Sell ing With "Sat is fac tion Guar an teed"
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JOUR NAL OF SERVICE
FruRE
chter,
SEARCH
Gers tner
/ May
/ SAT
1999
ISFACT ION GUAR ANTEED
Selling With “Satisfaction Guaranteed”
Gila E. Fruchter
Israel Institute of Technology
Eitan Gerstner
University of California–Davis
Satisfaction Guaranteed is defined as a selling policy as- ers interpret Satisfaction Guaranteed to apply not only to
suring that no consumer is worse off after purchase. The the products they buy but also to the shopping experience
authors show that for a wide spectrum of guarantee poli- and hassle involved when returning unsatisfactory mer-
cies, the most profitable policy is a Satisfaction Guaran- chandise. Table 1 gives the proportion of respondents from
teed policy. Setting a price equal to the willingness to pay a sample of 265 consumers who agreed that each unsatis-
of satisfied customers, but generously compensating dis- factory purchase experience (UPE) would be included in a
satisfied customers for all costs involved, this policy can be satisfaction-guaranteed policy.
a “creative device” to capture back-added economic value Many sellers do not meet these expectations. Some
created for consumers through the guarantee. Comparing claim to offer money-back guarantees (Davis, Gerstner,
this policy with a no-guarantee policy, a Satisfaction and Hagerty 1995; Moorthy and Srinivasan 1995), but in
Guaranteed policy comes with a higher price in a monop- practice, they offer only partial refunds. For example, cata-
oly market and in a competitive market. Conditions under logue retailers typically have separate nonrefundable
which selling with a Satisfaction Guaranteed policy is charges for shipping and handling (Hess, Chu, and
more profitable than selling without it are derived. Al- Gerstner 1996; Hess and Mayhew 1997), and some com-
though this policy seems to be an attractive offer to con- puter equipment retailers charge restocking fees of up to
sumers, the authors show that because of its high price, it 20% upon returning a product (Chu, Gerstner, and Hess
may not. Easy-to-satisfy consumers are better off without 1998). Other retailers accept returns only during a short
the Satisfaction Guaranteed policy. time period after the sale, and many require customers to
present sales slips upon returning merchandise (Davis,
Hagerty, and Gerstner 1998). Partial refunds and hassle
tactics can discourage opportunistic returns by consumers
Customer satisfaction has become an important goal in who buy products for a short-term use and then return
business (Anderson 1996; Hauser, Simester, and Werner- them for refunds (Longo 1995; Neuborne 1996). Unfortu-
felt 1994; Westbrook 1981; Woodruff, Cadotte, and nately, these tactics punish also consumers who return
Jenkins 1983). Many sellers claim to offer “Satisfaction products only when truly dissatisfied, and as a result, their
Guaranteed” with the products or services they sell (Hart willingness to pay is reduced.
1988; Hart, Heskett, and Sasser 1990). What is the mean- On the other hand, there are retailers with policies more
ing of Satisfaction Guaranteed? Schmidt and Kernan consistent with the consumers’ expectations mentioned in
(1985) conducted survey research and found that consum- Table 1. At Nordstrom and L. L. Bean, customers can re-
We would like to thank Prasad Naik and the participants of the marketing seminar at the Haas School of Business in Berkeley, at the
Technion, and at the Marketing Science Conference in Insead, for their excellent comments.
Journal of Service Research, Volume 1, No. 4, May 1999 313-323
© 1999 Sage Publications, Inc.314 JOURNAL OF SERVICE RESEARCH / May 1999
TABLE 1 manufacturer or a retailer to vouch for product quality
Proportion of Respondents Who Agree when it cannot be observed prior to purchase (Moorthy
That Each UPE Would Be Included in a and Srinivasan 1995). Lutz (1989) showed that when a
Satisfaction-Guaranteed Policy (in percentages) large consumer effort is required to maintain the product,
Proportion the optimal policy is to refund only part of the purchase
UPE Statement Who Agree price. Padmanabhan and Png (1997) consider return poli-
cies under which manufacturers allow retailers to return
Replace unsatisfactory items 100.0
Money back on unsatisfactory items 98.4 merchandise. They show that allowing such returns may
Rain checks on unavailable items 95.7 enhance competition by retailers, thus increasing the
Customers never need return products to manufacturer 78.3 manufacturer profitability while reducing retail margins.
