An Anchoring and Adjustment Model of Purchase Quantity …€¦ · Firms might receive net benefits...

BRIAN WANSINK, ROBERT J. KENT, and STEPHEN J. HOCH'

How do consumers decide how many units to buy? Whereas priorresearch on individual consumers' purchases has focused primarily onpurchase incidence and brand choice, the authors focus on the psycho-logical process behind the purchase quantity decision. The authors pro-pose that a simple anchoring and adjustment modei describes how con-sumers make purchase quantity decisions and suggests how point-of-purchase promotions can increase sales. Two field experiments and twolab studies show that anchor-based promotions—presented as multiple-unit prices, purchase quantity limits, and suggestive selling—canincrease purchase quantities. The final study shows that consumers whoretrieve internal anchors can counter these anchor-based promotionseffectively. Firms might receive net benefits from anchor-based promo-tions depending on whether increases in unit sales reflect increasedcategory consumption, brand switching, variety switching, store

switching, or stockpiling.

An Anchoring and Adjustment Model ofPurchase Quantity Decisions

Most behavioral and quantitative research investigatingconsumers" purchase behavior has focused on purchase in-cidence ("when") and brand choice ("what"). Less effort hasbeen directed toward understanding the psychology of thepurchase quantity decision—the "how much"' question(Gupta 1988). For managers of mature brands, focusing onhrand choice may he self-limiting; some marketing dollarsshould he allocated toward encouraging current users to pur-chase more of the brand and use it more frequently(Wansink 1994). In tbis article, we presenl a simple psycho-logical model that focuses directly on how current users ofbrands decide how much to purcbase.

Why is the quantity decision Important? The average con-sumer regularly shops at multiple stores and makes manyunplanned, discretionary purchases (Dreze and Hoch 1998;Dreze, Hocb, and Purk 1994). Most retailers and manufac-turers prefer guaranteed sales from a customer today to

'Brian Wansink is Associate Professor of Busiiiess Adminislraiion. Uni-versiiy of Illinois al Urbana-Champaign (e-mail: [email protected]).Robert J. Kenl is Assistant Professor of Markeling. College of Business andEconomics, University of Delaware (e-mail: [email protected]).Stephen J. Hi>ch is John J. Pomeranlz Professor of Marketing, WhartonSchool, University of Pennsylvania (e-mail: hiKhs@vk'hanon.upenn.edu).The aulhors are grateful to the Marketing Science In^tilute for its supponof the project. Helpful comments on various aspects of this research wereprovided by Chris Allen, Rick Andrews, J. Scott Armstrong, Pierre Chan-don, Don Conlon, Pete Fader, Howard Garland. Frank Kardes, RobertLusch. Robert Schindler, P. Rajan Varadarajaii, John Wansink. anonymousJMR reviewers, and tbe J. B. Williams Company,

prohabilistic future sales. For retailers, tbe more units soldon any shopping trip, tbe greater the share of sbort-term gro-cery dollars. For manufacturers, tbe same logic bolds; tbemore units sold (witness multiple-unit coupons and packag-ing), the less likely a consumer will run out of stock and pur-cba,se a cotiipeting product. We suspect tbat managers pre-fer selling large quantities if doing so (1) takes buyers out oftbe market. (2) facilitates repeated consumption tbat leads tohabit formation (pseudo loyalty tbrougb linear learning), (3)encourages promotion-driven stockpilers to switch stores orbrands (Jeuland and Narasimhan 1985), (4) passes invento-ry holding costs on to consumers (Blattberg, Fppen, andLiebemian 1981), or(5) enahles accelerated consumption innew situations or in place of other product categories(Wansink and Ray 1996).

Although increased purchase quantities can influenceconsumer stockpiling, we do not wisb to overstate tbeeconomic significance of higher purcbase quantities. Acomplete analysis of tbe benefits and costs of stockpilingrequires a dynamic approach thai considers multiperiodconsequences and competitive responses. Our intent is toilluminale tbe psycbology tbat governs bow consumersmake quantity decisions and to suggest how nmrkelers caninfluence these decisions.

We take as given tbat stockpiling can be beneficial tomanufacturers in some circumstances. For example, stock-piling can discourage the trial of potentially damaging newbrands and reduce consumer stockouts during usage-relatedadvertising campaigns. Still, stockpiling is less valuablewben not accompanied by an increase in consumption. Con-

71Journal of Markeiiiii; Re.'ieiirchVol. XXXV (Februarv 1998), 71-81

72 JOURNAL OF MARKETING RESEARCH, FEBRUARY 1998

sider an equilibrium in which competitive manufacturersfully responded to the promotional efforts of other manu-facturers. Under such circumstances, retaliation could nulli-fy any short-term gains from taking consumers out of themarket. If the marketer simply wants to stimulate trial andrepeated consumption does not increase preference, it maybe more profitable for retailers to minimize promotionalpurchases to ensure that consumers pay full price on laterpurchases.

