IsraelssonRingborg_Sales Promotions in the Swedish Lifestyle Category
1. Sales Promotions in the
Swedish Lifestyle Category:
An evaluation of promotional effects
DAVID ISRAELSSON
EDWARD RINGBORG
Master of Science Thesis
Stockholm, Sweden 2014
2. Sales Promotions in the Swedish Lifestyle Category:
An evaluation of promotional effects
David Israelsson
Edward Ringborg
Master of Science Thesis INDEK 2014:80
KTH Industrial Engineering and Management
Industrial Management
SE-100 44 STOCKHOLM
3. 3
Master of Science Thesis INDEK 2014:80
Sales Promotions in the Swedish Lifestyle
Category: An evaluation of promotional effects
David Israelsson
Edward Ringborg
Approved
2014-06-10
Examiner
Anna Wahl
Supervisor
Johann Packendorff
5. 5
Abstract
In recent years, a secular change in how marketers communicate with its consumers has
been observed within the Fast-Moving Consumer Goods (FMCG) industry; sales
promotion is now a key driver of marketing expenditure. To retain competitiveness
industry incumbents need to accurately measure and evaluate the promotional effects in
order to develop an efficient future marketing strategy. This also holds for the Swedish
Lifestyle Category β a former niche products market β that has been experiencing a
massive growth due to the current health trend. In this paper, the Swedish Lifestyle
Category is linked to the two theoretical frameworks; FMCG industry challenges and
evaluation of sales promotions. In particular, a customized model framework for
measuring sales promotions based on store sales data is developed through a case study
of a large Swedish Lifestyle manufacturer. Data was collected through both qualitative
and quantitative methods to increase quality of research. Results suggests that the
Swedish Lifestyle category in general behaves as other FMCG categories on the topic of
statistically significant price promotion effects and decomposition across cross-brand,
cannibalization and category expansion effect. However, no consistent pre- and post-
promotional patterns were found, which implies that Lifestyle consumer behavior holds
a particular set of characteristics. It was also found that there are large statistically
significant asymmetries of promotional effect across distribution channels, product types
and brands. The results imply that managers should direct extra attention to adapting
sales promotions to the particular setting (i.e. brand, product and dist. channel) along
with including these asymmetries in estimating return of investment.
Key words: sales promotion, Lifestyle Category, price promotion, promotional response,
evaluation model, decomposing promotions.
6. 6
Acknowledgement
This master thesis is the final examination within our Masterβs programme in Industrial
Engineering and Management at the Royal Institute of Technology (KTH) in Stockholm,
Sweden. The master thesis corresponds to 30 ECTS credits and the research has been
conducted between January 2014 and June 2014. Our supervisor was Johann
Packendorff (Associate Professor at the department of Industrial Engineering and
Management at KTH) whom we would like to thank for his great support and feedback
through the course of this study.
2014-06-10, Stockholm
David Israelsson Edward Ringborg
8. 8
Table of Contents
Introduction and Background.................................................................................15
Β
1
Β Introduction ......................................................................................................17
Β
1.1
Β Introduction and Background ....................................................................17
Β
1.2
Β Purpose and Research Questions ............................................................18
Β
1.3
Β Structure of the Master Thesis ..................................................................18
Β
Methodology.............................................................................................................21
Β
2
Β Methodology.....................................................................................................23
Β
2.1
Β Research process .....................................................................................23
Β
2.2
Β Underlying perception of knowledge .........................................................23
Β
2.3
Β Pre-Study ..................................................................................................24
Β
2.4
Β Case Study as research design ................................................................25
Β
2.5
Β Model Development ..................................................................................27
Β
2.6
Β Analysis and Conclusions .........................................................................28
Β
2.7
Β Delimitations..............................................................................................28
Β
2.8
Β Limitations .................................................................................................29
Β
2.9
Β Quality of research ....................................................................................29
Β
2.10
Β Summing up ............................................................................................30
Β
3
Β Model Development .........................................................................................31
Β
3.1
Β Introduction................................................................................................31
Β
3.2
Β Data description and selection ..................................................................31
Β
3.3
Β Approach to modeling own-brand sales....................................................32
Β
3.4
Β Contextualizing and Decomposing Sales Promotion Effect ......................35
Β
3.5
Β Summing up ..............................................................................................40
Β
Literature review ......................................................................................................43
Β
4
Β Introducing the Fast-Moving Consumer Goods Industry..................................45
Β
4.1
Β Introduction................................................................................................45
Β
4.2
Β Fast-Moving Consumer Goods .................................................................45
Β
4.3
Β Summing up ..............................................................................................47
Β
5
Β Sales Promotions .............................................................................................48
Β
5.1
Β Introduction................................................................................................48
Β
5.2
Β Sales Promotions ......................................................................................48
Β
5.3
Β Psychological factors.................................................................................53
Β
5.4
Β Sales Promotion Models ...........................................................................58
Β
5.5
Β Summing up ..............................................................................................63
Β
Swedish Lifestyle Category Overview ...................................................................67
Β
6
Β The Lifestyle Category and Case Study Object Observations .........................69
Β
6.1
Β About the Swedish Lifestyle Category.......................................................69
Β
6.2
Β Case Study Object Observations ..............................................................72
Β
Empirical Findings and Results..............................................................................77
Β
7
Β Evaluating promotional efficiency.....................................................................79
Β
7.1
Β Introduction................................................................................................79
Β
7.2
Β Promotional observations..........................................................................79
Β
7.3
Β Brand Sales Effects from Price Promotions ..............................................81
Β
7.4
Β Lead and Lagged Effect on Price Promotions...........................................83
Β
7.5
Β Decomposed Promotional Effects.............................................................83
Β
7.6
Β Cross-category result generalization.........................................................87
Β
7.7
Β Relationship between item market share and price promotional effect.....89
Β
7.8
Β Base Line Sales response to promotions..................................................91
Β
7.9
Β Summing up ..............................................................................................91
Β
9. 9
Analysis and Conclusion ........................................................................................93
Β
8
Β Analysis of Promotional Effect .........................................................................95
Β
8.1
Β Significant Effects of Price Promotions .....................................................95
Β
8.2
Β No statistically significant patterns for lead and lagged effects.................96
Β
8.3
Β Introducing to generalized category of findings.........................................97
Β
8.4
Β Promotional responsiveness primarily linked to brand size ......................97
Β
8.5
Β Distribution channel impact on promotional effect ....................................98
Β
8.6
Β Decomposition varies across product and distribution channel ................98
Β
8.7
Β No increased base line sales but possible underlying effects...................99
Β
8.8
Β Model application in practice...................................................................100
Β
8.9
Β Summing up ............................................................................................101
Β
9
Β Conclusion .....................................................................................................102
Β
9.1
Β Conclusion...............................................................................................102
Β
9.2
Β Managerial implications...........................................................................104
Β
9.3
Β Critical discussion....................................................................................104
Β
9.4
Β Suggestions for future research ..............................................................105
Β
Bibliography ...........................................................................................................107
Β
Appendix.................................................................................................................117
Β
10. 10
Table of Figures
Figure 1. Illustration of the Research Process ...........................................................23
Figure 2. Integration of different Data Sources ..........................................................28
Figure 3. Illustration of Model Framework process. ...................................................31
Figure 4. Primary components for modelling sales....................................................33
Figure 5. Decomposition of a βsales bumpβ following a sales promotion...................35
