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Acknowledging this, retailers have established many of their self-checkout lanes as express lanes, limiting by design the number of items that may be purchased in those locations, and the overall complexity of those orders. This might mean no PLUs, age-restricted products, bottle returns, food stamps, checks, or coupons. Smaller, self-scanned orders more frequently meet these conditions, so restricting coupon usage from self-checkout lanes would not necessarily have a significant impact on the consumers using those lanes.

Accept coupons on self-checkout lanes, but require attendant verification and scanning Many retailers who currently accept coupons on their self-scan lanes have established a system where a self-checkout attendant is responsible for verifying the validity of coupons presented, checking for expiration dates, and scanning the coupons on behalf of the customer prior to final payment. This type of coupon redemption process essentially replicates what occurs on regular checkout lanes.

It is, however, important to note that retailers typically staff only one attendant for every three to four self-checkout lanes, so during busy shopping times, the wait time for what was intended to be a speedy shopping trip could become frustrating and unacceptable to the customer. Accept coupons on self-checkout lanes, allowing customers to scan their own coupons, and then insert them into a coupon receptacle Although some self-scan lanes are equipped to handle redemption of coupons in this manner, there are intrinsic reasons that coupons may complicate a transaction, requiring attendant intervention in order to avoid retailer loss or customer frustration.

Free coupons, complex coupons, incorrectly coded coupons, high-value coupons, an excessive quantity of coupons, coupons, expired coupons, and store coupons, are all instances that might or should require attendant assistance. With the proposed future enhancements for coupon bar codes, there will be opportunities to improve the self-scanning of coupons by consumers, but until then, this method of redeeming coupons on self-checkout lanes is not recommended.

Summary As we know, coupons are highly effective promotional tools, both for manufacturers and retailers. We also know that most consumers use coupons at least occasionally. Enterprises S. Unilever Universal Winn-Dixie, Inc. This paper reports the development of a model that can both forecast the rate of coupon redemption and determine the degree to which various factors influence this redemption rate.

Content uploaded by David Reibstein. Author content All content in this area was uploaded by David Reibstein on Apr 01, Citations References 1. A second stream of research focuses on modeling coupon redemption rate as a function of the characteristics of the coupon promotion e. Although these models have shown several coupon characteristics, such as face value, to be related to the redemption rate, the aggregate-level nature of the analysis has typically preclud- ed consideration of such individual-level characteristics as coupon proneness.

Other researchers have examined the impact of coupon characteristics on redemption rates. Reibstein and Traver found that higher face value coupons and in-pack coupons are associated with higher redemption rates. Ward and Davis also reported higher redemption rates for higher face value coupons and direct mail coupons.

Coupon Attractiveness and Coupon Proneness: A Framework for Modeling Coupon Redemption. Although considerable attention has been paid in the couponing literature to the identification of factors that influence coupon usage behavior, relatively little work has been done to develop models that can help managers predict consumer response to specific coupons and design effective coupon promotions. The authors propose a model of coupon redemption that extends previous models of coupon usage by considering the joint effects of coupon attractiveness and coupon proneness on redemption, and does not require explicit measurement of these variables.

The proposed model also provides insights into consumer response to coupons that are not provided by the logit model. Overall, the model shows considerable promise as an aid to managers in designing coupon promotions and developing precision targeting strategies. At first, to asses their effectiveness, several authors considered just the pure redemption rate, i. In addition, Reibstein and Traver [31] developed a model to determine various factors which influence the redemption rate, namely amongst other things the method of distribution, the face value of coupons and the discount offered by the coupon.

Full-text available. Sep As webstores usually face the issue of low conversion rates, finding ways to effectively increase them is of special interest to researchers and practitioners alike. However, to the best of our knowledge, no one has yet empirically investigated the usefulness of various in-webstore marketing tools like coupons or different types of product recommendations. By analysing clickstream data for a shoe and a bed online store, we are contributing to closing this gap.

