Implementing social media marketing strategically: an empirical assessment

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Journal of Marketing Management

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Implementing social media marketing

strategically: an empirical assessment

Wondwesen Tafesse & Anders Wien

To cite this article: Wondwesen Tafesse & Anders Wien (2018): Implementing social media

marketing strategically: an empirical assessment, Journal of Marketing Management, DOI:

10.1080/0267257X.2018.1482365

To link to this article: https://doi.org/10.1080/0267257X.2018.1482365

Published online: 18 Jun 2018.

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Implementing social media marketing strategically:

an empirical assessment

Wondwesen Tafesse and Anders Wien

School of Business and Economics, UIT- The Arctic University of Norway, Tromsø, Norway

ABSTRACT

The purpose of this study is to examine how ﬁrms implement

social media systematically to drive strategic marketing actions.

To this end, the study conceptualises social media implementation

as a multidimensional, organisational construct composed of

social media strategy, active presence, customer engagement

initiatives and social media analytics. Using primary data, the

study operationalises the social media implementation construct

and tests its eﬀect on ﬁrm performance isolated into social media

performance and marketing performance. The results indicate that

all except the active presence dimension of social media imple-

mentation are positively related to social media performance. The

results further indicate that social media performance is positively

related to marketing performance. The study contributes to the

literature by oﬀering a novel conceptualisation and empirical

validation of the social media implementation construct.

ARTICLE HISTORY

Received 30 January 2018

Accepted 11 May 2018

KEYWORDS

Social media marketing;

social media

implementation; social

media strategy; social media

performance; marketing

performance

Introduction

The dramatic rise of social media has opened up new possibilities for marketers to

connect with their customers (Lamberton & Stephen, 2016). Social media facilitates a

dynamic space to reach customers, interact with them and leverage their voices for

greater impact (Hewett, Rand, Rust, & Heerde, 2016). However, ﬁrms struggle to

eﬀectively implement social media to drive strategic marketing actions. As ﬁrms

develop social media strategy, individual platforms are too often treated as stand-

alone elements rather than as parts of an integrated whole (Hanna, Rohm, &

Crittenden, 2011). Moreover, social media represents a rapidly evolving landscape,

which stresses the importance of a holistic perspective (Malthouse, Haenlein, Skiera,

Wege, & Zhang, 2013).

Social media marketing has attracted considerable research attention in recent years.

This research has illuminated relevant topics such as branded social media content

(Ashley & Tuten, 2015), customer engagement (Dessart, Veloutsou, & Morgan-Thomas,

2016), online brand communities (Brodie, Ilic, Juric, & Hollebeek, 2013) and social

media’s role in the marketing mix (Srinivasan, Rutz, & Pauwels, 2016). However, extant

research is largely bereft of a strategic perspective (Valos, Mapelstone, & Polonsky, 2017).

In particular, the critical issue of how ﬁrms implement social media to drive strategic

CONTACT Wondwesen Tafesse [email protected]

JOURNAL OF MARKETING MANAGEMENT

https://doi.org/10.1080/0267257X.2018.1482365

marketing actions has been neglected. The literature hardly oﬀers a holistic empirical

perspective on the systematic application of social media as a strategic marketing

platform (Lamberton & Stephen, 2016).

The purpose of this study is to investigate how ﬁrms implement social media system-

atically to drive strategic marketing actions. Although few prior studies have explored

social media implementation, those eﬀorts appear to lack both conceptual and mea-

surement precision. Prior studies have typically conceptualised social media implemen-

tation using the stages-of-growth approach – as a process that evolves in a linear

sequence of stages (Chung, Andreev, Benyoucef, & Duane, 2017;Eﬃng & Spil, 2016).

The challenge, however, is that the proposed stages are diﬃcult to empirically verify

(Solli-Saether and Gottschalk, 2010). At times, even seasoned managers have found it

diﬃcult to appraise their ﬁrms’ stage of social media development (Chung et al., 2017).

The ﬁrst contribution of this study is to conceptualise social media implementation as a

synchronous organisational process by which ﬁrms leverage social media to drive

strategic marketing actions. The study conceptualises social media implementation as

a multidimensional construct, with the construct itself and its dimensions clearly deﬁned

and operationalised.

Marketing research has also begun to address the eﬀect of social media on ﬁrm

performance (e.g. De Vries, Gensler, & Leeﬂang, 2017; Srinivasan et al., 2016), although

these eﬀorts are mostly focused on social media spending as a measure of ﬁrms’ social

media eﬀort. Consequently, important social media processes beyond spending, such as

social media strategy, active presence, customer engagement initiatives and data analy-

tics, have been ignored (Lamberton & Stephen, 2016; Valos et al., 2017). The second

contribution of this study is to link these social media processes to ﬁrm performance

partitioned into social media performance and marketing performance. Whereas social

media performance captures customer-based social media outcomes that result from

customers’ favourable perceptions, feelings or actions towards ﬁrms’ activities in social

media, marketing performance captures customer-based market outcomes that result

from customers’ purchase and post-purchase behaviours facilitated by social media.