Figure 7. Illustrating the Literature review based Narrowing of the Scope ................45
Figure 8. Sales Promotion orientation. Source: Shimp, 2008 ....................................48
Figure 9. Illustration of Sales promotional targets. Source: Shimp (2008).................50
Figure 10. Promotions between Manufacturers, Retailers and Consumers ..............51
Figure 11. Framework for understanding consumer behaviour .................................54
Figure 12. Influences on consumer purchasing behaviour ........................................56
Figure 13. Retail Sales following promotions.............................................................61
Figure 14. Factory Shipments following promotions ..................................................62
Figure 15. Relationship between promotion targets. Source: Blattberg and Levin (1987).63
Figure 16. Sub-category split for the total Swedish Lifestyle Category......................70
Figure 17. Swedish Lifestyle Category split between manufacturers ........................71
Figure 18. Top 10 Brands within the Swedish Lifestyle Category..............................70
Figure 19. Purchasing pattern for Weight Control 2013.............................................73
Figure 20. Illustration of the Case Study Object Sales Promotion process ...............74
Figure 21. Own-Brand Sales for Brand 1 in item class Bar for Chain 1.....................79
Figure 22. Own-Brand Sales for Brand 1 in item class Bar at Store 9.......................80
Figure 23. Total Category Sales for item class Bar at Store 9...................................80
Figure 24. Scatter plot of relation between market size and promotional effect ........89
Figure 25. Base Lines Sales plot for Brand 1 Bar......................................................90
Figure 26. Base Line Sales plot for Brand 1 Shake ...................................................90
Figure 27. Base Line Sales plot for Brand 1 RTD......................................................90
11. 11
Table of Tables
Table 1. Description of selected store-level data for analysis....................................32
Table 2. Price promotion promotions for Brands across Item Class..........................81
Table 3. Results of promotional effects on Brand 1 ...................................................82
Table 4. Lead and lagged effects on Brand 1 ............................................................83
Table 5. Cross-category decomposition effect for Brand 1........................................85
Table 6. Store-level decomposition effect for Brand 1. ..............................................86
Table 7. Average estimates for Cross-Category decomposition effects for Brand 1. 86
Table 8. Average estimates for Store-level decomposition effects for Brand 1. ........87
Table 9. Cross-Category decomposition effects for all category brands. ..................88
Table 10. Average Cross-Category decomposition of effects for all category brands. 89
Table 11. Average effects over distribution channels for all category brands............89
12. 12
Table of Terminology
Cannibalization Negative impact of a companyβs new product on the sales
performance on existing products
Category Generic classification of products or services. May be
narrowly or broadly defined
Category Expansion Incremental sales for some predefined category. Measured
through observing Total Category Sales over time
Consumer In this study of a manufacturer, the consumer is referred to as
the end-consumer
Cross-Brand Sales Sales of brands other than the own-brand (focal brand) item
Fast-Moving
Consumer Goods
Industry consisting of a broad range of retail products
characterised by being sold at low cost and being replaced or
fully consumed over a short period of time
Focal Item A selected item of study. Used interchangeably with βOwn-
Brandβ unless stated otherwise
Lifestyle Category Health nutrition retail products. Sub-categories are; weight
control, performance, vitamins/minerals, fish oil, cold,
stomach and other lifestyle
Nielsen One of the worldβs largest collectors of market data
Own-Brand Sales Sales of a selected focal brand within a predefined category
Point-of-Sale The point where the sale is registered. In other words, when it
passes the store cashier
Price Promotion A price offer limited to a short period of time
Promotion Short for βsales promotionsβ unless stated otherwise
Promotional Effects The observed effect following a promotion. Often sales
volume receives most attention
Psychographic It is the study of personality, values, opinions, attitudes,
interests, and lifestyles
Regression Analysis Statistical process for estimating relationship between a
number of variables
Sales Promotion Refers to any incentive used by manufacturer, retailer or
service provider in order to stimulate changes in brand
perception and value temporarily
Segmentation The process when determining a target group. E.g. who buys
the product or service?
Structural Data In this study it comprises of holidays and TV-advertising
13. 13
Table of Abbreviations
ACS Average Category Sales
ADS Advertising
CBPI Cross-Brand Price Index
CBS Cross-Brand Sales
DIST Distribution
FMCG Fast-Moving-Consumer-Goods
GT Grocery Trade
HOLID Holidays
HPCT Health and Personal Care Trade
KPI Key Performance Indicator
OBC Own-Brand Cannibalization
OBCPI Own-Brand Category Price Index
OBS Own-Brand Sales
PI Price Index
POS Point-of-Sales
RTD Ready to Drink
ST Service Trade
TCS Total Category Sales
TCPI Total Category Price Index
15. 15
Introduction and
Background
In this section, an introduction to the
studied subject, the underlying problem
and the purpose of the study will be
presented. Finally the structure of this
Thesis will be described and visualized.
17. 17
1 Introduction
1.1 Introduction and Background
Competitiveness in the Fast-Moving Consumer Goods (FMCG) industry is hard to maintain
given an environment of highly flexible consumer demands due to a rapidly changing competitive
landscape (Iglesias et al., 2011, Kitchen, 1989). Moreover, to maintain competitiveness and high
profitability in any competitive market, evaluation of sales promotion activities is a cornerstone
to boost companiesβ performance (Abraham and Lodish, 1987, Blattberg and Neslin, 1990,
Neslin, 2002, Rao, 2009, Wierenga, 2008, Valette-Florence et al., 2011, Kotler and Armstrong,
2013). However, these two theoretical frameworks have not, to our knowledge, been investigated
within the Swedish Lifestyle Category context.
The term FMCG industry refers to broad range of retail products characterised by being sold at
low cost and being replaced or fully consumed over a short period of time (Keller, 2003). In this
sense, FMCG companies need to be flexible in order to adapt to market dynamics. Retaining a
good flexibility to encounter the constantly changing competitive landscape consequently leads to
capturing as much market share as possible whilst building brand equity (Kitchen, 1989, Cravens
et al., 1991, Keller, 2003, Iglesias et al., 2011). In doing so, striving for high sales volumes at all
times is of great importance. Therefore, marketers employ a number of strategic tools within the
marketing mix to boost sales through stimulating end-consumer purchasing. Advertising and
Sales Promotions are two of the most prominent marketing tools used by practitioners (Kotler
and Armstrong, 2013).
In recent years a secular change in how organizations communicate with its customers and
business environment has been observed. Traditionally, advertising (e.g. TV and direct-media) has
been the most prominent marketing communication tool. Historical averages shows that roughly
70% of U.S. marketing expenditures were accounted for by advertising. (Shimp, 2008, Kotler and
Armstrong, 2013) Nowadays, for an average company within the consumer-packaged goods
sector, sales promotions (i.e. short-term sales incentives) accounts for around 77% of marketing
expenditures (Wierenga and Soethoudt, 2010, Kantar Retail, 2010). This shift towards sales
promotions is increasing demands on increased understanding in order to being able to properly
evaluate these activities and determine return of investment (Schultz and Block, 2011). Measuring
the promotional effects is however a complex matter and has been highlighted as a frequent
problem for marketers (Kotler and Armstrong, 2013, Wittink et al., 1987, Neslin, 2002, Wierenga,
2008). Following the global health trend observed over the last decade, extra focus has been
directed towards the Lifestyle Category. The Lifestyle Category β e.g. weight control, vitamins &
minerals and sports nutrition products β is therefore on the rise (Nielsen, 2012, Nielsen, 2014b).
In Sweden, this category has been a small niche market based on entrepreneurial spirit where the
massive growth now exerts new demands on industry players following increased competition.
The scope of this study will therefore be to investigate the sales promotional response within the
Swedish Lifestyle Category and addressing the issues on measuring and evaluating the
promotional outcome. The theoretical contribution will be bridge between the Swedish Lifestyle
Category issues from being a fast-growing industry and the two theoretical frameworks of FMCG
industry challenges and the complexity surrounding measurement and evaluation of sales
promotions respectively.
18. 18
1.2 Purpose and Research Questions
The purpose of this study is to examine the effects in store sales created due to sales
promotions. In doing so, a framework for measuring the underlying sources of the
promotional effects needs to be developed. The research questions this study will try to
answer are:
! How would it be possible to measure the effects of sales promotion activities and
understand the promotional effect characteristics evaluated at store-level within the
Swedish FMCG Lifestyle Category?
o What would be a practically applicable model for capturing and measuring
the sales promotional effects, specifically for the Lifestyle Category?
o What are the imminent effects of sales promotions within brand, across
item classes and distribution channels?
o How do the category brands behave in terms of temporal shifts in sales, i.e.
pre- and post-promotional effects?
o For any observed sales promotional response effect, how can this be
derived from the research based decomposed factors; own-brand
cannibalization, cross-brand sales and category expansion?
1.3 Structure of the Master Thesis
The paper consists of six chapters. The paper
begins with an introduction and background to
the subject of this study. The chapter of
methodology is divided into two parts; the first
part describes the methodology and methods
and the second part is about delimitations,
limitations and quality of research. Next chapter
is closely related to the methodology chapter
and describes the model development.
Furthermore, an opaque literature review is
presented, introducing vital concepts, theories
and earlier research regarding the area examined.
