ArticlePDF Available


Purpose: In this invited paper, the authors aim to offer an integrated marketing communications (IMC) framework for understanding how disparate customer touchpoints impact consumer engagement and profitability in an omni-channel environment. For each aspect of the framework, the authors recommend areas for further research. Design/methodology/approach: The authors review literature linking personal and electronic channels of communication in an omni-channel context to consumer engagement, with an emphasis on channel and message unity. Findings: Five major research areas were identified: research that better links omni-channel and IMC theory and practice; conceptual and empirical research that helps operationalize the consumer-brand engagement construct, including its antecedents and consequences; build understanding of off- and on-line consumer-brand touchpoints and how they may enhance engagement and profitability; how omni-channel IMC best monetizes buyer-seller relationships; and omni-channel IMC in other consumer decision contexts. Practical implications: The emergence of omni-channel marketing is breaking down the silos across available consumer-brand touchpoints. The intersection of effective omni-channel marketing and IMC strategic and tactical initiatives offers marketers an opportunity to engage their customers and to form pro table relationships. Originality/value: The authors proposed an omni-channel IMC Framework and a research agenda for advancing the field. As this is a new area of inquiry, the authors argue for the development of other comprehensive frameworks and general omni-channel IMC conceptualizations.
Omni-channel marketing, integrated marketing communications, and
consumer engagement: A research agenda
Elizabeth Manser Payne
University of Wisconsin–Whitewater, Whitewater, Wisconsin, USA
James W. Peltier
University of Wisconsin–Whitewater, Whitewater, Wisconsin, USA
Victor A. Barger
University of Wisconsin–Whitewater, Whitewater, Wisconsin, USA
Purpose – In this invited paper, the authors aim to offer an integrated marketing
communications (IMC) framework for understanding how disparate customer touchpoints
impact consumer engagement and profitability in an omni-channel environment. For each aspect
of the framework, the authors recommend areas for further research.
Design/methodology/approach – The authors review literature linking personal and electronic
channels of communication in an omni-channel context to consumer engagement, with an
emphasis on channel and message unity.
Findings – Five major research areas were identified: research that better links omni-channel
and IMC theory and practice; conceptual and empirical research that helps operationalize the
consumer-brand engagement construct, including its antecedents and consequences; build
understanding of off- and on-line consumer-brand touchpoints and how they may enhance
engagement and profitability; how omni-channel IMC best monetizes buyer-seller relationships;
and omni-channel IMC in other consumer decision contexts.
Practical implications – The emergence of omni-channel marketing is breaking down the silos
across available consumer-brand touchpoints. The intersection of effective omni-channel
marketing and IMC strategic and tactical initiatives offers marketers an opportunity to engage
their customers and to form pro table relationships.
Originality/value – The authors proposed an omni-channel IMC Framework and a research
agenda for advancing the field. As this is a new area of inquiry, the authors argue for the
development of other comprehensive frameworks and general omni-channel IMC
Keywords – Social media marketing, Multi-channel measurement, Brand management, Web
2.0, Online consumer behavior, Integrated marketing communications
Paper type – Conceptual paper
Citation: Elizabeth Manser Payne, James W. Peltier, and Victor A. Barger (2017), “Omni-
channel marketing, integrated marketing communications, and consumer engagement: A
research agenda,” Journal of Research in Interactive Marketing, 11(2), 185-197.
The rapid expansion of communication technologies has greatly increased the
opportunity for consumers to engage with brands when and where they choose (Rangaswamy
and van Bruggen, 2005). One consequence of this increasingly diverse array of personal and
electronic touchpoints is the need to seamlessly integrate messaging strategies and tactics across
multiple channels and the customer life cycle (Neslin and Shankar, 2009). This need has been
magnified in recent years due to the increased ability of consumers to select the channels they
use (Bell et al., 2014) and the presence of user-generated content, which may contribute to or
detract from message consistency (Schultz and Peltier, 2013). Marketers have been slow to re-
align their cross-channel communication programs with brand messaging strategies that are
consistent across consumer touchpoints (Ots and Nyilasy, 2015).
Although the merits of message unification are apparent, it is a challenge to achieve due
to the various ways consumers learn about, interact with, and share information about brands
(Cummins et al., 2014). As a result, a small but growing stream of research has emerged
investigating how diverse communication platforms can be leveraged to drive an “omni-channel”
approach to brand engagement, where consumers move freely between personal and online
communications as part of a “single” transaction environment. The unification of the brand
experience is thus not specific to one or more channels; rather, it is a result of a holistic approach
to integrated marketing communications (IMC) (Hansen and Sia, 2015).
Despite the growing literature investigating the interactions among marketing channels,
IMC, and consumer engagement, there has been little research in an omni-channel domain that
pertains to brand and channel choice (Kushwaha and Shankar, 2013, Li and Kannan, 2014,
Neslin et al., 2014). Even less is understood about how the IMC process impacts path-to-
purchase and conversion-to-sales as part of a single-transaction environment (Verhoef, 2012,
Brynjolfsson et al., 2013, Li and Kannan, 2014). Moreover, the extant research is virtually silent
on how information consistency (and inconsistency) across customer touchpoints in an omni-
channel environment affects customer satisfaction, engagement, and loyalty (Verhoef et al.,
2015, Fulgoni, 2016, Swoboda et al., 2016).
In this paper, we offer an IMC framework for understanding how disparate customer
touchpoints impact consumer engagement and profitability in an omni-channel environment (see
Figure 1). We review literature linking personal and electronic channels of communication in an
omni-channel context to consumer engagement, with an emphasis on channel and message unity.
Our framework also responds to calls for conceptual research that investigates omni-channel
through the lens of customer profitability, directly or indirectly through brand engagement
(Broussard, 2016). We next discuss the theoretical foundations of omni-channel marketing and
the role of IMC. We then provide a brief review of the literature linking omni-channel
touchpoints to engagement and profitability. For each aspect of the framework we suggest
fruitful areas for further research (Table 1).
Conceptual Development
Omni-channel marketing has conceptual underpinnings in two interrelated disciplines:
multi-channel marketing and IMC (Cummins et al., 2016). Below we discuss these concepts and
their relationship to omni-channel marketing.
Multi-Channel Marketing
Neslin et al. (2006) define multi-channel management as “the design, deployment,
coordination, and evaluation of channels to enhance customer value through effective customer
acquisition, retention, and development” (p. 96). In multi-channel marketing, marketers are thus
challenged to communicate and deliver goods and services via two or more synchronized
channels (Rangaswamy and van Bruggen, 2005). From a brand experience perspective,
marketers need to effectively manage interactive customer relationships according to customers’
channel preferences. These channels may include printed catalogs, telephone, kiosks, direct mail,
brick-and-mortar retail stores, digital media, including e-commerce and mobile platforms, among
others (Kushwaha and Shankar, 2013). Indeed, it is in the marketer’s interest to do so, as
research has shown that multi-channel consumers have higher lifetime values and are more loyal
buyers than uni-channel consumers (Kumar and Venkatesan, 2005, Venkatesan et al., 2007).
Multi-channel marketing is not without its limitations, however. These include siloing of
channel utility, narrow channel scope, lack of integration of channels/touchpoints in the buying
process, and inadequate consideration of how channels independently and jointly impact the
brand experience (Rangaswamy and van Bruggen, 2005, Cummins et al., 2016). In practice,
marketing channels have often been created and managed separately with little integration
(Verhoef, 2012). The meteoric growth of mobile platforms as a consumer touchpoint has
necessitated a change in perspective, from one of channel preferences to that of viewing all
channels as part of a singular brand experience (Verhoef et al., 2015).