Lowest prices on all products 43.7 Prod uct war ran ties, how ever, are dif fer ent than
Customers compensated for time spent waiting for delivery 28.7
money-back guarantees that allow consumers to return
No sales slip needed for exchange 27.6
Store picks up unsatisfactory item 25.2 products for a full refund, even if the product or service
Exchange for any reason during life of product 14.6 performs its intended functions. The problem is that some
consumers may abuse money-back policies by buying a
NOTE: UPE = unsatisfactory purchase experience.
product for a certain use with the intention of returning it
for a full refund (Longo 1995; Neuborne 1996). Davis,
turn products without any time limits. Embassy Suites and Gerstner, and Hagerty (1995) showed that when such con-
Hampton Inn promise a full refund to customers who are sumer opportunistic behavior is taken into account,
dissatisfied with their rooms. Under what circumstance is money-back guarantees on returns can still be more profit-
such a generous policy profitable? Do all customers bene- able than selling “as is.” This holds when a seller can sal-
fit when Satisfaction Guaranteed is offered? Unfortu- vage unsatisfactory products better than buyers (e.g., by
nately, little theoretical and empirical research is available selling returns at a discount to other consumers).
to help understand these policies (except Fornell and Sellers can limit “unjustified” returns by increasing the
Wernerfelt 1987, 1988; Schmidt and Kernan 1985). consumer’s cost of returning merchandise or by offering
This article presents a theory of selling, with Satisfac- partial refunds as argued by some of the researchers cited
tion Guaranteed defined as a selling policy assuring that above. On the other hand, Fornell and Wernerfelt (1987,
no consumer would be worse off after purchase. Consider- 1988) recommended that sellers offer generous compen-
ing a market in which each consumer has a different proba- sations as part of complaint management. They con-
bility of being satisfied from a purchase, we find that the cluded, “Complaint management can be an effective tool
optimal guarantee policy, among a wide spectrum of guar- for customer retention, because it can increase the con-
antee policies, is Satisfaction Guaranteed. Under the opti- sumer’s expected utility from purchase” (Fornell and
mal policy, price is equal to the willingness to pay of Wernerfelt 1988, p. 296). Do generous return policies
satisfied customers, but a generous compensation that cov- really benefit consumers?
ers the price paid plus hassle costs associated with a prod- We agree that generous return policies can be good for
uct return is given to dissatisfied consumers. We show that sellers but argue that they could be bad for consumers. To
this policy can be used as a “creative device” to capture demonstrate this seemingly surprising result, we deliber-
back the added economic value created by the seller for ately focus on a Satisfaction Guaranteed policy under
consumers through the guarantee. Moreover, under com- which every single consumer is guaranteed to be fully
petition, Satisfaction Guaranteed can be used to segment compensated for all the costs involved in returning unsatis-
the market in a profitable way through service differentia- factory products. Then we show that the high price that
tion. Comparing this policy with a no-guarantee policy, we sellers may charge under such a generous policy can actu-
find that Satisfaction Guaranteed comes with a higher ally exceed its benefits to easy-to-satisfy consumers. We
price. We derive conditions under which selling with Sat- conclude that these consumers could be better off without
isfaction Guaranteed is more profitable than selling with- such a guarantee. Why is our conclusion different than
out it and show that it can be more profitable even for Fornell and Wernerfelt (1987, 1988)?
perishable products such as services. In modeling the problem, these authors assumed that
Earlier research has focused on whether warranties by sellers with monopoly power do not adjust price (even in
manufacturers to fix or replace defective products can be the case of a single seller) when they offer generous com-
profitable and assure good product performance (Gross- pensations to unsatisfied consumers. Obviously, consum-
man 1980; Lutz 1989; Mann and Wissink 1990; Menezes ers benefit if sellers cannot extract this added economic
and Currim 1992; Padmanabhan and Rao 1993). Allowing value by raising prices. In contrast, we allow the seller to
consumers to return products may provide a way for a increase the price when Satisfaction Guaranteed is of-Fruchter, Gerstner / SATISFACTION GUARANTEED 315
fered. As a result, consumer-expected economic-added FIGURE 1
value and the postpurchase economic-added value are Seller’s Options and Customers’ Surplus
lower compared with the consumer-added economic val-
ues under no-guarantee conditions. To demonstrate how
consumers can end up in an inferior situation under Satis-
faction Guaranteed, we start by analyzing the single-seller
situation.
THE BASIC MODEL: MONOPOLY
We consider first a seller with monopoly power who
targets a product to a market of N potential customers. The
seller may offer the product with or without Satisfaction
Guaranteed (guarantee in short). Without a guarantee, the
seller sets the price, P, and dissatisfied consumers cannot
obtain a refund. Under a guarantee, the seller sets the price,
PG, and offers a refund, R, to dissatisfied consumers. The
seller’s unit cost is C, and the salvage value from a product
rejected by a dissatisfied customer is S.
Each customer may or may not be satisfied with the
product after purchase. If satisfied, the customer obtains a
value of V dollars (the reservation price of satisfied cus-
tomers). If dissatisfied, the customer’s value is normalized
greater than or just equal to zero. The seller’s guarantee
to zero. In addition to the paid price, an unsatisfied cus-
policy and price determine the number of customers who
tomer incurs a hassle cost, H, when claiming a Satisfaction
buy.
