=Paper=
{{Paper
|id=Vol-2089/6_Adaji
|storemode=property
|title=Shopper Types and the Influence of Persuasive Strategies in E-Commerce
|pdfUrl=https://ceur-ws.org/Vol-2089/6_Adaji.pdf
|volume=Vol-2089
|authors=Ifeoma Adaji,Kiemute Oyibo,Julita Vassileva
|dblpUrl=https://dblp.org/rec/conf/persuasive/AdajiOV18b
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==Shopper Types and the Influence of Persuasive Strategies in E-Commerce==
https://ceur-ws.org/Vol-2089/6_Adaji.pdf
Shopper Types and the Influence of Persuasive Strategies
in E-Commerce
Ifeoma Adaji, Kiemute Oyibo, Julita Vassileva
University of Saskatchewan, Saskatoon, Saskatchewan, Canada
ifeoma.adaji@usask.ca, kiemute.oyibo@usask.ca, jiv@cs.usask.ca
Abstract. Identifying the shopper type of e-commerce users has been shown to
help e-businesses better understand the attitude of their customers and what they
look out for in their shopping decision-making process. However, applying the
same influence strategy for all shopper types will not likely bring about the de-
sired behavior change. Because influence strategies have higher efficacy when
personalized, we propose a personalized approach to implementing influence
strategies for the different shopper types by identifying what shopper type is sus-
ceptible to which influence strategy. To advance research in this area, we explore
the influence of the commonly used shopper types convenience shopper, store
oriented shopper, balanced buyer and variety seeker on Cialdini's six influence
strategies (reciprocation, commitment, consensus, liking, authority and scarcity)
in order to determine what shopper type has the greatest influence on each per-
suasive strategy. To achieve this, we conducted a study of 226 e-commerce shop-
pers and developed a path model using Partial Least Squares - Structural Equa-
tion Modelling (PLS-SEM). We further carried out multi-group analysis between
female and male shoppers. Our results suggest significant differences of the var-
ious shopper types’ susceptibility to the persuasive strategies. In particular, bal-
anced buyer shopper type has the strongest influence on commitment persuasive
strategy and insignificant effects on the other strategies. In addition, while the
male variety seekers are susceptible to the influence strategy scarcity, the females
are not. Similarly, while the female convenient shoppers are susceptible to the
influence strategy scarcity, the males are not.
1 Introduction
Identifying and understanding the shopping motivation of clients is essential to e-busi-
nesses as this could help companies better understand the attitude of customers and
what they look out for in their shopping decision-making process [1]. This information
can help businesses create a better shopping experience for their clients [2]. There are
various classifications of shoppers based on their shopping motivation. One popular
classification is by Rohm et al. [1]. They classify e-commerce shoppers into four shop-
per types: convenience shoppers, variety seekers, balanced buyers and store-oriented
shoppers. The convenience shoppers are motivated by online shopping convenience.
Shoppers in this category do not typically seek immediate possession of their products
and they shop online for specific products and services. The variety seekers on the other
Copyright © 2018 held by the paper’s authors. Copying permitted for private and academic
purposes.
In: R. Orji, M. Kaptein, J. Ham, K. Oyibo, J. Nwokeji (eds.): Proceedings of the Personalization
in Persuasive Technology Workshop, Persuasive Technology 2018, Waterloo, Canada,
17-04-2018, published at http://ceur-ws.org
Shopper Types and the Influence of Persuasive Strategies in E-Commerce 59
hand are more interested in seeking variety of products across various retailers and
brands. The balanced buyers are motivated by the need to seek information online like
the variety seeker. However, the balanced buyers do not plan their shopping ahead. The
store-oriented shoppers want immediate possession of goods purchased and are more
inclined to social interaction. Shoppers in this category prefer the feel of a physical
store to an online marketplace. Despite these classifications of shoppers, there is little
knowledge of their susceptibility to the various persuasive strategies. Because influence
strategies are more effective when personalized [3], it is imperative to understand what
strategies particular shopper types are influenced by in order to personalize these strat-
egies to the shoppers. We hypothesize that identifying what influence strategies shop-
pers in each category are susceptible to could lead to a more personalized shopping
experience for the customer. For example, if the customers who belong to the shopper
type variety seekers are susceptible to the influence strategy scarcity, the e-commerce
system could personalize product selection, product display and product descriptions
using various scarcity strategies. This could bring about the desired positive change in
the customer.