Integrated Marketing Communications
IMC plays an important role in cross-channel synchronization. IMC has been defined as
“an audience-driven business process of strategically managing stakeholders, content, channels,
and results of brand communication programs” (Kliatchko, 2008, p. 140). “Interactive” IMC
emphasizes bringing together multiple consumer touchpoints, media, and messages (Peltier et al.,
2002). This interaction, along with emerging technologies, offer marketers the opportunity to
tailor how they communicate with consumers and in which forms (Kim et al., 2004). Although
scholars differ in terms of specific strategic approaches to effective IMC (cf. Duncan and
Moriarty, 1998, Kitchen and Schultz, 2001), the underlying concept is based on a core principle,
namely information consistency across messaging platforms (Moriarty and Schultz, 2012).
As with multi-channel marketing, a major complaint of IMC is the existence of
organizational silos, which impede the marketer’s ability to create unified messaging solutions,
address changing channel communication priorities, and optimize path-to-purchase (Peltier et al.,
2006, Cao, 2014). Much of the blame lies in problems associated with organizational
complacency and capabilities, particularly with regard to organizational structure, organizational
culture, interfunctional communications, information sharing, and technological assets (Peltier et
al., 2013, Ots and Nyilasy, 2015). This is unfortunate, as true IMC can lead to superior
communication campaigns that improve brand outcomes, such as market share and financial
performance (Luxton et al., 2015).
Omni-Channel Marketing
Although underdeveloped as a theoretical construct, omnis is Latin for “all” or
“universal”, meaning “all channels together” (Juaneda-Ayensa et al., 2016). Omni-channel
marketing thus follows a customer-centered focus featuring a “holistic” shopping experience,
one in which a customer’s buying journey is smooth and seamless, irrespective of the channels
used (Gupta et al., 2004, Shah et al., 2006). In this regard, in an omni-channel environment the
most critical interaction is not with the channel but with the brand (Piotrowicz and Cuthbertson,
2014). Seeking to maximize customer relationships, Verhoef et al. (2015, p. 176) defined omni-
channel management as the “synergistic management of the numerous available channels and
customer touchpoints, in such a way that the customer experience across channels and the
performance over channels is optimized.” Combined, these definitions operationalize omni-
channel marketing based on two key areas: how customers get the information and how
transactions are fulfilled (Bell et al., 2014).
Multi-channel marketing, IMC, and omni-channel marketing all share similar traits,
particularly with regard to message consistency across customer touchpoints. One of the key
differences lies in the firm’s approach to digital channels. Specifically, firms seeking to optimize
performance for each channel are practicing multi-channel marketing, whereas firms focusing on
overall customer profitability across all channels are employing omni-channel marketing
(Verhoef et al., 2015). This distinction has become more important as mobile platforms have led
to disruptive changes in the retail space (Rigby, 2011). Mobile platforms are thus a core
component of omni-channel marketing, blurring traditional cross-channel boundaries
(Brynjolfsson et al., 2013).
The transition to omni-channel marketing has further increased the need for an interactive
IMC orientation, in which organizational silos are diminished in favor of communication
synergies that enhance customer engagement vis-à-vis a unified brand experience (Hansen and
Sia, 2015). Instead of viewing communication touchpoints in the context of customer choices,
omni-channel marketing requires a unification of the total collection of available tools and
platforms into a single-choice environment (Cummins et al., 2016). This evolution enhances the
ability of firms to more quickly convert prospects into high-valued customers by creating a
personalized information-acquisition-and-use environment (Rocco and Bush, 2016). Omni-
channel IMC is thus not simply a “tactical tool,” but a key strategic element for creating platform
and message consistency across the entire organization (Porcu et al., 2012).
Omni-Channel IMC Framework
To guide future research in this area, we offer the omni-channel IMC framework shown
in Figure 1. In the following sections, we discuss the key components—consumer touchpoints,
brand engagement, and customer profitability—as well as potential moderators, including cross-
touchpoint unity, touchpoint utility, digital device used, customer lifecycle, product vs. service,
hedonic vs. utilitarian purchases, and consumer characteristics. While we acknowledge that the
framework is not exhaustive, it does reflect issues related to omni-channel IMC research needs.
Table 1 presents a more detailed list of research needs.
—Insert Figure 1—
—Insert Table 1—
Consumer Touchpoints
The importance of consumer touchpoints to brands is growing at a meteoric pace
(Quesenberry et al., 2012). This is due to five forces of change: (1) science and technological
advances, (2) proliferation of media landscapes, (3) skeptical and empowered consumers, (4) a
turbulent and hyper-connected world, and (5) disruptive new business and revenue models
(Wind and Hays, 2016a). Consumer touchpoints have been conceptualized in a number of ways.
For example, Baxendale et al. (2015) define a consumer touchpoint as an “episode of direct or
indirect contact with the brand” (p. 236). Recognizing the integrative potential of these
touchpoints, Wind and Hays (2016a) define touchpoint value creation as “the ongoing,
synergistic orchestration and optimization of all touchpoint value creation among an enterprise,
the people in its network, the people it seeks to reach and serve, and the societies and cultures in
which it exists and has responsibility.”
Researchers have identified a number of brand touchpoints, including traditional media,
in-store, telephone, salesforce, catalogs, customer service, payments, returns, loyalty programs,
digital, e-mail, paid and organic search, display ads, tradeshows, and interactive TV (Peltier et
al., 2003, Zahay et al., 2004, Li and Kannan, 2014, Baxendale et al., 2015, Broussard, 2016,
Wind and Hays, 2016a, Wind and Hays, 2016b). In Figure 1, we categorize brand touchpoints as
personal and non-personal. We define personal brand touchpoints as those in which consumers
and brand personnel have direct contact, face-to-face or digitally. Non-personal brand
touchpoints are those in which consumers interact with the brand without a personal encounter at
the time of contact. Both personal and non-personal touchoints may evolve over time.
Research Needs. Relatively little is known about the nature and scope of brand
touchpoints. For example, the number and variety of brand touchpoints that consumers utilize
pre- and post-purchase are rarely taken into account in the decision making process (Li and
Kannan, 2014). Given the proliferation of brand interactions, research conceptualizing the
overall parameters of each touchpoint and how they are dispersed across multiple buying
situations and decision scenarios has value. Specific research investigating shopper behavior
across touchpoints and the firm’s omni-channel retail mix is particularly promising (Verhoef et
al., 2015). Given the importance of cross-touchpoint message unity, research exploring firms’
IMC decision-making processes and the resulting IMC touchpoint tactics is also warranted.
Looking forward, the rapidly evolving nature and complexity of brand touchpoints argues for
research that forecasts future developments (Ots and Nyilasy, 2015, Fulgoni, 2016).
Consumer-Brand Engagement
Although consumer-brand engagement is not a new construct, there is surprisingly little
consensus regarding how to define it and how it should be measured (Schultz and Peltier, 2013).
For example, Hollebeek et al. (2014) define consumer-brand engagement as “a consumer’s
positively valenced brand-related cognitive, emotional and behavioral activity during or related
to focal consumer/brand interactions” (p. 154). In contrast, and recognizing the psychological
and contextual nature of consumer-brand engagement, Calder et al. (2016) define it as a
“psychological state that occurs by virtue of interactive, co-creative customer experiences with a
focal agent/object, under a specific set of context-dependent conditions, and exists as a dynamic,
iterative process in which other relational concepts are antecedents and/or consequences” (p. 40).
Part of the conceptual fuzziness is due to the proliferation of new touchpoints, which has resulted
in a general naiveté for how to measure consumer-brand engagement (Barger and Labrecque,
2013, Schivinski et al., 2016). This proliferation along with growing fragmentation of consumer-
brand touchpoints have increased the complexity of tracking, coordinating, and measuring
engagement (King et al., 2014, Straker et al., 2015).
