Abstract
Intuition suggests that a salesperson should not refer consumers to a competitor for products that they both sell. However, myriad examples reveal salespeople doing just that. The authors study specialist competitor referrals, a sales strategy by which one increases consumers’ purchase likelihood of a focal product (e.g., a painting at an art gallery) by (1) referring consumers to a competitor (e.g., a frame warehouse store) that offers a nonfocal product (e.g., a frame) at a lower price, while (2) stating that the stores differ in their specializations (i.e., the stores concentrate their efforts on different goods). Using a study and survey with salespeople, experimental studies, an incentivized negotiation experiment, and a field study, the authors show that specialist competitor referrals can indeed benefit sellers. Specifically, they build on equity theory to show that specialist competitor referrals increase focal product sales by reducing consumers’ perceived overpayment risk for the focal product via increasing perceived equity in the exchange. The authors also show that competitor referrals for nonfocal products that do not justify the price difference on the nonfocal product are ineffective.
If your competitor isn't really competing with your direct market, you can refer business to each other without anyone losing customers (Zwilling 2011).
Salespeople's beliefs about the efficacy of specialist competitor referrals are mixed, but the use of such referrals is common. Noting a lack of in-depth research on specialist competitor referrals in marketing, we conducted an exploratory study with 145 salespeople across multiple industries to gain some preliminary insights. The results revealed that 71% of salespeople have used specialist competitor referrals for a vast range of products (and nonfocal products), including a $695 sculpture ($100 base), $300–$1,000 beds ($20–$100 sheets), $1,000 televisions ($50 audiovisual wires), and $50 shoes ($15 socks). These salespeople also reported wide-ranging and varying beliefs about the effects of such referrals on sales of focal and nonfocal products and, thus, their potential impact on profits.
The uncertainty regarding the effectiveness of specialist competitor referrals is not surprising. On the one hand, receiving information about the price of a nonfocal product may not affect consumers’ likelihood of purchasing the focal product because it does little to assuage their concerns about the focal product's price. It also could reduce nonfocal product sales for the seller if the information prompts consumers to buy nonfocal products from the competitor (Park 2005). On the other hand, specialist competitor referrals provide valuable information to consumers, including not only different purchase options but also justifications for price discrepancies, on the basis of different specializations (e.g., the seller is an art gallery, the competitor is a frame warehouse store, and both sell frames). Such information could influence consumers, especially when consumers are uncertain about the lowest price for the focal product (i.e., they perceive overpayment risk; Dutta 2012). Because individuals are concerned not only about the value of a product to them but also about equity in the exchange (Darke and Dahl 2003; Kahneman, Knetsch and Thaler 1986), specialist competitor referrals are likely effective, as some salespeople believe them to be, to the extent that they can increase perceived equity in the exchange.
Previous applications of equity theory to salespeople–consumer interactions indicate that increasing consumers’ perceived equity positively influences their perceptions of the product, the salesperson, and the seller (e.g., Swan and Oliver 1991). In what follows, we argue that specialist competitor referrals increase consumers’ likelihood of purchasing the focal product by improving consumers’ perceived equity in the exchange and this shift in perceived equity functions as an informational cue about the store's pricing that helps reduce consumers’ overpayment risk for the focal product. 2 Furthermore, we argue that specialist competitor referrals are effective because the justification they offer for the price disparity (i.e., a difference in specialization) is credible and thus increases consumers’ perceived equity. That is, competitor referrals for nonfocal products without any justification are likely not as effective. To test these predictions, we conduct experiments in different purchase settings (paintings, mattresses), as well as in the field (consumers donating money in exchange for pumpkins).
Our findings contribute to marketing literature in several ways. First, whereas most research on referrals examines consumers who refer other consumers to sellers (i.e., word of mouth; for a review, see Berger 2014), we investigate situations in which salespeople refer consumers to competing sellers. As our salesperson survey shows, specialist competitor referrals are prevalent in the industry but not well understood; therefore, a better understanding and effective use of this sales strategy can improve seller outcomes. We thus contribute to a substantive research domain and offer further insights into how sellers can take control of referrals to benefit directly (Hada, Grewal, and Lilien 2014; Kumar, Petersen, and Leone 2010).
Second, we contribute to equity theory applied to salespeople and consumers. Most research addresses price fairness as an indicator of consumers’ perceived equity, because “consumers usually do not know either seller's cost structure or other pertinent information to determine seller's input accurately” (Xia, Monroe, and Cox 2004, p. 3). We show that specialist competitor referrals can increase consumers’ perceived equity by providing a credible information cue about the seller's structure. As perceived equity has been consistently shown to improve consumers’ purchase likelihood in literature (e.g., Haws and Bearden 2006; Morales 2005), this finding can be efficacious to sellers. Furthermore, by directly providing a credible information cue, sellers do not need to rely on comparing consumers’ transactions with other consumers’ transactions to establish equity in the exchange. This finding is especially important for purchase situations where such comparatives are not easily available, such as when a product is unique or infrequently purchased.
Third, our research provides managerial insights for helping salespeople close deals and create win-win situations for sellers and consumers (Dixon, Spiro, and Jamil 2001). Insights into consumer behavior that can be applied easily are critical to marketing (Grewal and Sharma 1991; Puccinelli et al. 2009), suggesting that these managerial implications are highly pertinent. We also conduct a profitability analysis (see Appendix) that shows the conditions under which specialist competitor referrals are a profitable strategy for salespeople.
We organize the remainder of the manuscript as follows: First, we present a brief literature review on referrals and salespeople's influence strategies. Second, we develop our hypotheses. Third, we present our studies, starting with an exploratory study and survey of salespeople, followed by the experimental studies, and concluding with a field study. Fourth, we discuss the results, account for the profitability conditions of specialist competitor referrals and alternative explanations, and present some implications.
Literature Review
Interactions between salespeople and consumers influence consumers’ purchasing behavior, including how they process product-related information (Sujan, Bettman, and Sujan 1986), their product performance expectations (Grewal and Sharma 1991), and satisfaction (Oliver and Swan 1989). However, these interactions can be challenging because consumers associate salespeople with profit motives, view their actions with skepticism (Brown and Krishna 2004), and actively take steps to evade them (Kirmani and Campbell 2004). Noting such perceptions, as well as unethical uses of influence tactics by some salespeople (Cialdini 1999), research suggests salespeople focus on adapting selling tactics to meet consumers’ needs (Kohli, Shervani, and Challagalla 1998; McFarland, Challagalla, and Shervani 2006) and assist consumers by providing expert information or alternatives (Goff et al. 1997; Harris and Spiro 1981).
To influence consumer decisions, salespeople must follow these suggestions in the context of consumers’ motivations and the information salespeople already have (Mallalieu 2006). However, despite vast amounts of available price information, considerable price dispersion for products may leave consumers uncertain about whether they should purchase a product at a specific price (Salop and Stiglitz 1982). Prices for the same product may vary due to sales promotions, even when provided by the same seller (Darke and Dahl 2003), so consumers come to recognize a range of market prices, which may create uncertainty about where a specific seller lies in that range. As Srivastava and Lurie (2001) show, consumers are influenced by their perception of whether the price they are getting represents a good deal (see also Biswas et al. 2002). This uncertainty about getting the “best” or “lowest” price (for a value of a product) evokes consumers’ concerns that they will pay too much and suffer a financial loss in the exchange (Grewal et al. 1994). This overpayment risk (Dutta 2012) influences consumers’ perceptions of offers by sellers and purchase decisions (Biswas, Dutta, and Pullig 2006) and affects their perception of the value of the offer (Nowlis 1995).
