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Does promotion channel matter in responsiveness to promotions? Customer
responsiveness and conversion in online vs. offline promotions
University of Amsterdam Faculty of Economics and Business
Minahil Iqbal (11190647) Supervisor: Umut Konuş
Master Thesis Business Administration - Marketing
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Statement of Originality
This document is written by Student Minahil Iqbal who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Acknowledgement
This thesis is my last and final step towards achieving my master’s degree in Business Administration and specialization in Marketing at the University of Amsterdam. From the moment Dr. Umut Konuş gave a lecture about this subject, I knew I wanted to write my thesis about multichannels. He is a true expert in his field and therefore I was very happy to find out that he was going to be my supervisor.
I would like to thank my supervisor Dr. Umut Konuş for providing me with periodical feedback and recommendations about my work and supporting me in writing my thesis in every possible way he could! It has been a great pleasure to work with him. Without his help this Master Thesis could not have been developed.
Hopefully, you will enjoy reading this master thesis.
Kind regards,
Minahil Iqbal
27th of January 2017
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TABLE OF CONTENTS
Abstract ... 6 1 Introduction ... 7 2 Literature review ... 11 2.1 Promotions ... 11 2.2 Price promotion ... 122.2.1 Offline Price Promotion ... 14
2.2.2. Online Price Promotion ... 15
2.3 Consumers’ Response towards Online vs Offline Price Promotions ... 19
2.4 Factors affecting consumers' response towards offline and online promotions ... 21
2.4.1 Demographic characteristics ... 21
2.4.2 Attitudinal characteristics ... 22
2.5 Gap and research questions ... 23
2.6 Contributions ... 24 2.6.1. Theoretical contribution ... 24 2.6.2. Managerial contribution ... 25 3. Conceptual Framework ... 27 3.1 Channel preference ... 28 3.2 Demographics ... 28 3.3 Attitudinal factors ... 29 4. Research design ... 31 4.1 Population sample ... 31 4.2 Measures ... 31 4.3 Analyses ... 33
5. Results and Analyses ... 34
5.1 Validity and Reliability ... 35
5.2 Model Testing ... 36
5.2.1. Results General Discount ... 36
5.2.2. Results Offline Discount ... 37
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6. Discussion and Conclusion ... 44
6.1 Managerial Implications ... 46
6.2 Limitation and Suggestions for Further Research ... 47
7 References ... 48
Appendix A- Measures ... 53
Appendix B Survey ... 54
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Abstract
The shopping environment has changed a lot with the inclusion of online and offline channels. Nowadays promotions are offered in multichannel: offline and online (also mobile) which are different purchase channels in marketing. Promotion is one era in these channels, which has been researched, but not simultaneously in both channels. This will be discussed in elaborating how consumers will react to promotions and which underlying factors will influence this behavior. Also, through this research it will become clear which groups to target through with channels and with which different promotion. This in order to target the right groups using the right promotion techniques which will lead to a more detailed overview of the suitability of promotion channels. The responsiveness towards promotion will also be researched by looking at moderating factors like demographic and psychographic factors. The possible moderating effect of these demographic and attitudinal characteristics will also be determined to examine what the possible underlying motivations of consumers would be in processing price promotions. An online survey was conducted, divided in 6 surveys in where different promotional percentages will be exposed to different consumers in online and offline channels in order to assess their response and make the external validity higher. Marketers can benefit from this research by making decisions for their channel strategy based on the result of this research. They can also improve their channels in order to meet the customer preferences in terms of channel choice and which promotional activity would be suitable for which channel.
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1 Introduction
Of all the tools available to marketers, none is more powerful than price (Han, Gupta and Lehmann, 2001). Price has a significant influence on consumers’ purchase behaviour and consequently on firms sales and profits. It is, therefore, not surprising that price promotion has become an increasingly large fraction of the marketing budget and an almost ubiquitous aspect of consumer choice (Han, Gupta, D.R. Lehman, 2001). In fact, consumers may be both conditioned to expect deals and desensitized to small ones (Han et al., 2001). So, price is a powerful tool for marketers and it has proven to impact the firms' sales and profit.
Promotions, in particular price promotions, are very common in grocery retailing. They are used by retailers to draw customers into the store and encourage them to purchase certain products during a given period of time (Arce-Urriza, Cebollada & Tarrira, 2016). Promotions can be defined as time-limited marketing strategies, implemented to directly influence customers’ purchasing decisions, with the underlying intention of achieving the objectives marked out in the retailer and/or manufacturer’s overall marketing strategy (Blattberg & Neslin 1990). Whereas retail promotions in the offline or traditional environment have been widely studied (Blattberg et al. 1995; Gupta 1988), there is a lack of understanding of the way they work in the context of online shopping.
For instance, looking at promotion design involving in promotions on one would look at it as a specific instance of product design. Promotion design also needs to be maintained, which also requires that the promotions vary in terms of the contents from one to another. However, certain characteristics of a series of promotions may need to remain constant over a period over time, such as long-term incentives. Studies show expenditures on sales promotion activities totalling 72% of the average firms' entire advertising and sales promotion budget (Gardner & Trivedi, 1998). So, the promotion design is an important era for managers in order to measure how promotions vary in terms of their content towards another channel and which channel to concentrate on for promotion activities.
Furthermore, Zhang & Wedel (2009) also find differences in the impact of promotions in the online versus the offline channel. They particularly discussed whether customized promotion had an effect in these channels, but they haven't discussed the effect of promotion in these channels simultaneously. Their study only analyzed two different groups and how they react to different products with different pricing. By investigating these aspects, one easily can
8 detect channels which are profitable for ones products. Another potential factor according to Zhang & Wedel (2009) is promotion sensitivity. In particular consumers with different purchase frequency rates may also differ with respect to their degree of sensitivity to prices and promotions. In particular, frequent customers are usually found to be more sensitive to promotions than infrequent customers (Bawa & Gosh 1991; Vakratsas & Bass 2002; Andreeva et al. 2010). The sensitiveness could be a factor which explains the differentiation between customers' responsiveness to promotions in online and offline channels.