Consumer-brand engagement has a wide array of consequences, which can be
categorized into brand effects, product effects, consumer effects, content effects, and market
effects (Barger et al., 2016). Brand effects are comprised of brand identity, awareness,
associations, personality, loyalty, advocacy, and perceived quality (Hamilton et al., 2014,
Graffigna and Gambetti, 2015, Schivinski and Dabrowski, 2015). Product effects include
outcomes such as attitude toward the firm’s product(s) and purchase frequency (Chakravarty et
al., 2010, Purnawirawan et al., 2012, Kronrod and Danziger, 2013, Purnawirawan et al., 2015).
Consumer effects are wide-ranging and include attitude self-prediction, consumer power, and
social capital (He and Bond, 2013, Labrecque et al., 2013, Pinho, 2013, Moore, 2015). Content
effects relate to consumer attitudes towards brand-related content, such as product ratings and
reviews, user-generated content, and re-sharing intentions (Berger and Iyengar, 2013, Huang et
al., 2013, Swani et al., 2013, Fulgoni, 2014, Herhausen et al., 2015, Kim et al., 2015). Lastly,
market effects focus on campaign effectiveness, purchase intentions, sales, willingness to pay,
conversion rates, and market level changes (Jiménez and Mendoza, 2013, Ludwig et al., 2013,
Langley et al., 2014, Dolbec and Fischer, 2015, Luxton et al., 2015).
Research Needs. The consumer-brand engagement construct is not well-defined, and
research is needed on the general parameters of engagement, particularly as a path-to-purchase
process from consumer touchpoints (Baxendale et al., 2015). A better understanding of the
explanatory power of different consumer-brand engagement metrics offers insights into better
evaluation and assessment (Barger et al., 2016). Taking a more granular approach, conceptual
and empirical research investigating the independent and joint impact that divergent consumer-
brand touchpoints have on brand loyalty offers considerable promise (Acar and Puntoni, 2016).
Customer Profitability
Consumer-brand engagement by itself is an insufficient measure of the effectiveness of
omni-channel IMC strategies and tactics. Although consumer-brand touchpoints may impact
engagement metrics, in the end the long-term success of a firm’s marketing efforts depends on
profitability measures such as conversions, margins, ROI, sales, customer retention, and
customer lifetime value (Li and Kannan, 2014, Broussard, 2016). The evolution from a multi-
channel to an omni-channel perspective requires the assessment of customer profitability not as a
summation of the profitability of each channel but as an aggregation of all touchpoints. In this
way, the integrative power of customer touchpoints offers greater insight than touchpoint-by-
touchpoint profitability assessment (Verhoef et al., 2015).
Research Needs. Profitability evaluation within and across consumer-brand touchpoints is
in its infancy, and research that lays the conceptual foundation for assessing profitability is
warranted (Herhausen et al., 2015). Additionally, empirical research is needed on the
independent and interactive impact of consumer-brand touchpoints on customer profitability.
Literature on the linkage between varied consumer-brand engagement measures and profitability
is sparse, suggesting that considerable opportunity exists for research on the strongest drivers of
customer profitability (Kushwaha and Shankar, 2013, Barger et al., 2016, Grewal et al., 2016).
In our omni-channel IMC framework, we identify a number of constructs that could
moderate the path-to-purchase process. These moderators include cross-touchpoint unity,
touchpoint utility, digital device used, customer lifecycle, product vs. service contexts, hedonic
vs. utilitarian purchases, and consumer characteristics. As would be expected given the newness
of the omni-channel construct, research potential exists across a large swath of theoretical areas
(Herhausen et al., 2015, Grewal et al., 2016).
Research Needs. A key element of omni-channel marketing is “cross-touchpoint IMC
unity” across all consumer-brand touchpoints. Given the dearth of research in this area,
investigations of how information inconsistency across channels affects brand engagement and
consumer profitability are highly desirable (Hansen and Sia, 2015, Luxton et al., 2015, Ots and
Nyilasy, 2015, Wind and Hays, 2016b). Also promising is research that examines how omni-
channel IMC may differ for products vs. services, particularly with respect to path-to-purchase
(Baxendale et al., 2015). Likewise, omni-channel research on the decision-making process and
IMC effectiveness for hedonic vs. utilitarian purchases will provide insights into rational vs.
emotional path-to-purchase effects (Kushwaha and Shankar, 2013). Major gaps in the literature
also exist with regard to touchpoint utility for varied consumer goals, including information
seeking, purchasing, customer service, payment, returns, and loyalty programs (Bell et al., 2014,
Wind and Hays, 2016a). Given the growth in digital means of communicating with customers,
and especially with mobile as a key hub in omni-channel marketing, research addressing
similarities and differences based on choice of digital device is worthwhile (Brynjolfsson et al.,
2013, Acar and Puntoni, 2016, Fulgoni, 2016). Since consumer-brand engagement is generally
earned over time, studies that examine omni-channel IMC across the customer lifecycle, from
prospect to new buyer to long-term buyer, offer promise (Li and Kannan, 2014, Graffigna and
Gambetti, 2015, Cummins et al., 2016). Lastly, as a relatively new discipline, omni-channel IMC
research is ripe for study across wide-ranging consumer characteristics and theories, including
demographic, psychological, sociological, and behavioral theories of inquiry (Verhoef et al.,
2015, Swoboda et al., 2016).
The emergence of omni-channel marketing is breaking down the silos across available
consumer-brand touchpoints. The intersection of effective omni-channel marketing and IMC
strategic and tactical initiatives offers marketers an opportunity to engage their customers and to
form profitable relationships. In this paper we proposed an omni-channel IMC framework and a
research agenda for advancing the field. As this is a new area of inquiry, we argue for the
development of other comprehensive frameworks, both for general omni-channel IMC
conceptualizations and for each of the dimensions shown in Figure 1. Although many research
opportunities exist, we close with four major areas: general frameworks, consumer touchpoints,
consumer-brand engagement, and customer profitability.
First, because marketers often have difficulty creating synergy across channels, we see
value in research that better links omni-channel and IMC theory and practice. Special attention
should be given to comprehensive omni-channel/IMC frameworks that incorporate diverse
theoretical dimensions, address international and cross-cultural perspectives, focus on the role of
organizational learning, structure, culture, and vision in business-to-business vs. business-to-
consumer frameworks, and explore user-generated content and information sharing in omni-
channel environments.
Second, included in these broader frameworks, research is needed that defines and
operationalizes the meaning and scope of consumer-brand touchpoints in omni-channel
marketing. Specific conceptual focus should be on the relative impact of multiple touchpoints,
the most effective touchpoint combinations, and consumer-brand vs. peer-to-peer touchpoints.
Because of the ability to track and measure omni-channel relationships, research is needed that
seeks to better understand appropriate methods for tracking touchpoint perceptions, including
real-time tracking, discrete vs. relational relationships, earned media (publicity) as a touchpoint,
and effective resource deployment. With the emergence of mobile technologies, online-offline
channel integration, customer search, intention and purchase, and fulfillment touchpoints all
offer lucrative research agendas.
Third, consumer-brand engagement is one of marketing’s core principles and has been
studied in multiple contexts. We thus encourage conceptual and empirical research that helps
operationalize the consumer-brand engagement construct, including its antecedents and
consequences. For example, Barger et al. (2016) defined brand engagement relative to social
media as “a mutually beneficial process through which firms and consumers co-create brand-
related content and social experiences on social media.” Other definitions are needed for
different consumer-brand touchpoints, including research focusing specifically on the definition
and operationalization of consumer-brand engagement within and across touchpoints (e.g.,
engagement for social media vs. retail) and resulting affective and behavioral responses to these
Lastly, the rapidly emerging (and, in some cases, disappearing) ways in which customers
and brands interact call for research that builds understanding of off- and on-line consumer-
brand touchpoints and how they may enhance engagement and profitability. In that there is
limited research on omni-channel IMC in terms of customer or business profitability, the ground
is fruitful for research that provides clear evidence of how omni-channel IMC best monetizes
buyer-seller relationships. The measurement of consumer profitability in an omni-channel
framework offers considerable research promise, especially as related to analytical approaches to
assessing and modeling omni-channel touchpoint mix, the short- and long-term impact of
touchpoints and engagement, the role and use of big data and data quality, and the contribution to
brand equity. Because we studied omni-channel IMC in the context of consumer decisions,
virtually everything discussed in this paper plus additional theories need to be discussed in
business-to-business contexts as well, including direct and indirect effects on business metrics.