Situations in which consumers perceive overpayment risk are common. For example, in interactions with salespeople, consumers might suffer uncertainty if (1) the product is unique (e.g., a painting), (2) the product has so many variants that it is difficult for consumers to compare prices across stores (e.g., mattresses, watches; Bergen, Dutta, and Shugan 1996; Srivastava and Lurie 2001), (3) consumers believe they can negotiate for a lower price (Blanchard, Carlson, and Hyodo 2016), or (4) consumers are focused on the equitable amount they should exchange for a product (Briers, Pandelaere, and Warlop 2007).
Referrals’ Role in Reducing Risk
Consumers search for information to reduce their price uncertainty (Mehta, Rajiv, and Srinivasan 2003), and referrals are important sources of information. A referral occurs if source A makes a recommendation to recipient B to purchase from source C (Hada, Grewal, and Lilien 2010; Spurr 1987). Most of the research to date investigates consumer-to-consumer referrals, often in the form of word of mouth, to understand a source's motivations for granting the referral (Anderson 1998; Berger and Schwartz 2011) and how the information influences the recipient's perceptions and behaviors (Chevalier and Mayzlin 2006; Villanueva, Yoo, and Hanssens 2008). Consumer-to-consumer referrals can effectively reduce consumers’ uncertainty and risk in purchasing situations (e.g., Murray 1991; Trusov, Bucklin, and Pauwels 2009). Referrals have been shown to be critically important in sales of new products and innovations as they can significantly reduce consumers’ risk associated with the product's characteristics and performance (e.g., Berger and Schwartz 2011). Notably, research has also found that referrals can have greater impact on the sales of riskier, more expensive products (e.g., Dellarocas 2003). Referrals effectively reduce consumers’ risk, so sellers can benefit from finding ways to generate positive referrals for themselves.
Competitor Referrals
Not all referrals are provided by consumers, however; the source A and the beneficiary C also could be sellers. Further, in such horizontal referrals (Hada, Grewal, and Lilien 2010), the two sellers are not necessarily competitors. Hada, Grewal, and Lilien (2010) note the example of a contract lawyer who refers a client to another lawyer who specializes in personal injury law. Reingen and Kernan (1986) also note the case of a piano tuner who benefits from referrals from music stores. When the source and recipient (consumer) have no existing exchange relationship, the referral does not cost the source any potential business and also may create expectations of potential future rewards (Lakhani and Von Hippel 2003).
Little marketing research has addressed competitor referrals for a product that the seller could offer (but see Mayzlin and Yoganarasimhan 2012); but these referrals have been considered in economics research that seeks to resolve the “matching” problem (Spurr 1987) whereby sellers sort which customers they should serve if sellers know they are not the most efficacious (i.e., specialists) at providing consumers a solution. Specialization refers to a seller's focus or concentration on a subset of products/services, to gain greater degree of efficiency (e.g., McConnell, Brue, and Flynn 2012). Such awareness by sellers about relative specialization in the market can result from various sources. For instance, a mattress store salesperson should be more familiar with the prices of bed frames in other stores than consumers, who infrequently shop for such products. Competitor referrals may be particularly likely in industries in which specialists diagnose the problem and refer customers elsewhere if needed, such as “in various types of consulting/advisory services, or in repair services of durable goods such as houses and automobiles” (Park 2005, p. 391).
In such competitor referrals, the salesperson has more information than the consumer does and decides whether to attempt to serve the consumer, refer the consumer to a competitor, or simply decline service without providing information about a competitor. Research suggests that, on average, salespeople should not recommend consumers to competitors (e.g., Garicano and Santos 2004), and instead should serve consumers themselves, even if they lack specialization or wind up misleading consumers (Arbatskaya and Konishi 2012; Bolton, Freixas, and Shapiro 2007; Park 2005). That is, when the seller lacks specialization and knows of a competitor that could do better, it faces a trade-off between “honestly advising clients to build a good reputation, and reaping a quick profit at the client's expense” (Grassi and Ma 2016, p. 938).
In summary, prior literature regarding salespeople's influence and competitor referrals offers several insights for our study. First, consumers’ perceived overpayment risk can hinder salespeople's efforts to conclude a successful purchase. Second, due to specialization differences, salespeople know that competitors may be able to offer better prices on similar products. Third, sellers likely do not benefit in the short term by recommending a competitor for a product that they themselves sell.
Theoretical Development and Hypotheses
In competitor referrals, the focal product or service may not the only one discussed during the interaction between the salesperson and consumer. For example, a mattress salesperson may believe that a consumer looking for a mattress also needs a bed frame. Such nonfocal products are offered by the focal seller but are not necessarily a purchase target for the consumer (DelVecchio 2005; Janakiraman, Meyer, and Morales 2006). Salespeople often are aware of the price ranges at which competitors offer their products, so they might use the information regarding the prices of nonfocal products to make a specialist competitor referral. We argue that doing so is to the seller's benefit if the consumer perceives overpayment risk and the competitor referral contains a credible justification for a lower price available from the competitor.
When consumers are uncertain about whether they can obtain a better price (or whether the price offered for the product is a good deal; Srivastava and Lurie 2001), they often question whether the transaction is equitable; equity theory suggests that parties to exchange relationships always compare their output-to-input ratios to determine whether the exchange is equitable (Adams 1965). As Haws and Bearden (2006) elaborate, a perception of equity reflects the judgment of the overall merits of an offer. In exchanges with salespeople, consumers thus evaluate their output-to-input ratio (product value-to-price) with the seller's output-to-input ratio (profit-to-cost) to determine whether the exchange is equitable (Oliver and Swan 1989). However, purchase likelihood also depends on whether consumers believe their outcome is proportional to the seller's outcome. If consumers sense that the seller is earning too much profit, they may find the sale inequitable and try to restore balance by negotiating a lower price or simply not buying. Such perceptions are especially relevant in consumer relationships because consumers expect sellers to bear the bulk of exchange costs and consider positive inequity in their own favor as fair (Bower and Maxham 2012; Lapidus and Pinkerton 1995).
Accordingly, perceived (in)equity reflects consumers’ perceptions, not objective inputs and outputs (Adams 1965); information about actual inputs and outputs often is not available to both parties. Consumers’ perceptions of their own input and output are straightforward, such that they must establish an expected value for a focal product and understand what the price means to them. However, they face considerable uncertainty about the seller's outputs and inputs. Consumers know the price but lack information about the seller's costs and thus its profits. Most research studies consumers’ perceived equity in sales exchanges as judgments of price fairness or price equity, derived from comparative transactions that involve different parties because consumers do not have the pertinent information to determine sellers’ input directly (Xia, Monroe, and Cox 2004). However, in situations in which such comparative information is difficult to access, such as when the product is unique, infrequently purchased, or on sale (which requires consumers to determine if the discounted price is “fair”; Darke and Dahl 2003), their uncertainty and overpayment risk increase. Instead, consumers might turn to other cues (e.g., loyalty status of another customer) to infer perceptions of equity (Darke and Dahl 2003). That is, if consumers could rely on information about the seller's benefits, it would enable them to estimate the equity in the exchange better.