In particular, we use our present data to build more general hypotheses on how such purchasing incentives might function and on how they could be used in practice. Another major factor is the attractiveness of the coupon offering e. Increased redemption has been linked to: The or iginal d ata set included in this study covers t he coupons distribut ed via online or o ff line from April.

The total n umber of coup o ns for the time per iod is 5,60 7 April, Among t he 5, co upons, For the sake of accurate comparisons bet ween o nline and o ff line coupo n. Amon g the 4 ,, 3, Coupon b enefits are. Percent-off , Dollar-off , Fr ee Pr oduct or Service which is related to a service. The coupon redemption rate is calculated as the number of r edeemed coupons divided by the number of. Redemption rate of o ffline coupon is co mputed as the number. In the case o f o nline coupo n,. The online coupon used i n this study is a co nsumer-requested type.

In cons umer-requested type of coupon,. T herefore, w e can consid er the numb er of visits ma de to the. Just visiting th e website is not enough to qualify it as an actual d istribution. Printing is eq uivalent to clipping in the offline co upon ca se. Although cons umers have to p rint the coupon to use it,. T herefore ,. T able 2 displays average rede mption rates o f online and offline coupons. As it can be see n in the table, there.

As expected,. T able 2: Sport and travel. Wedding and photo. Type of. Free product or service. H1 -1 and H pred ict d if ferent respo nse patter ns between coupon face value and rede mption rate for. T o test them, separate analyses are conducted for online and offline coupo ns. Since the. First, the hypothesized relationships are tested on the total sam ple by aggregating coupons. ANOV A tests o n t he di ff erences in rede mption rate across different coupo n f ace.

T he results are summarized in T able 3. T he r elationship. O ffline perce nt-off co upons show a non-significant. T hus, the. On t he other hand, t he r elationship patter n of the do llar-off coupon is found to be a negative li near p attern. Although we do ob serve d ifferent resp onse p atterns bet ween face value of coupon a nd redemption rate, the. Therefor e, H2 -1 and H ar e not. Figure 1, 2, 3, and 4 repr esent patter ns of coupo n redemption r ates accord ing to face value of the coupon. T able 3: Type of Benefits.

Online F-values. Offline F-values. Mean Differences. Figure 1: Redemption rates sharing same alphabets m ean that they are not diff erent, and redemption rates sharing diff erent. Figure 2: Offline Coupo n Redemption Rate. Online Coupon Redemption Rate.

Coupon Redemption

Figure 3: Figure 4: The relationship patterns ar e further inv estigated across different serv ice sectors to examine any possible. Si milar service sec tors are grouped together in order to secure enough sample sizes for. Entertai nment, Culture ,. Remaini ng service sectors are not analyzed due to the small sample. Although the results o f trend analyses are not as st rong a s t hose of the. Although they fail to reach the level of significance, the F-vlaue patterns f or the o nline coupon of Entertainm ent, Culture,.

The reason for the significant q uadratic. Offline Coupon Redem ption. Online Coupon Redem ptio n. Also, th e plo ts o f red emption rate generally rese mble th e pattern of the to tal sa mple r esult. So , the evidence f or.

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Next, H2 predicts diff erences in rede mption rate by coupon benefit type are tested using pair-wise t-tests on. Si nce t here are two types of free coupon i.


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A lthough it fails to rea ch the level of statistical. Thus, H2 is ge nerally suppor ted for. For o f fline coupo ns, the redemption rate of free p roduct type coupons is si gnificantly higher than t hat of. However , the redemption rate of free gift t ype coupons is s ignificantly lower tha n that of both per cent -off. T hus, H2 is partiall y.

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Service sector level analyses find a si milar pattern of respon se that we have ob serv ed from the total sample. Although th e results ar e not uniform across the examined service sectors , it can be co ncluded that the. T able 4: Pairwise Comparisons. Redemption Rate. T otal S ample. Dollar-of f. Dollar -off. This reduced coupon face value le vel might cause to detect any n on-linear pattern in this case.

However , the redemption rate p attern to that level resem b les th at of the total sample case. In the ca se of. Several interesting results are found fro m th is study. Therefore, coupon distrib ution through the Internet was d one ver y selec tively to. T herefore, online. I n additio n, the industry exa mined in this study seems to be another.