To advance research in this area, we carried out a study of 226 e-commerce shoppers
to investigate how the various shopper types are influenced by persuasive strategies.
We measured persuasive strategies using Cialdini’s six influence strategies [4] because
they are commonly used in several domains including e-commerce [5]. We developed
and tested a path model using partial least squares – structural equation modelling
(PLS-SEM). We further explored the moderating effect of gender on the model. The
result of our analysis suggests significant differences in the susceptibility of the various
shopper types to the different influence strategies. In particular, balanced buyer shopper
type had the highest influence on commitment persuasive strategy and has insignificant
effects on the other strategies. This suggests that balanced buyers are likely susceptible
to commitment strategy. In addition, convenience shopper had the highest influence on
scarcity, while store oriented buyer had the highest influence on consensus. Variety
shopper, on the other hand, had the highest effect on the influence strategy authority.
Furthermore, while the male variety seekers are susceptible to the influence strategy
scarcity, the females are not. Similarly, the female convenient shoppers are susceptible
to the influence strategy scarcity while the males are not.
These results suggest possible guidelines in the personalization of influence strate-
gies in e-commerce.
2 Related Work
2.1 Shopper Types
Classifying shoppers according to their shopping motivation and behavior has been
suggested as a way to help businesses effectively tailor products and services to the
various segments of customers [1]. It also helps businesses to better understand the
attitude of their customers and what they look out for in their shopping decision-making
process [2]. Several typologies of online shoppers have been developed in the past. Kau
60 Shopper Types and the Influence of Persuasive Strategies in E-Commerce
et al. [2] classified online shoppers into six categories based on the motivation and con-
cerns of online shoppers and their information seeking patterns. Rohm and Swamina-
than [1] identified shopper types based on the motivations of shoppers and proposed
four categories: convenience shoppers, variety seekers, balanced buyers and store-ori-
ented shoppers. According to the authors, the convenience shoppers are motivated by
online shopping convenience. Shoppers in this category do not typically seek immedi-
ate possession of their products. The variety seekers are more interested in seeking va-
riety of products across various retailers and brands. The balanced buyers are motivated
by the need to seek information online just like the variety seeker. However, the bal-
anced buyers plan their shopping ahead unlike the variety seekers. The store-oriented
shopper wants immediate possession of goods purchased and are more inclined to so-
cial interaction. Shoppers in this category prefer the feel of a physical store to an online
marketplace. We used this typology in our study because it focuses on online shopping
behavior and because the four categories identified by this typology are similar to that
of other researchers such as [2] and [6].
2.2 Persuasive Strategies
Persuasive strategies change peoples’ attitude or behavior without coercion or decep-
tion [4]. Several persuasive principles exist such as Cialdini’s six influence principles:
reciprocation, commitment, consensus, liking, authority and scarcity [4]. The principle
of reciprocation suggests that human societies subscribe to the rule of reciprocity,
hence, humans feel obligated to return a favor they have received in the past. The prin-
ciple of commitment suggests that humans tend to be consistent, therefore, it is likely
that people will honor things they have committed to. Consensus principle proposes
that people tend to manifest the same behavior and beliefs as others after observing
several people behaving in a similar manner. Authority principle suggests that because
humans are trained to believe in obedience of authority figures, hence in deciding what
action to take in any situation, information from people in authority could help humans
make decisions. Liking principle posits that people are more persuaded by some-
thing/someone they like. Scarcity strategy suggests that humans seemingly have a de-
sire for things that are scare, less readily available or limited in number.
These strategies have been used extensively in consumer studies and other domains,
thus, we adopted them in this study to explore how the various shopper types are influ-
enced by them.