Specialist Competitor Referrals
Swan and Oliver (1991) find that consumers are sensitive to what they receive in an interaction with salespeople and to salespeople’ efforts on their behalf; this “summary concept” of equity (p. 16) influences their purchase intentions and satisfaction. When a salesperson gives a specialist competitor referral, the salesperson may increase this summary concept of consumers’ perceived equity in two ways. First, assuming consumers want the nonfocal product, the referral enables them to obtain it at a lower price from the competitor, which reduces their total expected cost (i.e., total input) for any consumer who wants both products. Second, specialist competitor referrals affect consumers’ perceptions of the seller's output-to-input ratio. Equity theory suggests that many tangible and intangible factors determine consumers’ perceived equity, including salespeople's effort to help consumers (Morales 2005). By offering consumers an opportunity to forgo profits from the sale of a (nonfocal) product, the salesperson appears willing to reduce his/her own output, possibly by forgoing a sale (Grassi and Ma 2016). As such, even though the salesperson may not actually be giving up the sale of nonfocal products (e.g., if their purchase rate is low), the perception that the salesperson is willing to reduce his/her own output may be sufficient to improve consumers’ perceived equity, which in turn should improve evaluations of the seller (Campbell 2007; Swan and Oliver 1991). Therefore, specialist competitor referrals should increase consumers’ perceived equity in an exchange with the seller, and perceived equity should increase consumers’ likelihood of purchasing the focal product:
H1: Specialist competitor referrals for nonfocal products increase consumers’ likelihood of purchasing the focal product. H2: Specialist competitor referrals increase consumers’ perceived equity in the exchange with the seller.
In addition to providing information about the price for a nonfocal product available from a competitor (which increases perceived equity), a specialist competitor referral also offers information about price differentials. That is, a salesperson informs the consumer that a competitor sells the nonfocal product at a lower price, one that is better than what the seller offers. As previously mentioned, the literature on competitor referrals notes the lack of information on how consumers should be allocated to sellers of different specializations which vary in their ability to satisfy consumer needs 3 (Spurr 1987). Consumers might not know all potential sellers in a market or which is best suited for certain products, but they understand both that inherent differences exist in sellers’ specialization and that differences in costs may justify price differences among sellers (Bolton, Warlop, and Alba 2003). If consumers believe that stores specialize differently in the nonfocal product, a natural inference may be that the stores differ in their specialization in the focal product, too. This inference likely increases consumers’ confidence not only about a bad price for the nonfocal product (which seller does not specialize in) but also about a good price for the focal product (which seller does specialize in).
Indeed, research in equity theory indicates that consumers perceive whether the price is “right” not only on the basis of the actual price offer but also from the procedure and seller interaction that lead to the offer (Herrmann et al. 2007). Consumers believe that salespeople are motivated to increase their sales (Cialdini 1999; Kirmani and Campbell 2004), so they may require an equitable exchange before they will consider information about the specialization differential as credible evidence (even if indirect) that the seller can offer the “right” price for the focal product. Blanchard, Carlson, and Hyodo (2016) show that in the context of an equitable exchange, information provided by salespeople can increase consumers’ confidence in product prices. Similarly, a specialist competitor referral might reduce perceived overpayment risk (and increase purchase likelihood) only if that referral successfully increases perceptions of equity. Thus, in addition to the direct effect of increasing perceived equity, we expect an indirect effect through both perceived equity and reduced perceived overpayment risk on purchase likelihood. Formally, we hypothesize that:
H3: The increase in perceived equity due to specialist competitor referrals also increases consumers’ likelihood of purchasing the focal product by reducing their perceived overpayment risk for the focal product.
A Credible Justification for the Price Differential
We have suggested that specialist competitor referrals, whereby a salesperson informs a consumer that a nonfocal product is available at a lower price from a competitor, can increase sales of focal products. Moreover, we have argued that justifying the discrepancy between the competitors in the nonfocal product's price on the basis of specialization can be credible. As previously mentioned, specialization refers to a seller's focus or concentration on a subset of goods to gain efficiency (McConnell, Brue, and Flynn 2012). When salespeople mention that the seller (e.g., mattress store) concentrates its efforts on products like the focal product (e.g., mattresses) but not the nonfocal product (e.g., bed frame) that the competitor concentrates on, they are explaining why the seller has gained efficiency in one product (the focal product) at the expense of another (the nonfocal product). In doing so, salespeople simultaneously explain why the nonfocal product is more expensive at their store and provide evidence that the price of the focal product likely reflects the seller's gains from specializing in products like the focal product.
There is precedence for the idea that whereas consumers are generally naive about sellers’ costs, they do acknowledge store differences and they do expect prices to differ by store as a function of their cost differences (Bolton, Warlop, and Alba 2003). That is, consumers consider the cost of goods sold as an acceptable reason for price differences. Without a justification, however, informing the consumer that the price of the nonfocal product is lower at a competitor may not increase consumers’ perceived equity because consumers may not intuit why the seller cannot offer the nonfocal product as the same price as the competitor. In that context, and as consumers tend to suspect that sellers seek to keep the most profit for themselves (e.g., Verlegh et al. 2004), we do not expect that a competitor referral for a nonfocal product without a justification for the price discrepancy would positively affect consumers’ perceptions of equity in the exchange or increase their likelihood of purchasing the focal product. We hypothesize:
H4: Specialist competitor referrals do not increase consumers’ likelihood of purchasing the focal product if they fail to justify the nonfocal product price difference according to the different specializations of the competing sellers.
Overview of Studies
We begin with an exploratory study and survey of salespeople, in which we ask salespeople to imagine selling a focal product (painting) and see what they would do with the knowledge that a competitor offered a nonfocal product at a lower price (frame). We also assess whether salespeople have used specialist competitor referrals, and for which products, in practice. We then test H1, in the context of a painting gallery with posted prices for its painting (Study 1) 4 and with an incentivized negotiation experiment in which consumers must negotiate a price for a mattress, with real financial stakes (Study 2). In Study 3, we investigate the proposed process through which specialist competitor referrals operate (H2 and H3). Then, to test H4, in Study 4, we consider whether mentioning the difference in specialization is necessary for competitor referrals for nonfocal products to increase consumers’ purchase likelihood for focal products. Finally, in Study 5, we replicate the effect of specialist competitor referrals in a distinct context, namely, raising funds for UNICEF by asking people for donations in exchange for pumpkins, with pumpkin carving accessories acting as the nonfocal product. Table 1 summarizes our studies.
Summary of Studies
Exploratory Study and Survey with Salespeople
We started with an exploratory study to determine whether salespeople engage in specialist competitor referrals and what their beliefs are about their effectiveness as a sales strategy. To avoid recall bias and demand effects, we developed a scenario that mimics the choices a salesperson would have to make in a sales interaction (i.e., which strategy to use), reviewed their choices, and then administered a survey about their experiences. To reach a sample of respondents with real sales experience, we hired a market research company, Research Now Inc., which manages dedicated panels preselected by their members’ professions, to which we paid $21 per completed response. We offered the online survey to 1,007 salespeople in a wide range of industries (e.g., health care, software, real estate, financial loans, insurance, retail, travel) and received completed responses from 145 participants, with an average of 22 years of experience in sales and 13 years in their current firm. Web Appendix A provides additional sample details.
Stimuli and Survey
For the scenario-based portion of this exploratory study (see Web Appendix A), we sought a sales context that required little technical knowledge, so that salespeople from various backgrounds could relate. Specifically, we wanted a context in which there would be a natural potential for the presence of focal and nonfocal products; and for which our pretest indicated that consumers perceived high overpayment risk. We thus asked salespeople to imagine working at an art gallery that primarily sells unframed paintings, along with some nonfocal products such as frames. Next, the participants read, “A customer walks in and spends some time looking at the paintings. After taking some time to look around, they seem to settle in front of a painting, with a price of $220. Your intuition tells you that they like the painting. But, you also see them looking at the price tag and seem unsure.” They were told they could assume that the consumer would likely need a frame but that they might have one at home. As a salesperson, they also knew that the gallery's frames sold for $70 but that a frame warehouse store down the block sold an equally nice frame for $45. We described two selling strategies the salespeople could use—(1) suggesting the frame sold by the gallery after the consumer bought the painting or (2) making a specialist competitor referral 5 —and asked them which strategy would have more positive implications for the long-term sales of paintings (item 1) and frames (item 2) (responses on a five-point scale; see Web Appendix A). With this question, we could discriminate between participants who believe that the outcome of a specialist competitor referral will be strictly positive (i.e., better for sales of at least one product and no harm to the other), strictly negative (i.e., worse for sales of at least one product and no benefit to the other), equivalent (i.e., no difference between the two selling strategies), or mixed (e.g., beneficial for paintings but harmful for frames).
In the survey section, we then asked salespeople how often they use each strategy (end points “all the time” and “never”). Among those who indicated that they had used specialist competitor referrals, we asked for descriptions of the selling situation, including the focal and nonfocal products and their price ranges. We concluded with questions about their sales experience and demographic items.
Results
Salesperson beliefs
We find substantial heterogeneity in salesperson beliefs. Whereas 13.10% (19/145) believe that the two strategies will sell an equivalent number of paintings and frames, most salespeople do not hold this belief; they differ considerably in their expectations of the outcome. That is, 29.66% (43/145) believe that the effect of specialist competitor referrals will be strictly negative, but a similar 33.10% (48/145) predict that it will be strictly positive. The remainder are more nuanced, believing that specialist competitor referrals will help one of the products (15.86% painting; 8.28% frame) but hurt the other (see Table WA1 in Web Appendix A). Salespeople who expect positive effects do not differ from the other respondents in their experience, whether in total years or in whether they are actively selling products in their current role.
Industry and product descriptions
The survey reveals that 71% of salespeople have offered specialist competitor referrals for various products, across both consumer and business-to-business industries (20% of the sample). In consumer industries, examples included selling $50 diapers while recommending a local pharmacy for a $60 baby commode; selling $1,000 televisions at an electronic store while recommending Amazon.com for $50 audiovisual wires; selling travel packages while recommending online websites for flight tickets; and selling floor tiles for $5 per square foot while recommending Home Depot for the $25 installation materials. Table 2 contains a sample of specialist competitor referrals mentioned in the survey.
Examples of Specialist Competitor Referrals Reported by Salespeople
Discussion
This preliminary study illustrates that specialist competitor referrals are widely used in practice. However, salespeople vary widely in their beliefs about the strategy's effectiveness for selling focal and nonfocal products. In this study, we put salespeople in a setting in which they worked for an art gallery and had information that a competitor offered a frame at a lower price than the gallery. For the following series of studies, we reverse the perspective of the scenario by focusing on consumer reactions to the use of specialist competitor referrals.
Study 1: Specialist Competitor Referrals in Posted Price Settings
In Study 1, we ask consumers to imagine themselves in a scenario in which they seek a focal product. We manipulate the salesperson's strategy to isolate the effect of specialist competitor referrals on consumers’ likelihood of purchasing the focal product (H1) and nonfocal product.
Method, Manipulations, and Procedures
We recruited 157 participants from Amazon's Mechanical Turk (MTurk) to complete a three-minute study, in exchange for financial compensation. Participants were assigned to a two-condition (specialist competitor referral, control) between-subjects design, in which they read a scenario that asked them to take the role of consumers who wanted to buy a painting for their living room, had walked into a local art gallery, and liked one. All participants were informed of the price of the painting: “The painting is listed, on sale, at a price of $215. You like the painting, but remain uncertain about its selling price. You continue discussing with the store owner.” Then, on a second screen, we presented the owner's statement: “You've found a really nice painting. It is from a local artist who is popular with many of my customers. $215 is a good price too, only available for the current sale.” All participants were told that they had an old frame at home that they could use to display the painting but that the cost of the painting was still a concern.
Conditions
In the specialist competitor referral condition, participants read that as they continued to look at the painting, before they decided whether to buy it, the store owner added:
About half of the time, people who buy a new painting will buy a new frame to go with it. We specialize in getting the best prices in art, not frames, but we do carry some nice ones. In fact, I have a $70 frame that will nicely hold this painting. That said, I'll mention that just down the block is a frame warehouse store, where you can get an equally nice frame for $45.
In the control condition, participants were not told about the seller's offer of a frame (at this stage, before making the purchase decision). These conditions, before the consumer's purchase decision, were identical to the sales strategies presented to salespeople in our exploratory survey.
Purchasing the focal product
Participants indicated whether they would buy the painting (yes/no).
Purchasing the nonfocal product
After deciding whether to buy the painting, participants were asked about the frame. All participants knew that they needed a frame and had a suitable one at home (i.e., the need for the frame was salient in both conditions), but they possessed varying knowledge about the frames available. In the specialist competitor referral condition, consumers knew that the seller sold frames for $70 and a competitor sold a similar frame for $45. If they also had indicated they would buy the painting, we asked if they would buy the frame from the gallery, buy the frame from the frame warehouse, or not buy a frame from either store. In the control condition, if participants chose to buy the painting, the study indicated that the owner added, “About half of the time, people who buy a new painting will buy a new frame to go with it. We do carry some nice ones. In fact, I have a $70 frame that will nicely hold this painting.” We asked whether they would buy the frame from the gallery or not.
Results
In support of H1, participants in the specialist competitor referral condition were more likely to purchase the painting (55.7%; 44/79) than participants in the control condition (39.7%; 31/47; χ2(1) = 4.00, p = .05). However, the specialist competitor referral did not significantly influence the likelihood of buying the nonfocal product, such that participants in the referral condition were no less likely to buy the frame from the gallery (9.1%) than those in the control condition (16.1%; χ2(1) = .32, p = .57).
Study 1 shows that a specialist competitor referral increases consumers’ likelihood of purchasing the focal product from the seller, providing support for H1. Even when consumers receive information that a nonfocal product is available for less from a competitor, they are not less likely to purchase the nonfocal product from the seller.
Study 2: Incentivized Negotiation Experiment
With Study 2, we assess support for H1 in a different purchasing situation, a different product category, and a different setting, such that consumers believe they can negotiate on the price of the focal product. Such a negotiation setting is pertinent for studying specialist competitor referrals. First, consumers typically negotiate if they believe that the listed price is not the lowest price (Blanchard, Carlson, and Hyodo 2016) or that the seller is keeping too much profit for itself (Schurr and Ozanne 1985). That is, negotiations likely take place in purchasing situations in which consumers perceive overpayment risk, and a negotiation should induce that perception. Second, by engaging in price negotiations, consumers signal their belief that the seller's output-to-input ratio is higher than their own, implying low perceived equity (Balakrishnan, Patton, and Lewis 1993). Therefore, we investigate the effect of specialist competitor referrals on consumers’ likelihood of purchasing a focal product in a situation in which consumers are incentivized to achieve better financial outcomes. We adopt a negotiation paradigm (Srivastava and Oza 2006) in which participants obtain a performance bonus based on the price they negotiate with the seller.
Method, Manipulations, and Procedures
Scenario
The study started by explaining that participants would be involved in a purchase price negotiation with a salesperson and would receive $.20 as base payment. They could obtain a performance bonus if the “negotiations end in a sale.” The magnitude of the bonus depended on their performance, so obtaining the lowest possible price through negotiations would lead to a bonus of $.50. Participants were also told that the seller would likely reject extremely low offers and terminate the negotiation process if the participant did not make any concessions. The second screen introduced the shopping scenario: They were moving to a new residence and needed a mattress and bed frame for their guest room. They found a mattress they liked at a price of $1,800 and a bed frame listed at $500 at the seller's store.
