Customers acquired through a referral program have been observed to exhibit higher margins and lower churn than customers acquired through other means. Theory suggests two likely mechanisms for this phenomenon: (1) better matching between referred customers and the firm and (2) social enrichment by the referrer. The present study is the first to provide evidence of these two mechanisms in a customer referral program. Consistent with the theory that better matching affects contribution margins, (1) referrer–referral dyads exhibit shared unobservables in customer contribution margins, (2) referrers with more extensive experience bring in higher-margin referrals, and (3) this association between the referrer's experience and margin gap becomes smaller over the referral's lifetime. Consistent with the theory that social enrichment affects retention, referrals exhibit lower churn only as long as their referrer has not churned. These findings indicate that better matching and social enrichment are two mechanisms through which firms can leverage their customers' networks to gain new customers with higher customer lifetime value and convert social capital into economic capital. One recommendation for the managers of the firm studied is to recruit referrers among their customers who have been acquired at least six months ago, exhibit high margins, and are unlikely to churn.
AllisonPaul D. (1982), “Discrete-Time Methods for the Analysis of Event Histories,”Sociological Methodology, 13, 61–98.
2.
AralSinan, MuchnikLev, and SundararajanArun (2009), “Distinguishing Influence-Based Contagion from Homophily-Driven Diffusion in Dynamic Networks,”Proceedings of the National Academy of Sciences of the United States of America, 106 (51), 21544–49.
3.
ArmeliniGuillermo, BarrotChristian, and BeckerJan U. (2015), “Referral Programs, Customer Value, and the Relevance of Dyadic Characteristics,”International Journal of Research in Marketing, 32 (December), 449–52.
4.
BeamanLori, and MagruderJeremy (2012), “Who Gets the Job Referral? Evidence from a Social Networks Experiment,”American Economic Review, 102 (7), 3574–93.
5.
BenoitDries F., and van den PoelDirk (2012), “Improving Customer Retention in Financial Services Using Kinship Network Information,”Expert Systems with Applications, 39 (13), 11435–42.
6.
BermanAndrew (2015), “Referral Marketing: Harnessing the Power of Your Customers,”Business Horizons, 59 (1), 19–28.
7.
BrownMeta, SetrenElizabeth, and TopaGiorgio (2016), “Do Informal Referrals Lead to Better Matches? Evidence From a Firm's Employee Referral System,”Journal of Labor Economics, 34 (1), 161–209.
8.
BurksStephen V., CowgillBo, HoffmanMitchell, and HousmanMichael (2015), “The Value of Hiring Through Employee Referrals,”Quarterly Journal of Economics, 130 (2), 805–39.
9.
BursztynLeonardo, EdererFlorian, FermanBruno, and YuchtmanNoam (2014), “Understanding Mechanisms Underlying Peer Effects: Evidence From a Field Experiment on Financial Decisions,”Econometrica, 82 (4), 1273–301.
10.
CastillaEmilio J. (2005), “Social Networks and Employee Performance in a Call Center,”American Journal of Sociology, 110 (5), 1243–83.
11.
ChristensenClayton M., and RaynorMichael E. (2003), “Why Hard-Nosed Executives Should Care About Management Theory,”Harvard Business Review, 81 (September), 66–74.
12.
CoverdillJames E. (1998), “Personal Contacts and Post-Hire Outcomes: Theoretical and Empirical Notes on the Significance of Matching Methods,”Research in Social Stratification and Mobility, 16, 247–69.
13.
CraverCarl F., and DardenLindley (2013), In Search of Mechanisms: Discoveries Across the Life Sciences.Chicago: University of Chicago Press.
14.
DierkesTorsten, BichlerMartin, and KrishnanRamayya (2011), “Estimating the Effect of Word of Mouth on Churn and Cross-Buying in the Mobile Phone Market with Markov Logic Networks,”Decision Support Systems, 51 (3), 361–71.
15.
DiMaggioPaul, and LouchHugh (1998), “Socially Embedded Consumer Transactions: For What Kinds of Purchases Do People Most Often Use Networks?”American Sociological Review, 63 (5), 619–37.
16.
DustmannChristian, GlitzAlbrecht, SchönbergUta, and BrückerHerbert (2016), “Referral-Based Job Search Networks,”Review of Economic Studies, 83 (2), 514–46.