The rest of the article is organized as follows: First, we re-view previous research on the purchase quantity decisionand propose that a simple anchoring and adjustment judg-ment process adequately describes how consumers makethese decisions. This anchoring model also suggests waysthat marketers can influence quantity decisions through an-chors provided at the point of purchase (POP). Second, wereport a series of two field and two laboratory studies thatdocument and explain the effect of various POP anchors onquantity decisions (see Figure I). In Study 1, we manipulatethe anchor through multiple-unit pricing (e.g., "2 for," "3for") in 13 field experiments in an 86-store supermarketchain. Multiple-unit promotion pricing led lo a 32% increasein sales compared with single-unil pricing. Study 2 manipu-lates the anchor through supermarket quantity limits (e.g.,"Limit 12 per customer") and reveals a monotonically in-creasing impact on sales. In a lab setting. Study 3 shows thatsuggestive selling anchors (e.g., "Buy 18 for your freezer")can influence intended purchase quantities even without adiscount. Finally, Study 4 provides more direct evidenceabout the psychological processes that occur during pur-chase quantity decisions. It shows how internally-generatedanchors—default anchors ("How many units do you usual-ly buy?") and expansion anchors C'Think of al! the differentways you could consume this product over the next twoweeks")—influence purchase intentions and effectively nul-lify any impact of contemporaneously presented externalPOP anchors.

WHEN. WHAT, AND HOW MANY?

Several articles suggest that purchase behavior resultsfrom the consumer considering three questions: "Should Ibuy the category on this shopping trip?" "Which brandshould I buy?" and "How much should I buy?" (Bucklin andLaltin 1991; Chintagunta 1993; Gupta 1988; Hardie andBarwise 1996; Krishna 1994; Krishnamurthi and Raj 1988;

Figure 1SUMMARY OF ANCHORING STUDIES

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Neslin, Henderson, and Quelch 1985). The central empiricalfinding is thai most of the action occurs in the hrand choicecomponent followed by incidence and then quantity.Although these articles propose a variety of modeling andestimation solutions, they all focus on the simultaneity (orlack thereoO of the asking and answering of these threequestions (cf. Gupta et at. 1996). Researchers agree that thequestions asked and the resultant answers are not indepen-dent. The issue is one of degree. Most of the articles explic-itly recognize that the brand choice (what) and the purchaseincidence (when) questions are inextricably linked. Forexample, it is easy to imagine purchase situations in whichthe consumer notices an attractively priced brand and thenmakes the "when," "what," and "how many" decisionssimultaneously. Alternatively, consumers sometimes cometo the store already planning to buy the category; incidenceis ensured and only "what" and "how many" are in question.

Chiang (1991) forcefully argues that the answers to allthree questions are governed by the same underlyingforce—namely, a utility maximiz;ation process that is drivenby the difference between the price-adjusted quality of eachof the brands and the consumer's threshold reservationprice. The bigger this difference, the greater the probabilityof purchase incidence and brand choice and the greater thequantity purchased. Although Chiang's structural approachis appealing, we believe that the answers to the first twoquestions are linked more closely to each other than eitherof them is to the quantity decision. Our reasoning is drivenby a simple conjecture that most quantity decisions are notconsidered actively because the answer already is known.And our best guess is that the answer is usually a low num-ber consistent with routine purchases. This may be one rea-son why quantity elasticities typically are smaller than thosefor brand choice and incidence.

An Anchoring and Adjustment Judgment Process

We propose a simple behavioral model to explain pur-chase quantity decisions. When consumers see a productwhose price-adjusted utility rises sufficiently above athreshold, they might decide to buy it (brand choice) on thespot (purchase incidence). The question then becomes, howmany units to buy? Because of the frequent nature of mostpackaged goods purchases, the default value should be low.We contend that consumers often adopt low default anchors(such as one or two) and then adjust upward depending onprice attractiveness, stockpiling constraints, substitutionopportunities, purchase timing, perceptions of deal fre-quency, and budget constraints.

If this model reasonably characterizes the basic quantitydecision process, then consumers might not adjust muchfrom their initial anchor. There are at least two reasons forthis. First, anchoring and adjustment judgment processes arecharacterized by excess reliance on the starting point and in-sufficient adjustment for subsequently considered informa-tion (Wilson et al. 1996). Second, because food shopping isgenerally a mundane, low-stakes activity, most consumerswill not be motivated to engage in extensive adjustment ac-tivity that requires thinking about the dynamic costs andbenefits associated with stockpiling (Blattherg, Fppen. andLieberman 1981; Meyer and Assuncao 1990). As.sumingconsumers naturally anchor on a small quantity and then in-sufficiently adjust upward (depending on the price), they

Purchase Quantity Decisions 73

might purchase more of the product if they anchor on a larg-er quantity—such as one noted in a POP display—and thenadjust downward {again depending on the price).

Anchoring is observed in many natural contexts and ap-pears to he "extremely robust" even with experts and im-portant decisions (Pious 1993, p. 151). Potential anchoringvalues can be difficult to ignore. As with other heuristics,people often are unaware of an anchor's influence. Evenrandom and Irrelevant values that are converted to a re-sponse scale can act as anchors and influence quantity judg-ments (cf. Tversky and Kahneman 1974). These findingssuggest that retail promotions that explicitly provideproduct-unit values ean have an important impact on howmuch a consumer huys.

Current merchandising practice suggests that retailersmight have the same intuition. Product quantity values thatcan serve as anchors are found in multiple-unit prices (e.g.,prices that are presented as "4 cans for $2" instead of "50(iper can"), purchase quantity limits ("Limit of 6 per cus-tomer"), and suggestive selling (e.g., "Buy 12 for yourfreezer"). We hypothesize that though purchase anchors canbe presented in several ways, they will have similar impactson consumers.