As shown in Figure 1, and in addition to research needs associated with general
frameworks, consumer touchpoints, consumer-brand engagement, and customer profitability, we
encourage conceptual and empirical research that investigates moderation and mediation effects.
This would include cross-touchpoint unity, digital vs. non-digital touchpoints, products vs.
services, hedonic vs. utilitarian purchases, customer lifecycle issues, and consumer
characteristics and theories.
Figure 1: Omni-Channel IMC Framework: Touchpoints, Engagement and Profitability
Consumer Touchpoints
Non-Personal Touchpoints
• Traditional advertising media
• In-store non-personal
• Direct mail
• E-mail
• Catalogs (hard copy and digital)
• Digital–website
• Digital–social media
• Paid and organic search
• Loyalty programs
• Mail returns
Personal Touchpoints
• In-store personal
• Field salesforce
• Telephone (inbound and outbound)
• Live digital chat/conferencing
• Trade shows
• In-store returns
Cross-touchpoint unity
Touchpoint utility: information, sales,
customer service, payment, returns, loyalty
Digital device: smartphone, tablet, laptop,
Customer lifecycle: prospect, new buyer, long-
term buyer
Product vs. service
Hedonic vs. utilitarian
Consumer characteristics and theories
Table 1: Omni-Channel IMC Research Needs
Theoretical Domain
Research Needs
General Frameworks
Additional comprehensive omni-channel/IMC frameworks incorporating varied theoretical dimensions (e.g., resource-
based view, WOM); international/global frameworks; role of organizational learning, structure, culture, and vision;
business-to-business and business-to-consumer frameworks; user-generated content; information sharing.
Consumer Touchpoints
Definition and operationalization of consumer-brand touchpoints; relative impact of multiple touchpoints; most
effective combinations; methods for tracking touchpoint perceptions; consumer-brand vs. peer-to-peer touchpoints;
real-time tracking; discrete vs. relational contexts; earned media (publicity) as a touchpoint; resource deployment;
impact of mobile technologies; onlineoffline channel integration and customer search; intention and purchase;
fulfillment touchpoints.
Consumer-Brand Engagement
Definition and operationalization of consumer-brand engagement within and across touchpoints (e.g., engagement for
social media vs. retail); affective response to touchpoints.
Customer Profitability
Measuring consumer profitability in an omni-channel framework; analytical approaches to assessing and modeling
omni-channel touchpoint mix; short- and long-term impact of touchpoints and engagement; role and use of big data and
data quality; brand equity.
Cross-Touchpoint Unity
Definition and operationalization of touchpoint unity and IMC; level of IMC consistency necessary for different
contexts; messaging strategies and appeals (e.g., emotional vs. rational); strategies and tactics for creating message
consistency across touchpoints; personalization and privacy; role of customer support touchpoints.
Touchpoint Utility
Digital vs. non-digital utility; orchestrating value creation across all touchpoints; differential goals and values for
varied touchpoints; social media and message sharing.
Digital Device
Comparing digital to non-digital utility; comprehensive frameworks and studies for touchpoints utilizing digital
marketing; location-based marketing; use of platforms (and apps) available digitally (e.g., long and short videos, social
Products vs. Services and
Hedonic/Utilitarian Purchases
Similarities and differences for products/services and hedonic/utilitarian purchases for all elements in the model;
interaction between products/services and hedonic/utilitarian purchases.
Customer Lifecycle
Mapping the customer journey; needs and decision processes by consumer lifecycle.
Consumer Characteristics and
Generational cohort analysis; user technology skills; target market differentiators; consumer search processes; attitude
formation; cognitive, affective, and behavioral theories.
Acar, O. A. and Puntoni, S. (2016), "Customer empowerment in the digital age", Journal of
Advertising Research, Vol. 56 No. 1, pp. 4-8.
Barger, V. A. and Labrecque, L. I. (2013), "An integrated marketing communications
perspective on social media metrics", International Journal of Integrated Marketing
Communications, Vol. 5 No. 1, pp. 64-76.
Barger, V. A., Peltier, J. W. and Schultz, D. E. (2016), "Social media and consumer engagement:
A review and research agenda", Journal of Research in Interactive Marketing, Vol. 10
No. 4, pp. 268-287.
Baxendale, S., Macdonald, E. K. and Wilson, H. N. (2015), "The impact of different touchpoints
on brand consideration", Journal of Retailing, Vol. 91 No. 2, pp. 235-253.
Bell, D. R., Gallino, S. and Moreno, A. (2014), "How to win in an omnichannel world", MIT
Sloan Management Review, Vol. 56 No. 1, pp. 45-53.
Berger, J. and Iyengar, R. (2013), "Communication channels and word of mouth: How the
medium shapes the message", Journal of Consumer Research, Vol. 40 No. 3, pp. 567-
Broussard, G. (2016), "Enriching media data: A special report from the U.S. Coalition of
Innovative Media Measurement", Journal of Advertising Research, Vol. 56 No. 1, pp. 25-
Brynjolfsson, E., Hu, Y. J. and Rahman, M. S. (2013), "Competing in the age of omnichannel
retailing", MIT Sloan Management Review, Vol. 54 No. 4, pp. 23-29.
Calder, B. J., Malthouse, E. C. and Maslowska, E. (2016), "Brand marketing, big data and social
innovation as future research directions for engagement", Journal of Marketing
Management, Vol. 32 No. 5-6, pp. 579-585.
Cao, L. (2014), "Business model transformation in moving to a cross-channel retail strategy: A
case study", International Journal of Electronic Commerce, Vol. 18 No. 4, pp. 69-96.
Chakravarty, A., Liu, Y. and Mazumdar, T. (2010), "The differential effects of online word-of-
mouth and critics' reviews on pre-release movie evaluation", Journal of Interactive
Marketing, Vol. 24 No. 3, pp. 185-197.
Cummins, S., Peltier, J. W. and Dixon, A. (2016), "Omni-channel research framework in the
context of personal selling and sales management: A review and research extensions",
Journal of Research in Interactive Marketing, Vol. 10 No. 1, pp. 2-16.
Cummins, S., Peltier, J. W., Schibrowsky, J. A. and Nill, A. (2014), "Consumer behavior in the
online context", Journal of Research in Interactive Marketing, Vol. 8 No. 3, pp. 169-202.
Dolbec, P.-Y. and Fischer, E. (2015), "Refashioning a field? Connected consumers and
institutional dynamics in markets", Journal of Consumer Research, Vol. 41 No. 6, pp.
Duncan, T. and Moriarty, S. E. (1998), "A communication-based marketing model for managing
relationships", Journal of Marketing, Vol. 62 No. 2, pp. 1-13.
Fulgoni, G. M. (2014), ""Omni-channel" retail insights and the consumer's path-to-purchase:
How digital has transformed the way people make purchasing decisions", Journal of
Advertising Research, Vol. 54 No. 4, pp. 1-4.
Fulgoni, G. M. (2016), "In the digital world, not everything that can be measured matters",
Journal of Advertising Research, Vol. 56 No. 1, pp. 9-13.