In Korea, major online users ar e the young 20s. T his overlappin g nature of online user gro up and main custo mer group might. Although different patter ns are expected acco rding to distribution method i.

Self-Scanning and Coupon Redemption

The red emption p attern is found to be. This r esult rules out the p ossibility of diff erence in t he availability o f. A possible. Rather than using. In actual red emption data , it i s prob able. T hus , rather than the. For both online and. U ntil now , the relatio nship betwee n c oupon redemption and face. Results of t his study s uggest t hat ot her possible patterns co uld exi st in. The cubic patter n can be explained b y the interactive e ff ect bet ween perc eived savings from the coupo n and.

However , af ter reaching a ce rtain point o r a. T hey ma y infer that the regular p rice is in flated. When it p ass es another higher threshold p oint, it may be. In the cu bic trend of per cent-off co upon both online and. Although we. Although the trend analysis s uggests the po ssibility of a negative linear relationship patt ern for the dollar-. T he pair-wise post-hoc c omparison tests o n mean. T he pattern for. Further studies ar e warranted to confir m and verif y these new pat terns in the future.

This is. However , in the case o f o ff line free. This can be. In an online co upon case, co nsumers would do wnload coupons after co nsidering a num ber of factors, s uch as. On the other hand, in o ff line. In t his aspect, although it is free,. This lack o f rele vancy may. The findings of this stud y pr ovide useful implication s to marketers who are co nsidering pro motion in the.

Online co upons are f ound to be more eff ective in terms of. I f marketers can acces s t heir target seg ment us ing the. Internet, it is reco mmended to use online coupo ns. It will result in a higher rede mption ra te , contributing to a sales. When marketers have to use both online a nd offline coupons, the y ma y not need d iff erent approaches for.

Rath er , they. In t he case o f the do llar-of f framing co upon , although the p attern is neither o bvious nor stati stically. It is highly likely that the threshold points for both types of coupons are. T hus, marketers have to verify a nd identify the threshold points in their specific pro motion. The result of this study , however , can be used as a good star ting point guideline in their search e fforts. Although the results of this stud y pr ovide meaningful theoretica l and practical insights to coupon.

Fir st, due to the li mitation o f e mpirical data set, the eff ects o f.

Future studie s should. Second, the data examined in this study only cover s. T herefore, the co upon red emption pattern s found in this study m ight be. Further replicatio n is warranted , especially in the consu mer packaged good s industr y ,. T hird, this st udy only co vers one ki nd of offline coupons ; i.

So me other kinds of o ff line co upons might have si m ilar c haracteristics to online coupons. For exa mple,. Or, the red emption rates. Hence, future. Fourth , althou gh we use the same definition for redemption rate, actual meas ures o f. Interpretation and application of the findings o f t his. Finall y , t his stud y has a s trong point o f using act ual coupon red emption data. However , this adva ntage inevitab ly crea tes a li mitation of lacking the information on motivation al a spect of coupon.

Althou gh there ha ve been several studies to e xamine cognitive and ps ychological proce sses. Despite all the li mitations o f this study , the f indings of. He has a PhD in marketing and has. Internationa l Marketing , P sychology a nd Marketing and others. His research interests include areas of brandin g,. Bawa, K. Some Findings B ased on. Journal o f Marketing Resea r ch , 24 November , 37 0- 6.


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Srinivasa n, and R. Blundo, C. Ci mato and A. Campbell, L. The Characteristics of a Goo d. Carmody , B. W in ning Strateg ies and T actics , NY: W iley. Chen, S. Mo nroe, and Y. Ch oi, K. Diamond, W. E f fects on Reference P rice. An Approach to. Advances in Consumer Resea r ch , 17, Fortin, D. Han, K. A Cross - National Analysis of the. Resear ch in Kor ean , 13 2 , Henderson, C. Heilman, C. Naka moto, and A. Consumer Resp onse to. Usage an d Population Statistics , available at: