The battle for the Consumer
The effect of display characteristics of price on shelf talkers
on the consumers’ in-store behavior in a supermarket
(JHBertrand Inc., 2012)
The battle for the Consumer
The effect of display characteristics of price on shelf talkers
on the consumers’ in-store behavior in a supermarket
Joyce Nijensteen University of Groningen
Faculty of Economics and Business MscBA Marketing Management Master Thesis
14 February 2013
Address: XXXXX XXXXX Telephone Number: XXXXX
Email address: mail@joycenijensteen.nl
Student Number: S2033291
First supervisor: Dr. J.E.M. Van Nierop Second supervisor: Prof. dr. L.M. Sloot External supervisor: Ms. M. Baarslag
MANAGEMENT SUMMARY
Presenting yourself as a brand is very important in today’s retail channel. In-store communications are widely used within the supermarkets. Many researchers have studied the effects of in-store communications and the behavior of consumers’ in-store. However, the effect of shelf talkers is never investigated before. Shelf talkers are strips, used as means of communication, presented on the shelf where normally only price labels are presented. Main aim of this research is finding insights in the concept of shelf talkers. Besides the additional understanding of the effects of display- and product characteristics of shelf talkers on consumers’ in-store behavior will be addressed. The relationships are tested on six product categories within the supermarket.
Although no academic information is available about shelf talkers, a literature study is carried out to gain more insights in the relationship between display characteristics of price, product characteristics and consumers’ in-store behavior. A field experiment is conducted to test the hypotheses. Data is extracted from an experiment in the C1000 Vd Worp in Heino, the Netherlands. To test the relations linear regressions are used in SPSS.
The results indicate that shelf talkers do have an effect on consumers’ in-store behavior; however the relationship is only partially accepted. The effects of shelf talkers are tested on six product categories, the relationship between display characteristics of price and consumers’ in-store behavior is not supported for all six categories. The second part of the research consists of the relationship between product characteristics and consumers’ in-store behavior. The product characteristics consist of the type of product (PL versus A-brand) and the product category (food versus non-food). Both hypotheses are not accepted in the way they are originally stated; however in both cases the opposite effect is significant.
This research contributes by helping to fill the gap in research concerning the effects of display characteristics of price and product characteristics on consumers’ in-store behavior. This research gives insights in the effects of shelf talkers in supermarkets.
PREFACE
This thesis is the final piece of work of my Master Marketing Management at the University of Groningen. I’m very proud on the report that is presented in front of you.
When I started thinking about topics for my research I noticed something very special. I went shopping for my weekly groceries in the local supermarket. Yes, that’s C1000 Van de Worp in Heino! I made my shopping list at home, then I decided how to pay: by cash. But how much money did I need for my groceries? I tried to guess the prices of the products that I wanted to buy. Okay, I have enough money to pay the groceries, so I went to the supermarket. After shopping I found the paper which I wrote before shopping with the prices on it. I compared the prices, but ‘Auch!’ I guessed only 1 product correctly! I thought I was very price-conscious, definitely I wasn’t! I always look for the sales signs and try to buy the cheapest products in the shelves. My conclusions afterwards, when a product is on sale it does not automatically means that the product is the cheapest in their category. Besides, not all signs indicate sale. There are also signs with ‘NEW in the shelf’ or ‘permanently lowered’ or simply indications of price. After my shopping trip I found the perfect topic for my research: the effect of shelf talkers (without sale) on consumer behavior.
I would like to take the opportunity to thank a couple of people for making this research possible. First, I would like to thank my supervisor dr. Erjen van Nierop for his professional guidance, valuable feedback and patience throughout the whole process of writing my thesis. I would also like to thank my second supervisor, prof. dr. Laurens Sloot for the additional feedback to complete my thesis. Furthermore, I want to thank all the people working for C1000, for their hospitality of making it possible to test my research in practice. In specific: Kim Van de Worp, Marlinde Baarslag, Johan Schoemaker, all the employees of C1000 Vd Worp Heino and, Frank and Corné on the headquarter of C1000. Erik and Chris, for the design and development of the shelf talkers. And last but not least, I want to thank all friends and family for their support in my studies.
Joyce Nijensteen Heino, February 2013.
TABLE OF CONTENT
MANAGEMENT SUMMARY PREFACE TABLE OF CONTENT CHAPTER 1: INTRODUCTION ... 2 1.1 Introduction ... 2 1.2 Background ... 2 1.3 Company introduction ... 5 1.4 Problem statement ... 7 1.5 Research questions ... 71.6 Structure of the thesis ... 8
CHAPTER 2: THEORETICAL FRAMEWORK ... 9
2.1 Consumers’ in-store behavior ... 9
2.2 Display characteristics of price ... 12
2.2.1 Shelf talkers ... 12
2.2.2 Informative and visual stimuli ... 14
2.3 Characteristics of product ... 16
2.3.1 Type of product ... 17
2.3.2 Product category ... 20
2.4 Conceptual model ... 22
CHAPTER 3: RESEARCH DESIGN ... 23
3.1 Research method ... 23 3.2 Data collection ... 25 3.3 Plan of analysis ... 28 CHAPTER 4: RESULTS ... 30 4.1 Sample ... 30 4.2 Hypothesis testing ... 32 4.3 Overview of results ... 39
CHAPTER 5: CONCLUSIONS & RECOMMENDATIONS ... 40
5.1 Discussion ... 40
5.3 Limitations and guidelines for further research ... 42
CHAPTER 1:
INTRODUCTION
1.1 Introduction
Most consumer decisions for grocery products, about 70%, are made in the store which makes these in-store merchandising decisions critical to retailers’ performance (Aldata Solution, 2007; Neff, 2008). In later studies the percentage of in-store decisions are discussed. Research concluded that type of shopping trips influences the percentage, however even major shopping trips (weekly or less frequently) show almost 60% lift in unplanned buying (Bell et al., 2011). Bezawada et al. (2009) support that the retail environment has become a highly competitive environment in which retailers are using in-store communications to increase their sales. These communications in-in-store are mainly presented by displays, shelf talkers, wobblers and sales strips. How do these in-store communications effect the behavior of consumers? Consumers think they know exactly what their behavior is in a supermarket; however lots of decisions in-store are unconsciously made, e.g. by impulse buying, in-store communications play a huge role in these decisions.