Furthermore, Bell, Chiang & Padmanabhan (1999) analyzed deal depth in promotion activities. In their study a higher percentage discount from the base price greatly improves the quality-per-dollar equivalent of a brand. Consequently, greater depth should be accompanied by higher purchase acceleration (Golabi 1985, Ho et al. 1998). Raju (1992) hypothesizes that deep discounts can induce some consumers who are loyal to competing brands to switch to the promoted brand. So, higher discount percentages could lead consumers in switching to the promoted brands. Managers should take this into account knowing that a higher promotion percentage could lead to a higher customers' responsiveness.
In an article by Arce-Urriza et al., (2012) they provide relevant information about reaction of consumers to online and offline promotion. Their study provided evidence that the response multichannel customers have towards promotions caries according to purchase and also revealed that promotions presented in the offline environment produce reactions among multichannel shoppers. This implies that promotion in one channel could affect the purchase intention of customers in another channel. Chintagunta et al. (2012) provides more evidence regarding promotion effects in channel over the other. They explain that customers who have short time are not likely to seek out promotions online as offline promotions give them the ability to track their purchases and are therefore less likely to switch to brands.
Particularly, in this research the influence toward online and offline promotion will be discussed simultaneously to see if there are differences in the behaviour of costumers' responsiveness to promotions in different percentage levels and in different online/offline settings. As discussed the effects of promotion on the traditional environment has been researched. Little research has been done in online retailing, thus more insight is needed. Managers will gain more consumer insights that promotions have varying effect on customers' response to these promotions in online and offline channels.
9 If we assume that that there are differences in response towards online and offline promotions, there could be variables influencing this relationship? For example, the relationship could be influenced by demographical and attitudinal/behavioural characteristics. When customers search for information through different channels, but buy on a particular channel, is that because they are loyal to a specific channel for purchase? Does gender make a huge difference whether customers react differently when exposed to promotion in the different channels? Does general price information influence they way customer get influenced by promotions online and offline? And when they buy online or offline how does enjoyment during shopping and impulsiveness influence the direction towards different channels simultaneously?
The different reaction of consumer has also been conducted to measure how consumers perceive different promotion percentages. Grewal et al. (1996) predicted that when price discounts are low, consumers are unlikely to process information extensively since the price promotion has little monetary value. Similarly, when price discounts are high, consumers are predicted to be unlikely to process the information extensively since there is less uncertainty about the merits of the deal.
As discussed, managers have insight that promotion has an effect in online and offline channels, but more research should be done as discussed by Zhang and Wedel (2006) to gain more valuable insight towards responsiveness in online and offline channels. Through this research managers will know how consumers react in different channels and how to differentiate promotions across these channels. Particularly, through this research it will become clear which promotion channel will be suitable for which target groups. This will give managers insight which channel is suited for which specific promotional activity. Researchers in particular will know the importance of each channel when consumers are exposed to promotions. Considering, most previous literature focussed on cross-competitive promotion effects on brand or store choice within an offline channel; hereby the underlying motivation of consumers will also be discussed to gain greater insights in their purchase behaviour. The following chapter further elaborates on this gap discussing relevant theories, literature and concepts. Eventually, this results in the formulation of the research gap from which the research question is derived.
10 Thesis overview
In the following paragraphs, the literature relevant to the topic and the research gaps are reviewed, it follows the conceptual framework and methodology used. In the last stage the results are offered, as well as the discussion and the managerial implications. Moreover, some further research guidelines are presented.
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2 Literature review
In this literature review, we elaborate upon the theoretical background of the key concepts of this research. First, price promotions will be briefly discussed. Next, insights in online and offline promotions will be provided. Then the customers' responses towards online vs. offline promotions will be discussed. Finally at the end, the factors that could affect customers' responses to online vs. offline promotions will be discussed. At the end of each paragraph, a hypothesis based on the literature will be formulated. Finally, with the help of the previously described theoretical framework, the research gap and question for the current study is stated as well as the theoretical and managerial contributions.
2.1 Promotions
Promotions are a key marketing instrument used by retailers, both on and offline, to generate sales and increase market share (Grewal et al. 2011). Companies are making intensive use of promotions to persuade customers to buy their products or services. Firms-oriented firms use special offers, coupons and many other kinds of marketing strategies with the purpose of creating loyal consumers and attract new ones. The nature of the effect of promotions on customer behavior has been found to depend on the utility they perceive themselves to gain (Applebaum & Spears, 1950). The frequency of promotions is very important. Kalwani & Yim (1992) theorize that occasional promotions on a product can take the consumer by surprise, and induce them to grab the opportunity. Offline promotions on the one side have been widely studied, whereas less is known about online affects that impact promotions on consumer behavior. In figure 1 some promotion examples are exhibited.
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Figure 1: Consumer and B2B promotions (Kotler and Armstrong, 2010)
2.2 Price promotion
Discounting through price promotions has become quite important in the market place because marketers view it as an acceptable method of reducing price (Monroe, 2003, p. 478). Price promotions are temporary price reductions offered to the consumer (Blattberg et al. 1995). It is suggested that that price promotions are the result of a prisoner´s dilemma (McAlister, 1982), where the gains from dealing are significant if no one deals and hence every manufacturer and retailer ends up offering the similar deals. Most managers in fact are confronted with the profitability of promotions mostly respond as if it were a crucial factor to maintain market share in response to promotions by competitors. Another explanation expected by Blattberg et al. (1981) is based on the possibility of using it as a mechanism for discriminatory transference of inventorying costs across two types of consumers. In their model, one type of consumers have low inventorying costs and therefore are willing to stock up while other consumers have high inventorying costs and therefore buy only as much as consumed in a given time period. A Mixed strategy equilibrium is characterized where, typically, only one store cuts its price at a time, although it is possible for several stores to reduce their prices to different levels on the same day. The interval between two consecutive sales varies but is shown to have a minimum length of elapsed time. In a model with two types of consumers, informed and uninformed, Varian (1980) shows the nonexistence of a pure strategy equilibrium and then characterized a mixed strategy equilibrium where firms randomize their strategies over a range of prices in any given time period. It is important to note that in all these analyses the mixed strategy equilibrium concept is used because a single-period Nash equilibrium does not exist; moreover, the interpretation of a mixed strategy equilibrium as a form of price promotions seems to be appropriate only if one considers a
13 multi-period model and argues that randomizing over a range of prices in different time periods can be viewed as price promotions.