Drawing on the marketing performance literature (Katsikeas, Morgan, Leonidas, & Hult,

2016), social media performance is posited as a precursor to marketing performance.

The ﬁndings shed light on how social media implementation contributes to ﬁrm

performance.

A third contribution of the study lies in operationalising the social media implemen-

tation

construct. To our knowledge, no measurement scale for social media implemen-

tation has appeared in prior literature. The measurement scale developed here meets all

the requirements of a reliable and valid measurement scale and can be employed in

future research to measure social media implementation and investigate its antecedents

and outcomes.

The remainder of the paper is structured as follows. The ‘Literature reviewʼ

section reviews the relevant literature with a focus on the deﬁnition, adoption

and implementation of social media in a marketing context. The ‘Hypothesesʼ

section introduces the hypotheses. The ‘Methodologyʼ section describes the meth-

odology. The remainder of the paper reports the results a nd discusses their

implications.

2 W. TAFESSE AND A. WIEN

Literature review

Social media: an overview

Kaplan and Haenlein (2010)deﬁned social media as ‘a group of internet-based applications

that build on the ideological and technological foundations of web 2.0, and that allow the

creation and exchange of user generated content’ (p. 61). The authors analysed social

media platforms according to their aﬀordances for self-presentation/self-disclosure and

social presence/media richness and classiﬁed them into blogs, social networking sites,

virtual social worlds, collaborative projects, content communities and virtual games.

Social media platforms facilitate a range of user functionality. Kietzmann, Hermkens,

McCarthy and Silvestre (2011) discussed these functions along seven major categories:

identity disclosure, conversations, sharing, presence (the extent to which users are aware of

other users’ availability), relationships, reputation management and groups (the extent to

which users can form communities). Among the main marketing implications of the proposed

social media functions are that marketers should facilitate tools for user self-promotion, they

should monitor and inﬂuence online conversations, they should develop content manage-

ment systems and they should facilitate real-time and intimate interactions with customers.

Hanna et al. (2011) highlighted the power of social media to create connections that

result in a vast social network. This vast network creates a media landscape that empowers

consumers to become ‘active participants in the media process’ (p. 267). As a result,

marketing is no longer solely about capturing attention via reach; instead, it must focus

on capturing and maintaining attention via interactivity and engagement. This focus on

customer interaction and engagement has important implications for social media imple-

mentation, including the need for a holistic social media strategy that integrates multiple

platforms into a seamless social media experience (Hanna et al., 2011;Tafesse,2016).

Stephen and Brat (2015) discussed three main types of information ﬂow that are facilitated

by social media. First, social media allows for ﬁrm-to-consumer information ﬂow in the form of

brand posts and social media ads (Hewett et al., 2016). Second, social media facilitates

consumer-to-ﬁrm information ﬂow in the form of comments, reactions, sentiments and user

generated content (Gensler, Volckner, Liu-Thompkins, & Wiertz, 2013). Finally, social media

facilitates interactions among consumers themselves, which can take the form of WOM or

brand communities (Dessart et al., 2016). The major implication of Stephen and Brat’s(2015)

discussion is that ﬁrms need to acquire new organisational skills, such as customer engage-

ment and data analytics, in order to leverage social media’s information-rich environment and

to create value (Choudhury & Harrigan, 2014; Harrigan, Soutar, Choudhury, & Lowe, 2015).

To summarise, there is growing recognition in the literature about the nature and

dynamics of social media and their implications for marketing. The challenge for market-

ers is to implement social media eﬀ

ectively in ways that advance their ﬁrms’ strategic

marketing

goals (Berthon, Pitt, Plangger, & Shapiro, 2012).

Social media adoption versus implementation

In this section, we succinctly summarise the literature on the adoption and implementa-

tion of social media before we introduce our conceptualisation of social media

implementation.

JOURNAL OF MARKETING MANAGEMENT 3

Research on ﬁrm adoption of social media is scant, although few publications

have appeared in recent years (Par veen et al., 2015). Extant research has typically

conceived of social media adoption in terms of the possession (or dispossession) of

social media technologies. For instance, Harrigan et al. (2015)consideredsocial

media adoption in terms of the number of social media platforms that ﬁrms incor-

porated in their social media programmes. Among the platforms considered in that

study were Facebook, Twitter, LinkedIn, YouTube, corporate blogs and mobile apps.

Others expanded on this approach by embracing a more functionalist perspective,

thereby shifting the emphasis from the mere po ssessi on of social media platforms to

the organisational functions that they support (Parven et al., 2015). For instance,

Trainor, Andzulis, Rapp and Agnihotri (2014), t aking a CRM persp ective, identiﬁed

four broad functions of social media: information sharing, conversations, relationships

and online brand communities.

