Reciprocity Study Paper

Effects of Reciprocity 1
Running head: THE EFFECTS OF RECIPROCITY ON CONSUMER BUYING
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The Effects of Reciprocity on Consumer Buying Behavior in Electronics Retail
Matthew Fickett
Acknowledgements: Jordon Taylor
Supervised by: Gregory Neidert, PhD
Arizona State University
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Abstract
The norm of reciprocity has been examined widely in the social science community; in
particular, the effects of reciprocity on compliance have been studied in-depth. However,
practically none of these experiments examined the ability of reciprocity to trigger unequal or
disproportionate compliance outcomes. A field experiment was conducted at a well-known
electronics retail company which examined if giving a customer a gift-coupon during a “sales-
introduction monologue” increased the rate of compliance to purchase a computer and/or the
amount spent per transaction. Customers were randomly assigned to 1 of 3 conditions based on
the hour of entry into a specialized computer department in the store. Reciprocity was
manipulated both in the “sales-introduction monologue” that varied in each condition and the
discount amount given (no discount; 10% off; or 10+5% off). Compliance to a confederate sales
agent’s request to purchase a computer, as well as purchase amount, was recorded on an
experimental checklist. The results of a one-way ANOVA showed that the norm of reciprocity
had no effect on amount spent per transaction (p = .55). The likelihood of purchasing a computer
approached significance in the 10+5% off condition (p = .08); however, the overall likelihood of
condition predicting purchase decision was insignificant (p = .22). Although the results appear
inconclusive, distinct trends emerged (see Tables and Figures) that suggest a reciprocity effect
was present, warranting further research. Scientific and practical applications as well as
recommendations for continued field research are discussed.
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The Effects of Reciprocity on Consumer Buying Behavior in Electronics Retail
In the United States, retailing is symbolic of a long standing tradition of capitalism. The
retail industry is the largest employer in the U.S. providing over 14 million individuals with jobs.
It is also the second largest grossing industry with annual revenues of $3.8 trillion dollars (U.S.
Department of Labor, 2010). The retail industry is a substantial platform for maintaining the
lifestyle of a typical U.S. consumer and also the livelihood of millions of employees.
The success of retailers is derived largely from sales agents working within stores. These
salespeople represent the “brand” of the organization, acting as liaisons between the organization
and customers. Furthermore, sales-agents spend the most direct time with customers, providing
valuable product and company information, building business relationships and most
importantly, selling.
Sales are a fundamental day-to-day activity for the average retail worker; yet, according
to Carré, Tilly & Holgate (2010) retailers make minimal investments in training their sales staff.
On average, retailers only provide 3.7 hours of training to the average worker before hitting the
sales floor, whereas the standard for most industries is 10.7 training hours.
It seems hypocritical that retailers have almost universally adopted “service oriented
selling” models (also referred to as relationship-selling or customer-oriented-selling) in spite of
their meager investments in employee training. The touchstone of these selling approaches is not
to sell for the sake of selling, but instead to sell based on a customer’s specified needs, budget,
lifestyle, etc. Overall, the service oriented selling approach can be characterized by a
transformational customer experience; however, because most sales agents receive little formal

training, they are not being properly utilized by these organizations as a “key advantage.” As a
result, retailers may very well forego these transformational benefits (Sharma, 2001).
By retailer’s neglecting the training of their sales force, the service oriented model that is
so vehemently pledged becomes threatened. Without proper training, salespeople may not have
the resources or raw ability to close-sales and may alienate potential customers with a lack of
product knowledge or credibility. Inept sales associates are costly to an organization and can lead
to low profits, decreased customer loyalty & satisfaction, high product return rates, high turnover
or attrition and negative word of mouth marketing (Carré, Tilly & Holgate, 2010; Guenzi, De
Luca & Troilo, 2011; Homburg, Müller & Klarmann, 2011; Mayer & Greenberg, 1964).
It is no wonder that when the recession peaked, retail stores took a substantial hit.
Between 2008 and 2010, the retail industry was responsible for over 1 million layoffs, a
precipitous (20%) of the 2.6 million layoffs in the U.S. during this time. Retail organizations
during the recession were forced to close hundreds of stores across the country. Many well-
known chains were forced to altogether disintegrate, liquidating their assets. Combined with
increased competition from “e-tailing” or “e-commerce” over the last decade, retailers have been
forced to reevaluate how they do business. Most well-known retailers have adopted their own e-
tailing websites and internet marketing campaigns in an effort to stay competitive; however,
increasing e-commerce .
According to White (2010), e-commerce has grown at a steady 20% annually since 2001,
and is only presently leveling out. U.S. e-commerce sales growth has also been twice as high as
brick and mortar retail stores for the past three consecutive quarters. The rise of e-commerce has
been accelerated by several technological advancements that have aided its rapid growth; for

