Promotion Over Time: Exploring Expectations and Explanations

Carl Mela, University of Notre Dame
Joe Urbany, University of Notre Dame
ABSTRACT - The potential impact of long-term promotional patterns on brand quality perceptions is an important and under-researched question. Most research has focused solely upon the effect of current period’s pricing on brand perceptions. We interviewed 18 consumers to explore what, if any, inferences they make about frequently purchased brands in response to different price promotional patterns. Our interviewees participated in a "buying game" (cf. Krishna 1994) which exposed them to a simulated series of 36 monthly prices for three brands with different promotional patterns in a category. Several insights emerged from the analysis which suggest that consumers make inferences in response to a brand’s pricing history. Moreover, there is considerable heterogeneity in how respondents make those inferences. For example, some tended to believe that a brand with infrequent, deep discounts (i.e., more significant price variation) were slow movers and, therefore, of inferior quality. However, this inference was less common when price reductions were clearly flagged as sales. Consumer categorization of brands into brand tiers were moderated by respondents’ attention to brands’ regular prices relative to competitors’ prices. Research directions are discussed.
[ to cite ]:
Carl Mela and Joe Urbany (1997) ,"Promotion Over Time: Exploring Expectations and Explanations", in NA - Advances in Consumer Research Volume 24, eds. Merrie Brucks and Deborah J. MacInnis, Provo, UT : Association for Consumer Research, Pages: 529-535.

Advances in Consumer Research Volume 24, 1997      Pages 529-535


Carl Mela, University of Notre Dame

Joe Urbany, University of Notre Dame


The potential impact of long-term promotional patterns on brand quality perceptions is an important and under-researched question. Most research has focused solely upon the effect of current period’s pricing on brand perceptions. We interviewed 18 consumers to explore what, if any, inferences they make about frequently purchased brands in response to different price promotional patterns. Our interviewees participated in a "buying game" (cf. Krishna 1994) which exposed them to a simulated series of 36 monthly prices for three brands with different promotional patterns in a category. Several insights emerged from the analysis which suggest that consumers make inferences in response to a brand’s pricing history. Moreover, there is considerable heterogeneity in how respondents make those inferences. For example, some tended to believe that a brand with infrequent, deep discounts (i.e., more significant price variation) were slow movers and, therefore, of inferior quality. However, this inference was less common when price reductions were clearly flagged as sales. Consumer categorization of brands into brand tiers were moderated by respondents’ attention to brands’ regular prices relative to competitors’ prices. Research directions are discussed.


Owing to the managerial relevance of promotions, the attention they have received from innovative modelers, the availability of data, and simulated purchase paradigms studying promotional effects experimentally, the study of price promotions by marketers has been prolific (Blattberg, Briesch, and Fox 1995). Yet, issues relating to the long term effects of promotions remain important and largely unexplored (for exceptions, see Boulding, Lee, and Staeilin 1994; Lal and Padmanabhan 1995). Such effects are important because it has repeatedly been suggested that the long term health of a brand (i.e., brand franchise or equity) may be put at risk by a pattern of frequent price promotions (Blattberg and Neslin 1990; Nagle and Holden 1995). In spite of the recent panel-based stream of studies regarding promotions and consumer choice, there currently exists little empirical evidence on consumer interpretation of promotion patterns over time. It is our objective to examine whether and why promotion patterns which vary in frequency and depth (Rao, 1991; Krishna 1992, 1994) affect consumer price expectations and brand evaluations (specifically, perceived quality).

Price Expectations and Explanations

It is well-known that pricing patterns over time influence subsequent consumer price expectations (Jacobson and Obermiller 1990; Krishna 1991, 1992, 1994a,b; Lattin and Bucklin 1989; Winer 1986, 1989). Moreover, the literature on the frequency effect (Alba and Marmorstein 1987; Alba et al. 1994) leads to the prediction that brands with greater frequency of promotion will be perceived as having a lower reference price, although the issue of quality effects remains unexplored. Our point of departure from these studies is to explicitly examine whether and how deals affect brand perceptions in addition to price expectations.