Guaranteed (traveling and confrontation costs when re-
turning back merchandise). Next, we analyze the implications of both policies with
The economic-added value provided to a consumer by and without guarantees on both seller and customers.
the seller can be measured by the concept of consumer sur-
plus from economic, which is equal in our model to the No Guarantee
consumer value from the product, less the price and hassle
costs. Figure 1 describes the seller’s alternative offers and In this section, we derive the following result:
the resulting consumers’ surplus. Under a no-guarantee
condition, a satisfied customer obtains a surplus of V – P, Proposition 1 (no guarantee): Under no guarantee, only
the relatively easy-to-satisfy consumers are served,
and an unsatisfied customer obtains a surplus of 0 – P. Un-
and the seller cannot extract their surplus.
der guarantee, a satisfied customer obtains a surplus of V – PG.
A dissatisfied customer obtains zero value, incurs a cost of
To see this, consider Figure 1. A consumer obtains a
price plus hassle, PG + H, and obtains a refund of R. There-
surplus V – P if satisfied, and 0 – P if not (i.e., the postpur-
fore, the sur plus of a dis sat is fied cus tomer is equal to
chase surplus can be negative). Let Ui be the expected
0 – (P G + H – R).
value (prepurchase) of the surplus of a random consumer,
We assume that some customers are harder to satisfy i. By definition
than others, so each customer has a different probability of
being satisfied.1 Let si denote the probability of satisfying Ui = si (V – P) + (1 – si)(0 – P) = si V – P. (1)
consumer i, 1 ≤ i ≤ N (so 1 – si is the probability of dissatis-
fying the consumer), and let s1 represent the consumer who Consumer i buys only if the expected value of the sur-
is most likely to be satisfied, s2, the second most likely to plus from buying is nonnegative, that is, Ui ≥ 0. Recall that
be satisfied, and so on. the probability of a consumer being satisfied si decreases
A consumer buys the product if the expected surplus when i increases. Therefore, the expected value Ui also de-
(expected value less expected costs) from purchasing is creases when i increases. At any given price, P, consumers
who buy must obtain a positive surplus, and the marginal
1. Heterogeneity in the customer probabilities of being satisfied may re- consumer who buys, say consumer k, obtains zero surplus.
sult from differences in customer tastes, differences in fit between prod-
uct and customer, or differences in customer requirements. Why? Because to maximize profit, the seller raises prices316 JOURNAL OF SERVICE RESEARCH / May 1999
FIGURE 2
No Guarantee: Optimal Price and Number of Customers (marginal revenue = marginal cost)
until the customer is just indifferent between buying and ∏ ∗ = k (P* – C) = k (skV – C). (4)
not buying. The remaining N – k (harder-to-satisfy) con-
sumers do not buy because at price P they would obtain a Next we analyze the case of guarantee.
2
negative surplus. To confirm Proposition 1, however, we
need to show how k is determined. Guarantee
Figure 2 shows the market demand, which gives the
number of buyers at each price and the marginal revenue Definition: Satisfaction Guaranteed is a selling policy
curve. The demand curve has a staircase shape because the assuring no consumer obtains postpurchase negative surplus.
highest price that would attract an additional customer i is This definition implies that the minimum surplus a con-
the expected value, siV, which decreases in a discontinuous sumer will obtain after purchase from either keeping the
fashion with i. The marginal revenue curve lies below the product (V – PG) or returning it [0 – (PG + H – R)] is guaran-
demand curve, because the formula for the marginal reve- teed to be nonnegative.3 Using the definition with the basic
nue curve, siV – (i – 1)(si – 1 – si)V, represents both a gain and model described in Figure 1, we derive the following result:
a loss from including the marginal consumer. The gain oc-
curs because the price customer i is willing to pay, siV, will Proposition 2 (optimal guarantee): Under the optimal
be added to revenue. The loss occurs because the new low guarantee, (a) the price is set equal to the willingness
price, siV, needed to attract customer i, must be offered to to pay of satisfied customers, V, and dissatisfied cus-
the i – 1 customers, who would otherwise pay the higher tomers obtain back the price plus hassle costs; (b) all
price of si – 1V. The profit maximization price, P*, and the consumers are served, but their expected surplus, as
number of customers, k, to be included, are determined by
setting marginal revenue equal to marginal cost, C.
2. Adding the assumption that si is continuously uniformly distributed in
In conclusion, k is the solution of the equation the interval [0,1], consumer i will buy only if the expected surplus from
buying, given by Equation 1, is nonnegative, that is, si ≥ P/V. Therefore, the
profit of the firm is given by
skV – (k – 1)(sk – 1 – sk)V = C. (2)
Π=∫
1
(P − C )dsi = (P − C )(1 − P / V ).