STUDY I: DOES MULTIPLE-UNIT PRICING INCREASESUPERMARKET SALES':'

Supcmiarket consumers are exposed to potential quantityanchors whenever multiple-unit price.s are presented insteadof single-unit prices (e.g., "On sale—6 eans for $3" versus"On sale— fiO i"). When involvement is low, an anchoringperspective suggests that a multiple-unit price promotioncould stimulate more sales hy making salient a higher thannormal purchase quantity. Although each promotion offersthe same discount, the number of product units presented atthe POP is likely to serve as an anchor when consumersmake their quantity decisions. Conventional wisdom in theretail trade suggests that multiple pricing does work, but weknow of only one study documenting the effect (cf. Blat-tberg and Neslin 1990, p. 351). Using an econometricapproach to control for baseline sales and marketing vari-ables, "n for" pricing increased sales 12% across sevenhrands in three categories. We use field experiments to

examine the impact of multiple-unit pricing across a largerset of categories.

Method and Procedure

For the 13 products listed in Table 1, we conducted a one-week field experiment comparing multiple- with single-unitpromotional pricing. Each study used a simple two-grouppre/post design. Half of the 86 stores were assigned ran-domly to either a single- or multiple-unit pricing conditionseparately for each category. Baseline sales were computedfor each test item using the procedure outlined in Dhar andHoch (1996)—the average weekly sales over the previoussix months during all weeks in which the item was not pro-moted. The dependent variable was calculated as a percent-age ehange in unit sales compared with the baseline. Duringthe week of each experiment, the test item was sold with atemporary price reduction ranging from 9% to 44% signaledat the POP with a 3.5 x 2.5-inch "bonus buy" shelf tag. Thetag indicated the regular price (e.g., 990) but expressed thedeal price in single-unit (e.g., 75^) or in multiple-unit (e.g..2 for $1.50) form.

Results and Discussion

The results are summarized in Table I. As can be seen,multiple-unit prices resulted in a 32% increase in sales overthe single-unit control. This was calculated as a weightedaverage across the 86 stores. For 12 of 13 products, saleswere higher with multiple-unit pricing, and for 9 productsthe difference was statistically significant. A meta-analysisof all 13 tests indicates that the multiple-unit pricing effectis highly reliable (p < .0001). Multiple-unit pricing pro-duced substantial increases in promotional lift.

Before moving on to the rest of the studies, it is importantto be clear about what this experiment does and does not tellus about anchoring and quantity decisions. One possibilityis that some consumers might have been confused and be-lieved that they needed to buy multiple units to get the dealprice. Given the completely unobtrusive nature of the fieldstudy, we have no self-report data on the frequency of suchconfusion. Regardless, the retailer does not care whetherconsumer confusion caused the sales increase as long asthere is no loss of goodwill that later might affect store pa-

Table 1THE IMPACT OF MULTIPLE-UNIT PRICING ON SUPERMARKET SALES

Proiliicl

Biilhrtioin Ti.ssueCandyCereal (BrealvCu.-;!)CookiesFrozen DinnersFrozen DinnersFrozen EnireesPaper TowelsSoap (3-Bar Packs)Soft Drinks (2 t.ilcrs)Soup (Canned)Soup(Canned)Tuna (Canned)

Level ofDiscount

15%9%

33%44%12%20%26%31%iS%17%20%17%18%

21%

Form of PriceExpression

I/5()C versus 4/$2.OOI/50C versus 2/$ 1.00

l/$l.y9 versus 2/$3.98[/$1,67 versus 2/$3.34l/$2,49 versus 2/$5.OOl/$2.5O versus 2/$5.OOl/$l.25 versus 2/$2.5O

l/75(t versus 2/$ 1.501/$ 1.99 versus 2/$3.98l/$l.49 versus 2/$3.OOl/$1.33 versus 3/$4.00

l/50tf versus 2/$ 1.001/65C versus 2/$I.30

Percentage Change in

Single unii

+57+24+ 133+306+33+ 133+ 133+403+48+33+200+ 108+36

+ 125%

Unit Sales'

Multiple unit

+97+25+ 137+372+70+195+1S6+565+30•f«6+248+ tl2+66

+ 165%

p- Value

.02n.s.n.s.

.01

.003,0001.02.001n.s.

.01

.01n.s.

.004

.0001


tronage. We cannot rule out confusion calegorically, thoughit seems implausible that confusion consistently could haveproduced a 32% (I65%/125%) improvement in promotion-al lift (Hoch, Dreze, and Purk 1994). Also, because we aredealing witb store-level data, it is unclear wbetber individ-ual consumers bougbt more units tban normal or wbethermore consumers bougbt tbeir normal quantities of tbe iteminstead.

Clearly, tbere are natural limits to tbe sales impact of mul-tiple-unit prices. Some items are not amenable to multiple-unit pricing (e.g., two 50-pound dog food bags for $30). andtbe sales impact of using multiple-unit pricing on everytbingin tbe store would be negligible or possibly barmful becauseof confusion and Increased consumer vigilance. Eventhough some sales impact of multiple-unit pricing might bedue to its novelty and uniqueness, we believe tbere is moreto it than tbat.

Whereas managers are interested in whetber multiple-unitprices increase sales, researcbers are interested in wby tbeyincrease sales. To test more directly tbe impact of ancbor-ing, we searcbed for a natural and managerially relevantway to present monotonically increasing ancbor points. Acommon promotional metbod that fits these criteria is pur-chase quantity limits (e.g., "Limit 12 per customer").

STUDY 2: DO HIGH PURCHASE QUANTITY LIMITSINCREASE SALES?

In Study 2. consumers are presented with ancbor values intbe form of bigh purcbase quantity limits. This enables us togeneralize tbe external ancbor effect from Study 1 andexamine the purcbase bebavior of individuals. Retailers fre-quently limit the quantity of aggressively priced items usedto increase store traffic. These limits restrict sales of lossleaders and reduce tbe probability of out-of-stocks. Despitetbe widespread use of purcbase quantity limits, only twostudies bave examined them, and each used low limits (fourunits or less). Several critical questions about the impact ofpurchase limits on sales remain unanswered.