Graffigna, G. and Gambetti, R. C. (2015), The sustainable global marketplace: Proceedings of
the 2011 Academy of Market Science (AMS) annual conference, Springer.
Grewal, D., Bart, Y., Spann, M. and Zubcsek, P. P. (2016), "Mobile advertising: A framework
and research agenda", Journal of Interactive Marketing, Vol. 34, pp. 3-14.
Gupta, S., Lehmann, D. R. and Stuart, J. A. (2004), "Valuing customers", Journal of Marketing
Research, Vol. 41, pp. 7-18.
Hamilton, R., Vohs, K. D. and McGill, A. L. (2014), "We'll be honest, this won't be the best
article you'll ever read: The use of dispreferred markers in word-of-mouth
communication", Journal of Consumer Research, Vol. 41 No. 1, pp. 197-212.
Hansen, R. and Sia, S. K. (2015), "Hummel's digital transformation toward omnichannel
retailing: Key lessons learned", MIS Quarterly Executive, Vol. 14 No. 2, pp. 51-66.
He, S. X. and Bond, S. D. (2013), "Word-of-mouth and the forecasting of consumption
enjoyment", Journal of Consumer Psychology, Vol. 23 No. 4, pp. 464-482.
Herhausen, D., Binder, J., Schoegal, M. and Herrmann, A. (2015), "Integrating bricks with
clicks: Retailer-level and channel-level outcomes of online-offline channel integration",
Journal of Retailing, Vol. 91 No. 2, pp. 309-325.
Hollebeek, L. D., Glynn, M. S. and Brodie, R. J. (2014), "Consumer brand engagement in social
media: Conceptualization, scale development and validation", Journal of Interactive
Marketing, Vol. 28 No. 2, pp. 149-165.
Huang, J., Su, S., Zhou, L. and Liu, X. (2013), "Attitude toward the viral ad: Expanding
traditional advertising models to interactive advertising", Journal of Interactive
Marketing, Vol. 27 No. 1, pp. 36-46.
Jiménez, F. R. and Mendoza, N. A. (2013), "Too popular to ignore: The influence of online
reviews on purchase intentions of search and experience products", Journal of Interactive
Marketing, Vol. 27 No. 3, pp. 226-235.
Juaneda-Ayensa, E., Mosquera, A. and Murillo, Y. S. (2016), "Omnichannel customer behavior:
Key drivers of technology acceptance and use and their effects on purchase intention,"
Frontiers in Psychology, Vol. 7, pp. 1-11.
Kim, D.-H., Spiller, L. and Hettche, M. (2015), "Analyzing media types and content orientations
in Facebook for global brands", Journal of Research in Interactive Marketing, Vol. 9 No.
1, pp. 4-30.
Kim, I., Han, D. and Schultz, D. E. (2004), "Understanding the diffusion of integrated marketing
communications", Journal of Advertising Research, Vol. 44 No. 1, pp. 31-45.
King, R. A., Racherla, P. and Bush, V. D. (2014), "What we know and don't know about online
word-of-mouth: A review and synthesis of the literature", Journal of Interactive
Marketing, Vol. 28 No. 3, pp. 167-183.
Kitchen, P. J. and Schultz, D. E. (2001), Raising the corporate umbrella: Corporate
communications in the 21st century, Palgrave Macmillan, New York.
Kliatchko, J. G. (2008), "Revisiting the IMC construct: A revised definition and four pillars",
International Journal of Advertising: The Review of Marketing Communications, Vol. 27
No. 1, pp. 133-160.
Kronrod, A. and Danziger, S. (2013), "“Wii will rock you!” The use and effect of figurative
language in consumer reviews of hedonic and utilitarian consumption", Journal of
Consumer Research, Vol. 40 No. 4, pp. 726-739.
Kumar, V. and Venkatesan, R. (2005), "Who are the multichannel shoppers and how do they
perform? Correlates of multichannel shopping behavior", Journal of Interactive
Marketing, Vol. 19 No. 2, pp. 44-62.
Kushwaha, T. and Shankar, V. (2013), "Are multichannel customers really more valuable? The
moderating role of product category characteristics", Journal of Marketing, Vol. 77 No.
4, pp. 67-85.
Labrecque, L. I., vor dem Esche, J., Mathwick, C., Novak, T. P. and Hofacker, C. F. (2013),
"Consumer power: Evolution in the digital age", Journal of Interactive Marketing, Vol.
27 No. 4, pp. 257-269.
Langley, D. J., Hoeve, M. C., Ortt, J. R., Pals, N. and van der Vecht, B. (2014), "Patterns of
herding and their occurrence in an online setting", Journal of Interactive Marketing, Vol.
28 No. 1, pp. 16-25.
Li, H. and Kannan, P. K. (2014), "Attributing conversions in a multichannel online marketing
environment: An empirical model and a field experiment", Journal of Marketing
Research, Vol. 51 No. 1, pp. 40-56.
Ludwig, S., de Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M. and Pfann, G. (2013),
"More than words: The influence of affective content and linguistic style matches in
online reviews on conversion rates", Journal of Marketing, Vol. 77 No. 1, pp. 87-103.
Luxton, S., Reid, M. and Mavondo, F. (2015), "Integrated marketing communication capability
and brand performance", Journal of Advertising, Vol. 44 No. 1, pp. 37-46.
Moore, S. G. (2015), "Attitude predictability and helpfulness in online reviews: The role of
explained actions and reactions", Journal of Consumer Research, Vol. 42 No. 1, pp. 30-
Moriarty, S. E. and Schultz, D. E. 2012. Four theories of how IMC works. In: RODGERS, S.
and THORSON, E. (eds.) Advertising Theory. New York: Routledge.
Neslin, S. A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M. L., Thomas, J. S. and Verhoef,
P. C. (2006), "Challenges and opportunities in multichannel customer management",
Journal of Service Research, Vol. 9 No. 2, pp. 95-112.
Neslin, S. A., Jerath, K., Bodapati, A., Bradlow, E. T., Deighton, J., Gensler, S., Lee, L.,
Montaguti, E., Telang, R., Venkatesan, R., Verhoef, P. C. and Zhang, Z. J. (2014), "The
interrelationships between brand and channel choice", Marketing Letters, Vol. 25 No. 3,
pp. 319-330.
Neslin, S. A. and Shankar, V. (2009), "Key issues in multichannel customer management:
Current knowledge and future directions", Journal of Interactive Marketing, Vol. 23 No.
1, pp. 70-81.
Ots, M. and Nyilasy, G. (2015), "Integrated marketing communications (IMC): Why does it
fail?", Journal of Advertising Research, Vol. 55 No. 2, pp. 132-145.
Peltier, J. W., Schibrowsky, J. A. and Schultz, D. E. (2002), "Leveraging customer information
to develop sequential communication strategies: A case study of charitable-giving
behavior", Journal of Advertising Research, Vol. 42 No. 4, pp. 23-41.
Peltier, J. W., Schibrowsky, J. A. and Schultz, D. E. (2003), "Interactive integrated marketing
communication: Combining the power of IMC, the new media and database marketing",
International Journal of Advertising: The Review of Marketing Communications, Vol. 22
No. 1, pp. 93-115.
Peltier, J. W., Schibrowsky, J. A., Schultz, D. E. and Zahay, D. (2006), "Interactive IMC: The
relational-transactional continuum and the synergistic use of customer data", Journal of
Advertising Research, Vol. 46 No. 2, pp. 146-159.
Peltier, J. W., Zahay, D. and Lehmann, D. R. (2013), "Organizational learning and CRM
success: A model for linking organizational practices, customer data quality, and
performance", Journal of Interactive Marketing, Vol. 27 No. 1, pp. 1-13.