The profit-maximizing price is P /V
The optimal price, market size, and profit are (V + C)/2, (V – C)/2V,
and (V – C)2/4V, respectively.
P* = skV, (3) 3. In a mathematical form, Satisfaction Guaranteed satisfies
and the seller’s optimal profit is 0 ≤ Min {V – PG, 0 – (PG + H – R)}.Fruchter, Gerstner / SATISFACTION GUARANTEED 317
FIGURE 3
G
Customer Indifference Curves (U I = 0)
well as the postpurchase surplus, is extracted. Fur- are obtained by setting Equation 5 equal to zero, and solv-
thermore, the optimal policy is both unique and Sat- ing for PG,
isfaction Guaranteed.
PG = (1 – si)R + si(V + H) – H. (7)
To prove this proposition, we first derive the expected
surplus from buying. Considering Figure 1, a consumer
obtains a surplus V – PG if satisfied and 0 – (PG + H – R) if Equation 7 describes trade-offs between the price PG
dissatisfied. Let U Gi be the expected surplus of a random and refund R that gives customer i zero surplus. A higher
consumer, i. Then, price requires a higher refund to keep a customer indiffer-
ent. As i increases, the intercept and slope of the linear
U Gi = si (V – PG) + (1 – si ) [0 – (PG + H – R)] equation change. The only point in which all the indiffer-
(5) ence curves meet is the intersection point described in
= si(V – PG ) – (1 – si )(PG + H – R). Equation 6. That is, the policy in Equation 6 represents the
unique solution that extracts all customers’ surplus and
Consumer i buys only if this expected value of the surplus therefore maximizes the seller’s profit. (Because all cus-
is nonnegative, that is, 0. Following Equation 5, the ex- tomers’ surplus is extracted, there is no opportunity to earn
pected surplus U Gi consists of the two terms: the expected a higher profit.) The policy in Equation 6 is also Satisfac-
net value if satisfied (value V less price PG) and the ex- tion Guaranteed because under it, no consumer obtains
pected loss if dissatisfied (price PG plus hassle cost H less postpurchase negative surplus. This completes the proof
the refund, R). The expected surplus (Equation 5) is equal of Proposition 2.
to zero for every customer i for the following price and re- What is the intuition behind this result? Satisfaction
fund policy: Guaranteed removes consumers’ risk of being dissatisfied
because no consumer ever obtains postpurchase negative
PG* = V, R* = V + H. (6) surplus. Even though consumers are heterogeneous with re-
spect to the probability of being satisfied, every one is will-
That is, by setting the price equal to the value of a satis- ing to give the product a try at the high price they would
fied consumer, V, and offering to refund the full price and pay if satisfied (i.e., the reservation price). That is, if satis-
cost of hassle to a dissatisfied consumer, the seller can ex- fied, the consumer obtains a full value but pays the reserva-
tract the surplus of all N customers, and profit is maxi - tion price, so the surplus obtained is zero. If dissatisfied,
mized. the consumer is fully reimbursed (price plus hassle costs)
To see why the optimal guarantee policy is unique, look and again obtains zero surplus. This means, that under Sat-
at Figure 3. The indifference curves described in Figure 3 isfaction Guaranteed, all consumers’ surplus is extracted.318 JOURNAL OF SERVICE RESEARCH / May 1999
Using Equation 6, the seller’s optimal expected profit TABLE 2
under guarantee Π*G is, Satisfaction Guaranteed
Versus No Guarantee: The Monopoly Case
N
∏ G = N (V − C ) + ∑ (1 − si )( S − V − H ). Optimal Satisfaction
*
(8)
i =1
Outcomes No Guarantee Guaranteed
Price Lower Higher
The first term on the right-hand side of Equation 8 is the Market served Part All
revenue from selling the product to the N customer at a Profit Lower under Higher under
price V, and the second term is the expected loss from dis- Equation 9 Equation 9
Expected consumer surplus Positive Zero
satisfied customers (the sum of the probabilities of dissat- Postpurchase consumer surplus Positive or negative Zero
isfaction, 1 – si, multiplied by the salvage value, S, less the
4,5
refunded price and hassle cost, V + H).
In conclusion, the optimal policy has the following
k N
properties:
∑ (s
i =1
i − sk )V + ∑ (s V − C)
i =k+ 1
i
(9)
1. It is generous because the refund exceeds the N
price. + ∑ (1 − si )( S − H ) > 0.6
2. It is a unique solution that extracts all consumers’ i =1
surplus and therefore it is the most profitable
guarantee policy. Results (a) and (b) in Proposition 3 can be observed from
3. It is a satisfaction-guaranteed policy because no Figure 2. Under no guarantee, easy-to-satisfy customers
consumer is worse off after purchase. obtain a positive expected surplus. In contrast, under Satis-
faction Guaranteed they would obtain zero surplus. Fur-
Next we determine when Satisfaction Guaranteed is thermore, the postpurchase surplus of these best customers
more profitable than no guarantee. is likely to be positive, but under guarantee it will be zero.
Result (c) in Proposition 3 can be obtained by comparing
Comparing Policies the optimal profit Equations 8 and 4.
Result (a) conflicts with the conclusion of Fornell and
The analysis of this section leads to the following prop- Wernerfelt (1988) that generous compensations to dissat-
osition, and to the results in Table 2. isfied consumers lead to a higher expected utility from
purchase. Their result follows from a restrictive assump-
Proposition 3 (comparing policies): (a) Easy-to-satisfy tion that price remains fixed when these consumers’ bene-
consumers are more satisfied without Satisfaction fits are offered. Relaxing this assumption, we show that
Guaranteed; (b) the optimal Satisfaction Guaranteed
Fornell and Wernerfelt’s conclusion may not hold: The
completely extracts consumers’ surplus, whereas no
guarantee does not; and (c) the optimal Satisfaction generous compensations under Satisfaction Guaranteed
Guaranteed policy is more profitable than no guar- may hurt some consumers. No free lunch.
antee if and only if Satisfaction Guaranteed can be optimal even when
some hard-to-satisfy customers are not profitable. Why?
Because the contributions from the higher prices charged
4. Alternatively, under Satisfaction Guaranteed, the profit from a sat- to the relatively easy-to-satisfy customers could be suffi-
isfied customer i is (V – C). The profit from an unsatisfied customer is (V – ciently large to more than offset these losses. The seller
R + S – C). Therefore, the expected value of the profit from customer i will
be si(V – C) + (1 – si)(V – R + S – C). The summation of profits from all N cannot directly exclude the hard-to-satisfy customers from
customers is
N
the market and therefore must offer the guarantee to all
∑ S i (V − C ) + (1 − si )(V − R + S − C )
i =1
customers. Note from Equation 9 that Satisfaction Guar-
N
= N (V − C ) + ∑ (1 − s )(S − R )
i =1
i .
6. The first term of Equation 9, representing the additional gain from
N
extracting extra surplus from the k “easier-to-please” customers under
= N (V − C ) + ∑ (1 − si )(S − V − H ).
i =1
guarantee, is always positive. The second term is negative. It reflects the
loss from the N – k “harder to satisfy” customers, who will become buyers
This is exactly the formula in Equation 8. under guarantee. The third term can be positive or negative. It represents
5. Adding the assumption that si is continuously uniformly distributed the expected loss or gain when the guarantee is claimed. When it is, the
in the interval [0,1], the optimal market size is 1 and the profit becomes seller gains a salvage value, S, but dissatisfied customers must be com-
pensated for their hassle, H. The term will be positive if S is greater
1 than H.
Π *G = ∫ [(V − C ) + (1 − si )(S − V − H )]dsi = V − C + (S − V − H ) / 2.
0Fruchter, Gerstner / SATISFACTION GUARANTEED 319
TABLE 3
Profitable “Satisfaction Guaranteed” May Hurt Consumers:
Illustrative Examples (parameters: C = 2, S = 0, s1 = 1, s2 = .75, s3 = .5)
The Basic Model Heterogeneity in V Heterogeneity in H
Potential Customers: N = 3 Potential Customers: 2N = 6 Potential Customers: 2N = 6
H = 1, V = 4 H = 1, V1 = 4, V2 = 2 V = 4, H1 = 2, H2 = 1
No guarantee Buyers: k = 2 Buyers: 2 Buyers: 2
Price: P* = s2V = 3 Price: P* = s2V1 = 3 Price: P* = s2V = 3
Expected surplus: Expected surplus: Expected surplus:
k
∑ (s V − P *) = 1
i =1
i (4 – 3) + (3 – 3) = 1 (4 – 3) + (3 – 3) = 1
Profit: ∏ * = k( P * − C ) = 2 (
Profit: ∏ * = 2 P * − C = 2 ) (
Profit: ∏ * = 2 P * − C = 2 )
Guarantee Buyers: N = 3 Buyers: N = 3 Buyers: 2N = 6
Price: PG* = V = 4 Price: PG* = V1 = 4 Price: PG* = V = 4
Refund: R* = V + H = 5 Refund: R* = V1 + H = 5 Refund: R* = V + H1 = 6
Expected surplus: 0 Expected surplus: 0 Expected surplus: 0 + .75 = .75
Profit: ∏G = N (V − C ) −
*
(
Profit: ∏G = 3 PG* − C −
*
) (
Profit: ∏G = 2[ 3 PG* − C −
*
)
∑ (1 − s )( R ) ∑ (1 − s )( R ) ∑ (1 − s )( P − S )] = 3
N 3 3
i
*
− S = 2.25 i
*
− S = 2.25 i G
*
i =1 i =1 i =1
anteed could be profitable even if the salvage value of the the seller will be able to pick easy-to-satisfy customers
product is zero (see the example in Table 3, first column). from both segments.