We define consumer explanations to be inferences arising from promotional patterns about products or marketers. We consider the possibility that consumers observing promotion patterns over time may make inferences about why sellers price promote as they do and that the lowering of expected price which likely occurs with frequent promotion could reduce consumer perceptions of brand quality (cf. Blattberg and Neslin 1989) if quality is somewhat ambiguous over time (even with experience; Hoch and Deighton 1989). Since measures of perceived quality and other brand perceptions are not readily available or operationalized in standard scanner data sets, we turn to interviews with consumers to assess whether and what "explanations" consumers form in response to dealing patterns.

The exploratory and hypothesis generating nature of our research mandates the use of in-depth open ended interviews of consumers to assess the presence of promotional attitudes and decision protocols, we report the results of four phases of such interviews. Each wave of interviews was predicated upon what was learned in prior waves. Our method attempted to avoid injecting our research biases by being as general and non-leading as possible.



Eighteen respondents were interviewed in four different phases. In each phase, a standard set of exploratory questions were asked regarding the respondent’s shopping routines, products purchased, and response to advertising. They were also asked about their perceptions regarding pices and price promotions in stores and in particular product categoriesCinitially (in the earliest interviews) by having respondents "walk through" recent store features in the newspaper, and later by having them describe a trip through their usual store and the categories they frequently shopped. In the eleven interviews comprising phases 2, 3, and 4 (as discussed below), respondents were additionally presented with a formal "buying game" that simulated category purchases over several periods. Interviews took 30 minutes to an hour. The presentation below focuses on insights obtained from the buying game.

Phase 1

Phase 1 consisted of interviews with seven consumers, the latter four of whom were presented with prices for what were said to be three relatively new brands of cookies currently sold in other markets. Prices for the three brands were presented sequentially on 20 index cards, each card presenting prices for three brands in a given week. The control brand maintained a constant price of 2.49. The other two brands had regular prices of 2.49 and different promotion patterns. Each pattern yielded a total of $2.00 in discounts over the twenty weeks: the frequency brand had 10 price reductions during the 20 weeks to $2.29; while the depth brand was reduced twice to $1.49. We then asked respondents for their "impressions" regarding the brands. Two results emerged consistently across subjects: First, the control brand was thought to be a better or more popular brand because its price was constant (more direct questions are noted, otherwise the quotes below reflect responses to the general question about impressions):

... if (the control brand)’s staying at the same price all the time, they probably sell a lot of product at that price. (then in response to a direct inquiry about which of the three might be a national brand:) I think (the control brand) would be the national brand. (Jennie)

... (the control brand) would probably be the name brand 'cause they don’t fluctuate. (Edie)

... (the company making the control brand) obviously has a good following. (Tom)

Second, the brand with the infrequent, deep discount was put in a lower quality class:

I think A and B are probably more similar, and (the depth brand) is a different quality... for example, if you bought Pop Tarts... (the) Kroger brand is terrible. (The depth brand is like a Kroger Brand). (Peggy)

I would question the quality (of the depth brand). (Tom, written notes)

Another respondent indicated that the depth brand "would be the store brand" in response to a question explicitly asking her to classify the brands.

There was no consistent mention across the four respondents regarding the frequency brand. The frequency brand was alternatively described as "probably the Kroger brand ... because it’s lower consistently than the others" (Edie), "the mid-brand" (Jennie), and a "good quality brand" (Tom, written notes).

Phase 2 Procedure

The phase 1 results suggested the possibility that consumers extracted information from price promotion patternsCspecifically, that higher, more constant prices rflected better quality and that deep discounts signalled something wrong with the brand. In phase 2, we attempted to replicate these results with a more formal buying game. Three modifications were made. First, we created a game that mimicked the purchase task used by Krishna (1994a, b). The game instructed consumers to choose brands and purchase quantities such that they minimize their overall purchase and inventory costs subject to minimum consumption constraints. To enhance involvement, a $20 reward was offered to the respondent most successful at this task. The task was inserted after a few relatively innocuous questions regarding shopping routines and typical product categories purchased. The economic nature of the task served to discourage consumers from guessing our experimental objective. Moreover, the task encouraged them to attend to the pricing information. Second, we lengthened the number of periods over which the game was carried to 36 to present a longer history of price promotion patterns. Third, we used shampoo instead of cookies, given the precedent in Kahn and Louie (1990) and its longer interpurchase cycle, which allowed us to simulate monthly as opposed to weekly purchase intervals, thereby simulating three years of pricing history.