For example, different psychological processes have beenproposed to explain wby relatively low purchase limitsmigbt influence sales. Lessne and Notanuitonio (1988) sug-gest that low purcbase limits can increase purcbase inci-dence. Tbis is because consumers react to the loss of free-dom to buy more price-promoted units. However, consistentwitb tbe scarcity literature (cf. Lynn 1992; Verhallen andRobben 1994), it has been found that single-unit purchaselimits can increase purchase incidence by signaling tbat tbedeal is good (Inman, Peter, and Raghubir 1997). Indeed,single-unit limits can have particularly strong effects on dealevaluations. No previous studies, however, have examinedhow bigber purcbase limits infiuence sales. It migbt be ex-pected tbat a bigber limit (12 versus 4) reduces reactanceand weakens deal signals. Yet if progressively bighcr pur-chase limits begin to infiuence the quantity decision tbroughanchoring, tbey still could yield sales increases.

Study 2 uses unobtrusive observation to investigate howvarious purcbase limits infiuence supermarket sales of a fa-miliar, sale-priced consumer packaged good. If ancboringdrives purcbase quantity decisions, a bigb anchor should en-courage greater purchase amounts than a lower ancbor.


A field study was designed using end-aisle displays toadvertise a variety of Campbell's soups for 19<i per can. Theregular price was 89?. which implied a modest 12% dis-count. A sign was mounted bebind each display announcing"Campbell's soup sale—^79e/can" and presenting one ofthree limit conditions ("No limit per person." "Limit of 4 perperson," or "Limit of 12 per person").

Tbree supermarkets in Sioux City. Iowa participated intbe study on tbree consecutive evenings. Each night from8:00 to 9:{)0 P.M., a rear-aisle display was set up at eacb storeannouncing the sale under one of tbe purchase limits. Thepurcbase limits were rotated eacb evening, so that each storeoffered the sale under each limit condition. Rotating the dif-ferent purcbase limits across the supennarkets and acrossdays minimized any store-related or day-related confounds.Otber efforts were made to ensure that tbe tbree storesserved as replications of one anotber. Tbe three supermar-kets were selected because tbey bad similar sales volumesand a similar demographic mix of shoppers. Moreover.Monday, Tuesday, and Wednesday were selected becausethese are the tbree consecutive evenings tbat have the mostsimilar shopping volumes for tbese tbree stores.

Sboppers were observed unobtrusively at the end-aisledisplay. For eacb of the 914 sboppers who passed tbe dis-plays, observers noted wbether each customer purcbasedsoup and how many cans were purcbased. Because thestores would not allow signage in the interior aisles, directobservation was used to isolate purchases made from theend aisles. Data for 8 consumers wbo bought more itemsthan the limits allowed were excluded from tbe analyses (6of these sboppers bought from displays with a four-can lim-it), leaving 906 subjects.


An ANOVA was conducted to test wbetber we couldaggregate tbe data across the tbree stores. Altbough mean-level sales varied between tbe stores, no two- or three-wayinteractions (store x purchase limit x day) were significant,and tbe data were aggregated. Tbe results are displayed inTable 2.

The results show tbat purchase limits can increase saleseven witb a relatively small (100) discount (F2.77 = 233;/J< .01). Sboppers wbo bought soup from tbe displays witb nolimit purcbased 3.3 cans of soup, wbereas buyers with lim-its of 4 and 12 purcba.sed an average of 3.5 and 7.0 cans, re-spectively. Tbe buyers in tbe limit 12 condition purcbasedsignificantly more cans than consumers in either tbe no-

Table 2

THE IMPACT OF PURCHASE QUANTITY LIMITS ON

SUPERMARKET SALES

Quantity Limit Levei

Measure No Umii Until 4 Liinii 12

Pur;;huse Quantity per Buyer 3.3» 3.5» 1.0^Purchase Incidence 7% 10% 9%Total Units Sold 73'' MAd^ 188"

Note: Means with dit'ferenl superscripts are relinbly ditTcrent from oth-ers in that row at the p < .05 level according to the Duncan multiple com-parisons procedure.


limit condition (t77 = 16.2; p < .01) or the limit 4 condition(t77 = 6.0; p < .01). The magnitutle of the effect islarge—limit 12 signage increased sales per buyer by 112%.

Consistent with the work of Inman. Peter, and Raghubir(1997). purchase quantity limits encouraged directionallyhigher purchase incidence than the no-limit condition (10%and 9% versus 7%). It is important to note that when theseseemingly small variations in purchase incidence are multi-plied by the respective purchase quantities, differences in to-tal sales between the no-limit condition (73 cans) and the

limit 4 condition (106 cans) and the limit 12 condition (188cans) are magnified (F2.%2 = 5.0;p < .01). For every personwalking by the display, this translates into .25, .34, and .63cans, respectively. Total sales from the limit 12 conditionwere reliably higher than sales from the control condition(t77 = \4.4\p< .01) and the limit 4 condition (t77 = 5.8;/J<.01).