3 Research Design and Methodology
In this study, we developed a path model using PLS-SEM to measure the susceptibility
of the four shopper types (convenience shoppers, variety seekers, balanced buyers and
store-oriented shoppers) to Cialdini’s six influence strategies reciprocation, commit-
ment, consensus, liking, authority and scarcity [4]. Figure 1 describes our model which
is made of four constructs that measure shopper type and six constructs that measure
Shopper Types and the Influence of Persuasive Strategies in E-Commerce 61
the six persuasive strategies. Shopper type was measured using Rohm’s scale [1] while
the persuasive strategies was measured using the scale of kaptein [7].
Fig. 1. Research model. All paths assumed positive. CONV = Convenience shopper, STOR =
Store oriented buyer, BALA = Balanced buyer, VARS = Variety shopper
Table 1. Demographics of participants
Demographics Value Frequency (%)
Age Less than 30 years 55
Between 30 and 49 40
Over 50 5
Gender Female 44
Male 56
Household size 1 to 3 people 63
4 to 5 people 34
6 or more people 4
Household income Less than US$30,000 40
Between US$ 30,000 and 75,000 42
Above US$ 75,000 18
Continent of origin Europe 8
Asia 35
North America 48
Others 9
To carry out this study, we recruited 226 e-commerce shoppers through Amazon’s
mechanical Turk (AMT), online social media and news boards. We used AMT because
we wanted a diverse set of participants and because AMT is an accepted method of
recruiting participants [3]. We have successfully used online social media and news
62 Shopper Types and the Influence of Persuasive Strategies in E-Commerce
boards in the past with success [8], thus, we used them in this study. This study was
approved by the ethics board of the University of Saskatchewan. Table 1 describes the
demographics of our participants.
4 Data Analysis and Results
The aim of this paper is to examine the susceptibility of the four shopper types (con-
venience shoppers, variety seekers, balanced buyers and store-oriented shoppers) to
Cialdini’s six influence strategies: reciprocation, commitment, consensus, liking, au-
thority and scarcity. To achieve this, we carried out structural equation modelling using
the SmartPLS tool. We determined the reliability and validity of our constructs and the
relationships between the indicators and constructs as recommended in structural equa-
tion modelling [9]. Indicator reliability, composite reliability, convergent validity (us-
ing Average Variance Extracted - AVE) and discriminant validity were all met as re-
quired for structural equation modelling [9].
After establishing the reliability and validity of the constructs in our model, we ex-
amined the structural model. We computed the coefficients of determination (R2 values)
and the degree and significance of the path coefficients. Table 2 shows the path coeffi-
cients between constructs. The number of asterisks represents the degree of significance
of each direct effect. The number of asteriks ranges from 1 to 4 which corresponds with
the p-value of <0.05, <0.01, <0.001 and <0.0001 respectively.
Table 2. Path coefficient between constructs and their significance. AUTH = Authority,
COMM = Commitment, CONS = Consensus, LIKE = Liking, RECI = Reciprocity, SCAR =
Scarcity. n.s. = Not significant, *=P <0.05, **=p <0.01, ***=p<0.001 and ****=p<0.0001
AUTH COMM CONS LIKE RECI SCAR
Balanced 0.116 n.s. 0.327**** -0.078 n.s. -0.062n.s. 0.126 n.s. -0.054 n.s.
Buyer
Conven- 0.186** 0.203** 0.138 n.s. 0.240** 0.259**** 0.295*
ience
Shopper
Store 0.142* 0.084 n.s. 0.276**** 0.200* 0.105 n.s. 0.209*
Oriented
shopper
Variety 0.260** 0.153 n.s. 0.211*** 0.240** 0.170* 0.173 n.s.
seeker
Our result suggests significant differences of the shopper types to the susceptibility
of the persuasive strategies. Balanced buyer had the highest influence on the influence
strategy commitment and had insignificant effects on the other strategies. This suggests
that balanced buyers are likely susceptible to commitment strategy. According to the
commitment strategy [4], because people typically try to be consistent in nature, getting
people to commit to a behavior will likely mean that they will carry out that behavior
Shopper Types and the Influence of Persuasive Strategies in E-Commerce 63
in order to remain consistent. Therefore, getting balanced buyers to commit to a behav-
ior could likely lead to them carrying out the behavior because they are susceptible to
commitment strategy.