In the four phase 1 interviews in which prices were presented, the constant price brand had a higher average price than the frequency and depth brands. To provide a more stringent test of the notion that low price variance signals a better product, prices were set across the 36 months such that all three brands had an identical average price of $2.39. Our control brand was always $2.39, which was $0.10 lower than the regular price of the other two brands. The other two brands each had "regular" prices of $2.49; the frequency brand offered $0.20 discounts in 18 periods and the depth brand offered $1.20 discounts in three periods.

Based upon respondent open ends in phase 1, we also developed a more complete set of questions that followed the buying game. The questions elicited general reactions to the task, whether subjects made decisions similarly to their normal decision-making, what they were thinking about as they went through the task, and how they might subsequently choose between the frequency and depth brands if they were both priced at $2.49. We continued to ask for brand impressions. We then solicited specific price estimates: average price of each brand over the 36 periods, number of times each was on sale, the regular and "on sale" prices for each brand, a general categorization question, and a quality rating. The categorization question first asked respondents whether they felt they had enough information to categorize brands as "high-end/premium," "mid-range," or "low-end," and, if so, which brand(s) would go in which category (we emphasized that they could put all in one or each in one if they wanted). The quality rating was a 10 point scale ranging from 1 ("very poor quality") to 10 ("very good quality").

Phase 2 Results

The second phase involved two interviews; Carol and Linda. Carol is in her late 20’s and lives with her brother. She lives near the market "super store" called Meijer and shopped there almost exclusively. Linda is in her late 30’s/early 40’s, is married, with two children at home. Linda is the prototype of a vigilant shopper (cf. Urbany, Dickson, and Key 1991). She carefully reviews the grocery ads which came with the paper every Monday, determines where the best specials are, and develops a detailed shopping list. On Friday afternoon, given this preparation, Linda and her husband spend about three hours traveling to 4-5 stores buying specifically what was dictated by the specials at various stores. In the interview, Linda easily discussed which stores she felt had the best prices on particular items.

Price Expectations and Perceived Quality. Table 1 shows estimates of average prices, sale frequency and brand classification and quality ratings provided by respondents afterthe 36 period buying game. The frequency effect literature (Alba and Marmorstein 1987; Alba et al. 1994) suggests that the frequency brand would be perceived as having the lowest average price due to its large number of discounts. Carol ordered her average price estimates in a manner consistent with this effectCthe frequency brand received the lowest estimate ($2.29) and the depth brand the highest ($2.49) even though both brands actually had identical average prices. Her estimate for the average price for the constant brand was exactly correct, as was Linda’s. In contrast, Linda dramatically underestimated the average price for the depth brand. As the table indicates, she also substantially underestimated the number of times the frequency brand was on sale (Carol estimated this number correctly). Linda’s estimates were unexpected, given (1) her hyper-price sensitivity and vigilance in her actual shopping, and (2) the fact that she participated sincerely and earnestly in the buying game. Consider, however, how Linda described her play in the game:

Well, you just kind of figure when they put on a good sale like that for $1.29, it’s going to be a little while before it happens again. So you want to stock up. And until they have another sale like that, I’ll have enough to last me....So if you see a good one you go for it.

Once Linda had seen the $1.29 sale price for the depth brand she apparently adapted a heuristic of lying in wait for the next big sale from that brand and buying enough quantity to tide her over to the next $1.29 sale. It is possible that Linda’s misperception of the frequency brand’s promotion cycle (every sixth month instead of every other month) was due to diminished attention to its price variation induced by increased attention to the depth brand’s price.

Note that both Linda and Carol estimated the constant brand to have been price-promoted five times during the 36 months even though it had never been promoted. The result suggests that perception may be induced by a cross brand comparison of the $2.39 constant price to the competing brands’ $2.49 depromoted price. In addition, both respondents significantly overestimated the number of sales held for the depth brand (consistent with Krishna’s (1991) results).