Figure 2 displays the discrete density functions for eachof the three conditions. The overall pattern of data appearsto result from a combination of two separate influences,

Figure 2HOW PURCHASE QUANTITY LIMITS INFLUENCE CANNED SOUP PURCHASES

Percentageof Buyers

Purchasing NCans of Soup

100

90

80

70

60

50

40

30

20

10

0

No Limit Per Person

5 6 7 8

Number of Cans Purchased

10 12

Percentageof Buyers

9080706050403020100

Limit 4 per Person

5 6 7 8

Numher of Cans Purchased

10 11 12

Percentage(if Buyers

Purchasing NCans ofSoup

5 6 7 8

Numher of Cans Purchased

10 I I 12


both brought about by the presence of a particular limitlevel—one due to anchoring and the other to truncation. An-choring is evident from the mass point that appears al eachlimit level (note limit 4) and from a stretching out of the re-sponse scale (compare "no limit" with "limit 12"). The dataalso suggest that a reasonable number of consumers bumpedinto the limit level in the limit 4 condition and would havebought more if they had been allowed.

The findings in Study 2 are consistent with the idea thathigh purchase quantity limits provide consumers with an an-chor from which they insufficiently adjust downward. At thesame time, quantity limits have other properties—truncationand a potential scarcity signal—whose influence is difficultto gauge. Given our hypothesis about the underlying judg-ment process, other promotions that present product-quanti-ty values also could induce anchoring in the quantitydecision.'

STUDY 3: WILL SUGGESTIVE SELLING ANCHORS BEEFFECTIVE WITHOUT DISCOUNTS?

Thus far, we have shown sales increases when productquantity anchors are presented in multiple-unit prices andpurchase limits. If anchoring infiuences the quantity deci-sion as we suggest, then other POP anchors (e.g., "Buy 18Snickers bars for your freezer") also could affect purchasequantity intentions. In Study 3, we Investigate such anchor-based suggestive usage slogans. We also examine whetherthese anchors can influence purchase intentions whenaccompanied with no price discount.


One hundred twenty undergraduates from a large univer-sity participated in a shopping scenario being conducted for"managers of local convenience stores." Each subject wasoffered six well-known products at one of three price levels:an actual convenience store price (no discount), a 20% dis-count, and a 40% discount. All subjects were given sugges-tive selling claims that included either no product quantityanchor ("Snickers bars—buy them tor your freezer") or anexplicit product quantity anchor ("Snickers bars—buy 18for your freezer").^ The design was a 2 (anchor versus noanchor) x 3 (no discount versus 20% discount versus 40%discount) within-subjects design using six counterbalancedproduct replicates with randomized presentation order. Sub-jects were given no indication whether the price was a dis-count and were asked to provide purchase quantity inten-tions for all products.

'The anchoring literature suggests that consumers might be ieven by irrelevant anchors (cf. Pious 1993; Tvcrsky and Kahneman 1974),This was confirmed in a lab study, in which 98 students were given a shop-ping scenario and shown promotional signs for five price-promoted prod-uces (25% discount) thai were "shipped lo stores" in tnixes of a specifiednumber of units (7, 14. 28, or 56 units). Even though a sign ihai read"shipped to stores in boxes of n" arguably provided an irrelevant anchor,.subjects in the 7, 14. 28. and 56 conditions indicated they would purchasean average of 3,9. 5,6. 10,5. and 6.5 units, respectively. This main effect ofthe shipping carton anchor size was significant {/) < ,01), The higher theanchor, the more they intended to buy. except at the highest anchor (56),which appeared to backfire (see Study 3 in Wansink. Kent, and HcK;h1997),

-Other anchoring operationalizalions included "Quaker Oats granolabars—buy 18 for your backpack." "Wriglcy's guin—buy 18 for class.""Certs—buy 18 for studying," "Minute Maid orange juice boxes—buy 18for your room." and "Yoplait yogurt—buy 18 for dessert,"

Figure 3THE IMPACT OF SUGGESTIVE SELLING ANCHORS AND

DISCOUNTS

PurchaseQuuntilyIntention'!

(in uniis)

Anchor("Buy IK liir yiiu

^ • No Anchor, * 0-5) ("Buy some for your freezer")

2U% DiwcHinl

Discount Level


A MANOVA of purchase quantity intentions indicated amain effect of product type but no interactions with theother variables. Therefore, to control for tbe main effect ofproduct type, we mean-centered tbe data separately by prod-uct. The untransformed means are shown in Figure 3. Boththe anchor (F| j 14 = 4.1; /J < .05) and discount level (F2.114= 5.3: p < .01) increased purchase quantity intentions. Therewas no interaction between anchor type and discount level(F2J14 = 1.2; n.s). Simple main effect tests indicated a posi-tive trend for discount level in both anchor conditions.

Of particular interest is that the external anchor increasedintended purchase quantities even without a discount. Al-though this finding is reminiscent of work on mindless be-havior (Inman, McAlister, and Hoyer 1990; Langer. Blank,and Chanowitz 197S), it also provides further testimony tothe power of usage-related claims. Such claim.s huve beenshown to increase usage frequency and volume of invento-ried products such as Campbell's soup. Ocean Spray cran-berry sauce, and Jeil-O gelatin (Wansink and Ray 1996).Given tbis impact on usage, it is not necessarily surprisingto find a corresponding impact on purchase quantity inten-tions, even in the presence of no discount.

The first three studies are consistent with previous tlnd-ings on external anchors. However, we believe that super-market shoppers might be able to resist POP (external)anchors by using self-generated (internal) anchors. We ex-amine this in Study 4, thereby providing additional evidencethat anchoring is the psychological mechanism driving theresults of the previous experiments.

STUDY 4: CAN INTERNAL ANCHORS MODERATE THEIMPACT OF ANCHOR-BASED PROMOTIONS?