Pinho, J. C. (2013), "The eSOCAPIT scale: A multiitem instrument for measuring online social
capital", Journal of Research in Interactive Marketing, Vol. 7 No. 3, pp. 216-235.
Porcu, L., del Barrio-García, S. and Kitchen, P. J. (2012), "How Integrated Marketing
Communications (IMC) works? A theoretical review and an analysis of its main drivers
and effects", Comunicación y Sociedad, Vol. 25 No. 1, pp. 313-348.
Purnawirawan, N., De Pelsmacker, P. and Dens, N. (2012), "Balance and sequence in online
reviews: How perceived usefulness affects attitudes and intentions", Journal of
Interactive Marketing, Vol. 26 No. 4, pp. 244-255.
Purnawirawan, N., Eisend, M., De Pelsmacker, P. and Dens, N. (2015), "A meta-analytic
investigation of the role of valence in online reviews", Journal of Interactive Marketing,
Vol. 31, pp. 17-27.
Quesenberry, K. A., Coolsen, M. K. and Wilkerson, K. (2012), "IMC and The Effies: Use of
integrated marketing communications touchpoints among Effie award winners",
International Journal of Integrated Marketing Communications, Vol. 4 No. 2, pp. 60-72.
Rangaswamy, A. and van Bruggen, G. H. (2005), "Opportunities and challenges in multichannel
marketing: An introduction to the special issue", Journal of Interactive Marketing, Vol.
19 No. 2, pp. 5-11.
Rigby, D. K. (2011), "The future of shopping", Harvard Business Review, Vol. 89 No. 12, pp.
Rocco, R. A. and Bush, A. J. (2016), "Exploring buyer-seller dyadic perceptions of technology
and relationships: Implications for Sales 2.0", Journal of Research in Interactive
Marketing, Vol. 10 No. 1, pp. 17-32.
Schivinski, B., Christodoulides, G. and Dabrowski, D. (2016), "Measuring consumers'
engagement with brand-related social-media content: Development and validation of a
scale that identifies levels of social-media engagement with brands", Journal of
Advertising Research, Vol. 56 No. 1, pp. 64-80.
Schivinski, B. and Dabrowski, D. (2015), "The impact of brand communication on brand equity
through Facebook", Journal of Research in Interactive Marketing, Vol. 9 No. 1, pp. 31-
Schultz, D. E. and Peltier, J. W. (2013), "Social media's slippery slope: challenges, opportunities
and future research directions", Journal of Research in Interactive Marketing, Vol. 7 No.
2, pp. 86-99.
Shah, D., Rust, R. T., Parasuraman, A., Staelin, R. and Day, G. S. (2006), "The path to customer
centricity", Journal of Services Marketing, Vol. 9, pp. 113-124.
Straker, K., Wrigley, C. and Rosemann, M. (2015), "Typologies and touchpoints: Designing
multi-channel digital strategies", Journal of Research in Interactive Marketing, Vol. 9
No. 2, pp. 110-128.
Swani, K., Milne, G. and Brown, B. P. (2013), "Spreading the word through likes on Facebook",
Journal of Research in Interactive Marketing, Vol. 7 No. 4, pp. 269-294.
Swoboda, B., Weindel, J. and Schramm-Klein, H. (2016), "Crosswise and reciprocal
interdependencies within retailers’ multichannel structures", International Review of
Retail, Distribution, and Consumer Research, Vol. 26 No. 4, pp. 347-374.
Venkatesan, R., Kumar, V. and Ravishanker, N. (2007), "Multichannel shopping: Causes and
consequences", Journal of Marketing, Vol. 71 No. 2, pp. 114-132.
Verhoef, P. C. 2012. Multichannel customer management strategy. In: SHANKAR, V. and
CARPENTER, G. S. (eds.) Handbook of Marketing Strategy. Northampton, MA: Edward
Elgar Publishing.
Verhoef, P. C., Kannan, P. K. and Inman, J. J. (2015), "From multi-channel retailing to omni-
channel retailing: Introduction to the special issue on multi-channel retailing", Journal of
Retailing, Vol. 91 No. 2, pp. 174-181.
Wind, Y. and Hays, C. F. (2016a), Beyond advertising: Creating value through all customer
touchpoints, Wiley, Hoboken, New Jersey.
Wind, Y. and Hays, C. F. (2016b), "Of the "Beyond Advertising" paradigm: A model and
roadmap for creating value through all media and non-media touchpoints", Journal of
Advertising Research, Vol. 56 No. 2, pp. 142-158.
Zahay, D., Peltier, J. W., Schultz, D. E. and Griffin, A. (2004), "The role of transactional versus
relational data in IMC programs: Bringing customer data together", Journal of
Advertising Research, Vol. 44 No. 1, pp. 3-18.
... At every touchpoint, companies establish two-way communication with customers. According to IMC, all controlled touchpoints need to achieve consistent integration; in other words, this paradigm advocates for consistency and integration as key variables for marketing communications (Duncan and Moriarty 2006;Payne, Peltier, and Barger 2017;Šerić, Ozretić-Došen, and Škare 2020). Furthermore, as consumers move freely from one touchpoint/channel (e.g., website) to another (e.g., physical store), the company should offer a unified brand experience (Lee et al. 2019), which is only feasible if the company implements an integration strategy across channels, as is the aim in omnichannel marketing (Cai and Lo 2020;Lemon and Verhoef 2016). ...
... Consistent with this view, the customer is now at the core of IMC, which postulates that communication is no longer a one-way process; instead, the focus must be on communication with customers, with special emphasis on their role in generating brand content (Bruhn and Schnebelen 2017;Erdem et al. 2016;Finne and Grönroos 2017;Šerić, Ozretić-Došen, and Škare 2020;Vollero, Schultz, and Siano 2019). In the same vein, a critical part of the recent debate on omnichannel marketing focuses on how to optimize the consumer experience beyond the traditional operational dimension of channel integration (Lee et al. 2019;Miquel-Romero, Frasquet, and Molla-Descals 2020;Payne, Peltier, and Barger 2017). In sum, the new customer journey seeks to reconcile these two distinct, yet interconnected, theoretical perspectives by focusing on what they have in common -that is, (1) the need for integration, and (2) the need to follow a customer-centered approach. ...
... The customer journey and touchpoint concepts have been incorporated progressively to the IMC framework. In this regard, researchers state that in order to follow an IMC approach, all controlled touchpoints need to achieve consistent integration (Duncan and Moriarty 2006;Kuehnl, Jozic, and Homburg 2019;Reinold and Tropp 2012;Payne, Peltier, and Barger 2017). For instance, a company's brand page on Facebook has to resemble its corporate website, as well as its physical stores. ...
Full-text available
Digitalization and social media are transforming company-consumer interactions, opening new communication avenues. Companies are thus adopting an omnichannel strategy to offer multiple media and channels for use before, during, and after purchase-that is, during the customer journey. The success of this journey requires both effective integration of the company's offline and online channels and strong consistency in communication terms. In this context, offering a smooth transition between touchpoints along the consumer journey to optimize consumers' experience requires appropriate omnichannel integration. However, little is known about how to assess customer journey, despite the implications therein for companies' performance and consumer reactions. To fill this gap, the present paper proposes and validates indicators to measure the extent to which controlled touchpoints are really integrated and oriented toward the consumer and provide a satisfactory customer journey. Focusing on corporate website, brand pages on social network sites, apps, and physical stores as fully controlled touchpoints, we offer an instrument to assess integration and customer orientation , as well as avenues for further extension. Application of the indicators comprising the instrument reveals that integration is improving and customer-centric approach is gaining attention, but still has room for improvement. Theoretical and managerial contributions are discussed.