Price Variance and Brand Quality. Linda stated with fairly strong confidence that she generally did not believe there was a relationship between price and quality (i.e., "[many] private labels [had just as good] quality") and gave the brands all ratings of 6-8 on the quality scale. Carol rated the depth brand lowest on quality (5 on the 10 point scale), attributing its occasional deep discounts to the fact that it apparently did not sell as well as the other brands:

(The frequency and control brands) stay pretty much level. (The depth brand) doesn’t really sell very well. You have to really push its sales and get it going. (Carol)

Further, Carol suggested that "I’d probably put (the control brand) in the upper and the other two in the lower... (The control brand’s price stays) pretty much right on track."

Phase 2 Discussion. The phase 2 results added a complication to our consideration of whether promotion patterns produced inferencesCthe possibility that consumers do not accurately interpret price information presented sequentially. Carol behaved precisely as we initially expected subjects to behave; she estimated the number of sales for the frequency brand accurately across the 36 months and estimated that brand to have a lower average price, noting that its price did not vary much (see quote above). Also in accordance with our expectations, she believed the constant price brand was of better quality than the other two brands, citing its limited price variance. Lida, on the other hand, was unexpectedly inaccurate. She was an active shopper and attentive respondent, but had not attended to the "sales" held by the frequency brand, even in this simple environment. The significant variation for the depth brand swayed Linda’s estimate of its average price and led her to anticipate large price reductions for the depth brand, consequently distracting attention from other prices. Alternatively, she simply may have not interpreted the $.20 price variations for the frequency brand as "sales."

Phase 3 Procedure

Phase 2 results were partially consistent with phase 1 results in showing a link between promotion pattern and quality perceptions. We were interested in phase 3 in seeing if similar results emerged and also in seeing if the inaccuracies in Linda’s perception of the promotion patterns were unusual. Further, in making an incremental step toward greater realism, we decided to provide more brand information to respondents to address the potential problems associated with providing only a single cue for quality judgments (Olson 1977).

In the phase 3 interviews, we presented brand attribute information to respondents prior to beginning the buying task. Ratings were provided for the brands on attributes identified via the most recent Consumer Reports article on shampoo. The brand by attribute matrix was constructed so that no brand dominated all the remaining alternatives (Ha and Hoch 1986). The five attributes on which ratings were provided were combing, manageability, body, package, and lather (definitions based upon the Consumer Reports article was provided to respondents). While an initial pretest of 9 consumers prior to the interviews indicated no statistically significant difference across subjects regarding mean brand quality ratings (MANOVA, Wilks’=.57, F{2,7}=2.67, p=.14), subsequent pilot testing indicated that Brand B’s attribute set was favored somewhat over A’s and C’s (A and C had equal ratings). Given that Brand B was always the constant price brand, however, this has little bearing on interpretations of results for the frequency and depth brands, which were rotated between positions A and C.



Phase 3 Results

Marie is in her late 20’s, with husband and several children at home and regularly shops Aldi’s (for canned goods), Kroger, and Martin’s. Peggy is also married with children. Janet is single and in her late twenties.

Price Expectations and Perceived Quality. Table 2 shows estimates of average prices, sale frequency, brand classification and quality ratings for these three respondents, showing that they more closely resemble the responses of Linda (who we first thought was an outlier) than Carol (our model respondent) from Phase 2. Specifically, all three respondents gave the depth brand a lower average price than the other brands, two of whom did so by fairly substantial margins. In addition, two of the three dramatically underestimated the number of sales for the frequency brand.

Price Variance and Brand Quality. Counter to our expectations, Marie gave the constant price brand the lowest quality rating. This rating was apparently based upon her careful attention to relative price levelsCshe noted that the constant brand’s price was lower than the regular price charged by the promoted brands, suggesting to her that it was more likely a "low-end" brand. Both Marie and Peggy ironically regarded the (incorrectly) perceived lower price variance of the frequency brand to reflect a better selling or better quality brand:

I expect (the frequency brand’s price in the next 12 months) to go up. It rarely went on sale, so it must have a good turnover for them not to put it on sale. (Marie)

Actually, I think that when I shop, the better brand’s don’t tend to go on sale a lot. Actually, the medim shampoos probably do ... (The frequency brand is) probably a premium ... (Peggy H.)