instance, the proliferation of smart-phones, tablets and other mobile technology in the consumer
marketplace have enabled individuals to purchase from practically anywhere. E-commerce also
offers the appeal of avoiding salespeople and bustling store crowds. Purchasing online is often
more accessible to those who are either too busy or out of range of the nearest retailer of interest,
while still offering comparable pricing. Whatever the case, e-commerce is expected to continue
growing (Sharma, 2001; White, 2010).
With a reduced workforce, the closing and consolidation of hundreds of stores, as well as
a general lack of training among sales associates, the retail industry is caught in a delicate
position. Employees in these organizations are being required to learn new responsibilities and
product knowledge while adapting to an increasingly demanding work environment, all while
meeting lofty sales goals. In these high stress situations, it is not uncommon for sales agents to
adopt a transactional selling approach, negating the benefits of customer oriented selling.
Retailers who practice predominately transactional selling styles quickly realize that they are
insufficient to sustain the long-term relationships that lead to higher profit margins, customer
loyalty and satisfaction (Boles, Babin, Brashear & Brooks, 2001; Guenzi, De Luca & Troilo,
2011). With the retail industry facing a variety of new demands and looming competition, it is
more important than ever to maintain a competent and persuasive sales force.
There are many studies that provide insight into the makings of an effective salesperson
in the retail literature. Mayer and Greenberg (1964) for instance, suggest that an agents “ego”
instills the drive to be an effective seller, as well as “empathy” which helps in understanding a
customer, and tailoring the shopping experience towards products and services that are in line
with the customers needs. Salespeople who are rated as competent in these two characteristics

have been shown to effectively monitor a target’s needs, wishes, and personal motives to aid in
building a genuine relationships.
Research by Sharma (2001) suggests that “adaptive” salespeople are often the most
successful. Adaptive-selling requires the agent to be of a credible nature (trustworthy), available
to the customer (both physically and mentally), and empathetic (by assessing a customers needs
and providing solutions that are in line with those needs). These researchers also found that the
most effective adaptive salespeople demonstrated a solid ability to create “categories” of
customers that aid in future sales.
Sales agents in another study were most noted for consistently exceeding customer
expectations, which the authors referred to as “augmented personal service.” These salespeople
were noted for doing “unexpected” and “very special” things for their customers (i.e. one sales
agent lent her favorite earrings to a customer to match an outfit the customer had bought from
her). In so doing, sales agents “locked” customers into a (mutually beneficial) relationship.
Furthermore, the authors venerated the power of “augmented personal service” to not only
initiate relationships between employees and customers, but also its ability to enhance these
relationships (Beatty, Mayer, Coleman, Reynolds & Lee, 1996).
What this aforementioned study labeled “augmented personal service,” social scientists
call “the norm of reciprocity.” The norm of reciprocity states that “we should repay in kind that
which we have received,” and is one of the oldest operating norms in human civilization. Many
social scientists believe that this norm makes us distinctly human, and enabled cooperative
behavior to evolve, in turn allowing the human race to survive (Cialdini, 2009; Molm, 2010). In
Laursen and Hartup’s (2002) research, they found that the process of reciprocity from childhood