Guarantee policy. Under this policy the seller has to de-
Other Forms of Consumer Heterogeneity
cide whether to sell only to the customers with high value
V1, or sell to both segments. Using the same logic as in the
So far we have assumed consumer heterogeneity only
basic model, if it is optimal to serve only the high-value
with respect to si. Can Satisfaction Guaranteed work as a
segment, the price will be set at the high value V1, and the
surplus-extracting device if customers are heterogeneous
refund will be V1 + H. If, however, it is optimal to serve
with respect to other characteristics such as V or H? Such
both segments, the price will be set at low value V2, and the
heterogeneity produces a multisegment market. To ad-
refund will be V2 + H. Therefore, in this case, the seller will
dress this issue, we will consider two different scenarios.
not be able to extract all consumer surplus, but still, more
In both scenarios we will assume for simplicity two market
surplus can be extracted under guarantee. In Table 3 (sec-
segments. In the first scenario, each segment differs in its
ond column) we extend the example of our basic model to
product values, V1 and V2, where V1 > V2, but they have the
demonstrate that Satisfaction Guaranteed can be more
same hassle costs, H. In the second scenario, each segment
profitable than no guarantee under consumer heterogene-
differs in its hassle costs, H1 and H2, where H1 > H2 but has
ity in V and that the guarantee can extract all consumer sur-
the same product values, V. Each segment in each scenario
plus and therefore hurt consumers.
is still heterogeneous with respect to the probability of be-
ing satisfied, si, and for simplicity we assume that both seg-
ments have the same number of customers, N, and that the Second Scenario: Heterogeneity in H
probabilities, si, i = 1, . . ., N, within each segment are the
No-guarantee policy. This case is identical to the basic
same.
model, because the hassle cost is not relevant.
First Scenario: Heterogeneity in V Guarantee policy. Again, under this policy, the seller
has to decide whether to sell to only one segment or to both
No-guarantee policy. This case is almost identical to segments. The analysis is similar to the analysis in the first
the case of our basic model. One can draw the graph of Fig- scenario. If it is optimal to serve only the segment with the
ure 2, replacing the Vs with V1 and V2 to obtain the decreas- low hassle cost, the price will be set at V and the refund will
ing demand function and the corresponding marginal be V + H2. If it is optimal to serve both segments, the price
revenue function. The optimal number of customers and will be set at V and the refund will be V + H1. Therefore, the
the corresponding price are determined by equating mar- seller will not be able to extract all consumer surplus, but
ginal revenue to marginal cost. Note that under this policy, consumers may still prefer a no-guarantee policy. The ex-320 JOURNAL OF SERVICE RESEARCH / May 1999
ample in the third column of Table 3 demonstrates that Sat- TABLE 4
isfaction Guaranteed can be more profitable than no Satisfaction Guaranteed Versus
guarantee under consumer heterogeneity in hassle costs No Guarantee: The Competitive Case
and that consumers may prefer no guarantee to guarantee Equilibrium No-Guarantee Guarantee
because more consumer surplus is extracted under the Outcomes Seller Seller
guarantee.
Price Lower Higher
Market served Lower Higher
Profit Lower under Higher under
SATISFACTION GUARANTEED Equation A8 Equation A8
TO DIFFERENTIATE SERVICE Customer’s
expected surplus Positive Zero
Satisfaction Guaranteed can be used to differentiate NOTE: See appendix.
services in a competitive environment. The result of this
section is summarized in the following proposition. or if
Proposition 4 (competition): In a duopoly, when one PG − P (12)
seller uses Satisfaction Guaranteed and the other si ≤ 1 − ,
does not, the seller with the guarantee charges a higher R−H
price and extracts all the expected surplus of his or
her consumers. Both sellers earn positive profits. provided that U Gi ≥ 0 and Ui ≥ 0.