The first three studies show that external anchors canhave a pronounced impact on purchase quantity decisions.Tbis held across different types of proniotions (multiple-unitpricing, quantity limits, and suggestive .selling anchors) andin both field studies and controlled laboratory conditions.Yet we have provided no direct evidence that the psycho-logical mechanism driving the results is actually an anchor-ing and adjustment process. Obtaining process-level evi-


dence about judgmental heuristics through retrospective orconcurrent verbal protocols is not easy. And so Study 4relies on analysis of judgmental output but does so in thecontext of experimentally manipulated internal anchors.

We assume that the judgment process underlying thequantity decision is as described at the outset of the article;that is, when consumers decide whether and what to buy.they anchor on a small purchase quantity and make upwardadjustments depending on deal attractiveness. Our logic forunderstanding the psychological mechanism underlying thequantity decision is as follows: If respondents implicitlygenerate low anchors on their own, then their judgmentsshould not be altered when they explicitly generate similarinternal anchors before making quantity decisions. Alterna-tively, if we ask them to explicitly generate an anchor theyusually would not retrieve (such as a large anchor promptedhy considering an expanded set of usage occasions), weshould observe a divergence in their quantity decisions.

We examine the effect of two internally generated an-chors on purchase intentions. These anchors are in the formof a default anchor ("How many units do you usually buy?")and an expansion anchor ('Think of all the different waysyou could consume this product over the next two week.s").Given their personal nature, we believe that salient internal-ly generated anchors will influence quantity intentions andoverride any effect of a contemporaneously presented exter-nal POP anchor.


One hundred thirty-nine undergraduate students from alarge university participated in Study 4 in partial fulfillmentof a course requirement. The experimental setup was simi-lar to Study 3. Each subject was told that he or she wasinvolved in a shopping study for a local grocery store andwas given a shopping scenario involving 25-30% discountson single servings of well-known products (e.g., Coca-Cola,Oreo cookies. Snickers candy bars, Sunkist oranges,Wrigley's tlve-pack gum).

The experiment used a 4 x 3 mixed design involving afour-level external anchor and a three-level internal anchor.The external anchor was manipulated within subjects, andthe internal anchor was manipulated between subjects. Forthe external anchor, we used four purchase quantity limits:a no-limit control, limit 14. limit 28, and limit 56. The in-ternal anchor had three levels: a no internal anchor control,a default internal anchor, and an expansion anchor. Instruc-tions for the default anchor were as follows: After seeing thedetails of the promotional deal (i.e., product description,regular and discounted prices, and quantity limits if any),subjects immediately were instructed to answer the question"How many |units of this product (e.g., packs of gum)] doyou usually huy at a time?" After writing down a number,each student indicated his or her intended purchase quantityfor the item. Instructions for the expansion anchor were sim-ilar to those used by Wansink and Deshpande (1994). Afterseeing the deal, subjects were asked, "On each of the linesbelow, please write down a different situation in which youmight hnagine yourself (consuming this product (e.g.,chewing some gum))."' After listing different usage occa-sions, they were asked, "How many [units of this product(e.g., packs of gum)| do you think you might [use (e.g.,chew)j in the next month?" Finally, subjects provided theirintended purchase quantities.

We had only three firm expectations about the data. First,in the absence of external anchors, the default internal an-chor should produce results similar to the no internal anchorcontrol condition. Second, we expeeted that the expansioninternal anchor treatment would increase quantity decisionssubstantially. (Considering new uses of a prodtict might pro-duce an atypical anchor that supplants the smaller defaultanchor.) Third, we expected the external anchors to functionin a manner similar to that found in Studies 2 and 3. (t wasnot clear to us, however, what would happen when suhjectswere exposed concurrently to both internal and external an-chors. For example, it is possible tbat internally generatedanchors would be more powerful, both for motivational("it's my anchor") and informational (retrieval of relevantidiosyncratic information) reasons. Alternatively, the twoanchors might interact.


As was expected, there were differences in mean pur-chase intentions across products. Because the independentvariables did not interact with product types, we mean-centered the data by product. The pattern for the untrans-formed purchase quantity intentions data is relativelystraightforward, as displayed graphically in Figure 4. In theno-limit control condition, the default anchor led to pur-chase intentions close to those produced when no internalanchor was elicited (4.2 versus 5.0; F| 13 = .22). The expan-sion anchor, in contrast, increased intended purchase quan-tities substantially, an increase of 150% (10.7 versus 4.2;F|.1.16= 14-6;/7<.01).

A MANOVA of the full design reveals a significant maineffect of internal anchor (F2J36 = 3-3; p < .05). As is indi-cated in Table 3, purchase intentions in the default anchorcondition averaged 5.2 versus 10.3 in the expansion anchorcondition and 7.1 in the no internal control condition. Therewas a significant effect of external anchors (F, |3(-, = 2.9; p<.05), which ranged from a low of 6.6 in the no-limit controlto 8.9 in the limit 56 condition. These two main effects,however, were qualified by a significant intemal-by-exter-nal anchor interaction (F5 13 = 2.5; p < .05). Simple main

Figure 4DO SELF-GENERATED ANCHORS NULLIFY EXTERNAL

ANCHOR EFFECTS?

PurchaseQuanIJtyIntt'ntions

(111 units)

2

0

H

4

2

E.pun

-

No Sulitliilornal An

-

1

nl

n Anchor

^T-" Dcluull Anthur

1 . 1

Purchiue Quantily Limits


Table 3HOW INTERNAL ANCHORS MODERATE THE IMPACT OF EXTERNAL ANCHORS

1 me matAnchor

No InternalAnchor

DefaultAnchor

ExpansionAnchor

QuanlityIncidenceInternal Anchor

QuantityIncidenceinternal Anchor

QuantityIncidenceInlemal Anchor

No Limit

4.277%

n.a.