... This research considers only the impact of online activities and does not analyses impact of offline marketing (TV, radio, press, etc.) which can also impact online consumer behaviour. 49 In order to answer the above question, the role of the channel should be verified, which has already been done in the course of previous analyses (Table 10) and verification of significance for a particular function. Channel relevance is the ratio of the number of interactions within a given channel in one of the three functions (path openingfirst interaction, path sustaining -middle interaction, closing path -last interaction) to the total number of interactions for a given function. ...
Full-text available
The purpose of this paper is to verify the impact of missing the earned media and category media in multichannel conversion attribution models on digital media budget allocation. The analysis is based on a very unique approach: 532 users who declared their will to purchase a selected product in the next 3-5 months agreed to install special add-ons on all their devices connected to the Internet. These devices will register all the users' activities throughout three months. All user activities on the path to purchase were extracted by means of text mining (URL analysis) techniques. Finally, 5,171 activities were found and assigned to particular media areas and media channels. The average user spends 20 per cent of their time in the paid media and owned media areas. However, from the point of view of the number of touchpoints, 29 per cent of the activities occur in these two areas. The obtained results clearly show how much of consumers' activity in the decision-making process is beyond the control of marketers who, on the basis of this partial data, have to make daily decisions about allocating advertising budgets. The study compared the results of conversion attribution for the full funnel (paid media, owned media, earned media, category media) with the conversion attribution based only on paid media and owned media. The results indicate that not all attribution models lead to similar conclusions in both approaches.
... For retailers who wish to remain competitive, the rise of online shopping during the COVID-19 pandemic (Scott et al., 2020;Sheth, 2020) has made the provision of omnichannel retailingthe seamless integration of retail channels-and personalized customer experiences more important than ever (Lemon and Verhoef, 2016;Kannan and Li, 2017;Manser Payne et al., 2017;Piroth et al., 2020b). To develop these targeted, omnichannel marketing strategies, retail managers must understand the effects of consumers' underlying cognitive, affective, and behavioral tendencies (Puccinelli et al., 2009;Verhoef et al., 2009;Grewal and Roggeveen, 2020). ...
Full-text available
Nowadays, customers can utilize both online and in-store retail channels. Consequently, it is crucial for retailers to understand the possible drivers of retail channel selection, including customers’ personalities, degrees of trust, and product touch preferences. Unfortunately, current omnichannel research only scarcely addresses the effects of personality, trust, and desire to touch a product before purchasing it on willingness to purchase and how those effects vary between online and in-store shopping. Thus, we conducted an exploratory study. Our analysis of survey data ( N = 1,208)—which controls for respondents’ age, gender, and education—reveals that across both the willingness to purchase in-store and online, a higher level of e-vendor trust is a significant, positive predictor. However, we also identify several channel-related differences, including that Trust Propensity, as well as the Big Five traits of Extraversion, Agreeableness, and Conscientiousness are significantly positively related to in-store, but not online, purchase willingness. We also find that Instrumental Need for Touch (defined as goal-motivated touch of a product) is positively related to in-store, but negatively related to online, purchase willingness. Finally, we highlight opportunities for future research and discuss how retail managers might enhance customer experiences in their physical and online stores.
... Furthermore, the brand image should be consistent [24], and-especially relevant to the research conducted in this literature review-a promotional strategy should also be integrated across channels to facilitate the provision of a seamless customer experience [12,20]. Manser Payne, Peltier, and Barger [25] mention 'integrated marketing communications (IMC)' as a strategy to integrate the plethora of customer touchpoints, messages, and interactions; this can be seen as an approach of marketing that should be adopted by omni-channel retailers because, according to Yrjölä, Spence, and Saarijärvi [9] (p. 259) "without a clear strategic purpose, omni-channel initiatives can easily result in unbeneficial ( . . . ) investments". ...
Full-text available
The objective of this study is to ascertain the effects of omni-channel retailing on the promotional strategy of retail organisations in order to better understand how to alter the promotional strategy in accordance with the ever-changing needs of customers and ultimately provide the customer with a seamless experience. This research is based on a critical systematic literature review of articles related to the topics of ‘omni-channel retailing’ and ‘promotional strategy’. The analysis made evident that most literature is focused on developing an understanding of omni-channel retailing; uncovering consumer behaviours in omni-channel retailing; and ways to adapt promotional strategies related to merchandising, sales promotion, selling, and word of mouth. Past research is quite fractured and does not represent a holistic picture of the implications of omni-channel retailing for promotional strategy. The analysis provided in this paper provides a general guideline for researchers and practitioners concerning promotional strategies that can be adopted in omni-channel retailing.
... As claimed in previous literature, omnichannel research can be executed in three phases; developing, running, and monitoring (Saghiri et al., 2018). With literature review, it has been determined that research has been accomplished in regard to developing and running omnichannel retailing (Manser Payne et al., 2017;Saghiri et al., 2017;Larke et al., 2018;Wiener et al., 2018;Berman & Thelen, 2018;Marchet et al., 2018). Yet, no study has been executed concerning monitoring omnichannel retailing. ...
Purpose This study employed the commitment–trust theory in social psychology and relationship marketing to explore female customers' perception of channel integration quality in omnichannel retailing and its influence on their relationship commitment to and trust in the relationship with retailers, and thus on their stickiness. Channel integration quality consists of two dimensions: channel service configuration (channel choice breadth and channel service transparency) and integrated interactions (content consistency, process consistency and perceived fluency). Design/methodology/approach The study was carried out via a questionnaire survey, to which 868 valid responses were collected. The partial least squares technique was used to test the hypotheses. Findings Channel service transparency and perceived fluency influence relationship commitment; content consistency, process consistency and perceived fluency all have significant effects on trust. Interestingly, although less influential than integrated interactions, channel service configuration is the foundation of channel integration quality, testifying to its significant role. Originality/value This study provides strong evidence on how channel integration quality affects customer stickiness. Moreover, this study replicates the finding of significant relationships among relationship commitment, trust and stickiness in omnichannel retailing.
Even before the world wide web, integrated marketing communications (IMC) was gaining acceptance across all fields of business and industry. However, the explosion of online and mobile marketing has caused a convergence of marketing strategies at the same time that all forms of media are converging onto digital platforms. This has become more than just a “Digital Age.” For marketers it is the age of multimedia, the age of coordinated omnichannel communications with an increasing emphasis on mobile, the age of personalization, and an age that blends free and friendly inbound marketing with paid advertising that looks more and more like the organic content that surrounds it. This chapter explores the ongoing impact of the convergence of media, strategies and technologies on the 4 P's of the traditional marketing mix.
Purpose This study aims to examine the factors that motivate consumers’ omnichannel continuance intention from the utilitarian value perspective and to test the moderating role of product involvement. Design/methodology/approach Structural equation modeling was used to analyze the research model with data on 382 omnichannel consumers. Findings Three perceived utilitarian value dimensions – quality, monetary savings and convenience – positively influence consumers’ omnichannel continuance intention through their attitudes. Convenience is the main driver of consumers’ omnichannel shopping. Moreover, the effect of perceived quality on attitude is greater for consumers with low rather than high product involvement. Research limitations/implications This study refines the research on omnichannel consumer behavior, adds to the factors known to influence consumers’ omnichannel selection and identifies the critical role of product involvement in retaining consumers. However, it only investigates the basic dimensions of perceived utilitarian value and does not distinguish between types of omnichannel services. Future research can expand upon consumer intention by considering more utilitarian values and omnichannel services. Practical implications Omnichannel retailers should consider the significance of these findings in guiding consumer retention and channel integration. Specifically, they may suggest more convenient methods for shopping and measures of consumer product involvement to provide utilitarian value. Originality/value This study adds to the literature on omnichannel selection by investigating consumers’ continuance intention. Analyzing the effects of utilitarian value extends prior research on information systems, channel integration, supply chain management and consumer experience.