Offers and counteroffers
To start, participants indicated how much they would offer for the mattress (up to $1,799) and had to justify, in a text box, this offer to the store owner. We wanted to ensure that participants were paying attention to the scenario and interested in reaching an agreement, so if they offered less than $1,000 for the mattress, we dismissed them and indicated that the extremely low offer was rejected by the store owner, who terminated the negotiation. If they offered at least $1,000 (but less than $1,799), participants received a counteroffer from the owner, corresponding to 25% of the difference between the list price and the consumers’ first offer ($X). For example, if the consumer offered $1,000, the counteroffer ($Y) would be $1,600 (= $1,800 – [$1,800 – $1,000]/4). The owner also provided a reason for rejecting the participants’ first offer: “Your offer of $X isn't acceptable. This mattress is backed by a 10-year warranty, which should last the realistic lifespan of any mattress. I think it's a great choice, which is popular with many consumers, and it goes well with the bed frame at $500. I am willing to lower the price to $Y, but you need to know that $1,800 was already a very good price for this high-quality mattress.” After seeing the counteroffer, participants indicated whether they wanted to accept the offer, make a counteroffer, or reject the seller's offer and walk away from the exchange. If participants rejected the offer or accepted the counteroffer, we excluded them from any further analysis, because they could not be exposed to the manipulation.
Next, participants who decided to proceed provided a second offer ($W) and a second justification. Any participants whose second offer was equal to or lower than their original offer ($X) were rejected for failing to make a concession. The remaining participants, who provided the usable sample for our analyses, were informed that the owner agreed to sell them the mattress for $Z (>second offer of $W), with the comment that this offer was the seller's absolute lowest price. This offer price of $Z represented another 25% reduction between the consumer's second offer of $W and the seller's last offer of $Y.
Participants were then randomly assigned to one of two conditions. Participants in the specialist competitor referral condition were told that as they were pondering the offer, the owner added: “Unfortunately, we do not specialize in bed frames. But I'll just add that if you go a few blocks away to the nearby furniture store, you should be able to get a nearly identical bed frame for $350.” No further information was given in the control condition. Participants chose to accept, reject, or provide another counteroffer. Because of our interest in determining whether specialist competitor referrals increase consumers’ likelihood of purchasing the focal product, we used acceptance versus rejecting/countering the offer as our dependent variable. Participants who chose “another counteroffer” were informed that the owner rejected the idea of any further negotiation and walked away. Finally, all participants answered questions about their expertise with negotiations, level of comfort with negotiations, and ability to picture their interaction with the owner, along with demographic questions about their age, gender, and race.
Results
We sought to obtain responses from approximately 80 participants per condition. Therefore, we collected initial data from 189 MTurk participants, in exchange for a $.20 fee and a potential $.50 bonus (112 men, 77 women, mean age = 31.93 years), of which 30 exited before the second counteroffer from the seller. We were left with 159 participants for analysis. We found no differences in experience, comfort, difficulty imagining the scenario, or age between respondents who reached the manipulation stage and those who exited before it.
In the second stage of the negotiation, after assigning participants to the conditions, we found a positive effect of the specialist competitor referral on participants’ decision to purchase the mattress (63.3% vs. 48.8%; χ2(1) = 3.42, p = .06), a 29.71% increase. The presence of the referral did not affect the probability that the consumer would walk away (8.8% vs. 11.4; χ2(1) = .31, p = .58). These findings provide stronger support for H1 because specialist competitor referrals increased purchases of the focal products even when consumers faced real financial stakes.
Thus, Study 2 provides further support for H1. Although our focus is not on the effect of the price, excluding price from our model could create omitted variable bias. In Web Appendix B, we show that the effect of specialist competitor referrals is robust to controlling for the negotiated price. Next, we investigate the mechanism underlying this effect.
Study 3: Explanatory Mechanism
Using the same context as in Study 2 (without the financial incentives), we seek evidence that specialist competitor referrals increase consumers’ likelihood of purchasing the focal product by increasing perceived equity and thus reducing overpayment risk (H2 and H3).
Method, Measures, and Procedure
We recruited 201 MTurk participants who completed a mattress-shopping scenario similar to Study 2. Participants were randomly assigned to a 1 × 2 between-subjects conditions (control vs. specialist competitor referral) and read, “After spending some time trying different mattresses at the mattress store, you find a mattress that is appealing to you. The mattress is listed at a sales price of $1,120. The store also has a bed frame that you like, listed at $500.” The scenario indicated that they were fairly certain the owner would be open to reducing the price of the mattress, so they initiated a negotiation. A second screen presented the owner's response:
You've found a very nice mattress. It is backed by 10-year warranty, which should last the realistic lifespan of any mattress. I think it's a great choice, which is popular with many customers, and it goes well with the bed frame on special $500. For this mattress, you should know that $1,120 was already a very good price. It's at a sales price we only offer a few times in the year.
After deliberating and exchanging for a while, the owner agrees to sell the mattress for $1,000. For the manipulation, we did not provide any further information to participants in the control condition but told those in the specialist referral condition that as they were pondering the offer, the owner also added:
Unfortunately, we do not specialize in bed frames. But I'll just add that if you go a few blocks away to the nearby furniture store, you should be able to get a nearly identical bed frame for $350.
After making their decisions, participants completed scales to measure their perceived equity and overpayment risk. For perceived equity, we used three items (seven-point scale): “Overall with the owner, there is a balance in our dealings,” “Overall with the owner, we provided each other with equal benefits,” and “Overall with the owner, the benefits we provide and receive even out over time” (α = .91) (Pervan, Bove, and Johnson 2009). For perceived overpayment risk, we used four measures from Dutta (2012) (seven-point scale): “I am confident that I was offered the mattress at the lowest possible price by the owner,” “The final offer for the mattress is probably the lowest price available in the market for this item,” “I did not risk paying too much if I bought the mattress,” and “I am not likely to find a lower price for this mattress from another store” (α = .87). We also assessed perceived salesperson expertise (White 2005; α = .86) and trust in the salesperson (Tax, Brown, and Chandrashekaran 1998; α = .82). For each participant, the order of items within each scale was random. Finally, participants answered demographic questions.
Results
Specialist competitor referrals significantly increased consumers’ likelihood of purchasing the focal product (69.4% vs. 49.0%; χ2(1) = 8.51, p < .001), in line with the results from our previous studies. To assess support for H2 and H3, we must consider the effect of an increase in consumers’ perceived equity on their perceived overpayment risk and whether both factors explain the increase in the likelihood of purchasing the focal product. First, as we show in Figure 1, the specialist competitor referral increases consumers’ perceived equity (path a: β = .47, t(194) = 3.13, p < .01), and this increase in perceived equity affects the likelihood of purchasing the focal product, even when we control for all other variables (path c2: β = .87, Z = 3.75, p < .01), in support of H2. Second, as we also show in Figure 1, consumers’ perceived equity increases purchase likelihood indirectly, through reduced overpayment risk (path b1: β = .54, t(193) = 6.71, p < .01), which thereby increases purchase likelihood (path b2: β = 1.13, Z = 5.60, p < .01), as we predicted in H3. Third, if we control for perceived equity, we no longer find a significant effect of the specialist competitor referral on reduced overpayment risk (path c1: β = .15, t(193) = .91, p = .36) or the focal product's purchase likelihood (path c′: β = .47, Z = 1.23, p = .22).
Study 3: Process Measures for the Effect of Specialist Competitor Referrals on Likelihood of Purchase of the Focal Product
We then estimated the three indirect effects and their bias-corrected and accelerated 95% confidence intervals. We find a significant indirect effect of the specialist competitor referral through increased perceived equity alone (a × c2 = .4117 [.1503, .8594]), even while controlling for reduced overpayment risk for the focal product. Perceived equity operates through overpayment risk also; the indirect effect of increased perceived equity and reduced overpayment risk for the focal product (a × b1 × b2) is significant (.2790 [.1052, .5714]), in support of H3.