1.2 Background
Consumers nowadays are influenced by lots of stimuli in supermarkets. Every brand and product wants to attract the consumer. However, do all these communications have the intended effect on consumers? Consumers are overloaded with communications. Price is a very important factor that plays a role in consumers’ choice for a product. Price competition has become increasingly vivid in past years; related with supermarket price wars which fit in this trend (Ailawadi, 2001 and Van Heerde et al., 2008). The price of the brand posted on the shelf is a combination of the brand’s regular price and temporary price reductions (Chandon et al., 2009).
introductions or products with premiums. Because of this, these types of promotions are very interesting to investigate.
Obtaining more attention to the product might be provided by shelf talkers with informative and visual stimuli; examples of these types of shelf talkers can be found in figure 1. This research will test the difference in response between informative and visual stimuli on consumers’ in-store behavior. The specialization in function of brain hemispheres is known. Implications on advertisements provided that the left hemisphere supports text processing; where the right hemisphere supports picture processing (Janiszewski, 1988). Therefore, verbal information on the right side of the ad and pictorial information on the left side of the ad will be preferred by consumers. It is expected that these implications might support the difference between visual and informative stimuli in the shelf as well and will lead to a difference in in-store behavior of consumers when confronted with the shelf talker. Based on recommended walking directions within a supermarket the separation between left and right side of the shelves can be defined.
Grover & Srinivasan (1992) found that sale signs are perceived as an indication for reduced prices of products by consumers. On the other hand, Inman et al. (1990) and Inman & McAlister (1993) did research on the effects of signaling promotions. They studied the effect of signs on products with and without discounts, concluded sales increased even on the products without discounts.
It is likely that product characteristics play a role in the relationship between displaying price and consumer behavior. Presenting the attracting price display on a Private Label (PL) product can have a different effect on consumer behavior than on an A-brand. Same difference might exist with food and non-food products. Petty et al. (1983) state that consumers in different segments can be driven by different needs and have a different level of involvement with the product. Type of products can play a very important role in consumers’ behavior.
The relation between price displays and consumers’ behavior with the addition in effect of product characteristics is never been investigated before in this combination. Hereby this research has particular potential to be investigated and will obtain useful implications for managers and science.
whether a price display in the form of a shelf talker can influence shopping behavior of consumers. This will lead to higher sales with a focus on the right products.
Shelf talkers are not new in the world of in-store marketing communications, however hard results which indicate the increase of sales are missing. Academics never investigated research specifically on shelf talkers before. In real life, drug stores widely use shelf talkers in their shelves. In the Netherlands ‘Kruidvat’ and ‘Trekpleister’ are well-known drug stores. Their selling strategy is implemented with lots of in-store communications. Their shelves contain many shelf talkers, wobblers, price indications etc. Besides the drug strores in the current supermarket chains shelf talkers are used as well. Figure 1 presents some impressions of the shelf talkers in the supermarket chain.
Figure 1A. Visual stimuli shelf talkers in Dutch supermarket chain. 1B. shelf talker with informative stimuli.
1.3 Company introduction
The supermarket C1000 Van de Worp is centrally located in Heino. From origin the company started as a bakery with home delivery in the village Heino. After a while Van de Worp started selling groceries and in 1972 the first supermarket concept was a fact. Nowadays the supermarket is still in hands of the family Van de Worp, the third generation is currently running the business.
In 2001 the supermarket expanded rigorous to a floor space of 1650 m2 branded as C1000. Currently the C1000 chain is the second largest supermarket chain in the Netherlands (see figure 2). Behind the market leader Albert Heijn; Superunie does have the second largest percentage of market share, however Superunie is an overall supply organization of 14 supermarket chains (see figure 3). The third largest supermarket chain is Jumbo. Jumbo is not included as separate chain in figure 2 (included in others), because Jumbo doesn’t give detailed information to Symphony IRI (2012). On their own website they suggest that their Market Share (MS) is 8.9% in 2011 (Jumbo, 2012).
Figure 2. Market Shares of supermarket chains in the Netherlands (Symphony IRI, 2011)
The C1000 Van de Worp in Heino is running the ‘third generation’ concept of the chain. The third generation concept is known by the opened ceiling, the positioning of promotions in the middle of the store and the larger (fresher) assortment. The supermarket is divided by a ‘city’ and a ‘country’, separated by the ‘street with sales products’. The ‘city’ contains the groceries where the ‘country’ part of the supermarket contains the fresh department. C1000 Van de Worp is one of the stores which will be remodeled to the Albert Heijn chain (mid-2013).
C1000 Van de Worp has 79 employees of which 25 are fulltime employed. This makes C1000 as the largest employer in the village Heino. C1000 Van de Worp is one of the largest supermarkets in the area with a turnover of € 215.000 per week. C1000 Heino has a net rentable floor space of 1336 m2 (see figure 4), which represents the largest supermarket in Heino. An average supermarket of the C1000 chain has 1027 m2 rentable floor space (Symphony IRI, 2011). Because of the size of Heino, presence of other non-supermarket stores and free parking, lots of consumers from other places around Heino shop in Heino.
1.4 Problem statement
Marketers of fast moving consumer goods (FMCG) have an overwhelming assortment of promotion tools to choose from. Consumers will be triggered by lots of promotion tools in a supermarket. The goal of a marketer will be to use the most effective tools. But which ones are actually the most effective? Many studies focus on the position of brands in the shelf, displays and more general strategies to obtain attention of consumers in a supermarket. However, research specifically on the use of shelf talkers is never been investigated before. Marketers want to know whether shelf talkers lead to higher sales and want to know on which products the shelf talkers are more effective.
Main objective of this study is to examine the effect of displaying characteristics of price on shelf talkers on consumers’ in-store behavior. In addition, the effects of product characteristics as type of product and product category are researched. Therefore, this research focuses on the following problem statement:
“What is the effect of displaying price on a shelf talker on consumers’ in-store behavior for different types of products and in different product categories?”
1.5 Research questions
The following research questions will support the answering of the problem statement: - What is known about the relationship between display characteristics of price on a
shelf talker and in-store behavior of consumers?
- What is known about the effect of product characteristics on in-store behavior of
consumers?
- How does the relationship between display characteristics of price on a shelf talker
and
in-store behavior of consumers need to be investigated?
- How does the effect of product characteristics on in-store behavior of consumers
need to be investigated?
- What display characteristics of price effect the consumers’ in-store behavior?
- What product characteristics influence the effect of display characteristics of price on
1.6 Structure of the thesis
CHAPTER 2:
THEORETICAL FRAMEWORK
This chapter will present the academic argumentation of the effect that shelf talkers have on consumers’ in-store behavior. The foundation of this research is based on the relation between shelf talkers and consumers’ in-store behavior. However additional variables will be added to this relation, who will be concluded in the final conceptual model as presented in chapter 2.4.