to adulthood progresses from prominently self-interested exchanges, “to the matched exchange
of material resources, to a matched exchange of emotional and psychological resources, and
finally to a need-based exchange that emphasizes mutuality and collective concern.” They
contend that the earliest manifestations of a friendship occur as a “prototypical exchange
relationship.” These researchers suggest that reciprocity is an inborn trait among humans that
manifests itself starting with early childhood relationships, and progresses with cognitive and
social development.
The norm of reciprocity is so ubiquitous, that it has become internalized by most cultures;
in fact, reciprocity is often an integral part of a culture’s spiritual, ethical, and interpersonal
traditions. Even today, the norm of reciprocity manifests in the most primitive societies and the
most advanced (Schieffelin, 1980). The “Golden Rule” is a perfect example of the norm of
reciprocity epitomized throughout human history. It appears in early Chinese philosophy, the
Vedas, the Bible, not to mention dozens of other religious, philosophical, and classic texts; the
norm is pervasive.
Further support for an internalized norm of reciprocity comes from Burger, Sanchez,
Imberi, and Grande (2009) who found that when someone received a favor, they were more
likely to return it than if they had received no favor. This is consistent with the literature and
other experiments; however, what is particularly interesting is that participants reciprocated the
favor even when they knew they would never again directly interact with the original favor-doer.
In essence, the participants were subjected to the effects of the norm of reciprocity even when
self-presentation motives were systematically minimized, leading the researchers to believe the

norm of reciprocity acts as both a social and internalized norm. The results are also consistent
with the evolutionary perspective of the reciprocity norm (Burger et al., 2009).
Besides the ability of reciprocity to cultivate and broaden the depth of a relationship,
there are also numerous studies that illustrate how its power can be used to induce compliance to
requests (Cialdini & Goldstein, 2004). In the study by Beatty et al. (1996), customers reported
feeling “locked” into relationships with sales agent(s). The literature corroborates that this
feeling is associated with indebtedness and/or feelings of obligation to reciprocate a favor, gift
and/or concession. In compliance experiments, an agent of influence generally provides a favor
to a target (usually unsolicited), after the target accepts the gesture they are endowed with a sense
of obligation or indebtedness to repay this favor, increasing the likelihood of the target agreeing
to a request(s) (Burger, Ehrlichman, Raymond, Ishikawa & Sandoval, 2006; Burger, Horita,
Kinoshita, Roberts & Vera, 1997; Burger, Sanchez, Imberi & Grande, 2009; Dahl, Honea &
Manchanda, 2005).
One frequently used example of such effects comes from Regan’s (1971) experiment on
the norm of reciprocity. In this study, a confederate “gifts” a soda to the actual subject of the
experiment, the subject is later asked by the confederate to buy raffle tickets. Compared to
subjects who received no favor, subjects whom did receive one were significantly more likely to
buy raffle tickets, and more of them.
Ostensibly, reciprocity has been used in this fashion by salespeople and compliance
experts for centuries. However, the extant literature shows little research on the application of the
norm of reciprocity in increasing sales in a retail environment. Despite this lack of research,
there is a plethora of anecdotal evidence from customers like those mentioned by Beatty et al.

(1996). Some examples of the norm’s successes “in the field” include, for example: Free-gifts
inside of sales promotions that significantly increase the likelihood of visits to a store from
customers in its distribution zone. Another commonly used technique involves a monetary
incentive included with a survey to encourage completed returns, to be kept even if not returned
(Cialdini, 2009). In another study servers at a restaurant gifted “foil wrapped candy” (to be
distinguished from conventional mints) in one of several conditions while dropping off the
table’s check. Tips increased substantially in conditions where a dining party received a gift of
candy (Strohmetz, Rind, Fisher & Lynn, 2002). While these studies were not done in a retail
setting, they show that reciprocity is valid in producing substantial effects outside of a laboratory.
Many of these practices have become commonplace in marketing departments, survey research,
and as cited, in restaurants as well.
The present study examined if a personalized, unexpected, unsolicited gift could be used
to increase sales in a retail field setting. Numerous studies show that reciprocity is an effective
way to increase compliance to subsequent requests; however, much of this research has used a
reciprocal exchange situation featuring a favor and request of equal “proportion.” That is, the
favor and the subsequent request are generally on the same social, psychological, and/or
economic scale. In our current research, the norm of reciprocity is expressed as a gift-coupon,
which ultimately is “gifted” by a sales agent (a confederate, naïve to the experimental
hypothesis) in an attempt to gain a customers compliance to a request to purchase a new
computer. A request that has a much higher than the gift-coupon.
According to Cialdini (2009), there is reason to believe that even small gifts can foster
compliance to a request that exceeds the “cost” of the original gift. For instance, in Regan’s

