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Direct marketing on a social network

Author: Zubcsek, Peter Pal ; Sarvary, MiklosINSEAD Area: Marketing Series: Working Paper ; 2009/33/MKT Publisher: Fontainebleau : INSEAD, 2009.Language: EnglishType of document: INSEAD Working PaperAbstract: Direct Marketing (DM) - sending promotional messages to individual customers - is increasingly used by marketers as a result of the explosive growth of customer databases. Most current methods to calculate optimal budgets for such DM campaigns consider customers in isolation and ignore word-of-mouth communication (WOM). When the customer base forms a network (as is the case in telecom or social network databases) ignoring WOM clearly leads to suboptimal DM budgets. This paper develops a model to help address this challenge. We assume that firms know the network structure formed by customers but do not know (or are not allowed to use) data on individuals' connections. Under this scenario, we compare the optimal campaign of a monopolist to that of firms competing in simultaneous-move or sequential-move games. The analysis provides two key insights: (i) we show that ignoring the existence of WOM leads to significant profit loss for firms and this is more so under competition. In particular, knowing the ``density" of consumer connections is crucial for the design of optimal campaigns. (ii) Competition in DM exhibits strong first-mover advantages and, even in a simultaneous-move game between identical firms, highly asymmetric outcomes are possible. Specifically, at low levels of competition, the game only has symmetric equilibria, while at high levels of competition, one of the firms tends to saturate most of the network. The paper also explores three extensions. First, we generalize our model of social influence and show that our main qualitative insights remain valid. This remains to be the case for a model where DM activity endogenously grows the customer base. Finally, we also examine a somewhat simplified model in which firms know individuals' network positions. In this case, we find that, while targeting is more efficient, competing firms may be worse off than under ``blind' targeting as they have strong incentives to target the same customers.
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INSEAD Working Paper Asia Campus
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INSEAD Working Paper Europe Campus
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Direct Marketing (DM) - sending promotional messages to individual customers - is increasingly used by marketers as a result of the explosive growth of customer databases. Most current methods to calculate optimal budgets for such DM campaigns consider customers in isolation and ignore word-of-mouth communication (WOM). When the customer base forms a network (as is the case in telecom or social network databases) ignoring WOM clearly leads to suboptimal DM budgets. This paper develops a model to help address this challenge. We assume that firms know the network structure formed by customers but do not know (or are not allowed to use) data on individuals' connections. Under this scenario, we compare the optimal campaign of a monopolist to that of firms competing in simultaneous-move or sequential-move games. The analysis provides two key insights: (i) we show that ignoring the existence of WOM leads to significant profit loss for firms and this is more so under competition. In particular, knowing the ``density" of consumer connections is crucial for the design of optimal campaigns. (ii) Competition in DM exhibits strong first-mover advantages and, even in a simultaneous-move game between identical firms, highly asymmetric outcomes are possible. Specifically, at low levels of competition, the game only has symmetric equilibria, while at high levels of competition, one of the firms tends to saturate most of the network. The paper also explores three extensions. First, we generalize our model of social influence and show that our main qualitative insights remain valid. This remains to be the case for a model where DM activity endogenously grows the customer base. Finally, we also examine a somewhat simplified model in which firms know individuals' network positions. In this case, we find that, while targeting is more efficient, competing firms may be worse off than under ``blind' targeting as they have strong incentives to target the same customers.

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