We performed several robustness checks. First, inverting the two mediators provides a marginal effect through perceived equity (.14 [–.0078, .4048]); specialist competitor referrals do not directly reduce perceived overpayment risk (β = .11, t(191) = .76, p = .45). Second, our results are robust to controlling for salespeople's expertise and trustworthiness, as detailed in Web Appendix C.
Study 3 shows that when consumers receive specialist competitor referrals, it increases perceived equity between themselves and salespeople, which influences their purchase likelihood directly (H2). It also reduces their overpayment risk for the focal product (H3).
Study 4: Need for Justification
Our previous studies all feature specialist competitor referrals that include two components: the salesperson notes the difference in specialization between stores (i.e., specialization justification) and refers the consumer to a competitor that sells the nonfocal product at a lower price (i.e., competitor referral). In Study 4, we investigate the effect of failing to provide a justification when making a competitor referral for a nonfocal product (H4), with the expectation that the absence of justification will moderate the identified effect. However, it also may be that even if both pieces of information are necessary, they do not operate through consumers’ perceived equity. For example, purchase intentions for the focal product might increase for merely economic reasons, such that the referrals prompt consumers to shift their attention to the purchase of the pair of focal and nonfocal products and seek the best price for the combined offer (Hsee and Leclerc 1998). Alternatively, the economic component might not be necessary, if citing the seller's lack of specialization or the simple gesture of offering a competitor referral creates a social connection that encourages the consumer to prefer to buy from the seller (Dahl, Honea, and Manchanda 2005). With Study 4, we also seek to rule out these alternative explanations.
Method, Shopping Scenario, Manipulations, and Procedures
We recruited 207 MTurk participants and assigned them to four conditions (control, specialist information, competitor referral, specialist competitor referral) in a between-subjects design, using the same context as in Study 3. The scenario presentation was similar, such that they were confident the owner would reduce the price and thus initiated a negotiation. They read a statement in which the owner talked about the mattress and the bed frame and agreed to sell the mattress for $975. Participants in the control condition received no further information before making their decision. Participants in the specialist competitor referral condition read that the owner added, “Unfortunately, we do not specialize in bed frames. But I'll just add that if you go a few blocks away to the nearby furniture store, you should be able to get a nearly identical bed frame for $350.”
Participants in the specialist information condition only saw the first part of this statement: “Unfortunately, we do not specialize in bedframes.” Those in the competitor referral condition (without justification) only saw the second part: “I'll just add that if you go a few blocks away to the nearby furniture store, you should be able to get a nearly identical bed frame for $350.” All participants chose whether to accept, reject and counter, or reject the offer.
Results
We analyzed the probability that participants would accept the offer using logistic regression, with three condition indicators (and control as the default). Consistent with our prior findings, participants in the specialist competitor referral condition were more likely to accept the discounted offer for the mattress (68.6%) than participants in the control condition (49.0%; β = .822, p = .05). Providing only the specialist information (54.0%; β = .20, p = .62) or providing a competitor referral without justification (50.9%; β = .08, p = .85) did not increase participants’ likelihood of purchasing the focal product compared with the control condition, in support of H4 (Figure 2).
Study 4: Purchase Likelihood by Condition
This study provides support for H4. It also shows that the effect cannot be solely attributed to consumers’ expectation of decreased overall costs for their joint purchase of both products, nor did it result from salespeople simply creating a social connection with consumers by giving them a competitor referral or acknowledging a lack of specialization in the nonfocal product. It is the combination of a competitor referral for the nonfocal product and of a justification based on specialization differences that produces the positive effect of specialist competitor referrals.
Study 5: Field Study
The preceding studies offer evidence that specialist competitor referrals are effective in posted price settings and in negotiations, even when consumers are incentivized. However, we have yet to provide causal evidence that they work in the field. In Study 5, we seek such evidence and also shift to a different purchase context, that of soliciting donations. This setting offers an interesting test of the effectiveness of specialist competitor referrals because charities often solicit donations by offering a small token gift, so the exchange forces consumers to estimate an “appropriate” amount to donate (De Bruyn and Prokopec 2013). However, consumers lack information about what is equitable (i.e., cost of the good) (Bolton, Warlop, and Alba 2003), such that “asking for a lot of money in exchange for a worthless token might be perceived as unfair” (Briers, Pandelaere, and Warlop 2007, p. 17). As such, donations solicited through such exchange can elicit equity concerns. We leverage a real-life setting, namely, UNICEF's annual Halloween fundraiser, Trick-or-Treat for UNICEF. In support of this initiative, we obtained small painted pumpkins from a pumpkin farm, which we offered in exchange for a small donation to the charity. Thus, the pumpkins were the focal product, and we offered them for a suggested donation of $10, higher than their retail price of $4.50. 6 In addition to creating uncertainty about the donation amount, our Halloween fundraiser introduced a nonfocal product that was readily available elsewhere at a lower price: a “pumpkin carving accessory kit” to be sold for $4. The grocery store behind the fundraising table sold the same item for $2.
Method, Manipulations, and Data
We set up a table on a sidewalk in front of a grocery store (competitor), around the corner from its entrance (see Web Appendix D). A poster featured the logo of the Trick-or-Treat for UNICEF program, and on the table, we placed the small painted pumpkins, pumpkin carving accessory kits, and a sign that read, “Pumpkins for Halloween; Suggested Donation $10.” When a potential participant approached the table, a research assistant explained,
We are raising funds for UNICEF trick-or-treat through these pumpkins that a pumpkin farm donated to us. We take donations for the pumpkins, with a suggested amount of $10. If you need some, we also have these carving tools for $4 extra.
In the specialist competitor referral condition, the assistant added:
I'll tell you, though, we obtained these pumpkins through a donation from a pumpkin farm, but not the carving tools. In fact, I just saw that they are available at this grocery store for $2.
This latter information was not provided in the control condition. By flipping a coin, we randomly determined which condition to assign to people at the start. We conducted this study on Friday evening (4:00–6:00 P.M.) and Saturday (11:00 A.M.–4:00 P.M.) (it was canceled Sunday due to rain), and because of the rate of traffic changes throughout the day, we switched the conditions after every hour. Specifying that the pumpkins were donated by a pumpkin farm established the difference between the source of the focal and nonfocal products (and a pumpkin farm is definitely a specialist in pumpkins) and provided a justification for why the pumpkin carving kit would be more expensive at the fundraising table than at the grocery store. 7
During the sessions, 40 people interacted with the research assistants, so this number constitutes our sample size. We assigned 2 participants who donated without hearing the scripts to the control condition, because all the information shared in the control condition also was on display. Overall, 21 people were in the specialist competitor referral condition and 19 in the control condition.
Results
Among the participants, 10 people donated $10 in exchange for pumpkins (6 referral, 4 control), 11 people donated but opted not to take a product in exchange (8 referral, 3 control), and 2 people paid $4 in exchange for the carving kit (1 in each condition). Participants randomly assigned to the specialist competitor referral condition were more likely to donate (71.43%) than participants in the control condition (42.11%;
Study 5: Field Study Results
With Study 5, we demonstrate the effect of specialist competitor referrals in the context of consumers donating money to a charity in exchange for a small gift. This study thus replicates the effect in the field, in a distinct situation and price point ($10).
General Discussion
We show that salespeople who offer specialist competitor referrals for nonfocal products can increase the likelihood of their focal products’ sales. Building on equity theory, we determine that this effect functions by increasing consumers’ perceived equity and reducing perceived overpayment risk for the focal product. Without a credible justification for the price differential though (e.g., that the seller and competitor differ in their specializations), a competitor referral for nonfocal products is not sufficient to increase focal product sales.