17.
FaderPeter S., and HardieBruce G.S. (2010), “Customer-Base Valuation in a Contractual Setting: The Perils of Ignoring Heterogeneity,”Marketing Science, 29 (1), 85–93.
18.
FernandezRoberto M., CastillaEmilio J., and MoorePaul (2000), “Social Capital at Work: Networks and Employment at a Phone Center,”American Journal of Sociology, 105 (5), 1288–356.
19.
GodesAndrew (2011), “Commentary—Invited Comment on 'Opinion Leadership and Social Contagion in New Product Diffusion,'”Marketing Science, 30 (2), 224–29.
20.
GoelSharad, and GoldsteinDaniel G. (2013), “Predicting Individual Behavior with Social Networks,”Marketing Science, 33 (1), 82–93.
21.
GonzalezGabriel R., ClaroDanny P., and PalmatierRobert W. (2014), “Synergistic Effects of Relationship Managers' Social Networks on Sales Performance,”Journal of Marketing, 78 (1), 76–94.
22.
GuptaSunil, and ZeithamlValarie (2006), “Customer Metrics and Their Impact on Financial Performance,”Marketing Science, 25 (6), 718–39.
23.
GusevaAndrew (2008), Into the Red: The Birth of the Credit Card Market in Postcommunist Russia.Palo Alto, CA: Stanford University Press.
24.
GusevaAlya, and Rona-TasAkos (2001), “Uncertainty, Risk, and Trust: Russian and American Credit Card Markets Compared,”American Sociological Review, 66 (5), 623–46.
25.
HaenleinAndrew (2013), “Social Interactions in Customer Churn Decisions: The Impact of Relationship Directionality,”International Journal of Research in Marketing, 30 (3), 236–48.
26.
HaenleinMichael, and LibaiBarak (2013), “Targeting Revenue Leaders for a New Product,”Journal of Marketing, 77 (3), 65–80.
27.
HillShawndra, ProvostFoster, and VolinskyChris (2006), “Network-Based Marketing: Identifying Likely Adopters via Consumer Networks,”Statistical Science, 21 (2), 256–76.
28.
HinzOliver, SkieraBernd, BarrotChristian, and BeckerJan U. (2011), “Seeding Strategies for Viral Marketing: An Empirical Comparison,”Journal of Marketing, 75 (6), 55–71.
29.
HuYansong, and van den BulteChristophe (2014), “Nonmonotonic Status Effects in New Product Adoption,”Marketing Science, 33 (4), 509–33.
30.
IyengarRaghuram, van den BulteChristophe, and LeeJae Young (2015), “Social Contagion in New Product Trial and Repeat,”Marketing Science, 34 (3), 408–29.
31.
IyengarRaghuram, van den BulteChristophe, and ValenteThomas W. (2011a), “Further Reflections on Studying Social Influence in New Product Diffusion,” Marketing Science, 30 (2), 230–32.
32.
IyengarRaghuram, van den BulteChristophe, and ValenteThomas W. (2011b), “Opinion Leadership and Social Contagion in New Product Diffusion,” Marketing Science, 30 (2), 195–212.
33.
JingXiaoqing, and XieJinhong (2011), “Group Buying: A New Mechanism for Selling Through Social Interactions,”Management Science, 57 (8), 1354–72.
34.
KilianThomas, GreulingKathrin, and HennigsNadine (2013), “Communicating Competence in References: A Qualitative Analysis of the Utilization of References in Industrial Marketing,”Journal of Business-to-Business Marketing, 20 (2), 65–79.
35.
KingGary, and NielsenRichard (2016), “Why Propensity Scores Should Not Be Used for Matching,” working paper, Harvard University.
36.
KornishLaura J., and LiQuiping (2010), “Optimal Referral Bonuses with Asymmetric Information: Firm-Offered and Interpersonal Incentives,”Marketing Science, 29 (1), 108–21.
37.
KumarV., PetersenJ. Andrew, and LeoneRobert P. (2007), “How Valuable Is Word of Mouth?”Harvard Business Review, 85 (10), 139–46.
38.
LafleyA.G., MartinRoger L., RivkinJan W., and SiggelkowNicolaj (2012), “Bringing Science to the Art of Strategy,”Harvard Business Review, 90 (September), 56–66.
39.
LeeClarence, OfekE., and SteenburghThomas (2013), “Where Do the Most Active Customers Originate and How Can Firms Keep Them Engaged?” working paper, Harvard University.
40.
LinD.Y., and WeiL.J. (1989), “The Robust Inference for the Cox Proportional Hazards Model,”Journal of the American Statistical Association, 84 (408), 1074–78.
41.
LyonsAndrew (2011), “The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis,”Statistics, Politics, and Policy, 2 (1), 2.
42.
MontgomeryJames D. (1991), “Social Networks and Labor-Market Outcomes: Toward an Economic Analysis,”American Economic Review, 81 (5), 1408–18.
43.
NairHarikesh S., ManchandaPuneet, and BhatiaTulikaa (2010), “Asymmetric Social Interactions in Physician Prescription Behavior: The Role of Opinion Leaders,”Journal of Marketing Research, 47 (5), 883–95.
44.
NeckermanKathryn M., and FernandezRoberto M. (2003), “Keeping a Job: Network Hiring and Turnover in a Retail Bank,”Research in the Sociology of Organizations, 20, 299–318.
45.
NitzanIrit, and LibaiBarak (2011), “Social Effects on Customer Retention,”Journal of Marketing, 75 (6), 24–38.
46.
PallaisAmanda, and SandsEmily (2016), “Why the Referential Treatment? Evidence from Field Experiments on Referrals,”Journal of Political Economy, 124 (6), 1793–828.
47.
PieperJenna R. (2015), “Uncovering the Nuances of Referral Hiring: How Referrer Characteristics Affect Referral Hires' Performance and Likelihood of Voluntary Turnover,”Personnel Psychology, 68 (4), 811–58.
48.
PreisserJohn S., and QaqishBahjat F. (1996), “Deletion Diagnostics for Generalized Estimating Equations,”Biometrika, 83 (3), 551–662.
49.
PrenticeR.L., and GloecklerL.A. (1978), “Regression Analysis of Grouped Survival Data with Application to Breast Cancer Data,”Biometrics, 34 (1), 57–67.
ReichheldAndrew (2006), The Ultimate Question: Driving Good Profits and True Growth.Boston: Harvard Business School Press.
52.
SchmittPhilipp, SkieraBernd, and van den BulteChristophe (2011), “Referral Programs and Customer Value,”Journal of Marketing, 75 (1), 46–59.
53.
SchmoorC., and SchumacherM. (1997), “Effects of Covariate Omission and Categorization When Analyzing Randomized Trials with the Cox Model,”Statistics in Medicine, 16 (1/3), 225–37.
54.
SgourevStoyan V. (2011), “Leaving in Droves: Exit Chains in Network Attrition,”Sociological Quarterly, 52 (3), 421–41.
ToubiaOlivier, and StephenAndrew T. (2013), “Intrinsic Versus Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?”Marketing Science, 32 (3), 368–92.
57.
Van den BulteChristophe, and LilienGary L. (2001), “Medical Innovation Revisited: Social Contagion Versus Marketing Effort,” American Journal of Sociology, 106 (5), 1409–35.
58.
Van den BulteChristophe, and WuytsStefan (2007), Social Networks and Marketing.Cambridge, MA: Marketing Science Institute.
59.
WeiYanhao, YildirimPinar, van den BulteChristophe, and DellarocasChrysanthos (2016), “Credit Scoring with Social Network Data,”Marketing Science, 35 (2), 234–58.
60.
WuytsStefan, StremerschStefan, van den BulteChristophe, and FransesPhilip Hans (2004), “Vertical Marketing Systems for Complex Products: A Triadic Perspective,”Journal of Marketing Research, 41 (4), 479–87.
61.
YakubovichValery, and LupDaniela (2006), “Stages of the Recruitment Process and the Referrer's Performance Effect,”Organization Science, 17 (6), 710–23.
62.
ZhangXiaohang, ZhuJi, XuShuhua, and WanYan (2012), “Predicting Customer Churn Through Interpersonal Influence,”Knowledge-Based Systems, 28, 97–104.
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