The impact of a price promotion needs not be limited to its immediate effect. Purchase acceleration, for example, may cause a post promotion dip, i.e., additional sales come at the expense of future purchases (Blattberg and Neslin 1990). Dynamic effects can also enhance the initial impact of a price promotion through different forces at the level of the consumer, the promoting brand, and its competition. Consumer purchase reinforcement can stimulate subsequent category demand induced by the promotion of one brand. Competitive reactions and feedback loops can stimulate new promotions, either by the promoting brand or its competition. Lastly, company decision rules can also stimulate spending in other parts of the marketing mix, causing further demand increases (Dekimpe and Hanssens 1995a).
Recent studies have shown that that there may be systematic differences in customers' attitudes and behaviour for products and services chosen online versus offline (Shankar, Smith & Rangaswamy, 2002). Alba, Mela, Shimp and Urbany (1999) stated that a key difference between online and offline shopping is the ability of online consumers to obtain more information about both price and non-price attributes. More information on prices could increase consumer price sensitivity for undifferentiated products. But Alba et al., (1999) also stated that having more information on non-price attributes could reduce price sensitivity for differentiated products.
What was even more interesting is that they were no significant differences in the effects of promotions online compared to offline. Yet, there hasn't been any conceptual framework which explains the differences between online and offline choice behaviour (Burke, Harlam, Kahn & Lodish, 1992). There are no conclusive findings about the long-run effectiveness of promotions at the brand level, let alone at the category level (Blattberg et al., 1995). Another factor with regard to price promotions is price promotion intensity. Hereby Raju (1992) distinguishes two components; promotional frequency and promotional depth. Promotional frequency reflects the extent to which consumers are exposed to price promotions (e.g., the percentage of weeks with a price promotion), whereas promotional depth specifies the average size of the promotions to which consumers are exposed (e.g., cents off). Having talked about price promotion in general, the next chapter shortly will elaborate on the multichannel environment and directly after that the offline and online promotions will be discussed separately and how they differentiate from each other.
14 To understand the offline and online environment, one first has to understand the multichannel environment which is becoming more important (Wind & Mahajan, 2002). Many retailers use multichannel retailing using both conventional retail stores and the internet to their self-merchandise (Zhang, 2009). According to Ahmetoglu, Furnham & Fagan (2014) price has also become an essential tool for retailers. While some retailers reveal similar prices between multi-channel retailers' online and offline channels (Flores and Sun, 2014), others indicate that up to 60 percent of multi-channel retailers engage in channel-based differentiation and that this trend is increasing (Wolk and Ebling, 2010).
In another study by Chu, Junhong, Pradeep, Chintagunta, & Cebollada (2010) a different aspect of shopping behaviour of multichannel customers of a grocery chain was analyzed. Their research showed that customers reveal greater brand and size loyalty, but less price sensitivity when shopping online than when shopping offline and that these variables are linked to product and consumer characteristics. Furthermore, looking at price strategies, one would notice that the effect of price has been researched, yet the effect of price promotion on offline and online channels is a grey area which hasn't been researched.
2.2.1 Offline Price Promotion
Offline promotions, often called retail store promotions, historically could do promotional activities for two reasons. First, a manufacturer´s sales force provided evidence from syndicated sales auditing services supporting the effectiveness of promotion in cultivating new customers for a particular brand. The implication was that the retailer would instantly benefit instantly from the increased sales of the promoted brand. Second, trade deals were offered to maintain (or increase) the retailers' margin for the manufacturers' brand. Many retailers have installed scanners that provide daily information on product sales within a store. This information is often more timely and of higher quality. Furthermore, retailers soon will be able to investigate the effects of promotions on their store profit (Kumar & Leonie, 1988). Many retailers use a merchandising system called "category management" designed to support them develop pricing, promotions, item selection, space allocation, displays and retailer advertising tactics. A category is defined as a set of products which consumers perceive to be close consumption substitutes. Some retailers use tactical guidelines based on the category roles to set their promotional strategies. Examples of category roles are "traffic" or "flagship." When the category role is to generate traffic (i.e., bring customers into the retailer’s store), then promotions are likely to be deep, frequent and less profitable for the category. The retailer is not setting promotional profitability as its objective but rather the
15 power of the category to draw customers into the store. An example of a traffic generating category in grocery stores is carbonated beverages. For categories classified as flagship (large and profitable categories), the retailer will still promote but the depth of the promotional discount is lower and promotions will be evaluated based on how profitable they are. Another important affect of promotion which should also be considered is that promotion can enhance substitution and complementary effects within the store (Walters, 1991).
An example of a flagship category win grocery stores is cookies and crackers. Also a study by Anderson & Simester (2002) showed that deep promotion activities can have an influence on customers' future demand and purchase frequency. What was surprising is that deeper promotions increase repeat-purchase rates among first-time customers. In another the case the effect of price promotion on brand loyalty was discussed and showed that promotion can demand higher levels of trade support for activities that enhance brand loyalty compared to activities that detract from brand loyalty. Managers should take into account that if price promotions increase price competition between national brands, the result can be lower than overall category profits that are harmful to the private label. Retailers should therefore continually monitor loyalty levels and cross-elasticities (Gedenk & Neslin, 1999).
2.2.2. Online Price Promotion Consumer Promotions
Consumer promotions are promotions from a manufacturer directly to consumers. In the US the most common forms are rebates and coupons. In other countries, contests and risks are more prevalent. More and more consumer promotions are being offered on the Internet. The purpose of consumer promotions is for a manufacturer to communicate a discount directly to the consumer and avoid intermediaries (e.g., retailers) who may not provide the discount the manufacturer wants. In the design of consumer promotions, the critical decisions are medium, redemption system, restrictions and breakage. The medium used varies by type of consumer promotion. Print and the Internet are very common media used for consumer promotion because the promotion can be printed. Handouts, on-pack and in-pack promotions are also used (Blattberg and Briesch, 2012).
Internet Promotions
Although the effectiveness of differing forms of advertising varies, due to such a wide selection of advertising medium, advertising is a highly flexible form of promotion. For example, websites and magazines which attract certain customers can be used for
16 advertisements which more specifically target those customers. Advertisements designed targeting a specific client base can be written for websites and magazines that have a smaller and more specified viewer group (such as health magazines) while more general advertisements can be designed to reach a much larger group for magazines or websites that have a much larger and varied client base (such as news websites). It is also believed that there are some differences for e-tailers on choosing promotion strategies as inducement tools (Huang and Cheng, 2013). Price discount might have greater impact in online shopping context than in offline, since online shoppers tend to deem that product prices in online shop sales lower than in physical retail store (Grewal et al., 2003).