Because si is uniformly distributed in the interval [0,1],
To demonstrate, consider a competitive scenario with two for given prices, consumers will distribute themselves be-
identical firms competing with the same product. As in the tween the sellers consistent with Equation 12, which deter-
basic model, we assume consumer heterogeneity in the mines the market share of each firm. Let Π G and Π be the
probability of being satisfied, si, and add only the assump- corresponding expected profit functions of the firm with
tion that si is continuously uniformly distributed in the in- and without the guarantee. Then,
terval [0,1]. If the firms choose identi cal poli cies,
customers choose the firm with the lowest price. 1−
PG − P
∫ [s ( P ]
R− H
As in the monopoly case, each firm chooses whether to
∏G = i G − C ) + (1 − si )( PG + S − R − C ) dsi
offer Satisfaction Guaranteed or not. Under no guarantee, 0
dissatisfied customers choose the price P and their ex-
pected surplus is given in Equation 1. Under Satisfaction
(13)
( )
Guaranteed, dissatisfied customers obtain back the price,
( ) PG − P
2
1− PRG−−HP R − S
( PG + S − R − C )
PG , plus the hassle cost, H, so the refund R satisfies = + 1−
2 R−H
R = PG + H. (10)
and
In addition, the consumer’s expected surplus is given in
Equation 5. 1
( PG − P )( P − C )
Consider first what would happen if both sellers ∏= ∫ ( P − C )ds
PG − P
i =
R−H
. (14)
adopted the same policy. Here, all consumers would prefer 1−
R− H
a seller with a lower price. Bidding for customers, each
seller undercuts the rival’s price, until in equilibrium both For a Nash Equilibrium, the guarantee firm chooses its
sellers earn zero profits. As a result, consumers obtain price, PG*, to maximize profits subject to the Satisfaction
positive surplus. What happens if one firm offers Satisfac- Guaranteed policy described in Equation 10, given the best
tion Guaranteed and the other does not? price P* of the no-guarantee seller. Simultaneously, the
According to the corresponding expected consumer no-guarantee firm chooses its price, P*, to maximize profit
surplus Equations 1 and 5, customer i prefers to buy from given the best price of the guarantee seller, PG*.
the seller with the guarantee if this seller offers the con- In the appendix, we find the equilibrium and show that
sumer a higher surplus than the no-guarantee seller. That under a wide range of parameters, the equilibrium prices
is, if and the refund are
U Gi = si(V – PG) – (1 – si)(PG + H – R) ≥ Ui = siV – P (11) (V + C ) (15)
PG* = V, R* = V + H, and P* = .
2Fruchter, Gerstner / SATISFACTION GUARANTEED 321
FIGURE 4
Monopoly Versus Competition: Optimal Outcomes
In the appendix, we also derive the optimal values of the high price (equal to the willingness to pay of satisfied cus-
expected profit functions by substituting the equilibrium tomers). We find that this policy can be a creative device to
values in the profit Equations 13 and 14. Note that the cus- capture back the added economic value created by the
tomers of the guarantee seller are located left to the divid- seller for customers through the guarantee. Moreover, un-
ing point P*/PG* = (V + C)/2V. The surplus of consumers der competition, Satisfaction Guaranteed can be used to
who buy under Satisfaction Guaranteed is completely ex- segment the market in a profitable way through service dif-
tracted, but they would not buy from the no-guarantee ferentiation. We provide conditions under which Satisfac-
seller because their surplus would be negative. The con- tion Guaranteed can be more profitable than selling with
sumers located to the right of the dividing point buy from no guarantee and show that it can be more profitable even
the no-guarantee seller and obtain positive surplus. The if a returned product has no salvage value.
consumer at the dividing point is indifferent between the Satisfaction Guaranteed seems to be a policy designed
two sellers and obtains zero surplus ((V + C)/2 – P* = 0). to delight consumers. Our analysis shows that eventually it
Table 4 summarizes the section’s results. In Figure 4, we may not. The high price under Satisfaction Guaranteed
compare the monopoly and competitive optimal out- may counteract its benefits to easy-to-satisfy consumers.
comes, with and without guarantee (see also footnotes 2 This conflicts with the conclusions of Fornell and Werner-
and 5). felt (1987, 1988) that generous compensations to dissatis-
fied consumers increase consumers’ expected utility from
purchase. This conclusion follows from the assumption in
CONCLUSION their models that sellers do not raise the price when offer-
ing such generous compensations. Relaxing this assump-
In this article, we investigate a market in which con- tion, we conclude that Satisfaction Guaranteed could hurt
sumers are heterogeneous in their probability of being sat- consumers.
isfied from a purchase transaction. We introduce the Finally, Satisfaction Guaranteed may induce moral-
concept of selling with Satisfaction Guaranteed by defin- hazard behavior by consumers. Chu, Gerstner and Hess
ing it as a policy assuring that no consumer obtains post- (1998) showed that if some consumers behave opportunis-
purchase negative economic added value from purchasing tically by buying products for a short time use and then re-
a product. Considering a wide spectrum of guarantee poli- turning them for a refund, sellers may offer only partial
cies, we find that the most profitable one is a Satisfaction refunds. On the other hand, retailers such as Nordstrom or
Guaranteed policy that generously compensates dissatis- Hampton Inn believe that generous guarantee policies
fied customers for all costs involved (price paid plus the translate to benefits such as new sales, higher prices, and
hassle costs associated with a product return) but that sets a lower customer defections. Under their calculations, these322 JOURNAL OF SERVICE RESEARCH / May 1999
benefits exceed the losses from consumers who cheat and
(Hart 1988; Rust, Zahorik, and Keiningham 1996, p. 205).