First paragraph will go in depth on the types and benefits of in-store communication. The second paragraph will focus on the information available on shelf talkers and the difference in effect of informative and visual stimuli on the shelf talkers. The third paragraph is based on the product characteristics that influence the consumers’ in-store behavior. Information about the type of product and product category will be presented in this paragraph. Results of these paragraphs will be concluded in the complete conceptual framework, which will be the base of the research design.
2.1 Consumers’ in-store behavior
Retailers continually want to attract consumers to their store. Once the consumers are in their store; goal of retailers is to obtain the highest turnover and profit per consumer per visit. Retailers seek to attract attention and communicate a message via point-of-purchase display, weekly circular or websites (Puccinelli et al., 2009). Some other, more integrated tools in the retailer concept, used by retailers to attract consumers are: clear walking directions, fulfilling assortment, pleasant environment and point-of-sale materials. This research will be focused on the last one: point-of-sale materials.
Both manufacturers and retailers strive for the goal of making the highest profits. Both have the goal to attract as much consumers to the supermarkets to buy goods. However inside the supermarket manufacturers are focused on their own product and will present their brands on the best locations in the shelves. Whether retailers overall want to sell as much as possible. Retailers advertise the national brands, which attract people to their stores. Besides retailers sell private labels, which typically have lower variable cost and therefore potentially higher margins, to the price-sensitive segment (Hoch and Banerjee, 1993; Corstjens et al., 2000; Ailawadi et al., 2008). Another reason for retailers’ desire to grow their Private Labels are higher consumer store loyalty and negotiating leverage with national brand manufacturers (Ailawadi et al., 2008). All goals are best for manufacturers’ and retailers’ own wallets. Same is reflected in the in-store communications; manufacturers prefer lots of communications from their own brand, however preferably paid by the retailer and the other way around.
But what does the consumer want? Consumers prefer marketing communications that are relevant, besides consumers want more control (Walker Smith, 2006). Consumers want to have the power to determine when and where they will be exposed to marketing communications. Points of sale communications present both relevance and power and are therefore particular appropriate to reach consumers.
Past research found that most purchase decisions are made inside the store (Neff, 2008; Bell et al., 2011). Therefore in-store marketing is widely used. One reason will be that in-store marketing can trigger forgotten needs (Bell et al. 2011). In response, marketers allocate funds to in-store marketing to stimulate unplanned buying; mainly through displays, promotions and technological innovations (Albert & Winer, 2008). Bell et al. (2011) suggest that there is an important influence of factors formed early along the path to purchase; at the moment when the motivation to shop first emerges. Marketers can generate unplanned buying by persuading shoppers to evoke abstract goals. Besides, advertising abstract shopping benefits makes sense. The supermarket chain C1000 already does this by reminding consumers that they are ‘Doing Smart’ (In Dutch: ‘Slim Bezig’). Some other retailers do the same like Wal-Mart with ‘Save Money. Live Better’ and Tesco which communicates ‘Every little helps’.
percentage change in unplanned buying. This group represents a lift in unplanned buying of almost 60%. The group of consumers shopping for a major trip has the greatest ‘scope’ for unplanned buying because the shopping trip needs to satisfy needs of a total household. This group of consumers might make shopping list with ‘meal’ written on the list. Consumers need to make the decision of buying chicken, meat or fish for example in-store.
This unplanned buying can be further linked to impulse buying. Impulse buying can be defined as an unintended, unreflective and immediate purchase of an individual (Rook, 1987; Rook & Fisher, 1995; Jones et al., 2003). In the past consumer researchers supported that consumers vary in their impulse buying tendency (Beatty & Ferrell, 1998; Jones et al., 2003; Puri, 1996; Rook, 1987; Rook & Fisher, 1995; Rook & Gardner, 1993; Weun et al., 1998). Besides consumers shopping for a major trip, Bell et al. (2011) defined categories of fill-in trip shoppers, consumers shopping for meals on the same day, shopping for immediate consumption and consumers shopping for special offers or promotions.
After major trip shoppers, the consumers shopping for a fill-in trip show the highest percentage change in unplanned category purchases as a function of the overall shopping trip goal (when all other factors are held constant). The fill-in trips represent consumers shopping for ‘daily essentials’ and ‘topping up’; present a lift of 27% in unplanned buying. A trip receipt of consumers shopping for a fill-in trip show an average spending of €21.45. On average a receipt exists of 5.0 planned category purchases and 1.4 unplanned category purchases. Which means that the unplanned category purchases represent approximately €4.70 of an average receipt.
Shopping for meals on the same day, store-specific convenience, leads to 12% more unplanned buying. On the other side, general convenience with respect to a larger shopping plan reduces unplanned buying by a similar amount. Consumers shopping for special offers or promotions will give a negative change in unplanned buying, which is expected as well. These consumers specifically go to the supermarket to buy the special offers or promotions, are only focused on these products and will not be distracted by other (not) promoted products.
2.2 Display characteristics of price
Second part of the theoretical framework consists of the display characteristics of price. Retailers try to reach consumers by attracting them with for example in-store communications. Sale signs are an often used type of in-store communication. Sale signs are perceived as indication for reduced prices of products by consumers (Grover & Srinivasan, 1992). The effects of signaling promotions are further researched in the years after by Inman et al. (1990), Inman & McAlister (1993). They found that the effect of signs on products with and without discounts both increased sales, even the products without discounts. According to these studies it is proven that the effect of price indications without discounts help consumers to focus more on these products.
The effect of shelf talkers on the shelf, without price discounts, will be further explained in the next paragraph. Janiszewski (1988) studied the effect of different hemispheres on advertisements. Both, left and right hemispheres do have a different effect on processing information. Do these hemispheres also have a different effect on processing information of a shelf talker? More information of the different hemispheres can be found in the last paragraph of this chapter. Altogether this chapter will give insights in what display characteristics of price have an effect on consumers’ in-store behavior.
2.2.1 Shelf talkers
Very little information is available about shelf talkers, or its impact on consumers’ in-store behavior. There are no academic studies specifically studying the effect of shelf talkers. According to the Business Dictionary the following definition of a shelf talker is given: ‘Printed card or other sign attached to a store shelf to call buyers’ attention to a particular product displayed in that shelf’. Although less information is known about the shelf talkers, there is a lot of information known about effects of promotions on consumers’ in-store behavior. These results might be applicable on the concept of shelf talkers as well. Blattberg & Neslin (1990) define sales promotions as ‘action-oriented marketing event whose purpose is to have direct impact on the behavior of the firm’s customers’.
types of promotions, concluded sales signs without discount are likely to increase sales. Ailawadi et al. (2001) state that a substantial part of the marketing budget is spent on sales promotion. In the Netherlands 17.6% of food and drug retail sales are promoted sales (Symphony IRI, 2012).