5.089%

2.9

10.787%10.3

Limit 14

6.480%n.a.

4.589%

2.8

10.689%10.2

tixterna! Anchor

Until 28

7.788%n.a.

6.187%^6

84

5.6

Limit 56

10.481%D.a.

5.285%2ja^

11.289%10.2

Mean

7.182%

n.a.

5.287%

2.6

10.390%

9.1

effects tests in each of the internal anchor conditions re-vealed that the external anchor had an influence on judg-ment only in the no internal control condition (F3134 = 4.9;p < .01). This effect emerged because of a significant posi-tive trend in the data (F|n,^ = 14.3; p < .01). When subjectsgenerated either a default or an expansion anchor, the exter-nal anchor had no influence on quantity intentions. This sug-gests that salient internal anchors can nullify any impact ofexternal anchors, enabling consumers to counter POP an-chors effectively.^

We also computed correlations between the internal an-chors and intended purchase quantities. Collapsing acrossthe eight cells with an internal anchor, the correlation was.61 in the default anchor conditions and .71 in the expansionanchor conditions. Examination of the within-cell correla-tions indicates a strong relationship between the internal an-chor and quantity intentions in both the absence (no limit; r= .84; /7 < .01) and presence (limit 14, 28, 56; r = .62; p <.01) of an external anchor.

The notable average impact of the expansion anchor com-pared with the default anchor (10.3 versus 5.2) is intriguingfor both the manufacturer and the retailer. The challenge isone of in-store implementation. To use expansion anchors,marketers must motivate the consumer to rethink his or herdefault purchase quantity under noisy and rushed condi-tions. Because this is difficult to achieve in low-involvementshopping, a coordinated effort between manufacturers andretailers might be most effective. For example, expansionadvertising could be combined with POP retrieval cues (cf.Keller 1991) to emphasize a product's usage flexibility (e.g.,Chex cereal, A.I. steak sauce, and WD-40), thus encourag-ing consumers to generate expansion anchors.

SUMMARY AND DISCUSSION

This research explores tbe psychological process underly-ing the purchase quantity decision. Everyday shopping is alow-stakes, uninvolving chore for most consumers. Casualand controlled observation of supermarket shoppers suggest

-'We analyzed subjects' Ursi responses ynd found ihe same 7.-shaped pat-tern shown in Figure 4, but the interaction was noi significant because ofthe larger between-subjects error term (F(, ji? = 1.3; p = .27).

that they are expedient and, within reason, more interestedin minimizing shopping costs than in maximizing shoppingreturns. This is not to say that consumers are irrational; theysimply have adapted to the decision task at hand (Payne,Bettman, and Johnson 1992), Most of the time they act rea-sonably, but every so often they become inattentive and canbe influenced unduly by various merchandising methods.Given this low level of motivation and involvement, itmakes sense that consumers' quantity decisions could beinfluenced by "suggestions." Such suggestions can disruptthe normal tendency to anchor on and purcbase a smallnumber of units.

If the price justifies stockpiling, a consumer will make anupward adjustment from the small anchor; this adjustment,however, will not eliminate the impact of the starting anchorvalue. Because of this, retailers might be able to increasesales by using anchor-based promotions to present con-sumers with a larger than normal purchase quantity. In ef-fect, these large anchors supplant the smaller ones. Whenconsidering bow many units to buy, a consumer will makean insufficient downward adjustment trom this large anchor.This leads to larger purchase quantities.

The results of both field and lab studies show that POPanchors can reliably affect quantity decisions. Study 1 ex-amined how multiple-unit prices affect sales across 13 prod-uct categories in 86 supermarkets. Consistent with an an-choring explanation, multiple-unit pricing generated a 32%higher increase in baseline sales than did single-unit pricing.Study 2 examined the impact of high supermarket purchasequantity limits. The results of this field study show that pur-chase limits can increase the number of units a buyer pur-chases. A key insight from this study is tbat purchase limitsmust be set high enough not to truncate the number of unitsthat otherwise would be purchased. Using low values in oth-er anchor-based promotions (such as suggestive selling ormultiple-unit pricing) also could backfire by reducing thepurchase quantities of would-be heavy buyers.

To understand more clearly how anchoring can influencepurchase quantity decisions. Studies 3 and 4 were conduct-ed in a controlled lab environment. Study 3 shows tbat an-chors embedded in a suggestive selling slogan can increaseintended purchase quantities even when the price is not dis-counted. Finally, Study 4 examined whether internal anchorscounteract tbe influence of external POP anchors. The re-sults support our anchoring model by showing that both low


(past purchase quantities) and high (future usage quantities)internal anchors overpower the effects of external anchors.

Implications for Managers, Researchers, and Consumers

Consider a manufacturer or retailer that is given theoption of selling four units today or trying to sell one unit ineach ofthe next four weeks. Many manufacturers and retail-ers probably believe that four units in hand are worth morethan "four in the bush." Anchor-based promotions could beconsidered by these managers. It is important to note, how-ever, that any increases in unit sales may or may not gener-ate incremental revenues and profits for retailers. Furtherresearch should investigate whether unit sales increasesfrom anchor-based promotions retlect increased categoryconsumption, brand switching, variety switching, storeswitching, or stockpiling. These possible sources of salesincreases eould inlluence differentially retailer and manu-facturer profits. For example, though increased categoryconsumption ean benefit both the manufacturer and retailer,the effect of brand switching on retailer profits depends onprofit margins.