An important practical concern is that specialist competitor referrals may result in losses of nonfocal product sales that could damage seller profitability as a whole. We do not find any such evidence in our experiments or field study (Studies 1 and 5), but it is important to delineate the conditions in which the net effect of specialist competitor referrals on sellers’ profits might be negative. Therefore, in the Appendix, we detail the profit equations for the specialist competitor referral and control conditions and investigate situations in which the former are profitable. Across various levels of relative profit contributions by focal and nonfocal products and different baseline probabilities of purchasing the nonfocal products, we find that minimal increases in the focal products’ sales can be sufficient for specialist competitor referrals to increase sellers’ net profits. In particular, we suggest three factors to consider when trying to maximize main ways to maximize the effectiveness of the specialist competitor referral on total profits. First, as long as the probability of purchase of the nonfocal product does not decrease in the presence of the referral, any increase in purchase probability of the focal product will increase profits. Second, if the probability of purchase of the nonfocal product does decrease, profitability depends on (1) the ratio of the dollar margin of the focal and nonfocal products and (2) the decrease in odds of purchase of the nonfocal product. This implies that it is easiest to benefit from specialist competitor referrals when the dollar margin of the focal product is not much smaller than that of the nonfocal product, and when the odds that a consumer purchases the nonfocal product are relatively low in the absence of the referral.
Finally, we highlight that the positive effect of specialist competitor referrals is generalizable. Our study shows that salespeople use this strategy in practice, and it can increase the seller's profitability in various situations (see Appendix). With experiments, we show that the strategy significantly increases consumers’ purchase likelihood for focal products across varied categories (paintings, mattresses, shoes, 8 pumpkins), price conditions (posted price, negotiations, donations), and methodologies (online, field, with financial incentives). Taken together, our research identifies specialist competitor referrals as a useful sales strategy across many contexts.
Theoretical Implications
Referrals
Our main contribution is to the domain of referrals. First, we contribute to marketing literature on referrals by moving beyond consumer-to-consumer/word-of-mouth referrals and considering a setting in which both the source and the beneficiary are sellers (i.e., competitor referrals). For both consumer-to-consumer and competitor referrals, the purpose is to influence potential consumers. Thus, several factors that determine the influence of consumer-to-consumer referrals also could have a bearing on our findings, such as source trustworthiness and expertise (which moderates the influence of the source on the consumer; Gilly et al. 1998) and recipients’ prior price knowledge (which affects whether recipients need the referral; Hada, Grewal, and Lilien 2010). In Study 3, we find that even if we control for perceived seller trustworthiness and expertise, our proposed mechanisms hold (see also Web Appendix C). However, perceptions of the trustworthiness of the salesperson and perceptions of equity appear intertwined. Kickul, Gundry, and Posig (2005) note that perceptions of equity relate strongly to trust; in a salesperson interaction, some level of trust may be necessary before consumers will regard the information as credible, even if the salesperson possesses relevant expertise (Liu and Leach 2001). In that spirit, we conducted an additional study and manipulated perceived trust in the salesperson (see Study W1 in Web Appendix E). Consistent with the idea that some trust is necessary, at low levels of trust, specialist competitor referrals appear ineffective.
As we noted, the effectiveness of specialist competitor referrals could also depend on the knowledge consumers already have about the price of the focal product at the seller's store. However, when we provide participants with additional information about typical discounts at the retailer (see Study W2 in Web Appendix F), we fail to find that consumers’ prior knowledge moderates the influence of specialist competitor referrals. This study provides further evidence that our effect operates through changing consumers’ perceived equity. That is, even if consumers know what a good input (price) would be, they remain uncertain about equity, because they lack information about the seller's inputs and outputs, so specialist competitor referrals likely remain effective. Thus, we also contribute by integrating equity theory into the domain of referrals.
Equity theory
Reducing consumers’ perceived inequity leads to positive outcomes for sellers (Oliver and Swan 1989). However, as Xia, Monroe, and Cox (2004, p. 3) note, “equity theory uses buyer and seller input and output ratio as comparatives, [because] consumers usually do not know either seller's cost structure or other pertinent information to determine seller's input accurately.” In turn, most research studying equity in seller–consumer interactions has focused on consumers’ perceived price (un)fairness, which develops according to comparative transactions that involve different parties (Morales 2005). We show that a specialist competitor referral can directly influence consumers’ perceptions of sellers’ benefits without relying on actual comparatives, which are not always available or always in the seller's favor. We also show that even in a negotiation setting, which tends to evoke an initial sense of inequity and incentivizes participants to reach the lowest possible price, specialist competitor referrals can increase the likelihood that a consumer accepts an offered price.
Relatedly, Bolton, Warlop, and Alba (2003) reveal that consumers have a poor appreciation of the costs faced by sellers, such that they ignore anything other than the cost of goods, causing them to regard most sales transactions as inequitable. A competitor referral for nonfocal products, without the specialization justification, does not improve consumers’ likelihood of purchasing the focal product, which may signal consumers’ general disbelief about the seller's cost justifications (Bolton, Warlop, and Alba 2003). That is, providing a credible explanation for a price differential helps counter consumers’ natural insensitivity to most price differences that these authors observed.
Overpayment risk
Related to the contributions to referrals domain and equity theory are our contributions to understanding of consumers’ overpayment risk and how sellers can reduce it. First, referrals research has not explicitly studied the effect of referrals on consumers’ price-related risk assessments; it mainly focuses on risk or uncertainty about product choices. By studying a situation in which overpayment risk is present, we show how specialist competitor referrals can effectively reduce overpayment risk. Second, Darke and Dahl (2003, p. 337) call for research into whether consumers look for equity in their purchases because “they may suspect that they typically pay too much for regular priced items.” We respond that consumers seek equity in exchanges in which they perceive overpayment risk. Thus, we contribute to literature that investigates ways to reduce consumers’ overpayment risk, such as by posting higher prices and having salespeople offer lower, sale prices (Grewal, Monroe, and Krishnan 1998) or by providing low-price guarantees (Dutta 2012). Because perceived overpayment risks can lead consumers to increase their search for the best price or postpone their purchase (Biswas, Dutta, and Pullig 2006), reducing these risks offers clear managerial benefits, as we elaborate next.
Managerial Implications
Our exploratory survey shows that although 71% of salespeople have used specialist competitor referrals, there is little consensus about whether the strategy is profitable. Our studies confirm that specialist competitor referrals can be effective at increasing sales of focal products. We also fail to find any evidence that they harm the sales of nonfocal products.
In the Appendix, we specify the conditions in which specialist competitor referrals are most likely to be profitable. In conjunction with our experimental studies and the mathematical profitability analysis, we offer some key takeaways for managers. First, even with conservative assumptions (e.g., a nonfocal product whose conditional purchase probability of 30% is reduced by half; equal dollar contribution margins for the focal and nonfocal products), increasing focal product sales by small amounts (e.g., 13%) can still make the strategy profitable. In our experiments, the average increase in focal product sales was typically much greater than would be necessary (40% in Study 1, 30% in Study 2, 69% in Study 5). Second, in the worst-case scenario (i.e., if the seller entirely loses the sale of the nonfocal product to the competitor), the profitability of the strategy depends on the relative margins of the focal and nonfocal products. Third, the nonfocal product does not have to be one that is a complement to the focal product. Specialist competitor referrals are effective even when the nonfocal product is likely to be sold with the focal product (as our field study shows; pumpkin carving kits are not a complement to painted pumpkins), and profitable.
The strategy also can be helpful when engaging in negotiations. Consumers increasingly negotiate with sellers, for products ranging from Chelsea Clocks priced at several hundred dollars to Jos. A. Bank shirts; as one consumer commented, “I know these things are significantly marked up. I said ‘I'm buying three; I'd like 15 or 20 percent off’” (Clifford 2012). Specialist competitor referrals help sellers assure consumers that they are getting the lowest price possible and encourage the sale. Our field study also showcases how charities soliciting donations could use specialist competitor referrals to enhance their chances of success.