Convenience shopper had the highest influence on scarcity, while store-oriented
buyer had the highest influence on consensus. Variety shopper on the other hand had
the highest effect on authority.
4.1 Gender Based Multi-Group Analysis
In order to understand the moderating role of gender in the susceptibility of shopper
types to Cialdini’s six influence strategies, we carried out multi-group analysis between
male and female participants. Our result is shown in table 3; it describes only the sig-
nificant differences between females and males. The result suggests some significant
differences between females and males. Of worthy mention is the influence of shopper
type variety seeker on the influence strategy scarcity which is significant for males
(p=0.361**) and insignificant for females (p=0.026 n.s.). This suggests that male variety
seekers are susceptible to the influence strategy scarcity. Thus, when presenting prod-
uct descriptions to male variety seekers, using strategies that describe scarcity could
lead to the desired behavior change. One such strategy is Amazon 1’s use of “items left
in stock” to show that an item is about to be scarce. On the other hand, female conven-
ient shoppers are significantly susceptible to the influence strategy scarcity (p=0.384**)
while the male convenient shoppers are not (p=0.075 n.s.). Thus, when presenting prod-
uct descriptions to female convenient shoppers, using strategies that describe scarcity
could lead to the desired behavior change.
Table 3. Path coefficient between constructs and their significance for paths with significant
differences between females and males. COMM = Commitment, CONS = Consensus, LIKE =
Liking, RECI = Reciprocity, SCAR = Scarcity. n.s. = Not significant, *=P <0.05,
**=p <0.01, ***=p<0.001 and ****=p<0.0001
COMM CONS LIKE RECI SCAR
Balanced Female 0.257** -0.169n.s. -0.148n.s. 0.057n.s.
Buyer Male 0.538**** 0.185* 0.132* 0.341***
Convenience Female 0.384**
Shopper Male 0.075n.s.
Store Oriented Female
shopper Male
Variety Female 0.026n.s.
seeker Male 0.361**
This study is still ongoing; in the future, we will explore the moderating role of age
and culture on susceptibility of the shopper types to the persuasive strategies. In addi-
tion, we will explore and list specific recommendations that can be applied in e-com-
merce for each of the significant findings.
1 amazon.com
64 Shopper Types and the Influence of Persuasive Strategies in E-Commerce
5 Conclusion
In this work in progress paper, we explored the susceptibility of different shopper types
to Cialdini’s six influence strategies. Shopper types are used to categorize shoppers
based on their shopping motivation and has been shown to help companies better un-
derstand the attitude of customers and what they look out for in their shopping decision-
making process. In order to tailor influence strategies to the various shopper types and
increase their efficacy, we explore the influence of shopper types on the six persuasive
strategies reciprocation, commitment, consensus, liking, authority and scarcity. The re-
sults of the structural equation modeling carried out on 226 e-commerce shoppers sug-
gest significant differences of the various shopper types’ susceptibility to the persuasive
strategies. In particular, balanced buyer shopper type had the highest influence on the
strategy commitment and had insignificant effects on the other strategies. This suggests
that balanced buyers are likely susceptible to commitment strategy. In addition, con-
venience shopper had the highest influence on scarcity, while store oriented buyer had
the highest influence on consensus. Variety shopper on the other hand had the highest
effect on the influence strategy authority. We further explored the moderating effect of
gender on our model. The result of the multi-group analysis between females and males
suggests that the male variety seekers are susceptible to the influence strategy scarcity,
while the female convenient shoppers are significantly susceptible to scarcity. This
study is still ongoing; in the future, we plan to explore the moderating effect of other
demographic variables of the participants.
6 References
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[4] R. B. Cialdini, Influence: Science and practice, vol. 4. Pearson Education
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[5] M. Kaptein and P. Parvinen, “DYNAMICALLY ADAPTING SALES
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