After that, collected data from interviews and
research is presented. In this chapter, the
industry and how the company is using sales
promotions to stimulate the end-consumer to
purchase the products is described. Moreover,
empirical findings and results will be presented
regarding the effects of price promotions.
Finally, Analysis and Conclusions are presented.
21. 21
Methodology
The methodology section is divided into two
blocks. First, our research methodology is
thoroughly described along with a critical
discussion. Secondly, a model framework is
developed. This is later used to evaluate
sales promotions based on Lifestyle
Category sales data.
23. 23
2 Methodology
2.1 Research process
The research process consisted of approximately 20 weeks of work. The core of the
process was a solid case study consisting of both a qualitative and a quantitative approach.
As Figure 1 illustrated, the research process involved four sub- categories; a Pre- Study, a
Case Study, Model Development and finally Analyses and Conclusions. Parallel to these steps the
report was constantly written on.
Figure 1. Illustration of the Research Process
2.2 Underlying perception of knowledge
In the process of answering the research questions of this paper, the tools being used are
those often associated with a positivistic approach. This is based on many conclusions are
drawn out of empirical data. Positivistic approach is one of two approaches within
epistemology. Epistemology is often described as the doctrine of what knowledge is and
what separates knowledge from opinions. The other approach, the antithesis of the
positivistic view, is the interpretivistic view (Collis and Hussey, 2009). However, using
positivistic methods throughout the process of this research, the researchers maintained
the view of this research being mainly an interpretivist-based approach. The researchers are
aware that the subjective opinions and previous knowledge will affect the research even
though it is unintentional. Of course, the goal is to strive remain as objective as possible.
The opinion is that the researchersβ own perceived worldview is affecting the research in
two ways; first, since the research questions are constructed from the Pre-Study findings,
there is a risk that the Case Study objects are being influenced by the researchersβ opinions.
Second, there is a possibility that the researchers of this paper interpret the results from
residual cognitive realty following the experiences and knowledge gained throughout the
Pre-Study and time spent on-sight with the study object. It is almost impossible not being
24. 24
influenced in such an exposed context. Therefore this Master Thesis will embrace
perceptions from both a positivistic- and interpretivistic view. Hence, Sales Promotions
will be measured through a quantitative tool followed by objective results. On the other
hand, methods when forming the research questions and through the process of analysis
are possibly influenced by an interpretivistic point-of-view. This is an aspect being included
in critical evaluation of the research process and methodology related to reliability and
validity on this. The critical evaluation will be discussed more in detail in section 2.9. In this
Master Thesis the researchers are having a worldview fitting to the view of constructivism,
in a sense that organizations and cultures are believed to be affected by individuals and
therefore constantly changing. In contrast to believing organizations are independent units
affecting individuals (Bryman and Bell, 2003).
2.3 Pre-Study
The overall research question being developed after the pre-study was; how would it be possible
to measure the effects of sales promotion activities and understand the promotional effect characteristics
evaluated at store-level within the Swedish FMCG Lifestyle Category? To concretize the scope, the
research question has been divided into more precise and concrete questions. To be able to
address and answer these questions it is crucial to choose and apply the most appropriate
methodology and methods.
As a first step within the research process a Pre-Study took place. The Pre-Study was
important in the sense that it helped to gain access to knowledge regarding the study object.
This in turn led to selecting a relevant case, access to data and possibility to conduct the
analysis. Initially a preliminary scope was defined. However, throughout the course of the
research it was naturally being redefined to increase the depth and accuracy of the study. The
first step was to investigate the overall topic of an FMCG Sales force issues and as a causality
of the selected study object, focus of study was directed at the Lifestyle Category.
The Pre-Study contained a number of interviews and observations with employees within a
range of functions. It was also a deliberately choice to spend as much time as possible on-
sight with the company. This choice was made since it was the researcherβs philosophy that
this would prove the most efficient way to fundamentally understand the business
environment. This in turn was considered vital in order to make any kinds of theoretical
conclusions. Thanks to that it was possible to get a deeper insight and knowledge regarding
the employees, the business and its processes. With the knowledge gained from the Pre-
Study in combination with previous research the contextualization started to take form. The
contextualization obliged as a foundation for the Case Study where decision regarding what
would be analyzed or not. After the Pre study the research questions had been developed:
! How would it be possible to measure the effects of sales promotion activities and
understand the promotional effect characteristics evaluated at store-level within the
Swedish FMCG Lifestyle Category?
o What would be a practically applicable model for capturing and measuring
the sales promotional effects, specifically for the Lifestyle Category?
o What are the imminent effects of sales promotions within brand, across
item classes and distribution channels?
25. 25
o How do the category brands behave in terms of temporal shifts in sales, i.e.
pre- and post-promotional effects?
o For any observed sales promotional response effect, how can this be
derived from the research based decomposed factors; own-brand
cannibalization, cross-brand sales and category expansion?
2.4 Case Study as research design
After careful deliberation the choice was made to embrace the research methodology β a Case
Study. Case studies are used to develop a good understanding of the contextual issues (Collis
and Hussey, 2009), i.e. the implications for measuring the effects of sales promotions. This
research approach covers the relevant aspects of both qualitative and quantitative data under the
study object umbrella. This approach also fits the overall research design in a good manner
because when doing a case study you explore a single phenomenon in a natural setting using
different methods to gain deep knowledge (Collis and Hussey, 2009). This research
investigate and try to address how to optimise measures of effects when using sales
promotions. This implies that a certain depth of knowledge is needed and therefore a case
study is a highly relevant and suitable choice to meet this. When conducting a case study five
steps are usually being used. These are; (1) selecting a case, (2) preliminary investigations,
(3) data collection, (4) data analyses and (5) writing the report (Collis and Hussey, 2009).
Selecting a case β how would it be possible to measure the effects of sales promotion activities and
understand the promotional effect characteristics evaluated at store-level within the Swedish Lifestyle Category?
From the Pre-Study part of the research period, the research questions were defined. This
significantly helped to clarify the structured of the process and help build an edge on the
theoretical contribution. It is also an appropriate case in terms of the possibility to
generalise the theories that apply to this circumstance on other settings (e.g. other
companies or even a function within other FMCG businesses). According to theory on
research conduct, this is highly important when selecting a case (Collis and Hussey, 2009).
The selected study object is one of largest actors of the Swedish Lifestyle Category within
the FMCG industry. The object is a manufacturer in a sense that it owns, manufactures and
distributes a number of brands within the category. Making it highly relevant as the study
object when investigating the effects arising from sales promotions within the Lifestyle
Category. It is argued by the researchers of this paper that this makes it a suitable study
object in terms of being deeply interconnected with the market, which in turn implies that
industry and categorical expressions should be observable through the case study object.
Preliminary investigation β Deeper understanding of how the sales promotions activities works in
relation to the company
The process of becoming familiar with the framework was initiated through preliminary
investigations. In this case it meant scrutinising the use of sales promotions and
understanding its mechanisms. Questions raised were for example: βWhat sales promotions are
the company working with?β, βWho are working with it?β, βHow is it possible to evaluate them?β,
βWhich function in the processes are relevant?β etc. It is essential to get insight and understanding
of the context before starting to collect data (e.g. before conducting interviews quantitative
data collection).
26. 26
Collecting data β Research methods
The data is collected through different methods; both qualitative and quantitative methods
were used. The collected primary data is helpful when trying to understand how the sales
promotions activities work, how they are evaluated today, which data sources of tracking
sales exists etc. In short, data needed to draw significant conclusions on the research topic.
This facilitates creating an overall picture of how companies work with sales promotion
activities. Many of these methods can be referred to as controlled observations (Hansson,
2007). This concerns a planned observation where the researcher can measure relevant
variables but is not able to affect them and see what happens if you change them (Hansson,
2007). The main four methods being used are:
Qualitative methods:
! Qualitative interviews
! Observations
Quantitative methods:
! Point of Sales data
! Structural data
Semi-structured Interviews
The interviews were held with a number of people within the case study organization by
conducting semi-structured interviews. Not influencing the interviewees with the
researchersβ own opinions and perceptions was highly relevant due to the purpose of
mapping the processes in an objective way. The goal was to gather information and
knowledge regarding the research topic from different angles and from the start to
connect the dots and reflect on plausible actions. Some of the interviews were held
during Pre-Study part of the process to develop an understanding of the respondentsβ
contextual perceptions. This is a typical for unstructured and semi-structured interviews
(Collis and Hussey, 2009). During the Case Study more interviews were held to collect
information related to the research questions connected to the topic of sales promotions.