Finally, by granting specialist competitor referrals, salespeople can use the information they have about competitors and their prices to increase their sales in a manner that does not require them to reduce their prices, as long as they can justify the discrepancy. That is, in our studies, the seller did not offer a discount on the nonfocal product, even after admitting that the competitor offered a lower price. We did not explore the long-term benefits of this strategy, though their potential is clear; in particular, giving specialist competitor referrals might lead to repeat business and stronger relationships with consumers.
Limitations and Further Research
Specialist competitor referrals might operate in other contexts. Economics research that investigates referral fees (Arbatskaya and Konishi 2012) and other incentives for competitor referrals (Park 2005) suggests that it is not in the best interest of the seller to provide these referrals. However, salespeople already use this sales strategy (as our exploratory study shows), and we highlight the conditions under which it can benefit the seller. Further research accordingly might address different situations in which specialist competitor referrals help sellers, such as in business-to-business industries or contexts marked by relationships between the seller and the competitor.
In addition, we identify a credible justification based on the difference in specialization between the seller and the competitor as a moderator of the effect of competitor referrals on consumers’ purchase likelihood. This difference in specialization might manifest in differences in prices between the two competitors (as we study), or it could manifest as a difference in the quality of the products being offered. That is, if the consumer was price insensitive but uncertain about quality levels, then the seller could benefit by giving a specialist competitor referral for a competitor who sells higher-quality nonfocal products at a higher price (e.g., a frame store doing custom framework). Future research could consider these different kinds of competitor referrals for nonfocal products.
We have attempted to set widely different price levels (from a $10 pumpkin to a $1,000 mattress), but the effect still could differ at other price points or levels of involvement. Higher price points tend to incur greater price fluctuations (e.g., buying a car), so specialist competitor referrals may have particularly substantial impacts on these consumers, who likely are involved and concerned about both equity and overpayment risk (Viswanathan et al. 2007). We do not necessarily expect that the effect would be stronger (or weaker) as the price changes or for all situations in which consumers are highly involved. Indeed, although the price is probably the most commonly used proxy for involvement, in many situations, prices can be low when consumers are involved (Laurent and Kapferer 1985). We purposefully focused on situations marked by at least some minimal level of involvement due to perceived overpayment risk; such additional research might manipulate levels of involvement to test their effects.
Finally, a specialist competitor referral could have long-term consequences beyond the short-term outcome of purchase likelihood of the focal product. In this sense, our research can be considered in conjunction with studies that identify other benefits of greater perceived equity, such as increased consumer satisfaction. Traditional word of mouth and referrals offer sellers excellent long-term benefits (e.g., Kumar, Petersen, and Leone 2010). Accordingly, to the extent that the salesperson is truthful when making a specialist competitor referral, the effect should remain positive. However, we would be remiss if we did not acknowledge the potential for negative consequences. For example, the repeated use of specialized competitor referrals could reduce their effectiveness, or consumers might start their search process at the referred competitor for their next occasion. These potential long-term consequences provide ample opportunity for further research.
Conclusion
Competitor referrals come in many forms; the most famous example is probably from the classic movie Miracle on 34th Street, when Kris Kringle refers Macy's consumers to a toy store competitor just before Christmas. The premise of such a competitor referral is to sacrifice the first sale in hopes of long-term benefits. We show that competitor referrals can even be profitable without sacrificing a focal sale, if the referral is for a lower-priced nonfocal product that the competitor specializes in. Furthermore, in giving such a competitor referral, Kris Kringle would not only have increased Macy's sales but might have also gained loyal customers.
Footnotes
Appendix: Conditions for Profitability of Specialist Competitor Referral
Specialist competitor referrals for nonfocal products can increase focal product sales, but it is possible that in some conditions, specialist competitor referrals decrease nonfocal product sales. Although we find no statistical evidence for this in our studies, a decrease in nonfocal product sales could decrease profits. We therefore consider the parameters associated with the profitable use of specialist competitor referrals as a sales strategy, such that they produce a net gain in sellers’ profits. We formulate profit equations for both the control and specialist competitor referral (SCR) conditions to determine the minimum focal product sales increase needed for the seller to profit.
1
For example, the salesperson could explain, “We sell very nice frames for $70. However, I will just add that we are not specialists in frames, and the frame warehouse two blocks down offers equally nice frames for $45.” Thus, the salesperson has informed the consumer that the frame (nonfocal product) is available for less from a competitor, due to the difference in what the stores concentrate on, while still attempting to sell the painting (focal product).
2
One reason cited in industry articles and blogs for using specialist competitor referrals is that sellers might lose the current sale but reap benefits in the long term (future purchases, word of mouth). However, we anticipate that sellers can benefit even in one-time transactions.
3
Our argument relies on a difference in specialization, not on whether the effect is driven by a stated specialty in the seller's focal product (direct statement of specialty: “We are specialists in art”) versus mentioning that they are not specialists in the nonfocal product (indirect statement of specialty on the focal product: “We are not specialists in frames”). We assess both the specialty in the focal product (Studies 1 and 2, field study) and only the lack of specialty regarding the nonfocal product (Studies 2 and 3). We find the effect both ways.
4
In a pretest, we assessed consumers’ perceived overpayment risk in ten purchasing situations, where each involved a focal product sold at a specific kind of store. We find that consumers’ perceived overpayment risk was significantly higher for purchasing a painting in an art gallery than any other situation except purchasing a car from a dealership. The findings also confirm that overpayment risk is not product-specific; for example, respondents perceived higher overpayment risk for buying running shoes from a local running store than from a large sporting goods store. Buying a mattress from a mattress store represented the midpoint for perceived overpayment risk—significantly higher than buying a toaster from a department goods store, running shoes from a large sporting goods store, or silverware from a dollar store. Therefore, we conducted our experiments across distinct purchasing contexts: buying a painting at an art gallery (Study 1), buying a mattress at a mattress store (Studies 2–5), and buying running shoes from a local running store (available on request). Note that as we focus on a purchasing situation for a specific product, in effect, we keep product performance constant.
5
The stimuli also included a potential strategy in which the salesperson mentioned the frame sold by the gallery prior to the purchase decision. However, we did not obtain all measures for that scale (i.e., we did not compare it with the two other strategies); the limited results we have are available on request.
6
In a separate sample, we assessed whether consumers would perceive overpayment risk for a painted pumpkin in our field study setup. We asked 80 respondents on MTurk whether they would expect to overpay for a painted pumpkin in the described setup (1 = “a great deal,” and 5 = “not at all”); we find that they would (M = 2.55; significantly different from the midpoint of scale, p < .01).
7
To assess whether consumers saw a difference between UNICEF volunteers and the grocery store chain as differently able to obtain good prices on the carving tools (the specialization difference), we conducted an online test with 120 respondents on MTurk. We showed them the donation table setup, provided the information related to the specialist competitor referral condition, and asked them the focal question, “Which of the two stores do you think would be able to acquire the carving tools at a better price?” They responded on a mean-centered nine-point scale (−4 = “The grocery store chain should be able to acquire carving tools at a cheaper price than UNICEF,” and 4 = “UNICEF should be able to acquire carving tools at a cheaper price than the grocery store chain”). We found that the average evaluation on this scale was less than the midpoint (M = −.71, t(125) = −2.90, p < .01) suggesting that people were more likely than not to see the grocery store as being able to get a better price on the carving tools than the UNICEF volunteers.
8
Available from the authors.
9
When the purchase probability of a nonfocal product given the purchase of a focal product,
References
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