Purpose Understanding customer behavior from the perspective of channel integration has become a major stream of research in multi-channel retailing literature. Yet, despite recent advancements in scholarship, how retailers can most effectively sustain customers in online retailing remains unclear. Scholars have suggested online–offline channel integration (OOCI) as an effective multi-channel approach for increasing online loyalty; yet, few studies have explored OOCI's influencing mechanism. This study addresses that gap by investigating how OOCI helps achieve customer loyalty online and further examines the moderating role of retailer credibility in the influencing mechanism of OOCI. Design/methodology/approach The research model driving this study draws upon the stimulus-organism-response (S-O-R) model and cue consistency theory. The authors collected a sample of 259 customers in China with experience making multi-channel purchases from retailers that have implemented OOCI in online retailing. Structural equation modeling and response surface analyses were employed to conduct data analysis. Findings The results revealed that the relationship between OOCI and customers' online channel loyalty was mediated by customers' perceptions of the usefulness and risks of online channel usage. The results also found that congruence and incongruence between informational OOCI (IOOCI) and fulfillment OOCI (FOOCI) had different curvilinear associations with perceived online channel usefulness and perceived online channel risk. In addition, retailer credibility weakened the effects of IOOCI on perceived online channel usefulness and FOOCI on perceived online channel risk but strengthened the effect of IOOCI on perceived online channel risk and had no impact on the effect of FOOCI on perceived online channel risk. Originality/value Theoretical and practical implications of this study are also discussed.
Full-text available
Purpose: In “Social media’s slippery slope: challenges, opportunities and future research directions”, Schultz and Peltier (2013) asked “whether or how social media can be used to leverage consumer engagement into highly profitable relationships for both parties”. The purpose of this article is to continue this discussion by reviewing recent literature on consumer engagement and proposing a framework for future research. Design/methodology/approach: The paper reviews the marketing literature on social media, paying particular attention to consumer engagement, which was identified as a primary area of concern in Schultz and Peltier (2013). Findings: A significant amount of research has been conducted on consumer engagement since 2010. Lack of consensus on the definition of the construct has led to fragmentation in the discipline, however. As a result, research related to consumer engagement is often not identified as such, making it difficult for academics and practitioners to stay abreast of developments in this area. Originality/value: This critical review provides marketing academics and practitioners insights into the antecedents and consequences of consumer engagement and offers a conceptual framework for future research.
Full-text available
The advance of the Internet and new technologies over the last decade has transformed the retailing panorama. More and more channels are emerging, causing consumers to change their habits and shopping behavior. An omnichannel strategy is a form of retailing that, by enabling real interaction, allows customers to shop across channels anywhere and at any time, thereby providing them with a unique, complete, and seamless shopping experience that breaks down the barriers between channels. This paper aims to identify the factors that influence omnichannel consumers' behavior through their acceptance of and intention to use new technologies during the shopping process. To this end, an original model was developed to explain omnichannel shopping behavior based on the variables used in the UTAUT2 model and two additional factors: personal innovativeness and perceived security. The model was tested with a sample of 628 Spanish customers of the store Zara who had used at least two channels during their most recent shopping journey. The results indicate that the key determinants of purchase intention in an omnichannel context are, in order of importance: personal innovativeness, effort expectancy, and performance expectancy. The theoretical and managerial implications are discussed.
Full-text available
Mobile advertising allows retailers, service providers, and manufacturers to provide consumers with increasingly relevant offers. The success of such campaigns depends on an ever better understanding of environmental, consumer, and technological context variables; a strong focus on advertising goals; accounting for market factors related to the nature of stakeholders and market environment; and the use of appropriate mobile ad elements to improve relevant outcome metrics. This article provides an overarching framework to synthesize current findings in mobile advertising, as well as a research agenda to stimulate additional work in this nascent field.
Full-text available
This paper re-examines a definition of integrated marketing communications (IMC) previously published in this journal, and proposes a revision to that original definition. It reviews topics of research studies conducted on IMC since its inception to the present, and establishes that the theoretical foundations and definitional issues of IMC continue to be an important area of research for most academics. This paper introduces the four pillars of IMC as an offshoot of the proposed revised definition, and discusses each pillar in detail. The paper concludes by illustrating the interplay between the pillars and levels of IMC.
Full-text available
The growing number of consumer data sources with the complexity of integrations across multiple consumer touch points poses a challenge for end users to assess data quality. Gaining a better understanding of the underlying quality of data, to inform how best to deploy for advertising and marketing decisions, is the principal issue. The primary purpose of this study (conducted on behalf of the Coalition of Innovative Media Measurement [CIMM]) was to help inform the general media community about the quality, recency, consistency, and representative aspects of third -party data. The secondary purpose was to provide feedback on the industry's appetite for master data and reporting standardization.
Full-text available
The Internet and advances in digital technologies fundamentally are transforming marketing. Armed with an abundance of information and opportunities, consumers no longer accept the role of passive recipients of marketing communication. This is turning traditional communication approaches upside down
Full-text available
In 2006, the Advertising Research Foundation (ARF) provided one of the first marketing-focused definitions of “engagement” as “turning on a prospect to a brand idea enhanced by the surrounding context.”[1][1] The phrase “turning on” would appear to encompass any communication from a
The authors propose a communication-based model of relationship marketing and discuss how communication (rather than persuasion) is the foundation of the “new” customer-focused marketing efforts. The authors trace recent parallel shifts in communication and marketing theory and show the intersections between communication and marketing. Although communication always has been a critical element in marketing, the authors show how the increase in interactivity makes communication an even more valuable element of marketing by identifying those many points that link the two disciplines. Using the three key points at which the two disciplines intersect—messages, stakeholders, and interactivity—the authors develop a communication-based model of marketing. They demonstrate how interactive communication at three levels—corporate, marketing, and marketing communication—leads to the brand relationships that drive brand value.
“What if the most forward-thinking innovators from across disciplines and talents imagined what advertising and marketing could/should be, then provided steps to make it happen? What if all the forces of change now buffeting the advertising and marketing world came together to result in a far more desirable future?” These questions inspired authors Jerry Wind and Catharine Hays, creators of the Wharton Future of Advertising Program, to seek insight from more than 200 thought leaders from around the world in a massive project they called Advertising 2020. The responses, combined with Wind and Hays’ own research, formed the basis for their book, Beyond Advertising: Creating Value Through All Customer Touchpoints (John Wiley & Sons, 2016; Hoboken, NJ).1 We offer an adapted excerpt in the pages that follow. © 2016, World Advertising Research Center. All rights reserved.
Understanding consumer behavior across channels is the fundamental basis for implementing successful multichannel retailing strategies. This study analyzes the crosswise and reciprocal relationships between offline and online brand beliefs, offline and online retail brand equity and consumers’ conative loyalty to a retailer in multichannel structures. The relationships are contextualized by investigating fashion and grocery retail sectors and different prior channel performances that are likely to affect the paths to loyalty across channels. To provide insight into these issues, two cross-sectional and two longitudinal models are employed. The results show that former brick-and-mortar retailers are able to significantly increase consumers’ loyalty to the firm by primarily designing offline (secondary online) attributes and beliefs. The results hold for retailers in both fashion and grocery retailing, however, with stronger effects in fashion, as well as for retailers with strong vs. weak prior channel performance. However, indirect effects indicate that online brand beliefs and offline retail brand equity are the central strategic levers for prior strong (vs. weak) retailers. Reciprocal relationships between online and offline retail brands underline important channel interdependencies. Managers thus need to take these crosswise and reciprocal interdependencies between channels into account when designing successful multichannel retailing systems. This study introduces the novel idea of simultaneous crosswise and reciprocal relationships within multichannel retail structures and shows that paths to loyalty vary for retailers in different retail sectors and retailers with strong vs. weak offline and online channel performances.