Loyalty is also an important era when talking about online promotion. Danaher, Wilson and Davis (2003) researched that brand loyalty is higher in online stores in comparison to offline stores. Also a research by Zhang and Krishnamurti (2004) researched that promotions are not only tailored for individual households but also showed that promotion can lead to substantial profit increase in an online shopping environment.
Furthermore, retailers and manufacturers can use the Internet as a vehicle for targeting and reaching customers with promotions. Unlike direct mail, the Internet is a virtually zero-cost communication vehicle. If a customer is willing to provide his or her e-mail address, then the firm selling the goods or services can reach the customer at a low-cost. When using the internet, offering highly targeted promotions which were very expensive using mail or other distribution systems becomes almost costless. The other important method of the distribution of discounts using the Internet is websites. Many manufacturers or third-party sites offer consumers discounts on purchases of products. Consumers can print coupons, use codes or other instrument to retrieve discounts. The implication of a low-cost communication vehicle for offering targeted promotions combined with a wealth of consumer information available on the internet is that the types of promotions will be much more selective. Models are also needed to determine what types of offers should be provided to different segments of the market. Whether firms will ever be able to offer one-on-one promotions is an open question because of the cost and sophistication required to provide the relevant analytics.
In the next part mobile promotions will be shortly discussed, as this is emerging as an important channel Andrews & Goehring & Hui & Pancras & Thornswood (2016).
17 - Mobile promotions
Mobile promotions are becoming increasingly important. For the research this online channel will not be included, hence it is important to shed some light into this channel to see how managers can extend in this channel. Andrews et al., (2016) have studied mobile promotions and developed a theoretical framework. Broadly defined, mobile promotions comprise information that is delivered on a mobile device and offers an exchange of value, with the intent of driving a specific behavior in the short term (Andrews et al., 2016).
This definition of mobile devices holds that mobile promotions can be delivered at any point in time during the consumer purchase process. The second key component of mobile promotions is that they provide a fair exchange of value to the consumer (Shankar and Balasubramanian, 2009).
The third and fourth key components of mobile promotions involve activating a desired consumer behavior in the short term. The goal is to drive behavior towards the end of the purchase cycle, close to the point of purchase (Shankar and Balasubramanian 2009). In their research they particularly show how important mobile promotions are becoming and that further research is needed to see what other impact it has in other contexts.
In the next section a summary table of the articles regarding online and offline channels targeted on promotions will be presented.
Previous research has been done on certain moderating effects and an overview of these effects in the extending literature can be seen in table 1. This overview shows that most articles usually studied online and offline channels and studied the mobile channel less frequent since it was recently introduced and is a relatively new field of research.
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19 2.3 Consumers’ Response towards Online vs Offline Price Promotions
Grewal, Marmostein, and Sharma’s (1996) study showed that consumers’ response to price information depends on the context in which the price information is evaluated. In addition to this active information search, the Internet may also cause a heightened involvement. The pieces of information that the consumer sees depend on where the consumer wants to go from one step to the next. Specifically, on the Internet, a consumer generally has to find the marketer rather than vice versa and hence has to be engaged in information search to a greater extent than is the case with most traditional media (Berthon et al., 1996, p. 44). This conclusion is consistent with Beatty’s (1998) argument that online communication not only communicates more information but also is likely to be more engaging. In the figure below you can see the current discount levels combined with various prices and the percentage of shoppers for these prices.
Figure 1 Rates M- Shoppers (Quint & Rogers, Columbia Business School, 2013)
In a study by Zhang and Wedel (2009), competitive and loyalty promotions were tested in order see whether there were differences in consumers' responses. In their research optimal promotion frequency and depth are lower for loyalty promotions than for competitive promotions. Most noteworthy is the comparison between offline and online stores for the same promotion orientation. Loyalty promotions were more profitable in online stores than in offline stores, competitive promotions are more profitable offline than online. In their eyes this is driven by differences in the impact of past purchases outcomes related to that of current practice between the two shopping channels. The indication was that online consumers are more state dependant relative to their responsiveness to current price promotions than their offline counterparts. This means that it is easier to generate consumers to switch from the brand they purchased previously in offline stores than in online stores, thus competitive promotion are more profitable offline. In comparison, loyalty promotions are more profitable online because consumers are more inertial, and that's why it is easier to prevent them from
20 switching brands. These findings imply that online stores are more appealing for retaining a brands existing customers, and offline stores present a better channel for attracting competitors' customers.
Furthermore, one would notice that satisfaction and loyalty measures are becoming increasingly important variables in consumers' purchase decisions in the online and offline environment (Shankar et al., 2002). Managers are concerned about how an online medium influences satisfaction and loyalty and the relationship between satisfaction and loyalty (Shankar et al., 2002). Typically, online customers can more easily compare alternatives than offline consumers, especially for functional products and services. Therefore managers fear that the online medium will induce lower customer satisfaction and loyalty compared to the offline medium, and that increased satisfaction with a service may not lead to higher loyalty and a stronger relationship when that service is chosen online (Shankar et al., 2002).
Main difference between online and offline consumers
Chintagunta et al. (2012) find that transaction costs play a critical role in which channels consumers prefer more. In their article about the grocery retail sector, they provide monetary estimates of several of these costs, finding considerable heterogeneity in their magnitude across consumers. Also, in their findings they also discovered that the greater the distance between home and stores, the more likely the consumer will shop online. Also travel and transportation costs discourage consumers from visiting an offline stores, and report situational factors, such as weather conditions, day of the week, as possible determinants of the individual consumers' channel choice. In another article by Melis et al. (2015) they make an assumption that consumers choose the channel that maximizes their overall utility on a given purchase occasion. This means that consumers tend to base their channel choice on the basket of goods to be purchased.
Another aspect which is briefly discussed is the influence of different promotion percentage on customers' responsiveness in the different channels. Bell, Chiang & Padmanabhan (1999) analyzed a higher percentage discount from the base price greatly improves the quality-per-dollar equivalent of a brand. Raju (1992) hypothesized that deep discounts can induce some consumers who are loyal to competing brands to switch to the promoted brand. So, higher discount percentages could lead consumers in switching to the promoted brands.