Blattberg et al. (1995) found support for the negative long-term effect to promotions. Contrasting, shelf talkers without discounts might lead to positive (or zero) long-term effects, however these effects are not researched before. Nijs et al. (2001) partially support these findings, they found that price promotions have positive short term effect on category sales of 58% (37% no effect and 5% a negative effect). And on the other side, price promotions do have no effect (98%) on the long term (2% have a positive effect). These results can support predictions of a positive (or zero) effect of promotions without discounts on category sales. Nijs et al. (2001) researched how price promotions affect price image of brands; further research on these effects are useful for the effects of shelf talkers, without price promotions, on consumers’ perceptions of price.
It is expected that displays have a similar effect on consumers’ purchases than shelf talkers have. Inman et al. (2009) found that there is an positive effect of displays on unplanned purchases. Displays can trigger consumers generating unplanned purchases for product categories that are purchased relatively often. However, Inman et al. (2009) also found some factors that decrease the effect of unplanned shopping. Consumers shopping with a shopping list spend less on unplanned buying. Same accounts for the frequency of shopping, consumers shopping less frequently spend more on unplanned buying. The in-store behavior of consumers has an influence on the purchase behavior as well. When consumers spend a lot of time in the store, browse a lot and visit all aisles exposure will be increased, which will lead to more unplanned purchases. Something very different is the decision made before entering the store on how to pay: by credit or cash. When consumers decide to pay by credit, there will be less pain of paying, resulting in more spending.
Coming back to the displays their effects are perceived similar to that of shelf talkers, however the effects of shelf talkers will influence sales in lesser amount. In general can be concluded placing out-standing colors, displays, labels etc. in the shelves, consumers can be convinced to buy these products. Shelf talkers might have the same effect. Main effect of these promotions is switching between brands, though stock-piling plays an important role (Ailawadi et al., 2001). Stock-piling will not always be as profitable for manufacturers and retailers.
2.2.2 Informative and visual stimuli
Only using a shelf talker on the shelf in a supermarket is not enough; the message on the shelf talkers is way more important than using a shelf talkers itself. The message on the shelf talker can attract consumers to the shelf and convince them in buying the product. In general, Ward & Davis (1978) state that different types of point-of-sale (POS) materials have proven to effect consumers’ behavior. The attention of the consumer is necessary to sell the product to the consumer (Valenzuela & Chandon, 2009).
product categories. However, the purchase intention within a category during a shopping trip can be category dependent.
The way in which consumers are familiar or trust a stimulus results in the effect that consumers like the stimuli more (Zajonc, 1986). Fransen et al. (2010) did research on relating processing styles of consumers. They continue their research on that of Jacoby (1983); which distinguish two styles: driven and data-driven. The conceptually-driven processing style is known as the top-down processing; is focused on generating and elaborating information that is related to the stimulus. The conceptually-driven processing style is strongly based on existing schemes to form expectations of incoming information. On the other side, the data-driven processing style is known as bottom-up processing; based on detailed processing of superficial characteristics of a stimulus. This way of processing is mainly focused on recognizing and decoding a stimulus without directly giving a meaning to it. Fransen et al. (2010) conclude, based on their findings, that visual advertisements (compared to auditory advertisements) can be used best for products visually presented, for example in a supermarket. These results indicate that consumers don’t react similar to shelf talkers. Some consumers are more familiar with a product and will show more conceptually-driven processing, whether other consumers process more data-conceptually-driven for the same product in the shelf.
Finally, Janiszewski (1988) did research on the differences in effect of the left and right hemisphere of consumers related to processing information. They found that the left hemisphere supports text processing when seeing an advertisement. The right hemisphere supports picture processing in an advertisement. This research, focused on advertisements, is applicable for shelf talkers as well. Ellis & Miller (1981) suggest that some organizational formats are preferred over others. Janiszewski (1988) continue on their research and found that verbal information on the left side of the ad and pictorial information on the right side of the ad are preferred. It is likely that these differences are applicable on shelf talkers as well. However, position of the consumer within the shelf or supermarket is very important to define the left and right positions. These positions are defined through the recommended walking directions of consumers within the stores.
Altogether, several researches indicate that the effects of shelf talkers most likely are positive on consumers’ in-store behavior. It is supported that there is a difference between informative and visual stimuli; however which one will lead to higher effects needs to be supported within this research. Therefore, the following hypotheses will be tested:
H1: A shelf talker with informative stimuli lead to higher sales increases compared to no shelf talker.
H2: A shelf talker with visual stimuli lead to higher sales increases compared to no shelf talker.
2.3 Characteristics of product
This paragraph will address several product characteristics. Literature confirmed that in-store communications will obtain differing results for different type of products. In this research therefore a distinction is made in type of product which consists of Private Label (PL) and A-brand products. A second distinction is made in product category which consists of food and non-food product categories.
(PL/A-brand) and the product category (food/non-food). What is known about the effect of promotions with differences between PL and A-brand? And do consumers react different to promotions on food products than non-food?
2.3.1 Type of product
Private Labels (PL) in the fast moving consumer goods (FMCG) industry gained ground in recent years. Private label (PL) is defined as a store brand of a specific supermarket chain sold in the supermarket segment. In Western Europe the market share (MS) of Private Label products account for more than one on five items sold every day in supermarkets, drug chains and mass merchandisers (Kumar & Steenkamp, 2007). Western Europe presents the highest scores on PL shares over the world; nowadays PL sales will approximately account for one third of total sales (Kumar & Steenkamp, 2007). Luijten & Reijnders (2006) found that the market share of PL in major categories in the Netherlands increased. The market share of PL in supermarkets increased from 29.5 to 35.0% between 2003 and 2006 (Luijten et al., 2008). Most recent data of Symphony IRI (2011) state that the share of PL within the supermarket assortment accounts for 27.2% (excluding fresh except for dairy and Ready-To-Eat); the share of PL is still rising across Europe with an average value share of 35.6% and a unit share of 45.1% (Symphony IRI, 2012). The share of PL of food categories has increased in all countries across Europe in the past year but non-food is only increasing in the countries: the Netherlands, Italy and Spain (Symphony IRI, 2012). The United Kingdom has the highest country value share of PL in Europe with 50.5% (Symphony IRI, 2012). At the same time, the acceptance of PL brands by consumers increased last years; around the world two out of three consumers believe that ‘supermarket own brands are a good alternative to other brands’ (Kumar & Steenkamp, 2007). PL brands are particularly associated with price consciousness, low quality consciousness and store loyalty (Ailawadi et al., 2001). Many consumers discovered that the quality of PL brands was actually better than expected on beforehand, for example price conscious consumers in their student days or in less ideal economic times. Since then, consumers continued to regularly purchase PL products. Do marketers need to approach these price conscious consumers differently with in-store promotions? Or do they react the same as national brand (A-brand) buyers?
promotions than A-brand buyers have. A-brands are defined as national brands of a specific manufacturer sold in the supermarket segment. Besides, the involvement in type of product the amount of shelf space allocated to a product in relation to that of the total product category, positively affects product sales (Desmet & Renaudin, 1998). The amount of shelf space influences the choice consumers have to make between PL and A-brand products.
Sales promotions account for a substantial part of the marketing budget in packaged goods firms. Due to the increased MS of PL products the percentages changed, back in the nineties around 75% of marketing budget went to sales promotions (Ailawadi et al., 2001). More recently Luijten and Nagtzaam (2005) did research on the promotion effects for the product category toilet paper (dry); further investigated by Luijten et al. (2008). They found that the A-brands of toilet paper are almost continuously on promotion in some stores. As a result approximately 55% of their volume is realized under promotional conditions. On the other hand, Luijten and Van Heerbeek (2010) found in their research that sales promotions do not have the desirable effect of attracting more consumers. Besides, the effects of the Dutch price wars between 2003 and 2004 were, that due to price decreases overall price level of A-brands decreased by 11% (Sloot, 2011).
Ailawadi et al. (2008) did research on use of private label and store loyalty; they mainly discussed the differences between the two retail channels Albert Heijn (AH) and C1000. On the moment of research, AH (the flagship of Royal Ahold, one of the world’s largest grocery retailers) presented a MS around 27%, where C1000 accounts for 15% of the market. Comparing price and quality these supermarket chains are closely related. In general, AH stores are larger than C1000 stores, resulting in a deeper assortment for AH. Prices at AH are higher than C1000, supported by price data of Q2 and Q3 2012 of Supers (2012). However, PL plays a larger role in AH stores with 22.7% of the SKUs in a category compared to 16.8% in C1000 stores. In result, PL averages 42.1% of total purchases at AH versus 28.8% at C1000. Findings of Kumar & Steenkamp (2007) found a different PL share of 48% for AH; they didn’t studied the PL share of C1000. Luijten and Van Heerbeek (2010) developed a store choice model which measured the effect of promotions on different supermarket categories. They found that the model only showed significant effects of the promotions on all the product categories at the chains Albert Heijn and C1000.
important thoughts in the effect of shelf talkers on PL- and A-brands. Additional research prove that the effect of stockpiling and stockpiling-related consumption fulfill a more important role than was previously expected. They found that switching does account for the majority of the promotion’s effect (Ailawadi et al., 2001; Ailawadi & Neslin, 1998; Bell et al., 1999; Bucklin et al., 1998; Dillon & Gupta, 1996).
Ailawadi et al. (2001) divide consumers in three segments: PL-focused, A-brand focused and consumers with a very broad scope not specifically focused on one of the two. The PL-focused segment contains store-loyal, price-conscious customers; this group of consumers is not quality conscious and is neither a shopping expert nor a stockpiler. For this group it would be appropriate to stress the relatively consistently low PL price, which consequences that consumers do not need to stock up (Ailawadi et al., 2001). Many managers use a High-Low (HI-LO) price strategy or an Every Day Low Pricing (EDLP) strategy. The best strategy for PL-brands is a EDLP strategy, that is closely linked to the promoted price of A-brands. In contrast, A-brands actually benefit from a HI-LO strategy. Manufacturers of A-brands can use this strategy to price discriminate and compete with PL-brands for the consumers that buy both A- and PL-PL-brands (Ailawadi et al., 2001). If manufacturers of A-brands want to battle the PL-brands they can reach the consumers with price- and convenience-oriented messages and in-store displays designed to encourage impulsive purchases. However, there will always be segment of consumers that will always buy PL-products, even when the A-brand is on sale. These consumers are not impulsive, do not plan and do not stockpile. This segment seems inaccessible to the types of promotions commonly used by manufacturers of A-brands (Ailawadi et al., 2001).
In conclusion, the PL-brands benefit most of an EDLP strategy that is closely linked to the promoted price of A-brands (Ailawadi et al., 2001). Where A-brands on the other side benefit most of an HI-LO strategy; to price discriminate and compete with PL-brands. So, the shelf talkers might obtain larger effects on sales of A-brands than on PL-brands. Shelf talkers will not use sales promotions; however it could be that consumers do observe the shelf talkers as sales promotions. Even the consumers ‘normally’ buying PL-products might be convinced to buy an A-brand when confronted with a shelf talker on an A-brand. These predictions are concluded in the following hypothesis:
2.3.2 Product category
As mentioned before, Petty et al. (1983) state that consumers in different segments can be driven by different needs and have a different level of involvement with the product. Type of products can play a very important role in consumers’ behavior. This indicates that it might be important to look at the distinction between the different effects of shelf talkers on food and non-food products.
Bucklin and Lattin (1992) obtained useful insights in where consumers make decisions in buying promoted products. They define the three components of household response to promotional activities: store choice, category purchase incidence and brand choice. As described in section 2.1, once consumers made a store choice in-store communications start playing a role. Brand choice is closely linked to the category purchase incidence. Consumers first make a choice for a specific category followed by the brand choice. Relating the choice of category to the distinction made in food and non-food products; non-food products are characterized with lower rotations.
Research of Sloot (2011) states that food is mainly sold to consumers via three channels in the Netherlands: foodservice (e.g. catering, restaurants), specialty stores (e.g. bakery and butcher shops) and supermarkets. The dominant sales channel of Dutch consumers for food products is the supermarket with a food sales market share of 48%.
Consumer goods are available through several channels or retail formats. Inman et al. (2004) did research on the choice behavior at the highest level in the purchase decision tree: the selection of the channel. In specific, the associations between the channel and particular product categories. The grocery channel tends to be most closely associated with food items. Product categories associated with the grocery channel are characterized as products with a high category purchase frequency and a moderate category differentiation. These findings support research of Sloot (2011) stating that the dominant sales channel for food products is the supermarket channel.
When focusing specifically on the food product sold in a supermarket, Dhar et al. (2001) find four category roles. All food products sold in the supermarket are grouped on frequency of purchase and the percent of households buying the products (penetration). Dhar et al. (2001) defined the following four category roles: ‘staples’ score high on frequency and high on penetration; ‘niches’ score high on frequency and low on penetration; ‘variety enhancers’ score low on frequency and high on penetration; and fourth category ‘fill-ins’ score low on frequency and low on penetration. Some examples that Dhar et al. (2001) gave in their research of products within the categories are: ‘staples’ are Ready-To-Eat (RTE) Cereal and coffee, ‘niches’ are macaroni and cheese, ‘variety enhancers’ are pickles and rice, and finally ‘fill-ins’ are pancake mix and syrup.
In-store promotions will be most effective on fill-in categories and in lesser extent to variety enhancers and niches (Dhar et al., 2001). Main reason for the lower effect is caused by the smaller shelf spaces. Staple categories already have a significant shelf-presence; high increases in effect based on in-store promotions will be less likely. These findings mainly present the different effect within food product categories; and indicate that not all product categories will present the same effects when executing an in-store promotion.
Combining all results will give the following insights. When consumers enter a supermarket the choice of store is made. In-store category decision will be most important at that moment. Food products do have a higher rotation than non-food products, resulting in more visits of consumers to the shelf.
The grocery channel is most associated with food products. Thereby the dominant sales channel for Dutch consumers for food products is de supermarket. All findings suggest that in-store promotions will have a higher effect on food products than non-food products. Therefore the following hypothesis will be tested:
2.4 Conceptual model
The conceptual model will help answering the problem statement whether displaying price on a shelf talker will have an effect on consumers’ in-store behavior in different product categories. Sub questions explained in hypotheses 1 to 6, support answering the problem. In figure 5 below, the complete conceptual model will be presented.
Figure 5. Conceptual model
Display characteristics of price
Of price
- Informative stimuli - Visual stimuli
- No stimuli Consumers' in-store behavior
CHAPTER 3:
RESEARCH DESIGN
To test the hypotheses, data are collected through scanner data of the C1000 supermarket. This chapter gives an overview of the research method used in this study. Chapter 3.1 outlines the choice of research and type of experimental design. In chapter 3.2 is described how the data is collected. Final chapter 3.3 states the plan of analysis, which includes information about the databases and the tests in SPSS.
3.1 Research method
In this research, we investigate how consumers shopping in a supermarket respond to shelf talkers presented on specific shelves. Thereby the role of different types of shelf talkers and different product characteristics are tested. We obtained market share, product- and category sales data from a major Dutch supermarket store for 18 weeks. Our empirical analysis is conducted on 6 product categories, including food product categories (chips, chocolate sprinkles and biscuits) and non-food product categories (diapers, household cleaners and dishwashing detergent); within these categories both Private Label (PL) and A-brand products are tested. Our data is collected via product scanning at the check-outs of the supermarket; this data is automatically registered.
Consumers overestimate their willingness to pay for products (Ajzen et al., 2004), therefore the choice of a field experiment is made instead of a survey or interview for example. Our analysis is based on a field experiment using two types of shelf talkers: one with informative stimuli and one with visual stimuli. The informative stimuli are tested on the product categories: chips, household cleaners and chocolate sprinkles; the visual stimuli are tested on the product categories: biscuits, dishwashing detergent and diapers.
products that differ in their frequency of purchase. These findings are very useful for further research on the choice of food products to test on.
Research of Inman et al. (2004) identified product categories that are associated with particular channels based on category purchase frequency and category differentiation. By defining product categories for this research, studies of Inman et al. (2004) and Kuenzel & Musters (2007) are combined. However the list of these product categories was very large. Therefore it’s chosen to focus on preferred categories of the specific retailer only (ECR Europe, 1998). The product categories serving the role of preferred category at the C1000-chain are mainly the dry grocery products. The preferred category forms the bulk of the shopping basket of consumers; and account for 50-60% of sales. These products are part of the basic assortment of most retailers. Retailers compete on low prices and sharp promotions to be competitive within these categories.
In addition, research of Dhar et al. (2001) defined four category roles as explained in chapter 2.3.2: staples, niches, variety enhancers and fill-ins. The products in the category of fill-ins are most suitable for in-store promotions. The EFMI business school (2011) did several researches on the amount in which consumers plan brand purchases. They found strong differences across product categories. One of the results is that there are many chances for in-store marketing on the product categories of eggs, chips and detergents. With the choice of product categories these findings of previous studies are taken into account.
Besides the theoretical insights for the choice of product categories, the practical insights are very relevant as well. Listing all the product categories in the above mentioned studies resulted in 17 food product categories and 9 non-food categories. A checklist is made on several key requirements on the different product categories; this checklist can be found in appendix A.
types of flavors, brands and PL. Final requirement is very important for the additional effects on sales; the number of promotions within the weeks which will be tested. The product categories need to have at least two weeks without any promotions. That means no promotions on PL and no promotions on the A-brands. These promotions are known 5 to 6 weeks on forehand by the retailer. In conclusion, there are 6 food categories and 5 non-food categories that fulfill all requirements. In the final decisions, 3 categories for both, food and non-food are chosen to test on. These decisions are based on the highest rotations within the store, and on the locations within the store. This leads to the food categories: biscuits, chocolate sprinkles and chips. And the non-food categories: dishwashing detergent, household cleaners and diapers. On the basis of the recommended walking directions within the store three product categories (chips, dishwashing detergent and household cleaners) are located on the right side of the consumer and three product categories (biscuits, chocolate sprinkles and diapers) on the left sides.
3.2 Data collection
Our data comes from a major grocery retailer, a C1000 store, in Heino (near Zwolle, the Netherlands). The data represent this specific store only; the retailer has one physical store. The C1000 has a Hi-Lo (high-low) chain wide promotion policy. Besides the national strategy of the C1000 chain, local store owners have the freedom of making their own choices in assortment and promotions besides the national promotions and assortment that is supported by the headquarters.
the tasks (Jacoby & Hayman, 1983; Fransen et al., 2010; Roediger & Blaxton, 1987). Therefore the same font type is used to maintain consistency.
As mentioned before, there are two types of shelf talkers: one with visual stimuli and one with informative stimuli. The shelf talkers with visual stimuli consist of the base color red with the price labels. The gaps between the price labels are filled with brand logos of the brands presented in the specific shelf, see figure 6. In case of the PL products, the logo of C1000 is used.
Figure 6. Shelf talker biscuits Verkade with visual stimuli
Figure 7. Shelf talker household cleaners C1000 with informative stimuli
The shelf talkers are tested on six different product categories and spread over two test weeks. All the measures are tested within one test week: six categories, type of product (PL/ A-brand), product category (food/ non-food) and the type of shelf talkers (informative/ visual). Figure 8 presents the scheme in which all measures are tested.
Figure 8. Testing scheme
PL A-brand
Food Non-Food Food Non-Food
Informative
stimuli Chocolate sprinkles (wk1) Household cleaners (wk1) Chocolate sprinkles (wk2) Household cleaners (wk2) Chips (wk1) Chips (wk2)
Visual
without promotions. As described before, an overview of the presence of promotions can be found in Appendix A. Decision had to be made to test in week 40 and 42, because these two present only a small number of promotions. Although, the promotions let no choice for testing a couple of days in calendar week 43 (second part of C1000 week 42), this week will be the autumn holiday. However later in the year will the promotions and products be focused on ‘Sinterklaas’ and Christmas; this period will not be comparable with the weeks before because purchases will be much higher in this period.
3.3 Plan of analysis
Data of the specific weeks in which the hypotheses are tested will be provided by the headquarter of C1000. The collected data will be analyzed in IBM SPSS Statistics 19. Before entering the data in SPSS, the data needs to be redesigned. The original raw data of C1000 exists of a couple of columns like weeks/subgroup/article/number/brand/description/ volumes/prices; both volumes and prices are available including and excluding promotions. The raw dataset of C1000 must be redesigned to a useful database for the hypotheses. One of the changes in the database is the definition of the category. In this research are categories defined based on positions in the shelf, C1000 uses a broader definition of the category. Consequently, certain brands and SKUs (stock keeping units) need to be deleted from the database. Besides the category definitions, two important changes in the database are the selling price and sales column. The selling price is based on the original database of C1000 combined with promotional prices; these can be found in sales leaflets of the testing period. Prices are based on a reference date, in this case a Saturday because that they will provide the most useful data (most hits). These prices are based on regular prices in the C1000 Heino (no national prices). Then the sales column is calculated by multiplying the selling price with the volume including promotions. With the addition of these new columns and the new category definitions is the database ready to use.
To test the hypothesis in SPSS a complete dataset is required. Market shares and average prices per brand need to be defined, same as the dummy variables for type of product and product category. The market shares are calculated for one brand (e.g. Verkade) within the subcategory (e.g. biscuits) per testing week.
the tested brand (e.g. within chips: Lays and C1000). For hypothesis 2 the same tests will be provided for the visual stimuli.
CHAPTER 4:
RESULTS
In this chapter, the results from the analysis will be presented accompanied by the interpretations of these results. The results will give insights in our main hypothesized relationship between display characteristics of price and consumers’ in-store behavior. This chapter will start with general findings of this study and sample. Followed by the results of the linear regressions; the most important SPSS output findings of the analysis can be found in figure 14. Final subchapter shows a summary of the results; the summary of results will give insight in whether or not the hypotheses are supported by the analyzed data.
4.1 Sample
The sample of this research consists of all purchases at C1000 Vd Worp in Heino within the testing week. The testing period starts in week 27 2012 and ends in week 44 2012. In addition, only the purchases of the six product categories are measured in this research.
Figure 9. Number of SKUs in the shelf
Figure 10. Number of facings and shelves per tested category
Category Number of facings Number of shelves
Biscuits PL 10 2 A-Brand 9 2 Chocolate sprinkles PL 20 2 A-Brand 20 2 Chips PL 12 2 A-Brand 13 3 Diapers PL 12 4 A-Brand 12 3 Dishwashing detergent PL 10 1 A-Brand 11 1 Household cleaners PL 8 1 A-Brand 8 1
25
38
11
15
19
18
0 5 10 15 20 25 30 35 40 Biscuits Chocolate sprinklesChips Diapers Dishwashing
detergent
Household cleaners
4.2 Hypothesis testing
In this paragraph, the results of the hypotheses will be presented. As described in chapter three, all hypotheses will be tested with linear regressions. The results of the tests will be discussed per hypothesis.
With the first hypothesis the relationship between a shelf talker with informative stimuli and sales increases are tested compared to sales increases without any shelf talker. The second hypothesis will test the same relationship but then for visual stimuli on the shelf talker compared to no stimuli. Figure 11 shows the hypothesis as presented in the conceptual model.
Figure 11. Hypotheses 1 and 2 in the conceptual model
Before looking at the results derived from SPSS an analysis on the raw data from C1000 is provided. The promotional and non-promotional data will be shown during the 18 testing weeks. Therefore, the lift percentages can be calculated. The lift percentages are calculated by dividing the number of products sold in the week with the shelf talker by the average number of products sold in the period before the week with the shelf talker (week 27 to 39). Figure 12 and 13 present the graphs with promotional and non-promotional data; the lift percentages are written under the graphs.
Some conclusions based on the lift percentages will be that the food categories sell much more than non-food categories. Thereby does the PL-category show higher lift percentages (on average +1.17) than the A-brand (most of the time no uplift) categories do (except for the chips category; PL+1.01 and A-brand +1.05). And the product categories with informative stimuli on the shelf talkers score slightly better (4 categories do give an uplift of +1.07 on average) than the visual stimuli (only 3 give an uplift of 1.26 on average).
Figure 12 A to F. Promo/ non-promo data
Legend:
12A. Lift +1.35 12B. Lift +1.17
12C. Lift +1.06 12D. Geen lift
12E. Lift +1.01 12F. Lift +1.05
Figure 13 A to F. Promo/ non-promo data
Legend:
13A. Lift +1.27 13B. Geen lift
13C. Geen lift 13D. Geen lift
13E. Lift +1.14 13F. Geen lift
However, the results based on the lift percentages are not proven significant. Therefore, further analysis will go in depth on the statistical outputs. The most important results of the SPSS analysis can be found in figure 14. First, the results of hypothesis 1 will be discussed.
H1: A shelf talker with informative stimuli lead to higher sales increases compared to no shelf talker.
Hypothesis one is tested per category per brand. The shelf talker with informative stimuli is tested on the three categories: chips, chocolate sprinkles and household cleaners. The R2 shows the variability in market share that can be accounted for the differences in
shelf talkers (informative versus no shelf talker). The PL chips category shows 37.4% of variance and the A-brand (Lays) category of chips presents 25.6% of variance. Chocolate sprinkles present variances of 0.2% for PL and 2.7% for A-brand (De Ruijter). Last category are the household cleaners PL presents 47.3% in this category and A-brand (Ajax) 3.9%. All categories show variances in the market share that can be accounted for the differences in shelf talkers. Figure 14 presents more specific details about the variances, significances and coefficients.
In addition, the ANOVA test gives insights in the significance of the R2. Results of the
ANOVA test show that only the PL brands in the categories chips and household cleaners show significant differences in the variances; respectively with a confidence level of 95% and 99%. Based on these results can be concluded that hypothesis one is partially accepted. The shelf talker with informative stimuli lead significantly to higher sales increases compared to no shelf talker for the PL categories of chips and household cleaners.
H2: A shelf talker with visual stimuli lead to higher sales increases compared to no shelf talker.
The R2 of the visual stimuli shelf talkers are much higher than the variances of the
informative stimuli shelf talkers. The PL-brand in the biscuits category presents 1.6% of variance. The A-brand (Verkade) in the biscuits category presents even a variance of 46.1%. The variances in the category of dishwashing detergents are respectively 31.0% for PL and 52.0% for the A-brand (Dreft). Last category is the one of diapers; PL presents 49.0% variance and A-brand (Pampers) 19.5%.
Figure 14: Overview of results per hypothesis
Significance: *p<.10; **p<.05; ***p<.01.
NS: no stimuli; IS: informative stimuli; VS: visual stimuli.
NA: not available – price is constant and does not show changes in the testing period. Therefore, the regression can’t be measured for this variable.
Hypothesis Category Brand R2 Anova-p Constant
In the first two hypotheses the display characteristics of price are tested: informative and visual stimuli compared to no shelf talker. The following hypotheses will test the differences in product category on which these shelf talkers are tested. Starting with the type of product; hypothesis three tests the relationship between shelf talkers on PL brands and on A-brands. Figure 15 shows the hypothesis as presented in the conceptual model.
Figure 15. Hypotheses 3 and 4 in the conceptual model
H3: Shelf talkers on A-brands lead to higher sales increases than shelf talkers on PL-brands.
Hypothesis three is tested over all six categories (biscuits, chocolate sprinkles, chips, diapers, household cleaners and dishwashing detergent) and all brands (PL and A-brand). First the R2 of both categories are checked. The R2 shows the variability in market share that
can be accounted for the differences in type of product (PL versus A-brand). The R2 is higher
for the Private label product categories than for the A-brand product categories. 2.9% of the variances can be accounted for the differences in type of product in the A-brand category; compared to 7% of variance in the PL category.
The ANOVA test explains the significance of the variability in type of product. The results show no significance for the A-brand product categories. However, the PL categories are proven significant with a confidence level of 95%. Hypothesis three will be rejected; the results do not support the relationship. However, the opposite effect is proven significant. The shelf talkers on PL-brands lead to higher sales increases than shelf talkers on A-brands.
H4: Shelf talkers on food products lead to higher sales increases than shelf talkers on non-food products.
The final hypothesis tests the relationship of the product category (food versus non-food). Again all product categories are tested, the food category consists of the product categories: biscuits, chocolate sprinkles and chips. The non-food category consists of the product categories: diapers, household cleaners and dishwashing detergents. The R2 of both
categories are tested again. For the food categories can 0.1% of the variance be explained by the differences in product category (food versus non-food), where in the non-food category 11.0% of the variance can be explained by the differences in product category.
However, the variances of the food category are not proven significant. On the other hand, the variances in the non-food category are significant; with a confidence level of 99%.That means that hypothesis four is rejected. However, the opposite effect is proven significant. Shelf talkers on non-food products lead to higher sales increases than shelf talkers on food products.
4.3 Overview of results
Before continuing with the general conclusions of this research the main results will be presented in the overview below, see figure 16.
Figure 16: Acceptance of hypothesis
Accepted Rejected H1 A shelf talker with informative stimuli lead to higher sales
increases compared to no shelf talker. * H2 A shelf talker with visual stimuli lead to higher sales
increases compared to no shelf talker. * H3 Shelf talkers on A-brands lead to higher sales increases than
shelf talkers on PL-brands.
H4 Shelf talkers on food products lead to higher sales increases than shelf talkers on non-food products.
CHAPTER 5:
CONCLUSIONS & RECOMMENDATIONS
The last chapter of this research, the conclusions, will obtain further insights in the results as presented in chapter 4 combined with the findings of the literature study as presented in chapter 2. In the conclusions, the recommendations for C1000 Vd Worp and other retailers and manufacturing companies will be presented. After the conclusions of this research, the limitations and implications for further research will be discussed.
5.1 Discussion
The main objective of this study was to examine the effect of shelf talkers on consumers’ in-store behavior. Thereby, the following problem statement was defined:
“What is the effect of displaying price on a shelf talker on consumers’ in-store behavior for different types of products and in different product categories?”
The first relationship between display characteristics of price and consumers’ in-store behavior is tested in hypotheses 1 and 2. Literature study suggests that shelf talkers with informative and visual stimuli both give a higher effect on sales increases than no shelf talker. These suggestions are supported with findings of this research. However, the suggestions are not proven for all product categories. The results show that the shelf talkers only obtained significantly higher sales increases for the categories with informative stimuli on the shelf talkers: PL chips and PL household cleaners; and the visual stimuli on the shelf talkers: PL diapers, PL dishwashing detergent, A-brand biscuits and A-brand dishwashing detergent. That means that the shelf talkers obtained more significant sales increases with the visual stimuli on the shelf talkers (four categories) compared to the informative stimuli (two categories). One of the reasons for the sales increases in the category diapers might be explained by a news item just before the testing weeks. A factory of sub-fabrics for diapers in Japan that accounted for 20% of the diapers market exploded (NU.nl, September 30th
2012). It might be that consumers responded based on the news by stockpiling diapers in the weeks after. However, significant sales increases are only measured in the PL category and not in the A-brand products.
research suggest that visual stimuli on shelf talkers lead to higher sales increases than informative stimuli on shelf talkers do. However, we must keep in mind that not all product categories lead to higher sales increases when presented with a visual stimuli shelf talker.
Second part of this research consists of the differences among type of product (PL versus A-brand product categories) in the relationship between the use of shelf talkers and consumers’ in-store behavior. In chapter two, theory suggested that shelf talkers will lead to higher sales increases on A-brands than on PL-brands. In this research, the hypothesis of higher sales increases for A-brands compared to PL brands is rejected. However, the opposite effect of higher sales increases for PL-brands compared to A-brands (not hypothesized) is proven in this research. One reason can be that the theory is not interpreted correctly. Ailawadi et al. (2001) suggest that A-brands benefit most of an HI-LO strategy to price discriminate and compete with PL-brands. The supermarket in which the hypotheses are tested has a HI-LO strategy. Based on Ailawadi et al. (2001) and other theories (see chapter 2.3.1) is concluded that shelf talkers on A-brands lead to higher sales increases than on PL-brands. The lack of information about shelf talkers might result in incorrect hypotheses. It might be that results in the use of displays or other sales materials do not account for the same effects in sales increases as for shelf talkers.
