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Quantitative Marketing and Economics

Erschienen in:

27.11.2018

Targeting and salesforce compensation: When sales spill over to unprofitable customers

verfasst von: Sumitro Banerjee, Alex P. Thevaranjan

Erschienen in: Quantitative Marketing and Economics | Ausgabe 1/2019

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Abstract

Targeting selling efforts towards profitable customers is widely known to increase sales and allow firms to charge higher prices. In this paper, we show that targeting of selling efforts may also inadvertently lead to sales spilling over to unprofitable customers when they are not identifiable. Such spillover sales are more likely when the ability of the salesperson and the profitability of target customers are above a threshold. We also show that firms can solve this problem by lowering the sales incentives as well as the price to make their offer unattractive to the unprofitable customers, a strategy commonly referred as screening. When the ability and profitability are both very high, however, the firm is better off allowing sales to unprofitable customers because the cost of preventing sales from spilling over is excessive. This is because the reduction in profits from the target customers that results under screening exceeds the loss from allowing sales to unprofitable customers. Such an accommodation strategy becomes more attractive as the fraction of unprofitable customers in the market decreases. Finally, we show that the spillover problem is even more acute when firms can monitor the selling efforts of a salesperson.

Vorheriger Artikel Dynamic stochastic games with random moves

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The problem of identification of target customers exists even in retail situations. An incident that gained widespread notoriety, happened in August 2013 when a salesperson at Zurich’s Trois Pommes had reportedly refused to show a $38,000 Hermes handbag to a customer (who was later revealed to be Oprah Winfrey), telling her that she could not afford it. Source: http://www.usatoday.com/story/money/business/2013/08/09/a-38000-handbag-not-unheard-of-in-luxury-market/2635871/(last accessed on 13 November 2014).

All the qualitative results of the paper can be shown to remain valid more generally for v_L ∈ (0,c). Details are available in Appendix A.

The utility maximization, given common knowledge of the parameters, is based on rational expectations of selling effort and price using all available information including word of mouth. When the resulting utility is non-positive, we assume that there is neither any interaction between the customer and the salesperson nor any sales. When the resulting utility is positive, note that the customer still needs to experience the salesperson’s effort for the utility to materialize and result in sales.

Note that assuming a Normal Distribution of the error term allows sales to a customer, particularly that of the ‘lows’, to be negative. We interpret negative sales as customer returns. At the level of abstraction where our single (accounting) period model represents one of many repeated stages with the same general characteristics of the model except parameters such as customer valuation, customer returns may include items from inventory carried over from previous accounting periods (Lal and Srinivasan 1993, p.783).

Note that negative aggregate sales may be interpreted as the number of units returned by customers from the previous periods being more than new units purchased by them in the current period. However, Lal and Srinivasan (1993, p. 784) point out that the probability of negative aggregate sales is very small. Here, even in case of the lows, the probability of such negative aggregate sales is lower than 0.5% when n_L ≥ [3σ/ (e − p)]².

If a = 0 (i.e., the salesperson’s ability is zero), it does not make sense for the firm to hire the salesperson. At the other extreme, when a = 1, it can be shown that the firm will be able to induce infinite effort to earn infinite profits. We therefore restrict attention to the realistic case where a ∈ (0, 1).

Note that the demand functions (2) and (3) can be restated in terms of selling time t_i (similar, for example, to Lal and Srinivasan 1993) as $x_{i}=n_{i}\left (v_{i}-p + 2\left (at_{i}\right )^{\frac {1}{2}}\right ) +\varepsilon _{i}$.

The particular form of the salesperson’s utility function we use is u (w) = 1 − exp [−r (w − C (T))].

See, for example, Pratt (1964) and Mas-Colell et al. (1995).

The model assumes, as in the literature (e.g., Inderst and Ottaviani 2009, p. 885), that in equilibrium, the customers are aware of their potential valuation of the information provided by the salesperson. This assumption is based on the commonplace hearsay information about the level of selling efforts that the customers may receive.

As explained in the subsequent paragraphs, in this model any increase in price without a corresponding increase in selling efforts leads to lower sales to the target segment. While the purpose of screening is to prevent expected sales to the lows, its aim is also to preserve sales to the highs. A strategy using a higher price with a lower selling effort reduces sales to the highs more than the alternative strategy using lower effort and a lower price which is the solution to this problem.

It is possible that when customers are heterogeneous in terms of their sensitivities to selling efforts (not in our model) such that $x_{i}^{\ast } =v_{i}+s_{i}e_{i}-p_{i}$ where s_L≠s_H, and v_L ≥ c, the firm may want to serve both highs and lows by offering a menu of discriminating contracts.

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Titel: Targeting and salesforce compensation: When sales spill over to unprofitable customers
verfasst von: Sumitro Banerjee
Alex P. Thevaranjan
Publikationsdatum: 27.11.2018
Verlag: Springer US
Erschienen in: Quantitative Marketing and Economics / Ausgabe 1/2019
Print ISSN: 1570-7156
Elektronische ISSN: 1573-711X
DOI: https://doi.org/10.1007/s11129-018-9208-2