The interviewees were selected to reflect all key functions within any FMCG company.
All interviewees (except the Salespersons) where interviewed once during the Pre-Study
and once during the Case Study. The functions of the interviewees were:
! Sales Director
! Marketing Director
! CFO
! Key Account Manager
! Sales Manager
! Product Group Manager
! Two Brand Managers
! Two Salespersons
All interviews were held by both researchers and were conducted face-to-face. The
reason for being two researchers was to facilitate comparison of collected data and for
quality assurance. The interviews were all approximately 60 to 90 minutes and all the
respondents, because of confidentiality reasons, are reported unnamed denoted simply by
corporate function. They were also conducted in Swedish and therefore are all the quotes
and information in this paper translated to English. The interview templates are also
translated. The type of interviewing questions used were open and closed questions.
Interview guides for the semi-structured interviews are presented in Appendix A and B.
To secure the quality of collected data from the interviews different employees with
diverse roles at the company were interviewed creating a wide spectrum of data, which
facilitated triangulation when analysing the results.
27. 27
Observations
Observation is a method for collecting data used in a natural environment to observe
peopleβs actions and behaviour (Collis and Hussey, 2009). To increase reliability of the
observations both researchers were observing the salespeople. The reason for adding
observations to the study is because interviews often are biased by opinions. For
example, the interviewees might express a certain opinion while being interviewed and
acting differently when being observed in a practical setting (Yin, 2003). The observation
method being used was integrated observation, meaning that the observers are active in
engaging in the practical environment (Collis and Hussey, 2009). Both researchers
conducted this type of observations throughout two full days. The first day of field
observations, was a part of the Pre-Study to generate an understanding of the industry
processes. The second day, was conducted in purpose of answering the Case Study
specific research questions. To increase the quality of the observations, two people
observed and then followed by comparison of individual observations were made. Again,
increasing the quality of observations through triangulating the findings.
Point-of-Sales Data and Structural Data
To make it possible to contribute with interesting results and to answer the overall
research question of evaluating sales promotions, quantitative data was a corner stone of
the research process. In particular, sales data on the Swedish Lifestyle Category was of
primary focus. When collecting this quantitative dataset, it was important that the data
was dynamic and could be specified after demand. The primary quantitative data source
was Point-of-Sales Data. This data enabled analysis consumer behaviour at store-level.
This was collected through access given to datasets of two of Swedenβs largest grocery
trade chains. Since the data in its nature is very sensitive the name of the two grocery
trade chains will not be revealed. However, the two accessed datasets covers a large part
of Swedenβs grocery trade, and hence a large part of Lifestyle Category sales. This implies
that results would be generalizable in terms of category wide consumer trends should be
reflected in the data due to its size. The structural data being used are in term of holidays
and TV-advertising. More about the specific use of data and how supporting discussion
on quality of the data will be conducted as a part of the Model Development chapter.
2.5 Model Development
As part of the Case study a Model Development passage of the research was initiated.
With the collected data (store sales and observations) a model was developed. Through
this modelβs ability to integrate sales- and structural data it was made possible to measure
and evaluate the effect of observations captured throughout the Case Study. The model
development approach was to incorporate the key issues that were expressed throughout
the first passages of the research process. First, the case study objectsβ own products are
modelled in a confined setting through ordinary least square regression analysis. Second,
the model is extended to a framework incorporating competitive behaviour and a
contextualised setting. This step was taken to increase generalizability of the results. More
about the model, the developing part, delimitation, assumptions and mechanisms are
explained in the Model Development description found in chapter 3.
28. 28
Figure 2. Integration of different Data Sources
2.6 Analysis and Conclusions
The research is conducted for one study object and hence being limited to within the case
study analysis. This requires complete understanding and familiarisation β becoming one
with the data to be able to draw relevant conclusions. From the collected data and the
regression analysis it was possible to construct several scenarios in sales promotion
activities, what is prosperous and finally draw conclusion and clustering successful
patterns. Analysis of the results from evaluating sales promotions through the
constructed model framework was conducted through using the literature review and
collected empirical data from the Case Study. Here it was very helpful using the
observations and the deliberate choice of spending time on-sight with the case study
company. This allow gathering of a broader coherent knowledge of how the different
elements of promotions are linked to each other.
2.7 Delimitations
The delimitation of this research is based on five aspects. They are geographical, one industry
sector, one study object, one sales channel. The Swedish market makes up the geographical
delimitation. The selection of the Swedish market was made due to Sweden being the
biggest market platform in Scandinavian. This enables accurate data collection, which
should serve as a proxy across Scandinavia.
The industry sector is the FMCG industry. In particular, the study is limited to the
Lifestyle Category in particular (also known as the health segment). Again, the company
is an important actor within the Swedish Lifestyle Category, thus making it highly
relevant as study object related to the FMCG environment and has experience of being a
company owning multiple brands. The main focus is on the biggest of these brands. Itβs
one of the biggest brands in the total Lifestyle Category which makes it relevant because
the brand is always involved in sales promotions and the sales people constantly work
with sales towards the market. The Grocery Trade (GT) is also the primary sales channel.
It is the biggest when it comes to sales volume and it is a channel where the sales people
do all there sales activities related to the sales promotions. The unit of analysis will be to
look sales promotions β the sales promotions related to the study object. Unit of analysis
refers to the level of data aggregation of within the analysis (Forza, 2002).
Moreover, it is important to note that in-store activities are excluded from the scope due
to deficient data. The data from the sales people activities in the stores had not been
collected nor tracked for more than four months and therefore making it impossible to
present any accurate results regarding the effects of them. Also, the tracking of this data
29. 29
was not as specific as needed to be in order to extract patterns. Therefore focus lies on
studying the effects of the price promotions from a central level.
2.8 Limitations
Limitations of the study are the complexity of establishing the scope of the case study. It
was extremely important at an early stage to delimit the scope to include a feasible
knowledge space given the confined amount of time available to conduct the study. This
is also one of the main pitfalls for a case study (Collis and Hussey, 2009). This was done
through making a Pre-Study. It was also important to continuously keep updating the
scope and reflect if the work followed the right track and not losing course when
working. Another important aspect to have in mind is that when conducting a Case
Study on one single object is that this is often criticised in terms of findings not being
generalizable. However, therefore the importance of continuously striving for increasing
the generalizability of the results is highly relevant. In this study, the study object and its
particular brands selected are amongst the largest in the industry. This should lead to
increased generalizability in the findings and is the primary measure taken in order to
increase the theoretical importance of potential conclusions. Furthermore, to increase the
generalizability an extended analysis section have been created measuring the effects of
price promotions for the biggest competitors as well. These results was then compared
with the companyβs effects to see if there is any similarities and dissimilarities. In this way
it enabled investigation whether the findings are generalizable or not.
2.9 Quality of research
Reliability refers to the consistency of the study, which means that if using the same
method but different circumstance will generate approximately the same results (Collis
and Hussey, 2009). In this case reliability of the study is high. If someone would repeat
the study for a similar case within the Lifestyle Category the results would probably be
the same characteristics. Issues as measuring the effects of sales promotions are a
relevant and difficult issue for many companies and with the model being developed it is
possible to re-use it with new imported data. The model is based on quantitative
methods which means using the same methods the model will look the same in
construction and then when using same data it would be accurate to repeat the study. It
was also very important to evaluate the results and to see if they were statistical
significant which the results being presented are. Nevertheless, the results being specific
from our case and the price promotions being analysed. Different sales promotions can
have different effects and therefore measuring these for new studies demands doing so
carefully and make sure that the results are statistical significant.
External validity states the degree of generalizability of the study to other settings. Case
studies are often criticized regarding that matter (Collis and Hussey, 2009). The model is
of great importance regarding the external validity of the study. It enables other
companies to examine the sales promotion effects using it. Also, in our case the results
can hopefully be of high validity managed when scrutinizing the effects from the price
promotions for the main competitors for the same item classes. If similar results will
appear it will facilitates generalizing the findings to the whole Lifestyle category. It is
important to bear in mind that this research is specific regarding which type of sales
promotion and item classes being analysed. Earlier research, as presented, can see
tendencies regarding the different promotions but it varies depending on the category of
study. This research is limited to price promotions and the Lifestyle category, which is
30. 30
limits the ability to draw conclusions between sales promotion borders and outside the
Lifestyle category.
Internal validity in this case is high. Taking into consideration a lot of data, within the
frames of the delimitations, knowledge gathered from the company making it relevant.
Testing and measuring the effects of the most pertinent promotions, testing the top three
major item classes and in all the stores within the Grocery Trade, approximately 400
stores (data is described further in next section). This will hopefully generate a high
internal validity as a decision-making tool.
2.10 Summing up
Throughout this chapter the overall methodology has been described. The selected
methodology of research was a Case Study. In the light of this, the approaches to
collecting data have been described. A discussion on issues in generalising Case Study
results has been conducted. The delimitations and limitations are also conducted. The
next step is the Model Development. This chapter is closely linked to the Methodology
chapter in the sense that the suggested model framework is the tool being used to
evaluate and measure the effects of sales promotions on consumer behaviour. However,
note that the Model Development is based on findings from the Literature Review
presented in chapter 4 and 5. Therefore it is recommended for any reader not previously
familiar with sales promotion modelling to proceed to chapter 4 and 5 before reading the
Model Development chapter.
31. 31
3 Model Development
3.1 Introduction
In this section a model framework for measuring unit-sales response on store-level of
sales promotions is developed. The unified model framework will be based on empirical
observations and findings in previous research. Therefore, it is recommended for readers
not previously familiar with sales promotions to first read the Literature Review
presented in chapter 4 and 5. In this chapter we will proceed with the following steps;
first, we show how to mathematically model store-level unit-sales in order to evaluate
effect on own-brand of price promotions including pre- and post promotional dips. This
first section should be considered a preliminary approach underlying the full model that
is presented subsequently. Hence, secondly, the full model that in a robust manner
captures and decomposes sales promotion effect into cross-brands, cannibalization and
category expansion is presented.
Figure 3. Illustration of Model Framework process.
The model framework (see Figure 3) is selected and defined in such a way that it aims to
incorporate important findings that were observed throughout the case study and
discovered in the literature review. Note that the model framework is based on modelling
unit-sales and not the sales value. This is indeed a very important distinction and is based
on the fact that sales value modelling is harder in terms of data being manipulated by
differing pricing-levels between stores.
3.2 Data description and selection
Two datasets from two Swedish grocery chains with data on Swedish Lifestyle Category
sales were put at disposal for this research. The datasets are weekly, store point-of-sales
data specified to item level stretching over 78 consistent weeks. In addition, data from
the sales tracking giant ACNielsen was made available for the Swedish Lifestyle Category.
3.2.1 Initial approach: Understanding store level sales data
When approaching the problem of modelling the effect of sales promotions within the
Lifestyle Category the first action is to understand the data structure in order to
understand possibilities and potential limitations due to this structure and depth of
information. In the dataset the data include store identification, week of sales, name of
item sold, number of units sold, value of units sold and unit price across the entire
Swedish Lifestyle Category sold within Grocery Trade.
32. 32
3.2.2 Selecting modelling data: Weight Control
From the pre-study it was found that Weight Control sub-category accounts for more
than half (>50%) of the 560 mSEK Swedish Lifestyle Category. Since the store sales data
is noisy in its very nature (i.e. many hard-to-measure factors that are affecting sales
fallout) products with larger turnover should reduce the noise to a minimum and be
dominated by the most influential factors on sales. Because of this reasoning, the Weight
Control sub-category was selected for this study and considered an approximation for
the Lifestyle Category. Furthermore, due to the entrepreneurial spirit of the Lifestyle
Category many of the smaller brands (which is indeed the case for most brands in the
other sub-categories) do not even have the financial resources to conduct promotions.
The smaller sub-categories are therefore stripped away from the dataset included in this
study. An overview of the selected store-level data provided is presented in Table 1.
Table 1. Description of selected store-level data for analysis
Description of Data
Country Sweden
Category Lifestyle
Sub-category Weight Control
Item Class (Form) Bar Shake RTD
Data level Product Product Product
Unit type for evaluation 1/2-pack 24/25-pack 330 ml cans
Number of brands 3 4 3
Number of stores 378 357 376
Number of weeks 78 78 78
Number of price promotions 23 12 22
Number of observations 368 243 88 946 291 569
Number of model variables 16 16 16
3.2.3 Important terminology
Throughout this research paper (unless stated otherwise) when using the definition
βSwedish Lifestyle Categoryβ, the selected data sample within the sub-category Weight
Control is the specific set of data referred to. This follows directly from the reasoning
above. Furthermore, the category is further sub-divided over which Form of product
being used (i.e. Bar, Shake or RTD). This will be referred to as Item Class throughout
this paper. Within each item class, depending on brand incumbents respectively, the unit
types of evaluation within the sample data are 1- or 2-packs, 24- or 25-packs and 330 ml
cans for Bar, Shake and RTD. The reason for the differing sizes for Bars and Shakes is
intra-brand variations. However, due to almost being equally sized they are considered
equal in terms of consumer behaviour. Furthermore, throughout the text focal brand and
own-brand will be interchangeable.
3.3 Approach to modeling own-brand sales
In this section it will be described how the model framework was approached and how
each step was motivated and constructed. The approach was initiated by carefully
selecting a model that would capture own-brand sales based on store-level data. Again,
note that it is unit-sales (i.e. volume) being selected as dependent variable.
3.3.1 Parameter selection: Price promotions prominent factor
When modelling sales data, a number of influential factors need to be considered. Here,
the selection of these parameters will be explained and described (see Figure 4).
33. 33
Figure 4. Primary components for modelling sales
The most prominent factor amongst sales promotions tools according to both literature
review and initial sample analysis was price reduction. Therefore, the price reduction
parameter is selected as the approach and basis when modelling own-brand sales.
The price promotional effects are split into immediate effects seen in week t (i.e.
promotion week) and the lead and lagged effects of the promotion in weeks t-T to t-1
and t+1 to t+Tβ respectively (T defined as number of lead effect weeks and Tβ number of
lagged effect weeks). This regression based model uses store-level data as basis to
estimate the effects. This model can be applied to brand, brand product group (e.g.
Coca-Cola 33cl size cans) or a specific product. In the following text, this applicability
will simply be referred to as data applied to a brand i. Therefore, the store-level unit sales
in store j, for a brand i, occurring in week t is defined as π!,!,!. Furthermore, according to
previous discussions, this model is primarily based on the effect of promotions spotted
in price changes in point-of-sales data.
To include this in the model a price index is created. The weekly sales prices are extracted
from the datasets for each brand i, store j and periods t that are being the focal objects of
the study. From these prices the price index is defined based on the following
assumptions. The regular (ordinary) price for the particular focal brand should over a
reasonably short period of time be the mode seen in the observations. Therefore the
price index is calculated as the price observed in week t as a ratio of the mode of a
reasonable number of subsequent periods R. I.e. the price index for brand i, in store j for
period t is defined as
ππΌ!,!,! =
π!,!,!
ππππ π!,!,!!!
β
, π!,!,!!!!!
β
, π!,!,!!!
β
, β¦ , π!,!,!
β
( 3.1 )
By selecting R reasonably small potential regular price increases or decreases over time
will not affect the index. In order to avoid errors in identifying the mode store sales data
are rounded to the nearest integer (π!,!,! β π!,!,!
β
).
Furthermore, following empirical findings given in previous sections, the Lifestyle
category has been found to be heavily dependent on seasonality factors. The finding in
the literature review was also supported by interviews within the case study object (Sales
Director, 2014, Key Account Manager, 2014) where it became evident that there seems
36. 36
First, the total category sales (TCS) during some time period t can be decomposed into
sales of the focal item (OBS β own-brand sales) at time t, the non-focal item own-brand,
i.e. cannibalization, sales (OBC β own-brand cannibalization) and the cross-brand sales
(CBS) at time t. That is,
ππΆπ!
β
= ππ΅π!
β
+ ππ΅πΆ!
β
+ πΆπ΅π!
β ( 3.3 )
Using this notation we can reconstruct Equation ( 3.3 ) in the sense that
- Β ππ΅π!
β
= ππ΅πΆ!
β
+ πΆπ΅π!
β
β ππΆπ!
β ( 3.4 )
where the star indicators are used preliminary during this model approach. Furthermore,
since stores vary in size, it is appropriate to transform all sales data such that promotional
effect is proportionally equal. This is done by dividing dependent variable data (own-
brand sales) with average category sales (π΄πΆπ!) for the store i, or if studying aggregate
data the average category sales over multiple stores π΄πΆπ!
!
!!! . If π!,!,! indicate unit sales
in store i, for brand j, item k, in period t, then the dependent variables for the quadruple
regression analysis is defined as
ππ΅π!,!,!,! = β
π!,!,!,!
π΄πΆπ!
( 3.5 )
ππ΅πΆ!,!,! =
π!,!,!,!
π΄πΆπ!
!
!!!
!!!
( 3.6 )
πΆπ΅π!,!,! =
π!,!,!
π΄πΆπ!
!
!!!
!!!
( 3.7 )
ππΆπ!,! = β
π!,!,!
π΄πΆπ!
!
!!!
( 3.8 )
Cannibalization
Β
Cross-Ββbrand
Β Sales
Β
Category
Β Expansion
Β
Figure 6. Illustrating expected decomposed effect of promotions
39. 39
Β Β πΆπ΅ππΌ!,!,! = Price index for cross-brands. I.e. relative price level on average for all
brands except focal brand j. Constructed according to our price index construct above.
Β Β ππ΅πΆππΌ!,!,! = Own-brand except for focal brand j price index for period t. Average
pricing level captured according to our price index definition above.
Β Β Β πΌ, π½, πΎ, πΏ and π are the regression parameters and π! are the regression residuals for the
various periods.
The parameters are estimated through Ordinary Least Squares (OLS) regression. The
statistical tool used when writing this paper is simply Microsoft Excel. Since the model
framework in Equation 3.9 is logically consistent and the model definition in Equations
3.10 through 3.13 are regressed over the same set of parameters the results from the
model framework leads to
π½!" = π½!"# + π½!" + π½!"
( 3.14 )
or in other words price promotion effect on own-brand sales is decomposed into the
effect of own-brand cannibalization, cross-brand, and category expansion effects.
Furthermore, for more easily interpreted results, effects are presented terms of fraction
of own-brand effect.
3.4.4 Model validity and statistical significance
For testing the model validity a number of statistical quality measures and statistics are
employed. These are of great importance in ensuring the quality and understanding of
model fit. First off for significance testing of parameters a regular t-test is employed.
These tests are well-known and standard test of significance. The test statistic is
produced by first generating the so-called t-statistic test variable
π‘ =
π½! β π½!
!
ππΈ(π½!)
( 3.15 )
where π½! is the some estimated parameter k , π½!
!
is the hypothesis of testing and SE(π½!)
is the estimated standard deviation of the parameter estimate k. In this report the
statistical hypothesis testing of interest is simply if the estimated promotion response
parameter is significantly distinct from 0. Therefore, the hypothesis for any parameter π½!
!
is set to 0 unless stated otherwise.
Furthermore, the R2
statistic is used in order to validate the goodness of fit of the model.
This is also a standard statistical testing method produced automatically when using any
statistical software. The definition of the statistic is
π !
=
πππ π₯π½
πππ π¦
( 3.16 )
where x refers to the input independent variables (e.g. Price index, holiday dummy, ads
dummy), π½ is the set of regression parameters and y is the response variables. I.e. the
response variables are the point-of-sales data on own-brand sales, cross-brand sales,
own-brand cannibalization and total category sales. This measure is carefully monitored
in the sense that it describes how much of the data variance is captured by the estimated
model. These tests will be employed for testing the parameter estimates for the model.
43. 43
Literature review
The literature review is divided into two
main sections; FMCG industry specifics
and sales promotions. First, FMCG is
described to get a general industry
overview and insights into key difficulties.
Second, the notion of sales promotions is
introduced along with psychological
consumer aspects. Last, a number of
previous quantitative models on sales
promotion evaluation are discussed.
45. 45
4 Introducing the Fast-Moving
Consumer Goods Industry
4.1 Introduction
In this chapter an overview of Fast-Moving Consumer Goods (FMCG) along with
important characteristics described in previous literature. This will provide a good
framework for understanding the dynamics of the industry. Following this chapter, the
literature review will proceed to introducing the more specific issue of sales promotions
and its modeling.
Figure 7. Illustrating the Literature review based Narrowing of the Scope
4.2 Fast-Moving Consumer Goods
Fast-Moving Consumer Goods (FMCG) refers to a broad range of retail products
characterised by being sold at low cost and being replaced or fully consumed over a short
period of time. Where a short period is defined as time frame up to one year (Keller,
2003). Much research has been carried out in the field of implications revolving the
FMCG sector. Rapid changes add pressure and necessity of great flexibility in the supply
chain to meet shifting high-level consumer demand (Christopher and Holweg, 2011).
Within the FMCG supply chain it is important to highlight the distinction between
consumers (i.e. the end-user of a product) and the retailers through which products are
being sold. This means that the FMCG producers experience extra dimension from
trying to master the difficulties involved with indirect sales and distribution through
retailers and wholesalers. This model could be argued to relate to outsourcing of non-
core functions in terms of focusing on establishing a strong brand and a lean production.
However the model increase complexity downstream in the supply chain. It has been
suggested that wholesalersβ and retailersβ integration in the supply chain is a key to
manage this complexity (Rickards and Ritsert, 2011). The indirect sales and distribution
model of FMCG companies also leads to difficulties in forecasting consumer demand.
This perspective also supports the suggested approach of integrating the supply chain
downstream to reduce lack of information. Recent studies show that analysing Point-of-
Sale (POS)-data often is a better tool than order history when forecasting consumer
demand (Adebanjo and Mann, 2000, Williams and Waller, 2010). POS-data refers to
everything that passes through a cash register in a store or in other words products sold
over-the-counter (Kotler and Armstrong, 2013).
Over the past two decades the FMCG sector has been experiencing a secular shift in
terms of private label brands massive increase of market share (Hultman et al., 2008). In
46. 46
the space of FMCG, the short lifespan of a product makes the brand a priority in order
to retain consumers over time. Brands are considered the main point of differentiation
amongst competitor brands and are perceivably ensuring quality and level of consumer
satisfaction. When considering the most well-known contemporary brands such as Coca-
Cola, Apple and McDonalds, they typically fall under the umbrella of manufacturer
brands (Keller, 2003). What defines these types of brands is that they are produced in-
house and hence the manufacturer itself controls the brand and its entities. Historically
the retailing industry has been providing its customers with manufacturer brands.
However, the retailers has now come to realise the competitive benefits by providing
their own brands (Hultman et al., 2008). These brands are often referred to as βretailer
brandsβ, βwholesaler brandsβ, βown brandsβ or βprivate labelβ. This shift however is
well worth considering since it is suggested to have great influence on the future
competitive landscape of the FMCG sector (Nijssen, 1999, Hultman et al., 2008).
FMCG companies often struggle in terms of retention rates over time due to the very
nature of the industry and its dynamics. Relationship marketing has been an emerging
paradigm seen over the last two decades ultimately striving to increase customer loyalty
and satisfaction over time (Gummesson, 1997, Leahy, 2011). Evidence shows that
consumers in general tend to have a negative attitude towards how relationship
marketing is operationalized within FMCG markets. From a consumersβ perspective is is
not considered to exist any relationship and the FMCG sphere is largely impersonal in
nature. (Leahy, 2011) This entails implications on how FMCGs should conduct
marketing strategies efficiently and has large effect on how the FMCGsβ sales force
should operate.
In order to maintain competitiveness in what seems to be an industry with low barriers
of entry and where consumer-brand relationships are hard to establish (Leahy, 2011),
FMCG companies need to operate with strategic precision to retain consumers as good
as possible to capture new market trends. Among the range of strategies available to
FMCGs line extensions is an important way to revitalize a brand and to boost financial
growth. However recent studies concludes that the effect of a line extension varies
significantly pending on varying market settings, i.e. over level of competition in the
market place, retailersβ power and consumersβ variety seeking behaviour (Nijssen, 1999).
Hence, despite brand equity being one of companiesβ most important assets, extra
attention should be directed to how it is managed as well as being navigated through the
competitive landscape. Sales Promotions has also been occurring as a more frequently
used marketing strategy amongst FMCG incumbents This marketing tool boost short-
term sales and accounts for roughly 70% of industry marketing spending (Shimp, 2008,
Kotler and Armstrong, 2013). More on this topic will follow in the proceeding chapter.
Further degrees of difficulties exerting the FMCG sector are the implications from
dealing with both multiple marketplaces and simultaneously dealing with a broad range
of brands. Marketplaces vary significantly in terms of level of competition, retail power
etc. adding an extra dimension to consider in terms of strategy. Similarly brands with
largely varying characteristics and values needs also be considered. This complexity
requires that broad spectrums of brand management methodologies are included to cope
with the variety of challenges of the FMCG sector (Iglesias et al., 2011). Factors such as
despite being first-to-market and/or operating at a concentrated market place still induce
large competitive pressure on incumbents (Kitchen, 1989).
47. 47
4.3 Summing up
The findings described abover forms a general overview of the issues relating to the
FMCG industry and raises awareness of the specific difficulties the industry incumbents
face. In the next chapter, the particular topic of sales promotions will be introduced.
48. 48
5 Sales Promotions
5.1 Introduction
This chapter will be devoted to explaining the main issues related to sales promotions. In
addition, this will be extended with an overview of the psychological factors influencing
sales promotional effect. Finally a number of the more prominent modelling attempts
existing in literature will be described.
5.2 Sales Promotions
5.2.1 Definition of Sales Promotion
Sales promotions refers to any incentive used by manufacturer, retailer or service
provider in order to stimulate changes in brand perception and value temporarily (Shimp,
2008, Kotler and Armstrong, 2013). Sales promotions (often referred to as promotions)
is a part of the marketing communications mix and unlike advertising which offers
reasons to buy a product and a service, sales promotions offers short-term incentives to
buy a product now (Kotler and Armstrong, 2013). The challenge facing marketers is how
to convert the promotional short-term effect into changes in long-term consumer
behaviour and brand perception. An overall categorisation of key sales promotions is
consumer-oriented promotions and trade-oriented promotions, respectively.
Figure 8. Sales Promotion orientation. Source: Shimp, 2008
In literature there are several definitions of sales promotion. In Blattberg and Neslin
(1990) a number of definitions are given. Some of these are:
Sales promotion consists of a diverse collection of incentive tools, mostly short-term, designed to stimulate
quicker and/or greater purchase of a particular product by consumers or the trade (Kotler 1988,
p.645).1
Sales promotion is the direct inducement or incentive to the sales force, the distributor, or the consumer,
with the primary objective of creating an immediate sale (Schultz and Robinson 1982, p.8).2
Sales promotion, deals, and display can be defined under the general term of βshort-term inducements to
customer buying action' (Webster 1971, p.556).3
1
Kotler, Philip (1988), Marketing Management: Analysis, Planning, Implementation, and Control, 6th ed.,
2
Schultz, Don E. and William A. Robinson (1982), Sales Promotion Management, Chicago: Crain Books.
3 Webster, Frederick E. (1971), Marketing Communication, New York: Ronald Press.
49. 49
Sales promotion represents those marketing efforts that are supplementary in nature, are conducted for a
limited period of time, and seek to induce buying (Davis 1981, p.536).4
From this Blattberg and Neslin (1990) form their own definition of sales promotion. In
particular, they exclude the frequently occurring distinction βshort-termβ from the
definition. This separation is made since the relevant issue of study also includes the
long-term effects of sales promotions. Their definition is:
Sales promotion is an action-focused marketing event whose purpose is to have a direct impact on the
behavior of the firm's customers.
In this paper, this definition will be used when referring to sales promotions. This is
important since throughout this study there will be elements of long-term considerations
included in the analysis and discussion.
5.2.2 Budgetary allocation shift towards promotions
Sales promotions are today a major element of attention amongst marketers as well as in
academia (Neslin, 2002, Van Heerde et al., 2004, Valette-Florence et al., 2011, Kotler and
Armstrong, 2013, Netemeyer et al., 2004). The use of sales promotions is particularly
salient within the consumer-packaged goods industry. Estimates shows that over 20% of
sales volume occurs as a causality from promotions in a product category (Teunter,
2002). In recent years we have observed a secular
change in how organizations communicate with
its customers and business environment.
Traditionally, advertising has been the most
prominent marketing communication tool.
Historical average shows that roughly 70% of
U.S. marketing expenditures was accounted for
by advertising (Shimp, 2008, Kotler and
Armstrong, 2013). However, in recent years, for
an average company within the consumer-
packaged goods sector, sales promotions
accounts for 77% of marketing expenditures (Wierenga and Soethoudt, 2010, Kantar
Retail, 2010).
There are several reasons causing the transition from advertising- towards promotional-
focused marketing. First, it seems that product managers face greater pressure and demand in
improving current sales. Since sales promotions in its very nature have proven to boost
short-term sales, this has become an attractive alternative for managers to deliver short-
term results (Neslin, 2002). Secondly, the power of the trade β i.e. the retailers and
wholesalers involved in getting the product or service into the hands of the end-user β
has increased significantly as the retailers has become more sophisticated. Sales
promotions are a way to increase reseller awareness of a manufacturer brand and lead to
increased cooperation. Third, advertising efficiency has declined significantly due to rising costs,
media clutter (e.g. multiple advertising vehicles) and high brand proliferation. Finally,
4
Davis, Kenneth R. (1981), Marketing Management, 4th ed., New York: John Wiley.
KEY DRIVERS OF SHIFT FROM
ADVERTISING TO PROMOTIONS
1. Increased managerial pressure
2. Balance-of-power shift
3. Media clutter
4. High consumer awareness
Source: Shimp (2008), Kotler and Armstrong (2013).
50. 50
consumers are more aware and mindful in choosing brand and product. The overall
consumer-goods markets seems to be relatively mature with consumers who may know
many of the brands available and may also not be perceiving them as very different.
Moreover given the current economic conditions, consumers demand lower prices and
better deals. These are the main factors explaining the rapid shift observed in marketing
expenditure structure. (Shimp, 2008, Kotler and Armstrong, 2013)
5.2.3 Promotional objectives
There are three target groups of a sales promotion; the manufacturerβs sales force,
retailers and consumers. First, promotions are a tool supporting the sales force to sell a brand
or a product more aggressively to the retailer and wholesaler. I.e. providing an incentive
for salespersons to put extra selling emphasis on a promoted brand or product. The
second target of sales promotions is the trade (i.e. the retailers and wholesalers involved in
getting the product or service into the hands of the end-user) through a range of tools
discussed more in detail in the next section. These trade-oriented promotions have the
common characteristics of supporting retailer pushing the manufacturer products
through the value chain to the consumer. Therefore, trade promotions are often referred
to as push activities. Finally, the third target of sales promotions is the consumer. By
using consumer-oriented promotions the manufacturer can help create a pull through the
channel by in various ways by providing consumers with a special reason to buy a
product. (Shimp, 2008, Kotler and Armstrong, 2013)
Figure 9. Illustration of Sales promotional targets. Source: Shimp (2008)
5.2.4 Consumer and Trade promotions
As the reader might expect there exist a broad range of sales promotion tools.
Frequently, these tools are classified along the lines of the promotional target groups
described above; namely being consumer-oriented and trade-oriented respectively. This
classification will be applied when discussing the existing major promotion tools and its
overall objectives.
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Figure 10. Promotions between Manufacturers, Retailers and Consumers
Consumer promotions
Consumer-oriented promotion methods often include coupons, price deals, premiums,
contests and sweepstakes, bonus packs, sampling, point-of-purchase displays and loyalty
programmes. Objectives include primarily:
β’ Trial persuasion: Coupons, price deals, premiums and contests are often efficient
ways to persuade consumers to try a particular product.
β’ Accelerate purchase process: e.g. contests, premiums.
β’ Increase repurchase: loyalty programmes etc.
β’ Increase usage: volume discounts
β’ Brand building: long-term effects
A few of the most prominent tools are described below:
β’ Sampling β i.e. giving a way product sample to raise consumer interest β is a very
effective but (unfortunately) expensive way to introduce a new product and gain
trial consumers.
β’ Point-of-purchase promotions β for example in-store sampling with demonstrations.
β’ Coupons β consumer receives a price discount when presenting the particular
coupon to the retailer.
β’ Price promotions β various kinds of price promotions offered to consumer. E.g. in
the form of a pure price reduction or a discount on buying multiple products
β’ Premiums β additional perks offered as an βadd-onβ to the purchased product.
β’ Promotional products β products with manufacturer logotype. Often referred to as
giveaways. E.g. a shake with some protein powder manufacturerβs logotype,
pencils, t-shirts etc.
β’ Contests, games and sweepstakes β letting customers compete and win products.
Good for brand attention and consumer involvement.
Given the multitude of consumer promotional activities available, determining and
assessing the profitability of the optimal promotional tool is indeed a great challenge for
marketers. E.g. it has been reported that consumer view of the value and importance of
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in-store promotional activities vary greatly across product and consumer categories.
(Neslin, 2002, Rao, 2009, Schultz and Block, 2011)
Trade promotions
Manufacturers are currently directing more sales promotion money on trade-oriented
promotions (81 percent) than to end-consumer (Kantar Retail, 2010). The objective of
these type of sales promotions is primarily to build support of your brand with the retailer. By
using trade-oriented activities the retailer is persuaded to help carry the brand, giving up
more shelf space, promote in advertising (in-store, direct media, etc.) and in various ways
push it to the consumers. Specific objectives of trade promotions include:
β’ Attract new customers and expand into new markets: When a manufacturer is trying to
expand into a new market and/or attract a new customer group sales promotions
can be an efficient tool.
β’ Increase sales support and stimulate trade merchandising: Through cooperative
advertising and trade allowances (discounts) the manufacturer might try to have
the retailer exert sales efforts on the brand or product.
Similar to the case of consumer promotions also trade-oriented methods consist of a
several tools. In fact, many of the consumer promotions β e.g. point-of-purchase displays,
contests, and premiums β might also be used in a trade context. A manufacturer can also
offer the retailer a straight-off discount on the price list for an agreed limited period of
time. Akin, manufacturers can offer trade allowance in return for the retailer featuring the
product or brand in an agreed way. E.g. a display allowance compensates the retailer for
using product displays or advertising allowance compensates for advertising the product.
(Shimp, 2008, Kotler and Armstrong, 2013)
5.2.5 Fundamental empirical findings
This section discusses the fundamental empirical findings existing in current literature.
The research on the topic of sales promotions is substantial and consequently the focus
will be limited to the prominent results along with articles supporting these claims based
on the concluding article by Blattberg et al. (1995).
β’ Sales promotions in the form of temporary price reductions have been documented to
generate substantial sales increase. This result is central to all research on the topic
promotions and is well documented. (Blattberg et al., 1981, Moriarty, 1985,
Kotler and Armstrong, 2013)
β’ Permanent effects of promotions are very small. Evidence suggests that the permanent
long-term effects of price promotions are very small to virtually inexistent. (Nijs
et al., 2001, Steenkamp et al., 2005).
β’ The deal frequency changes consumersβ reference price. Heavy promotion of a brand might
have negative effect on brand equity in terms of changed perceived price level.
(Mayhew and Winer, 1992, Kalwani and Yim, 1992)
β’ Higher frequency of promotions changes height of sales spike. This relates to the previous
point on changing consumerβs reference price and is also likely to be caused by
consumerβs expectation on up-coming deals (Van Heerde et al., 2004).
β’ Cross-brand effects are asymmetric. Brands seem to be responding different to
promotions. Suggested reason being brand differences in brand equity. Brand
switching has been documented extensively and many studies suggest that
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promotion by higher tier brands generates higher level of brand switching than
promotion by lower tier brands. (Blattberg and Levin, 1987, Neslin, 2002, Nagar,
2009, Richards et al., 2012)
β’ Promotions often have cross-categorical effects. There is a high probability (approximately
61%) that a price promotion affects sales of at least one other category. (Leeflang
and ParreΓ±o-Selva, 2012)
β’ Retailer pass-through is far less than 100 per cent. The retailer pass-through is defined
as the number of sales incentives given by manufacturer to retailer that is passed
through to consumers. Numbers of pass-through range from 0 to 200%.
However the range is somewhat limited in terms of the pass-through often is less
than 100% (Neslin, 2002), and often higher than 60% (Besanko et al., 2005).
β’ Display and feature advertising is a significant contributor to increased sales. The effect is
relatively accepted amongst practitioners and has been confirmed. Also, there are
signs interaction effects in terms of synergies between displays, feature
advertisings and price discounts (Kumar and Leone, 1988, Neslin, 2002,
Wierenga and Soethoudt, 2010).
5.2.6 Summarising Sales Promotions and its characteristics
Throughout the preceding section, sales promotion has been defined along with detailed
description of the topic. This has been accompanied with a number of the most
important fundamental findings on the topic. To summarise a few important findings;
there is a sales bump response to promotions, promotion frequency might change
consumer perceptions and cross-promotional effects are asymmetric. With these findings
in mind, psychological factors connected to how end-consumers evaluate and respond to
sales promotions will be introduced and discussed.
5.3 Psychological factors
To support comparing and building relevant conclusions regarding psychological factors
impacting the consumersβ responsiveness to sales promotions, a deep and fundamental
theoretical understanding of the topic is necessary. This section will present existing
theories on consumer behavior and reactions to sales promotions. First, psychological
factors such as different dimensions of consumer behavior along with geographic,
demographic and psychographic factors will be presented. Second, with an increasing
complexity in the market development, new and developed theories becomes vital and
one of them is geodemography, a combination of demography and geographic aspects
(Jobber and Fahy, 2009).
5.3.1 Understanding consumer behaviour
When working with sales and marketing it is important to understand consumer behavior
in order to drive long-term sales growth. The understanding of what particular influence
that actually drives and end-consumer to purchase a particular product in a grocery store
is vital. According to Jobber and Fahy (2009) there are five key questions a marketer
should ask him- or herself when trying to examine consumer behavior. These questions
are: (1) Who is important? (2) How do they buy? (3) What are their choice criteria? (4)
Where do they buy? and (5) When do they buy? The goal of this five-question
framework is to develop concepts that influence the end-consumer to buy the product.
In Figure 11 the model is visualized. To facilitate answering these question companies
can do market research including different methods for example customer surveys,
interviews or draw patterns through quantitative data. The first three questions are the
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most intractable and will be discussed further while the last two are more straightforward
and therefore not discussed in the literature review (Jobber and Fahy, 2009).
Who buys
One of the first steps when planning marketing activities is to determine the target
group. That is, who buys the product or service? This process is commonly referred to as
segmentation. Segmentation means identifying and separating individuals into categories or
groups by constructing joint characteristics frames (Vollering, 1984). Segmentation is the
first step when looking to communicate an offer to the end-consumer. The second step
in communicating an offer to segmented group is referred to as targeting. Targeting refers
to selecting one or several of the defined segments. The last step is known as positioning.
This refers to positioning the offer by figuring out what to say and how to communicate
it to the targeted segment. These three steps are called target marketing (Γ sberg, 2010).
There are a number of frames and subcategories frequently used when segmenting. The
most common ones are geographical, demographical, psychographic and behavioral
segmentation. Geographical segmentation is to divide a population by mapping where they live.
Figure 11. Framework for understanding consumer behaviour
For example countries, districts, neighborhoods and blocks. These types of segments
become more and more irrelevant because globalization erase the borders more and
more and one of the biggest reasons is the internet. The most commonly used one in
Sweden is metropolitan- and countryside classification (Γ sberg, 2010). Demographical
segmentation is a commonly used method to divide individuals into groups. Groups such as
gender, age, occupation, education, civil status etc. Different groups behave differently
towards diverse offers. Itβs a relatively easy and fast way of doing segmentation with the
goal of reaching particular customer groups. One downside is though that stereotyping
like this not always are accurate in the long run. Psychographic segmentation involves dividing
after social classes, life styles and personal characteristics. Some of the reasons to why an
end-consumer purchases a product is to express themselves, who they are and to show
what kind of lifestyle they live. This is a good method for building segments because it
takes into account how people actually live depending on occupation, education etc. One
of the downsides is that it can become quite complex since there are so many possible
segments. The last sub-category of segmentation is behavioral segmentation. This revolves
Customer
Who is
important?
What are
their
choice
criteria?
When do
they buy?
Where do
they buy?
How do
they buy?