Consistent with the lower evaluations described above, some questions were raised about the depth brand

(The depth brand) was normally $2.49 and on sale for $1.29, which is quite a blast. I kind of wonder why. If I thought the quality was just the same, I would go with the cheaper one. I’m wondering if they have so much in stock that they can’t push, so they put them on sale to get rid of it or what. I’m not sure. (Marie)

(The depth brand) probably a low, because it went on sale a lot. (Peggy H.)

Peggy also interpreted the Consumer Reports information as indicating that the constant price brand was "a little cheaper," yet she still rated it an 8 or 9 on quality in part because its "price stayed the same." Janet distinguished the frequency and constant price brands by saying that these brands "had the same price," while the depth brand "dropped often." Janet further stated "(the brands) kept going back and forth so much, $0.10, $0.20 constantly". So, even though she believed that the frequency brand had been promoted 15 times, she still concluded that its price had not varied much. She gave her highest quality ratings to the constant price and frequency brands. Apparently, she relied upon the attribute information rather than the pricing history to make her quality judgments. She primarily purchased the frequency brand and mentioned that the lather and manageability (rather than price) drove her choices. She was therefore a prototypical loyal and her relatively accurate assessment of the number of deals (15 estimated) for the frequency brand may have been driven by her loyalty and involvement with this brand.



Phase 4 Procedure

The surprising failure of respondents to note the number of times the frequency brand went on sale appears to be in part a function of the small increments by which its price was changed and the attention attracted by the relatively large promotions of the depth brand. Past research has shown, however, that the "flagging" of promotions (e.g., shelf tags) can have a powerful impact on promotion response (at least among some consumers; Inman, McAlister, and Hoyer 1990) and, presumably, perception of promotions. To investigate the effect of a promotional announcement, and to determine if the frequency effect would become more obvious when promotions were signaled, in phase 4 we labeled the price changes on the monthly price cards as "sales." Respondents were 6 consumers who were primarily responsible for the grocery shopping in their households. Other experimental manipulations were similar to those previously described.

Phase 4 Results

Price Expectations and Perceived Quality. Table 3 presents the results for our Phase 4 respondents. Our initial expectation was that labeling the price reductions as "sales" would create greater attention to the frequency brand’s larger number of promotions and produce more accurate perceptions of the number of sales and potentially lower price expectations for that brand. In fact, the frequency bias did not go away. When sales were not flagged (in phases 2 and 3), the mean perceived number of deals for the frequency brand was 8.8, compared to 9.8 in phase 4 with the sales flagged. However, the phase 4 respondents did perceive the number of promotions for the depth and constant price brands much more accurately. Five of six phase 4 respondents estimated the number of depth brand promotions correctly, while 4 of 6 recognized that the constant brand never promoted. It is possible that the processing and consequent storing of a small number of dihotomous cues such as deals is an easier task than memorizing a distribution of absolute prices. Even though the flags did apparently enhance the accuracy of the depth and constant sales deal frequency perceptions, the depth brand was still most frequently estimated to have the lowest average price.

Brand quality perceptions also changed compared to phase 3. While none of the phase 3 subjects had rated the depth brand as "premium" or "high-end," three of the six phase 4 subjects classified it in the high tier and a fourth (who gave no brand classification) gave it the highest quality rating. One possibility for this reversal is the fact that it is the brand most frequently priced at $2.49 (33 of 36 periods) became clearer when sales were flagged, leading respondents to give the brand a higher evaluation:

"... I think (the depth brand) was higher priced, it was a high end product, even though its sale price dropped really low. I think it was an incentive to make us buy the product and like it." (Ed)

The quality inferences also furnish insight into the reversal in categorizations for the depth brand.

Price Variance and Brand Quality. It is interesting that none of the phase 4 respondents classified the constant price brand in the high tier; four of six gave it the lowest quality rating and two of them classified it as a store brand. Consider the following explanations:

The store brand doesn’t go on sale (Amy).