21 2.4 Factors affecting consumers' response towards offline and online promotions Several factors can influence how consumers react to promotions which are held offline vs. promotions online. Amongst them are demographic characteristics, as this relationship might differ per gender or cultural nationality. Attitudinal/behavioural also effect this relationship, amongst them are shopping enjoyment, impulsiveness and general price orientation. Previous research has shown that there is a different effect per product category. Due to time and financial constraints, this research will focus on the difference in tangibility for 'Consumer Electronics and Flying Tickets'.
2.4.1 Demographic characteristics
Demographic characteristics are features of individuals such as age, gender or education level. These factors can determine whether there are significant differences between groups. This research will assess particularly whether there are differences in consumers' response towards offline and online promotions.
Gender
Research findings on the effect of gender on online purchasing showed mixed results. While some studies show that men are more likely to engage in online shopping (Teo, 2001; Korgaonkar and Wolin, 1999), other studies found that women are more likely to buy on the Internet than men (Goldsmith and Flynn, 2005). As discussed, there are still mixed results in which gender buys more online. For example women find shopping to be a social and pleasurable activity and are more likely to go shopping with friends or family (Alreck & Settle, 2002). However, men on the other side are more likely to by and spend more on the internet than women (CBS, 2015). Hereby the consideration of the offline channel hasn't been considered to see which gender is more strongly related. It is therefore expected that gender will have a significant impact on customers' responsiveness in online and offline channels.
Cultural nationality
People are deeply influenced by the cultural values and norms they hold. The tremendous advances in global travel, communication, and media have led to suggestions that cultures are converging and that the globalization of markets will create, or at least lead to, a common culture worldwide. Cultural imperatives are likely to have a profound impact on the adoption and the use of the Internet in international marketing. For example, since Internet shopping tends to be impersonal, methodical, and policy-driven, it is not clear that a Confucian-based
22 culture of personal interaction is well suited to it. Furthermore, cultures that score high on uncertainty avoidance are less likely to be early adopters of Internet marketing schemes, even if other cultural imperatives are met (Park & Jun, 2003). People with different values and norms could hold different views towards shopping in online and offline channels and therefore have a different impact how they react upon promotions. Therefore, differences in culture nationality will have a profound impact on customers' responsiveness towards online and offline channels.
2.4.2 Attitudinal characteristics
In a study by Lichtenstein et al., (1990) the lack of distinction made between attitudinal and behavioural constructs while measuring sales promotion studies. “Attitudes are learned predispositions to respond to an object or class of objects in a consistently favourable or unfavourable way” (Assael, 1998, p. 282). “It is not behaviour; it is a predisposition towards a particular behaviour” (Blythe, 1997, p. 69). Because attitudes are not tangible, they must be inferred from statements or behaviour.
Shopping enjoyment
Shopping enjoyment is the extent to which a shopping experience with a store is perceived to provide reinforcement in its own right (Childers, Carr, Peck, & Carson, 2001). In an article by Cai & Xu (2006), the description of shopping enjoyment is the extent to which the shopping experience with a web store is enjoyable in its own right. Shopping enjoyment in this sense is not the psychological state of a person, but rather the enjoyability of the store (Cai & XU, 2006). For this research it is interesting to study how consumers react to price promotions and if they are keen to shopping enjoyment as opposed to consumers who only shop because it is a need. Also, can it serve as an explanation why consumers behave in a certain manner when exposed to promotions. Hence, it is expected that a high sense of shopping enjoyment will have a profound impact on offline promotions.
Impulsiveness
Researchers as well as marketers believe in the existence of impulsive behavior (Hilgard, 1962, Rook & Fisher, 1995). However, an impulsive behavior or intention does not directly translate into action, because many other factors such as time pressure and economic position may interrupt the transition from impulsive tendency to impulsive action (Rook & Fisher, 1995). Impulse buying behavior on the internet environment provides promising research opportunities because online buying eliminates the constraints of time and space, that
23 consumers often face (Eroglu, Machleit & Davs, 2001). Solomon (2002) defines consumers’ impulsive buying behavior as behavior that “occurs when a consumer has a sudden irresistible urge to buy” (p.301). The impulsiveness of consumers will study if consumers act in an impulsive manner when they are shopping and how this differs from offline and online channels. This factor is equally important as it will show if purchases are driven by impulsiveness and/or commitment and will also show insights in the behavior of consumers. Therefore it is expected, that impulsive customers will be more prone to online promotion vs. offline promotion.
General Price orientation
Firms must develop their pricing strategies carefully to ensure that their prices optimize their profits and convey their desired messages. Setting prices and developing a consistent strategy is much more complicated for a retailer than a manufacturer because of the vast number of stock keeping units involved (Levy et al., 2004). Consumers' behavior towards price is also a factor which one should take into account when making price decisions. Strategic consumers want to maximize their individual utility. At each time point they might purchase the product at current price, remain at a cost to purchase later, or exit. Another interesting finding is in the article form Alba et al (1999) pointing out that the key difference between online and offline shopping is the ability of the online consumers to obtain more information about both prices and non-price attributes. Therefore it is expected that a high price orientation will have a positive influence to the responsiveness of customers towards online promotions.
2.5 Gap and research questions Research gaps
As discussed earlier, a lot of research has been done on behaviour of consumers online and offline (Gonçalves & Silva, 2016). Studies have shown systematic differences between customers' attitude and behaviour for products and services chosen online versus offline. Alba et al. (1999) stated that a key difference between online and offline shopping is the ability of online consumers to obtain more information about both price and non-price attributes. More information on prices could increase consumer price sensitivity for undifferentiated products. So, consumers find price an important attribute when shopping offline and online, but there hasn't been much research on price and in particular price promotion effects in offline and online channels. However, all these articles lack the inclusion of factors which could influence their online and offline behaviour, e.g. demographic and attitudinal/behavioural
24 characteristics. Little research has been done on particular attitudinal characteristics, e.g. consumers' commitment to one channel over the other or how they perceive price in general. Therefore, there is a need to expand the knowledge on certain moderators that examines how this influences their responsiveness between offline and online promotion. Most of the data is used from companies which makes it hard to generalize. In contrary, this study will conduct a survey where the customers will be asked to respond to different product categories in the offline and online channels. However, there is no research on customers responsiveness to price promotions in different (%) discount levels in online and offline channels/ and which factors may influence this relationship - and this is important for managers because they may need to make their promotion decisions and allocate their resources accordingly.
Research Question
This research is trying to answer the following question:
How does customers' responsiveness to price promotions on different (%) levels differ in online and offline purchase channels? What are the demographic and attitudinal factors that
might have an impact on these response levels?
2.6 Contributions
2.6.1. Theoretical contribution
This research adds to the extending literature as discussed in table 1 where the research gap is summarized. Even though there has been some literature on online and offline channels, little research has been done in comparing online and offline channels simultaneously and customers’ reaction to promotions on online and offline channels. The usage and behavior of consumer via these channels also changes over time. Also, the shopping behavior of consumers in online and offline channels keeps changing and should taken into account to come with new insights. Hence, it is important to renew existing literature so it will not become obsolete. Most articles have focused on how consumers respond in online and offline channels en some insights in their reaction towards promotion. Previous research by Zhang & Wedel (2009) discussed customized promotion in offline and offline channels aimed at the profit potential customized at various levels of granularity in online and offline channels particularly related to sales promotions. Other factors, like attitudinal characteristics, have not been discussed to assess in dept why consumers behave in such manner through different channels. However, there is no research on customers responsiveness to price promotions in different discount percentage levels in online and offline channels/ and which factors may
25 influence this relationship - and this is important for managers because they may need to make their promotion decisions and allocate their resources accordingly.
Most articles focused on how consumers act differently towards online and offline channels, but not to the extent of the reasoning why certain behavior leads to one channel choice over the other. Also the use of big data sets of companies is used for quantitative research, which makes it harder to generalize the outcomes of the research. This research will provide insights in how different factors influence consumers' response towards promotions online and offline. Previous research did this partly simultaneously based on one particular category, while this research will mostly focus on customers' response towards promotion in online and offline channels. Also, value will be added through the demographical and psychographic factors. These factors will add to the literature that the underlying reasoning of consumers is not only influenced by their preference of channel over the other, but is rooted in the mind of the consumer based on these factors. Therefore, value will be added to previous research and findings.
2.6.2. Managerial contribution
Online channels are becoming important; marketers should consider focusing and expanding their reach through this channel. Organizing through an online channel is an investment which should be thought about. The benefit in expanding toward an online channel will differ between companies and the types of products and/or services they deliver to consumers. To be able to predict this approach will eventually be beneficial for the company in the long run. For instance, when looking at gender in a particular product category shows a complete other picture then a company initially stated with their strategy will give a whole new insight for their strategy and how to attract consumers the right way. Hereby managers will know which promotion channel will be suitable for which gender and target specifically to be beneficial in the long run. The rationale also applies for attitudinal factors, e.g. shopping enjoyment, impulsiveness and general price orientation of a firms' target group. The outcome of this research makes it able to weigh down the responsiveness based on these moderators of consumers in the online and offline channels.
Shopping enjoyment influences the relationship how consumers perceive promotions online and offline. This is important as the enjoyment of consumers could vary between online and offline consumption and therefore on promotions. This insight will show managers the differences in consumers' motivation to shop and how that affects their reaction on
26 promotions. These insights will also show which factors have an influence on promotions and the reason why consumers react differently in online and offline channels and thus why they react differently to promotions. Managers will be able to make more accurate predictions and determine which channel they should focus on.
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3. Conceptual Framework
This chapter will visually show the hypothesized relationships in a conceptual framework, and briefly explain why these hypotheses will be studied.
H0 +
H1 +
H2 - H2 -
Figure 2: Conceptual framework
Figure 1 provides a visualization of the conceptual framework of this research framework. The main goal of this study is to provide insights whether consumers respond differently toward promotions presented in an offline or online context. As explained in the literature review, little research has been done toward offline and online promotion simultaneously. The aim is thereby also to present what those differences are and which moderators have an influence in their response.
Main/general question
As we discussed the main facts that could affect customers' responsiveness towards online and offline promotions, for this research we also propose one main question regarding customers' responsiveness. Leaving all factors aside: Can we say (in general) that customers are more responsive towards online (or offline) promotions on the same discount percentage level. So therefore, we propose our main hypothesis
Online and offline
price promotions - 5% discount - 10% discount - 20% discount Customer responsiveness (purchase intention) Demographics - Gender H3 + - Cultural Nationality H4 - Attitudinal/Behavioral - Shopping Enjoyment H5 - - Impulsiveness H6 +
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H0 (main hypothesis): Customers are more responsive to small discounts in online channels
and more responsive to big discounts in offline channels. 3.1 Channel preference
As discussed in the literature review consumers shop in online or offline channels, and in some cases both. The differences in behaviour of consumer toward a channel will lead to different impact towards promotions as their commitment with one channel over the other. Therefore it is expected that a specific channel choice will have an impact in the responsiveness towards online or offline promotions.
H1: A choice preference towards online channels is expected to have a significant positive
impact in responsiveness toward online promotion
As previously discussed consumers will react differently when they are committed to a specific channel. Also, the responsiveness of consumers will be influenced how the perceived promotions differ in terms of high or low percentages. Therefore it is expected that small promotion percentages will lead to a significant higher responsiveness toward online channels.
H2: Responsiveness to online promotions in comparison to offline promotions is higher for
price promotions with small percentages. 3.2 Demographics
Gender
As discussed in the literature review there are still mixed results which gender reacts more to online or offline channels. While some studies show that men are more likely to engage in online shopping (Teo, 2001; Korgaonkar and Wolin, 1999), other studies found that women are more likely to buy on the Internet than men (Goldsmith and Flynn, 2005). However, in a report by the CBS (2015)it was measured that men more likely to by and spend more on the internet than women. Women for example find shopping to be a social and pleasurable activity and are more likely to go shopping with friends or family (Alreck & Settle, 2002). So, this suggests that women are less likely to buy online because of its lack of the social component. Therefore, it is hypothesized that men will have a significant influence on online promotion
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H3: Customer responsiveness towards online promotion is higher for male for male
customers.
Culture nationality
As discussed in the literature review cultural values en norms play an important role in influencing people's behaviour. Cultural imperatives are likely to have a profound impact on the adoption and the use of the Internet in international marketing. As stated, people from different cultures have different values and norms and take that into account when exposed to decision making heuristics. Therefore, it is hypothesized that people from a different nationality will react diversely to promotions held online or offline
H4: Customers from Europe are expected to be more responsive towards online promotion.
3.3 Attitudinal factors Shopping enjoyment
Shopping enjoyment relates to the extent whether consumers enjoy shopping, rather than the psychological state of a person. This means that the enjoyablity of the consumer whilst shopping is taken into account and sees how they respond to shopping in different channels, e.g. online and offline. It is an important era to know whether people actually enjoy shopping and will be more pronounced towards promotion held online and offline, than people who only shop as for it is seen as a need. Therefore, it is hypothesized that consumers that have a high level of shopping enjoyment are more pronounced towards offline than online promotions.
H5: People who enjoy shopping more are expected to be more responsive towards online
promotion.
Impulsiveness
The impulsiveness of consumers will study if consumers act in an impulsive manner when they are shopping and how this differs from offline and online channels. This variable is equally important as it will show if purchases are driven by impulsiveness and/or commitment and will show insight in the behavior of consumers. As defined by Solomon (2002) consumers’ impulsive buying behavior as behavior that “occurs when a consumer a sudden irresistible urge to buy” (p.301). Whether this impulsive behavior will result in action, is uncertain as this is also influenced by other factor than only impulsiveness per se. Consumers
30 who therefore are impulsive will behave differently in their shopping behavior, whether it is offline or online. It is therefore hypothesized that responsiveness towards online and offline promotion is more pronounced when the customer has a higher degree of impulsiveness.
H6: Impulsive customers will be more prone to online promotion vs. offline promotion
General Price orientation
Price is an important variable when consumers are purchasing, whether it is online or offline. As discussed in the literature review firms must ensure that their prices optimize their profit and convey their desired messages. Consumers' behaviour towards price is also a factor which one should take into account when making price decisions. Consumers' reaction towards price orientation plays a role in their buying behaviour. Therefore it is likely that this orientation will have an influence on their response to offline and online promotions. Another interesting finding is in the article form Alba et al pointing out that the key difference between online and offline shopping is the ability of the online consumers to obtain more information about both prices and non-price attributes. It is therefore hypothesized, that a high level of price orientation will positively affect the responsiveness towards online and offline promotion.
H7: Customers with a high price orientation are expected to be more responsive towards
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4. Research design
For this research an online questionnaire was distributed. Thus, a quantitative approach is needed. In order to gain information about the responsiveness of consumers toward online and offline promotion, the difference between demographic and attitudinal characteristics, a survey was conducted to gather cross-sectional data. All the respondents received the same online questionnaire. The questionnaire was available in Dutch and English. At first a Pilot Study was done to make sure that the questionnaire was clear and understandable. This was also done to make sure that all the questions could be answered given within the given timeslot.
4.1 Population sample
The population-sample used for this sample from online and offline shoppers aged between eighteen and older. The questionnaire was made via Qualtrics and was spread through internet while using a convenience sample. Due to financial and time restriction, the questionnaire was spread via social media, i.e. Facebook, email, family and friends.
4.2 Measures
The respondents were asked to answer which channels, i.e. offline/online, they used to search for information about the purchased products in the past six months. The survey will be distributed three times. The three surveys will be the same, expect for the promotion percentages which will be presented in the distributed surveys and divided in three different categories. Also the respondents which are representative for the three various surveys will be different as to avoid bias in their responses. The three different product categories of the survey are: clothing/apparel, consumer electronics and flight tickets. Since the main question of the research is to find out what consumers' responsiveness is towards online and offline promotions, the questionnaire started with question about their shopping experience and whether that was held offline or online. To measure the channel commitment, consumers will be asked about their shopping behaviour (in percentages) in offline and online channels. To measure shopping enjoyment, impulsiveness and general price orientation, the commonly used questionnaires from Babin et al. (1994, Rook & Fisher (1995) & Lichtenstein et al. (1990) were conducted. A more detailed description can be found in appendix A.
32 Shopping enjoyment was measured using a validated scale with a Cronbach's alpha of 0.91 (Babin et al. (1994). These two items were used on a 5-point Likert scale. Impulsiveness was measured using a validated scale with a cronbach's alpha of 0.70 (Weun, Jones & Beatty, 1997). The 4 items were measured using the 5-point Likert scale. Price orientation was measured using a validated scale with a cronbach's alpha of 0.85. These 2 items were measured using the 5-point Likert scale. An overview of all variables, their measures and measure levels can be seen in table 2.
Table 2 Summary table measures and measure levels of variables
The questionnaire ended with asking the respondents about their demographics, i.e age and gender. Since these questions were confidential, respondents were asked at the end of the survey in order to increase the response rate (Gravetter & Forzano, 2015; Saunders & Lewis, 2012). The responses were processed anonymously. An overview of all variables, with their measures and measure levels can be seen in table 2.
Variable Meausures Level
Demographics Gender Female= 0, Male=1 Nominal (dummy variable)
Culture Nationality Europe, Asia, America/Latin America, Other
Ordinal
Attitudinal Shopping Enjoyment 5-point Likert scale Interval/Ratio
Impulsiveness 5-point Likert scale Interval/Ratio
General Price Orientation 5-point Likert scale Interval/Ratio
Responsiveness to promotions
5-point likert scale Interval/Ratio
Product categories Flying Tickets No= 0; Yes= 1 Nominal (dummy variable)
Electronics No= 0; Yes= 1 Nominal (dummy
33 4.3 Analyses
The data were analysed with SPSS (Version 22.0.0.0, IBM Corporation). Since the survey was distributed six times based on the different promotional scenarios for the three product categories, i.e. consumer electronics and flying tickets, the data were separately analysed based. The main effect of online and offline promotion was also analyzed per category
The analysis of the purchase intention of consumers was measured by a multivariate linear regression. A separate analysis were done per 2 (consumer electronics and flying tickets) x 2 (main effect, moderating effects). For each separate two product categories a multivariate linear regression analysis on the main effect of purchase intention was performed, as well as a multivariate linear regression analysis with moderators included as independent variables.