A consistent finding in these studies is that consumerspurchase more units when tbey see high anchors in POPpromotions. For example, our field results indicate that pur-chase limits and multiple-unit pricing can increase purcbasequantities wben discounts are low (12%). Even if retailerspass no discounts through to consumers, our lab findings in-dicate that suggestive selling anchors at the POP (and per-haps in advertisements or on packages) still can increasequantity decisions. These findings can be combined witbthose of Inman, Peter, and Raghubir (1997) to generate po-tential strategic applications for low and high purchase lim-its. Whereas very low or single-unit limits may increase thenumber of buyers through deal signaling, bigher limits mayincrease the number of units eacb buyer purchases tbroughancboring. Therefore, some managers migbt use tow limits

to stimulate trial of new or low-sbare brands and higber lim-its to stimulate stockpiling of established brands in usage-variant categories. Table 4 offers additional suggestions onbow anchor-based promotions can be executed, improved,and better understood.

Our studies focus on how anchor-based promotions influ-ence purchase quantity, noi on bow they might influenceconsumption. Yet there is evidence that some suggestiveselling and expansion ancbors can increase consumptionfrequency by expanding tbe set of situations in which prod-uct use is considered. Just as advertisements suggesting al-ternative usage situations and substitution opportunities canincrease the usage frequency of packaged goods (Wansinkand Ray t996), so can suggestive .selling and expansion an-chors increase usage frequency norms.

Moreover, evidence is emerging that promotional stock-piling sometimes can accelerate consumption. Sucb effects,however, appear to be highly category-specific. Consumerstockpiling has been shown to generate temporary con-sumption increases for cookies and fruit juice (Cbandon andWansink 1997), but significant increases have not beenfound for detergent or ketchup (Ailawadi and Neslin 1996).In general, consumption acceleration can be influenced bypackage size and perceived unit costs (Wansink 1996) andappears most notable among products tbat are substitutable,salient, familiar, and convenient. More work must be doneon this topic. For example, products tbat are most prone tousage acceleration could be strong candidates for anchor-based promotions.

Consumers also can benefit from an improved under-standing of anchoring. We have shown that internal ancborsbased on potential uses or on past purcbases ean overwhelmPOP anchors and increase or decrease purchase intentions.We suspect that purcha.se quantities will increase wheneverconsumers retrieve or generate an internal anchor that ex-ceeds their usual purchase quantity (see the last column of

Table 4EXECUTING AND IMPROVING ANCHOR-BASED PROMOTIONS

Execuiions

ImplemenlationConsiderations

ResearchOppununities

Mulliple-UnilPricing

•J (or $1.97.•12 for the price ot" 10.•Baker'.s dozen for $2.99.

•Discounts of IO%-2O%can increase sales whileprotecting niargin.s.

•The larger and moreexpensive ihe product.the lower the suggestednumber should be.

•When does confusionmoderate anchorel'fectiveness and whendoes it enhance it?

•When will total pricecounteract the effect ofmultiple-unit pricing?

Anchor-Based Promoinms

PurchaseQuanlity Limits

•Limit of 12 per person.•Limit of I per visit.•4 per person per day.

•Very low limits increasepurchase incidence; highlimits increase purchasequantitie.s.

•To avoid truncating sales.set limits at least twotimes higher than thetypical quantity boughton deal.

•What determines theideal quantity limit?

•What joint impact dopurchase quantity limitshave on purchaseincidence and purchasequantity?

SuggestiveSelting

•Grab 6 for studying.•Buy 8 and save a trip.•Buy 12 (or your freezer.

•Anchor-based salessuggestions may workwithout a correspondingsales promotion.

•Suggestive selling can bemost effective withfamiliar, inexpensiveitcm.s such as snacks anddrinks.

•Do suggestive sellingappeals influenceperceived .social norms?

•Does suggestive sellinginfluence purcha.seincidence?

Expan.iionAnchors

•10! uses!•Buy a month's worth.•Buy for all your friends.

•Advertisements.packages, and POPmaterials can increasepurchase quantities bystimulating thoughts ofnew uses.

•Expansion anchors canbe u.sed in advertisingcampaigns and without asales promotion.

•How can involvement beincreased so thatconsumers generateinternal anchors?

•Do usage-basedexpansion anchorsaccelerate con.sumption?


Table 4).4 Yet it might be risky for marketers to encouragereflection on prior product-re!ated behavior. For many con-sumers, the most salient prior behavior might be a purchaseepisode rather than a consumption episode. And as we haveshown, a focus on prior purchases can lead to a low initialanchor. Although low anchors are not beneficial to man-agers, they might be beneficial to consumers who wish tolimit their purchases and maintain self-control (Hoch andLoewenstein 1991). To generate low anchors, consumersdeliberately could recall past purchase quantities or modifytheir shopping lists to include purchase quantities.

Conclusion

We have examined a question of emerging importance toresearchers, retailers, manufacturers, and consumers: Howdo shoppers decide "how many'" units of a product they willbuy? Consider the findings on how anchoring at the POPalters purcha.se quantity decisions. In addition to contribut-ing to a better understanding of consumer behavior, theseresults also show retailers and manufacturers how inexpen-sive marketing efforts can increase purchase quantities. Atthe same time, these results provide consumers with a sim-ple strategy they can use to help counter the effects of thesepromotional efforts. The findings extend the relevance ofanchoring by suggesting how it can be used by managers toincrease purchase quantities and by informed consumers toresist such attempts.

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