(1971) classic illustration of reciprocity (mentioned previously) the researchers observed a five-
hundred percent return on investment. Following this reasoning, it is not unwarranted to posit
that retail customers who receive an unexpected and personalized gift may feel obligated to
reciprocate the salesperson’s apparent generosity by making a purchase.
With this in mind, a field experiment was conducted by our research team
investigating the effects of an unsolicited, personalized, and unexpected gift-coupon on a
consumer’s purchase decision in a well-known electronics retailer’s computer department. Three
conditions were explored to help provide an answer.
Experiment
Customers in our field investigation either did or did not receive a gift in the form of a
store coupon from a confederate sales agent during an initial sales-introduction monologue. This
was followed by a request by the sales agent to show the customer some computers. Depending
on the condition, a customer received no coupon (Condition 1: Control), a coupon for a 10%
discount on select products (Condition 2: Reciprocity Level 1), or a 10+5% discount for
qualifying products (Condition 3: Reciprocity Level 2). Considering these conditions, we put
forward two hypotheses:
H1: A customer who receives an unsolicited, personalized, and unexpected gift coupon
for a 10% off store discount from the sales agent will be more likely to make a purchase
and/or spend more per transaction than those in the control condition.
H2: A customer who receives an unsolicited, personalized and unexpected gift coupon for
a 10% off store discount from the sales agent who then increases the discount to 15% off,

will be more likely to make a purchase and/or spend more per transaction than customers
in the control group and the 10% discount condition.
Reciprocity is so deeply embedded in our consciousness it can override logic in a
situation, forcing us into the prescriptive social, psychological and cultural dictations of the
norm. Through our research, we expect to find that after receiving a gift-coupon, customers will
feel obligated to reciprocate by purchasing more often and/or spending more per transaction than
if they had not received a coupon. In condition 3, we expect that a customer’s sense of
indebtedness will be amplified when the salesperson increases the value of the gift by an
additional 5% off. We believe that this act will enhance the reciprocity effect by generating an
even stronger sense of obligation to repay this gesture compared to conditions 1 and 2. It is our
hope that this research will demonstrate the efficacy of the norm of reciprocity in triggering
unequal exchanges. Moreover, we hope to show the utility of the norm of reciprocity in a retail
context by demonstrating it’s scientific and practical application.
Method
Participants
A total of 193 consumers of a well-known electronics retail corporation in Chandler, AZ
served as participants in this study. All participants were shoppers who entered a specialized
computer department, a segment of the larger computer department within the store.
Materials
Our research team and select employees of the retail organization developed the gift-
coupons used in the experiment. These coupons reflected information such as the sales associates
name, store logo and contact information, the percentage off, exclusions and restrictions (listed

on the back of coupon), and a space for the sales agent to write-in the customer’s name. The gift-
coupon could not be used towards computers, but was valid towards other items in the store such
as TVs, cameras & camcorders, and both small and large appliances. Qualifying merchandize
was determined by the organization.
For each of the three experimental conditions, a “sales-introduction monologue” was
scripted. In each condition, the script was varied to either include or not include a name
exchange and gift-coupon. Each sales-introduction monologue ended with a request from the
sales agent to show the customer some computers (see Appendix A). Due to ethical
considerations, the company’s name and characteristics that could be used to identify the
company have been removed from documents listed in the Appendix section.
A randomized schedule of experimental conditions was created using a web-based
random number generator. This was used to vary conditions on an hourly basis during the sales
agents shift each day. Additionally, a checklist was created and used in conjunction with the
“condition schedule” to keep track of both the frequency of customer interactions and whether a
customer bought from the sales agent in each experimental condition. Receipts from each sale
were stapled to that day’s checklist and delivered to a member of the research team. These
receipts provided total sales amount, number of items purchased, and the date and time of
purchase. Please see Appendix B for reproductions of these materials.
Procedure
The experiment started in November 2008 and ended June 2009 and was conducted in
two phases each lasting 2-3 months. A male sales agent with roughly 5 years of experience in the
electronics retail industry served as an experimental confederate. Before data collection, our

confederate memorized three scripted “sales-introduction monologues,” one for each condition
to ensure uniformity during actual sales encounters.
Before starting his shift each day, the sales agent was provided with an hourly (color
coded) schedule of conditions, an experimental checklist and gift-coupons. Customers were
approached based on their entry into the computer department where the sales agent worked.
Considering the hour the customer entered the department, one of three conditions applied. The
sales agent was instructed to greet the customer with one of the three scripted sales-introduction
monologues within 30 seconds of the customer entering the department.
The control condition introduction featured neither a name exchange nor gift-coupon,
followed by a request to show the customer some computers. In the second condition, a customer
was greeted with a name exchange, followed by an unsolicited, unexpected and personalized
gift-coupon for 10% off, then a request by the sales agent to show them some computers. Lastly,
in the third condition customers received the same script as condition two, with one important
change. While the sales agent wrote the customers name on the coupon for 10% off, he stopped
and stated to the customer, “you know [customer name], I can give a discount of up to of 15%
off on a small fraction of these coupons, and I’d like to do that for you.” In this third condition,
the gift-coupon was still delivered in an unsolicited, personalized and unexpected fashion;
however, the sales agent appeared to be making an extra, meaningful gesture by affording the
customers an additional 5% off.
After the confederate sales agent completed the sales-introduction monologue, regardless
of condition, a request was made to show the customer some computers. The sales process after
this point was unscripted. After each interaction the sales agent used the provided checklist to

record the customer’s purchase decision, the hour the customer entered the department (to denote
which condition applied) and stapled duplicate receipts from successful sales to the checklist.
Results
Effect of Condition on Average Sales Amount
An analysis of variance (ANOVA) was used to determine if the experimental conditions
affected the amount spent by subjects (N = 33) who made purchases (excluded 4 missing
transactions). The means and standard deviations for sales amount by condition are listed on
Table 2. Concerning mean sales amount, the one-way AVOVA of condition showed no
significant difference of amount spent, F(2,30) = .60, p =.55, r = .04.
Likihood of Customers Choosing to Make Purchase
A logistic regression analysis was conducted to determine if compliance to a computer
sales request from 193 consumers was explained by exposure to one of the three experimental
sales conditions. A test of the full model against a constant only model was not statistically
significant, indicating that the predictors as a set did not reliably distinguish between consumers
that bought or didn’t buy a computer X2(2, N = 193) = 2.99, p = .22. However, the Wald criterion
suggested that condition 3 (Reciprocity Level 2) approached significance (p = .08) when
compared to the overall effect. The frequency of sales versus non-sales and close-rates are listed
on Table 1.
Trends
Despite a lack of statistical significance, distinctive trends emerged in the data. These
trends can be seen in Figures 1 and 2. In particular, the percentage change in close-rate and
revenue from the control condition compared with condition 3 appeared substantial. The

proportion of total revenue accounted for by each condition is represented in Figure 2, notice that
condition 3 accounts for nearly half (44%) of the total dollars spent between all conditions. In the
logistic regression the EXP(B) = 1.54, which indicated that a person in condition 3 was one and a
half times more likely to comply to the request to buy a computer from the sales agent than those
in the control condition, suggesting that a reciprocity effect was present.
Discussion
Studies show that reciprocity is often a critical step in building, maintaining and
enhancing relationships. Personal, professional and even relationships between consumers and
sales agents are all subject to the influence of reciprocity. Gift-giving and the exchange of favors
is often a method of social integration, the gift or favor itself can even reveal the level of
intimacy between the giver and receiver. By its very nature reciprocity requires trust in the other
party and after the cycle of giving, receiving and repaying is complete, social capital is generated
between all parties involved. This capital helps individuals decide whom to trust when
determining for instance, who to involve in a future business venture, or in the case of the
present research-who to buy a computer from (Beatty, Mayer, Coleman, Reynolds & Lee, 1996;
Gouldner, 1960; Molm, 2010; Sherry, 1983).
The norm of reciprocity prescribes that when someone receives a favor, particularly one
that is unexpected, personalized, and meaningful--that person is both social obligated and
personally indebted to the giver, to repay the favor. Does this mean however, that someone who
receives a favor will be more likely to agree to a request that is much larger than its face-value?
Overall, the results of the present study did not sufficiently support this assertion; however,
distinct trends suggest that further research is warranted.

One limitation that may have impeded the true effects of reciprocity from being
detectable was our relatively small sample size. Having only one experimental accomplice acting
as a sales agent made it difficult to obtain a sample size that afforded the power necessary to
detect effects. Also, two extraneous factors could have been responsible for our results: The
economic recession and increased consumer mindfulness.
The effects of the recession may moderated the reciprocity effect. In a recession
individuals tend to be more reluctant about making “luxury” purchases. People switch to less
expensive brands for things they need and avoid making unnecessary or expensive purchases
(Tranzer, 2010). In times of recession, consumers tend to be more cognizant of the purchases
they make, and put in more effort in finding ways to save money.
In social influence research, participants often act in a click-whirr fashion to an influence
technique. Little conscious thought is exerted when complying to a request, instead participants
act in accordance to a “script” or behavioral heuristic that is automatically and usually
mindlessly triggered by social, environmental and/or behavioral cues (Cialdini, 2009). Research
by Pollock, Smith, Knowles and Bruce (1998) found that when subjects mindfully considered
buying a box of chocolates that was relatively expensive, they were less likely to be influenced
by the “that’s-not-all” technique. Conversely, when the box of chocolates was inexpensive,
researchers found the “that’s-not-all” technique substantially increased the purchase of
chocolates. They argue that when a consumer becomes more mindful about making a purchase,
they use central processing (versus peripheral processing) to guide their decision. These
consumers will consider things like the quality of the item, their desire to have the item,
consequences of buying the item, personal finances, etc.

While the Pollock et al., (1998) study specifically examined the impact of mindfulness
when using the “that’s-not-all” technique, they contended that mindfulness may nullify the
effectiveness of other influence techniques as well. These two factors offer a valid perspective as
to our results. Consumers may not have bought or spent more on computers under the reciprocity
conditions because a shift in consumer spending attitudes during the recession, or because the
sheer magnitude of the purchase ($1000 was the starting price of computers in this department)
may have caused subjects to use a “central” decision-making process, ostensibly diminishing the
ability of the norm of reciprocity to increase compliance to a target request.
These extraneous variables may have affected the results of our research; however, some
distinct trends in the data that suggest that there may have been a reciprocity effect. For instance,
the close rate (how many sales made / total interactions) for condition 3 appears quite
distinguishable from the other conditions (see Table 1); in fact, condition 3 showed a percentage
increase of (62.5%) in close-rate when compared to the control condition. This condition also
accounted for (44%) of the total revenue between all conditions, a percentage increase in revenue
of (76%) over the control condition (see Figure 1 & 2). Despite a lack of statistical significance,
these trends suggest that a reciprocity effect was present.
While these trends are in line with existing research, customers who did not buy a
computer may also have been influenced by the norm of reciprocity. Research by Dahl, Honea
and Manchanda (2005), found that retail customers who decided not to make an initial purchase
but had established an even modest level of social-connectedness towards a sales agent, reported
feelings of guilt. In their subsequent lab study, these researchers found evidence that these
customers often take “reparative actions during future purchase interactions with the salesperson,

to reciprocate the initial connection they established.” These feelings of guilt (and arguably
indebtedness) were powerful enough that when reparative actions were taken by the customer,
they were directed specifically towards the sales agent that had initially helped them.
Similar findings were reported by Jacobs, Evans, Kleine and Landry (2001) in an
insurance sales “role-play” experiment they conducted. These researcher’s noted that the self-
disclosures (a basic form of reciprocity) of the sales agent during an initial sales interaction led
customers to be more likely to agree to purchase, more satisfied with the agent and more likely to
repeat business with the agent. Furthermore, self-disclosure has been linked to increases in trust
between parties (Johnson & Noonan, 1972).
With these studies in mind, it is not unreasonable to speculate that customers in our study
who received a coupon, even if they had no intention of purchasing, spent more time with the
sales agent and were more “open” to the information the sales agent provided. Also, customers
who received a gift-coupon and did not purchase a computer may have simply not been “in the
market,” yet because of the gesture may purchase from that sales agent, or the company the agent
works for, the next time they are in the market. They may even recommend the sales agent to a
friend who is looking for a computer, to reconcile their “debt” with the sales agent and/or the
company.
Directions for Future Research:
Originally, we had intended to track the redemption of gift-coupons throughout the store.
In so doing, we hoped to see if customers, rather than reciprocating the sales agents “favor” by
buying a computer system, repaid the agents gesture by using the gift-coupon for other

qualifying products. Unfortunately, due to company restrictions the tracking of gift-coupon usage
was prohibited.
This would make for an interesting adaptation in a future study as it could demonstrate
that customers who don’t reciprocate a sales agents generosity directly, might choose to repay the
gesture to the company by buying something that is more affordable, or that the customer has a
greater need or desire. Most retailers are able to generate barcodes (or an equivalent) to track
items, this could easily be applied to gift-coupons like the ones in our study. These barcodes
could be made to be unique to each condition of the experiment, the day of the month and other
variables of interest.
Retailers could enable a powerful tracking system to determine, for instance: How many
gift-coupons were used in each condition and the average time between receiving the coupon and
its usage. Many retailers have loyalty programs that are digitally linked to a database of a
customer’s history with the company (e.g. spending history), such data could potentially allow
researchers to observe long-term effects of an act of reciprocity compared to a baseline. For
example, do customers that receive an act of reciprocity spend more in a year than a customer
that does not? Research of this nature would be a truly novel way to observe how reciprocity
affects the relationship between a customer and the company, the store and even an individual
sales agent.
Conclusion:
Understanding the norm of reciprocity and the behavioral outcomes it is responsible for is
a valuable avenue of research, not only because of implications for social scientists, but also for
consumers and businesses alike. Veteran sales agents are well versed in the power and

applications of reciprocity; however, overall the retail industry is plagued by a lack of training
and experience among a majority of its retail salespeople (Beatty, Mayer, Coleman, Reynolds &
Lee, 1996; Carré, Tilly & Holgate, 2010). If retailers can increase the amount of sales training
and teach ethical applications of reciprocity, there would likely be lasting social and economic
dividends for the organization.
Reciprocal relationships are responsible for many positive interpersonal outcomes; yet,
the norm of reciprocity is not without a dark-side. Keysar, Converse, Wang and Epley (2008)
observed that when an individual, group or an organization takes from another party, albeit: A
physical item, service or even a privilege or policy previously offered. The action cannot be
undone simply by giving back something comparable in return. Actions of taking (before giving)
activate reciprocity’s doppelgänger, retribution. These researcher’s suggested a revision of the
reciprocity axiom, ‘‘you scratch my back and I’ll scratch yours; but, if you take my eye-I’ll take
both of yours.’’
Today retailers and other industries face an intense environment of competition and
internal restructuring that stretches the fabric of these organizations thin. To stay competitive and
distinguished in the industry, these organizations must be cognizant of both the positive and
negative characteristics of reciprocity. That being said, the trends in our data in combination with
the extant literature suggest that by understanding and implementing (mutually beneficial)
reciprocity driven interactions, industries such as retail could: Increase sales revenue, build,
maintain, and enhance relationships with new and existing customers and improve loyalty,
satisfaction and word-of-mouth marketing from both employees and customers.
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"