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5. Results and Analyses
In total 257 respondents filled in the survey, but 48 respondents were excluded from the results as the results were fabricated. The remaining 209 respondents were used for the final analysis. The survey had a gender distribution of 57, 4% male and 42, 6% female. The culture nationality of the respondents was translated in 'Europe' which took 88% into account. 'Asia' had a distribution of 9.1%. There were only 0.5% respondents from 'America/Latin America' and 2.4 % of the respondents fell in the 'Other' category. An overview can be seen in table 3.
Table 3. Baseline Demographics
Variable (N= 209) N (209) Gender Male (%) Female (%) 89 120 42,6% 57.4% Culture Nationality Europe (%) Asia (%) America/Latin America (%) Other (%) 184 19 1 5 88,0% 9,1% 0,5% 2,4%
The mean of Offline promotion is 0, 44 (SD= 0.499), whereas the mean of Online promotion is 0,69 (SD=0,463). The mean in the product category 'Consumer Electronics' is 1,60 (SD=0,489) and the mean of 'Flying tickets' is 1,36 (SD=0,482). Finally, the mean for '5% Discount' is 0, 66 (SD=0,477). The mean of '10% Discount' is 0, 52 (SD=0,504) and the mean of '20% Discount' is also 0, 52 (SD=0,04). An overview can be seen in table 4.
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Table 4. Overview of Variables
(N=209) M Med SD Promotion Offline Online 0,44 0,69 0,00 1,00 0,499 0,463 Product type Consumer Electronics Flying Tickets 1.62 1.36 2,00 1,00 0,489 0.482 Discount 5% 10% 20% 0,66 0,52 0,52 1,00 0,477 0,504 0,504
5.1 Validity and Reliability
The external validity of the survey is not optimal since it is not representative for multichannel shoppers due to financial restrictions. When comparing the multichannel shoppers based on their demographics, there were significantly more males (M=1,46, SD=0,50) purchased more Flying Tickets in Online stores (M=1,36, SD=0,48), t (84, 86 ) = -1.75, p= 0,054, 95% (-0,45, -0,05), d=0,65. Furthermore, males purchased more Flying Tickets Online when there was a 20% discount (M=0,65, SD=0,75), t (180, 25) = 2,05, p= 0,023 (0,26, 0,30), d= 0,35.
Cronbach’s alpha is a test which determines whether multiple items will form a reliable scale. This is tested on the basis of the correlations of these items. The results also show ‘scale if item deleted’, which allows improving the reliability of a certain scale by deleting a certain item. The scales measuring the Psychographic variables (Shopping Enjoyment, Impulsiveness and Price Orientation were all reliable in our study (α > 0,6), see table 5. The Cronbach’s alpha of the scales could not be improved by deleting a certain item.
36 Table 5. Reliability Analysis Psychographic Variables
5.2 Model Testing
A linear regression analysis was used, in order to test the hypothesis, so as to determine the relationship between the predictor variables and the outcome variable. A hierarchical regression analysis was performed to analyze how three price promotion percentages (5%, 10% and 20%) and 5 moderated interactions (gender, culture-nationality, shopping enjoyment, impulsiveness and price orientation) were able to predict the responsiveness of consumers towards promotions (general, offline and online). The moderators are present in the equation through variables composed by the multiplication of the usage variables and the particular moderator. The regression analysis was conducted for general, offline and online discount. The analysis was conducted within the two categories Consumer Electronics and Flying Tickets.
The following three subsections test the hypotheses for both industries analyzed and elaborate on the acceptance or rejection of the hypotheses. Thus, the discussion of the results is now presented.
5.2.1. Results General Discount
As seen in table 7 being more online oriented consumers have a significant positive effect on responsiveness to promotions (B=0,006, p=0,02). Also when we take a look at the discount percentage dummies, the higher the discount percentage (in comparison to 5%) the purchase intention increases (10% B=0,418, p=0,02, and 20% B=0,333, p=0,05). Impulsiveness is surprisingly the only moderator that has a positive significant effect on purchase intention after promotions held in general (B=0,440, p=0,000). What was more surprising is that there are no significant effects for other variables in the general model (product type, gender, country and shopping enjoyment) and these factors do not matter when customers are exposed to general discounts. Reliability Analysis Psychographics Shopping Enjoyment Impulsiveness Price Orientation Cronbach's α 0,743 0.877 0,731
37 5.2.2. Results Offline Discount
In table 8 we see a slightly different situation. In comparison to general discount, product type does matter in offline promotion. Here the consumers are more responsive to offline promotions for consumer electronics than flight tickets (B=-0,376, p=0,02). If we look at the discount percentage dummies, the higher the discount percentage (in comparison to 5%) in offline promotions, the purchase intention increases (10% B=0,476, p=0,026 and 20% B=0,544, p=0,007). For offline discount impulsiveness also has a positive effect on purchase intention after offline promotion (B=0,322, p=0,001). ). As we can see for offline discount there is no significant effect for other variables in the offline model (product type, gender, country, shopping enjoyment and impulsiveness) and these factors do not matter when customers are exposed to general discounts.
5.2.3. Results Online Discount
The main hypothesis stated that customers are more responsive to small discounts in online channels and more responsive to big discounts in offline discounts. Here we make a comparison between the two channels based on percentage levels. As seen in table 8 customers are responsive towards bigger discount percentage in offline channels (10% B=0,476, p=0,026 and 20% B=0,544, p=0,007). In table 9 we can see that surprisingly customers are more responsive towards smaller discount percentage in online channels. Here, the coefficient of the responsiveness of consumers towards online and offline promotion has resulted to be negative yet significant (online 10% B=-0,046, p=0,820 and 20% B=-0,050, p=0,795) and therefore the main question is partially accepted.
The first hypothesis stated that a choice preference towards online promotion will have a positive impact in responsive towards online promotion. Thus, the coefficient from the regression for the online promotions variable should be positive, in order to increase the level responsiveness to promotion. In this case, the coefficient of the use of online shopping has resulted to be positive and significant (B=0,013, p=0,000). Therefore H1 is supported. Hypothesis 2 stated that responsiveness to online promotions promotion is higher for price promotions with small percentages. If we look at the discount percentage dummies, we see that the discount percentage does not have a significant effect towards online promotions, but is significant at the same time within the linear regression (10% B=-0,046, p=0,820 and 20% (B=-0,050, p=0,795). Therefore H2 is not supported. As we can see regarding H3, the coefficient studying that the responsiveness of male customers should be positive towards
