignite epidemics of demand , 2007 .

[19]  Vikas Mittal,et al.  The Right Way to Manage Unprofitable Customers , 2008 .

[20]  Lawrence Feick,et al.  A Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood: , 2007 .

[21]  Florian von Wangenheim,et al.  Behavioral Consequences of Overbooking Service Capacity , 2007 .

[22]  J. Algina,et al.  Generalized eta and omega squared statistics: measures of effect size for some common research designs. , 2003, Psychological methods.

[23]  David Godes,et al.  Firm-Created Word-of-Mouth Communication: Evidence from a Field Test , 2009, Mark. Sci..

[24]  C. Bulte,et al.  Referral Programs and Customer Value. , 2011 .

[25]  Wilson C. K. Poon,et al.  Phase behavior and crystallization kinetics of PHSA-coated PMMA colloids , 2003 .

[26]  V. Mahajan,et al.  Innovation Diffusion and New Product Growth Models in Marketing , 1979 .

[27]  M E J Newman Assortative mixing in networks. , 2002, Physical review letters.

[28]  Bruce J. West,et al.  How Social Network and Opinion Leaders Affect the Adoption of New Products , 2011 .

[29]  Chris Volinsky,et al.  Network-Based Marketing: Identifying Likely Adopters Via Consumer Networks , 2006, math/0606278.

[30]  Katherine N. Lemon,et al.  The Customer Pyramid: Creating and Serving Profitable Customers , 2001 .

[31]  Jacob Cohen,et al.  A power primer. , 1992, Psychological bulletin.

[32]  Roland T. Rust,et al.  Will the frog change into a prince? Predicting future customer profitability , 2011 .

[33]  Vijay Mahajan,et al.  An Approach for Determining Optimal Product Sampling for the Diffusion of a New Product , 1995 .

[34]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[35]  A. Galeotti,et al.  Influencing the influencers: a theory of strategic diffusion , 2009 .

[36]  Robert C. Blattberg,et al.  Database Marketing: Analyzing and Managing Customers , 2008 .

[37]  Matthew J. Salganik,et al.  Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market , 2006, Science.

[38]  Christophe Van den Bulte,et al.  Social Networks and Marketing , 2007 .

[39]  J. Goldenberg,et al.  The NPV of bad news , 2007 .

[40]  Aristides Gionis,et al.  Social Network Analysis and Mining for Business Applications , 2011, TIST.

[41]  Miklos Sarvary,et al.  Advertising to a social network , 2011 .

[42]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[43]  Sara B. Soderstrom,et al.  Dynamics of Dyads in Social Networks: Assortative, Relational, and Proximity Mechanisms , 2010 .

[44]  Ted Schadler,et al.  Empowered : unleash your employees, energize your customers, transform your business , 2010 .

[45]  Detlef Schoder,et al.  Valuing the Real Option of Abandoning Unprofitable Customers when Calculating Customer Lifetime Value , 2006 .

[46]  Yogesh V. Joshi,et al.  New Product Diffusion with Influentials and Imitators , 2007 .

[47]  Andreas M. Kaplan,et al.  Unprofitable customers and their management , 2009 .

[48]  Sinan Aral,et al.  Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion , 2010, Mark. Sci..

[49]  Christophe Van den Bulte,et al.  Opportunities and Challenges in Studying Customer Networks , 2011 .

[50]  Thomas W. Valente,et al.  Opinion Leadership and Social Contagion in New Product Diffusion , 2011, Mark. Sci..

[51]  Jennifer J. Argo,et al.  The Influence of Friends on Consumer Spending: The Role of Agency–Communion Orientation and Self-Monitoring , 2010 .

[52]  D. Collings,et al.  Valuing customers , 2005 .

[53]  W. Reinartz,et al.  The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration , 2003 .

[54]  Francis J. Mulhern,et al.  Customer Profitability Analysis: Measurement, Concentration, and Research Directions , 1999 .

[55]  Rosanna Garcia Uses of Agent-Based Modeling in Innovation/New Product Development Research , 2005 .

[56]  J. Goldenberg,et al.  The Role of Hubs in the Adoption Process , 2009 .

[57]  P. Moran Notes on continuous stochastic phenomena. , 1950, Biometrika.

[58]  William Rand,et al.  Evolving viral marketing strategies , 2010, GECCO '10.

[59]  M. Haenlein A social network analysis of customer-level revenue distribution , 2011 .

[60]  Michael Trusov,et al.  Determining Influential Users in Internet Social Networks , 2010 .

[61]  Brian W. Rogers,et al.  Meeting Strangers and Friends of Friends: How Random are Social Networks? , 2007 .

[62]  Jan U. Becker,et al.  Seeding Strategies for Viral Marketing: An Empirical Comparison , 2011 .

[63]  Robert C. Blattberg,et al.  Can We Predict Customer Lifetime Value? Can We Predict Customer Lifetime Value , 2004 .

[64]  Tad Hogg,et al.  Inferring preference correlations from social networks , 2010, Electron. Commer. Res. Appl..

[65]  Sunil Gupta,et al.  Valuing customers , 2007 .

[66]  V. Kumar,et al.  Practice Prize Report - The Power of CLV: Managing Customer Lifetime Value at IBM , 2008, Mark. Sci..

[67]  Robert P. Leone,et al.  How valuable is word of mouth? , 2007, Harvard business review.

[68]  Martin H. Levinson Linked: The New Science of Networks , 2004 .

[69]  Marco Gonzalez,et al.  Author's Personal Copy Social Networks Tastes, Ties, and Time: a New Social Network Dataset Using Facebook.com , 2022 .

[70]  David R. Bell,et al.  Spatiotemporal Analysis of Imitation Behavior across New Buyers at an Online Grocery Retailer , 2010 .

[71]  Dominique M. Hanssens,et al.  Customer Equity: Measurement, Management and Research Opportunities , 2007 .

[72]  E. Dahan,et al.  Preference Markets in New Product Development , 2011 .

[73]  Éric Vernette,et al.  Targeting Women's Clothing Fashion Opinion Leaders In Media Planning: An Application For Magazines , 2004, Journal of Advertising Research.

[74]  Zuo-Jun Max Shen,et al.  Customer Influence Value and Purchase Acceleration in New Product Diffusion , 2012, Mark. Sci..

[75]  Paul DiMaggio,et al.  How Network Externalities Can Exacerbate Intergroup Inequality1 , 2011, American Journal of Sociology.

[76]  John H. Miller,et al.  Complex adaptive systems - an introduction to computational models of social life , 2009, Princeton studies in complexity.

[77]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[78]  Katherine N. Lemon,et al.  The Theoretical Underpinnings of Customer Asset Management , 2002 .

[79]  Lerzan Aksoy,et al.  Undervalued or Overvalued Customers: Capturing Total Customer Engagement Value , 2010 .

[80]  D. Watts,et al.  Influentials, Networks, and Public Opinion Formation , 2007 .

[81]  Peter S. Fader,et al.  RFM and CLV: Using Iso-Value Curves for Customer Base Analysis , 2005 .

[82]  Christian Homburg,et al.  Customer Prioritization: Does it Pay off, and how Should it be Implemented? , 2008 .