Table 1
Frequency Descriptives and Close-Rates for Each Condition  
* Note: Close-Rate was determined by dividing the number of sales by the total interactions in each condition.
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Sales Non-Sales
Condition N N Total Close-Rate (%)*
1 11 58 69 15.9
2 9 50 59 15.3
3 17 48 65 26.2

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Table 2
Means and Standard Deviations for Items and Dollars Spent per Sales-Transaction
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Items / Transaction Dollars Spent
Condition M SD Total Items M SD Total Revenue
1 4.38 2.56 35 $1,893.29 $601.25 $17,039.65
2 5 3.25 40 $2,292.34 $1085.10 $20,631.07
3 4 1.92 60 $1,989.20 $743.41 $29,838.07

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Figure Captions
Figure 1. Percentage change in close-rate and revenue between conditions.
Figure 2. Percentage of total revenue accounted for by each condition.
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Figure 1
PercentageChange
-10%
18%
45%
73%
100%
Condition Comparisons
Condition 1 Condition 2 Condition 1 Condition 3 Condition 2 Condition 3
41.92%
76%
24%
73.3%
62.5%
-6.25%
Close Rate
Revenue

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Figure 2
44%
31%
25%
Condition 1: Control
Condition 2: Reciprocity Level 1
Condition 3: Reciprocity Level 2

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Appendix A
Sales-Introduction Monologues
Condition 1 [Control Introduction]:
“Hi there, how are you doing today? Are you an [insert computer brand name] user? [After the
customer responds say...] Would you mind if I show you some of our new [insert computer
brand name] computers?”
Condition 2 [Reciprocity Level 1]:
“Hi there, how are you doing today? My name is Jordon, what’s your name?... Hi ____, It’s nice
to meet you. Are you an [insert computer brand name] user? [After customer responds, in a
manner consistent with just having remembered something very important, say] Oh, before I
forget: I've been given permission to give out some special discount coupons for 10% off
merchandise in this store. While the coupon excludes select brands such as [insert brand name],
and [insert brand name], it can be used for 10% off of popular items such as TV’s, Cameras, as
well as many accessories. I have only a few to give out each day, and I'd like for you to have one.
[At this point you will fill out the coupon with the customer’s name then hand it back to them.
Then say...] There is no expiration date so please feel free to use it today, or at a more convenient
time... Would you mind if I show you some of our new [insert computer brand name]
computers?”
Condition 3 [Reciprocity Level 2]:

“Hi there, how are you doing today? My name is Jordon, what’s your name?... Hi ____, It’s nice
to meet you. Are you an [insert computer brand name] user? [After customer responds, in a
manner consistent with just having remembered something very important, say] Oh, before I
forget: I've been given permission to give out some special discount coupons for 10% off
merchandise in this store. While the coupon excludes select brands such as [insert brand name],
and [insert brand name], it can be used for 10% off of popular items such as TV’s, Cameras and
Camcorders, as well as many accessories. I have only a few to give out each day, and I'd like for
you to have one. [Start to fill out the coupon, then while filling it out, pause, look up at the
customer and say] You know _______, I can give a discount of up to of 15% off on a small
fraction of these coupons, and I’d like to do that for you. [Then proceed to clearly cross out the
10% off, and write in 15% off and initial. Then say,] There is no expiration date so please feel
free to use it today, or at a more convenient time... Would you mind if I show you some of our
new [insert computer brand name] computers?”
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Appendix B
Condition Schedule and Experimental Checklist

Reciprocity Study Paper

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