The (constant price brand) wasn’t ever on sale, therefore it would be a store brand. (Jen)

Evidently, some consumers believe (and much store scanner data bears this out) that low-tier brands in many categories do not go on sale very often. By defining price changes as sales in the phase 4, it is possible that we made it clearer that the constant price brand never changed (see also Marie in Table 2). When unflagged, it appeared that the frequency and constant brands were vacillating in relative price. So, while low price variance is consistent with brand popularity (as indicated in our earlier phases), it may signal store brand quality when coupled with a somewhat lower regular price.


The results suggest some potential biases in consumer interpretation of price promotion frequency over time in a controlled setting, but also suggest some interesting differences in consumer beliefs about the meaning of promotion patterns. Respondents dramatically underestimated the frequency of sales for a brand promoted half the time, possibly because of the difficulty in tallying or remembering large counts in memory and a tendency to rely on some base rate perception of promotion frequency even when sales are flagged. However, flagging price reductions as sales reduced the tendency to overestimate low and zero promotion frequencies, making it clearer to respondents that our constant price brand was never on sale and that the depth brand had a specific "reason" for its price reductions.

There was heterogeneity across our respondents in their explanations regarding the relationship between low price variance and quality. Some felt that lower price variation reflected "better" (or at least more popular) brands. Similarly, our initial interviews suggested that a greater variance in price indicated low sales or something wrong with the brand (e.g., Carol, Marie, Peggy). At the same time, the high variance-low quality heuristic was less evident when price reductions were clearly flagged as sales, possibly because this provided an alternative explanation for the deal (incentive to buy).

Thesefindings, along with the results of a larger follow-up study, suggest some speculative hypotheses. Noticeable swings in price over time may motivate inferencing about the seller and brand quality when quality cannot be judged directly prior to purchase, although such inferencing may be moderated by the presence of an explanation for the price reduction. Stable prices, on the other hand, may be associated with brands that have a clearer positioning in the market (either low-end or high-end). However, what the consumer concludes from stable prices about brand quality may vary significantly, depending upon the regular price levels of the brand and, naturally, brand name. What may be of particular interest is how promotion patterns within a tier influence consumer perceptions of relative brand quality.

Limitations and Research Agenda

The most important limitation here is our ability to generalize results from the 11 respondents who participated in the full buying game. At the same time, a small sample was merited in providing insight into individual level perceptions. The research is also limited in that the information environment, while essentially the same as other simulations reported in the literature (e.g., Krishna 1994), is much simpler than the real marketplace and therefore may overestimate consumer attention to price information (e.g., Dickson and Sawyer 1990). However, the open-ended portions of our interviews did suggest that nearly all interviewees knew prices in their stores for at least two or three products, and that some were very confident in their knowledge of price promotion patterns. The methodology simulates the behavior of at least a portion of the consumer market for a given category, since, for all categories, there is a segment of the market who is knowledgeable about prices. Further, and in spite of the simplicity of the methodology, the key empirical findingsCthat small promotions may not be noticeable (or memorable) and that brand perceptions may be influenced by variation in prices over timeCboth make intuitive sense and have important dynamic pricing implications for retailers. While there may be some concern that the structured nature of the task motivated inferences that may not have occurred otherwise, we note Winer’s (1986) refutation of a similar concern in the attribution theory literature. It is not clear that a more subtle method would reveal less inferencing among those who attend to price (although it would, by definition, find no inferencing among those who ignored price).

Subsequent research should examine differential promotion pattern effects for brands in low, middle, and high tiers, and more fully examine the price sensitivity implications of these different patterns. For example, there may be greater resistance to purchase off promotion (see Kahn and Louie 1990) for brands with different promotion patterns, yet equivalent average prices. In addition, our early interviews and a subsequent study suggest that the different promotion patterns may produce different perceptions of price fairness, which may influence brand choice. This research is a first step in pursuing a more in-depth understanding of consumer inferencing in light of information regarding brand marketing activity. Not all consumers attend to pricing information, but enough may become aware of such activity that any inferences they make from it will have an impact on a brand’s equity over time.


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