(V − C )
2
In our model, the impact of moral-hazard behavior is in- (A6)
cluded implicitly. When the proportion of the hard-to- Π =*
.
4V
satisfy customers is large, many consumers buy the prod-
uct knowing that the probability of returning it is high. We
The profit of the no-guarantee seller (Equation A6) is
have shown that in these circumstances, the seller will pre-
always positive. The expected profit under Satisfaction
fer not to offer Satisfaction Guaranteed. This result is simi-
Guaranteed is positive if the salvage value satisfies,7
lar in nature to the result of Chu, Gerstner, and Hess
(1998).
S > C + H, (A7)
APPENDIX (Obviously S < V).
Assuming that Equation A4 holds, comparing Equa-
To find the Nash Equilibrium, we first differentiate the profit
tions A5 and A6, the optimal Satisfaction Guarantee pol-
function Equation 13 of the guarantee firm with respect to PG. We icy is more profitable than no guarantee if and only if
obtain
(V + C ) V + C S − H −C (A8)
∂Π G PG − P R − S PG + S − R − C (A1) 2V 4V + H + V − S
= 1− 1− − .
∂PG R − H R − H R−H
(V − C )
2
For a Satisfaction Guaranteed policy, that is, for R = PG (H + V − S ) − > 0.
+ H, the right-hand side of (A1) is positive if and only if 4V
PGC > (PG – P)(S – H). (A2)
In other words, if Equation A2 is satisfied, the seller
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2
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2V 4VFruchter, Gerstner / SATISFACTION GUARANTEED 323
——— and G. Mayhew (1997), “Modeling Merchandise in Direct Mar- Gila E. Fruchter is a lecturer of marketing (parallel to assistant
keting,” Journal of Direct Marketing, 11 (2), 20-35. professor) at the Technion–Israel Institute of Technology. After
Longo, T. (1995), “At Stores, Many Unhappy Returns,” Kiplinger’s Per-
sonal Finance Magazine, 49 (June), 103-104. receiving her D.Sc. in mathematics from the Technion, she stud-
Lutz, N. A. (1989), “Warranties as Signals under Consumer Moral Haz- ied marketing at the Recanati Graduate School of Business Ad-
ard,” RAND Journal of Economics, 20 (Summer), 239-55. ministration, Tel Aviv University, and spent several summers as a
Mann, D. and J. Wissink (1990), “Money-Back Warranties vs. Replace- visiting scholar at the Olin School of Business, Washington Uni-
ment Warranties,” American Economic Review, 80 (May), 432-36.
versity, St. Louis; MIT Sloan School of Management; and Haas
Menezes, M.A.J. and I. S. Currim (1992), “An Approach for Determina-
tion of Warranty Length,” International Journal of Research in Mar- School of Business, University of California–Berkeley. Her re-
keting, 9, 177-95. search focus is on the applications of optimal control to competi-
Moorthy, S. and K. Srinivasan (1995), “Signaling Quality with Money- tive marketing strategy. Her specific research topics include
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Neuborne, E. (1996), “Burned Retailers Are Fed Up, Clamping Down,”
USA Today, June 3. marketing. Her other research has appeared in Management Sci-
Padmanabhan, V. and I. Png (1997), “Manufacturer’s Return Policies and ence and the European Journal of Operational Research.
Retail Competition,” Marketing Science, 16 (1), 81-94.
——— and Ram Rao (1993), “Warranty Policy and Extended Service
Contracts: Theory and an Application to Automobiles,” Marketing Eitan Gerstner is a professor of marketing at the University of
Science, 12 (3), 230-47. California–Davis. His research articles on pricing, distribution
Rust R., A. Zahorik, and T. Keiningham (1996), Service Marketing. New channels, and service marketing were published in marketing
York: HarperCollins.
Schmidt, S. and J. Kernan (1985), “The Many Meanings (and Implica- and economics journals including the Journal of Marketing Re-
tions) of Satisfaction Guaranteed,” Journal of Retailing, 61 (4), 89- search, Marketing Science, the Journal of Service Research, the
108. Journal of Business, and the American Economic Review. He
Westbrook, R. (1981), “Sources of Consumer Satisfaction with Retail serves on the editorial board of Marketing Science and served on
Outlets,” Journal of Retailing, 57 (Fall), 68-85. the editorial board of the International Journal of Research in
Woodruff, R., E. Cadotte, and R. Jenkins (1983), “Modeling Consumer
Satisfaction Processes Using Experienced-Based Norms,” Journal of Marketing. He consulted with organizations in the United States
Marketing Research, 20 (August), 296-304. and abroad in the areas of service marketing and marketing
strategy.You can also read