However, the social media adoption literature has failed to illuminate the critical issue

of how ﬁrms eﬀectively implement social media. The mere emphasis on possession of

social media technologies disguises important social media processes that shape their

eﬀective utilisation. Social media implementation deals with both the adoption and

utilisation of social media (Habibi, Hamilton, Valos, & Callaghan, 2015; McCann & Barlow,

2015). It is concerned with the decisions and actions taken by ﬁrms to put social media

to eﬀective marketing use. Only a few studies have empirically probed social media

implementation along this line (e.g. Chung et al., 2017;Eﬃng & Spil, 2016; Mergel &

Bretschneider, 2013). These studies suggest that ﬁrms implement social media, over

time, in a linear sequence of stages, and, typically, they identify benchmark variables

against which the progress of ﬁrms is assessed.

For instance, Eﬃng and Spil (2016) proposed three broad stages of social media

implementation: initiation, diﬀusion and maturity. These stages are anchored in seven

benchmark variables consisting of target audience, channel choice, goals, resources,

policies, monitoring and content activities. The authors suggested monitoring and

content activities as the principal markers of social media maturity. Chung et al. (2017)

proposed ﬁve stages of social media implementation: experimentation and learning,

rapid growth, formalisation, consolidation and integration and institutional absorption.

Their model was based on eight benchmark variables consisting of strategy, business

processes, structure, adopted technologies, application of technologies, impact on

internal stakeholders, impact on external stakeholders and ROI. Here, business process

and external stakeholders are indicated as the main markers of social media consolida-

tion and integration.

Overall, the staged models of social media implementation are characterised by

incremental levels of formalisation and resource commitment. Firms at advanced stages

are presumed to formalise and institutionalise social media to coordinate complex tasks.

Although these models illuminate the path to social media maturity, their value for

research is hampered by the diﬃculty of empirically verifying the proposed stages (Solli-

Saether and Gottschalk, 2010). At times, even seasoned managers have found it diﬃcult

to appraise their ﬁrms’ stage of social media development (Chung et al., 2017). The

benchmark variables lack speciﬁcity, and the proposed stages are too broad, rendering

the models unwieldy for operationalisation.

4 W. TAFESSE AND A. WIEN

A proposed conceptualisation of social media implementation

The limitations associated with the stages-of-growth models call for a more precise

conceptualisation of social media implementation. As indicated earlier, social media

implementation is concerned with the decisions and actions taken by ﬁrms to put social

media to eﬀective marketing use. It is about leveraging the reach, interactivity and

engagement attributes of social media to drive strategic marketing actions (Hanna et al.,

2011). More formally, social media implementation can be deﬁned as the process by

which ﬁrms employ social media strategically, for customer-facing purposes, by producing

content regularly, engaging customers in an ongoing relationship and generating analytics

and customer insights to drive strategic marketing actions. Several aspects of the pro-

posed deﬁnition are noteworthy. First, the deﬁnition characterises social media imple-

mentation as a synchronous rather than sequential organisational process. Firms are

presumed to execute the decisions and actions integral to social media implementation

concurrently, since many of them will be requisite for eﬀective social media programmes

(Habibi et al., 2015; Valos et al., 2017). Second, the deﬁnition ties social media imple-

mentation to strategic marketing actions, thus suggesting that the success of social

media implementation should be gauged on the basis of its contributions to the

attainment of strategic marketing goals. Third, the proposed conceptualisation accords

well with the practitioner literature. For instance, Hootsuite (2016), a leading provider of

social media solutions for marketers, recently suggested a guideline for ‘creating a social

media strategy’. The guideline incorporates the following steps: clarify your business and

social media goals, audit your current social media status, develop your content strategy,

use analytics to track progress and adjust your strategy as needed. These steps largely

overlap with our deﬁnition of social media implementation. Finally, we should note that

although we adopted the more generic ‘social media’ in our deﬁnition, our study is

primarily focused on the organisational use of social networking sites, such as Facebook,

Twitter, LinkedIn and YouTube, among others. This focus on social networking sites is

warranted, as they represent the most inﬂuential group of social media platforms in

terms of both marketing budget and impact.

Overall, the conceptualisation presented here is holistic and integrates core social

media processes into a single framework. Next, we elaborate the individual dimensions

of social media implementation and derive relevant hypotheses.

Hypotheses

Social media strategy

Drawing on the digital strategy literature, Eﬃng and Spil (2016)deﬁned social media

strategy as ‘a goal-directed planning process for creating user generated content, driven

by a group of internet applications, to create a unique and valuable competitive

position’ (p. 2). The authors identiﬁed a range of considerations that constitute a

comprehensive social media strategy, including target audience, channel choice, goals,

policies, monitoring and content activities. These considerations emphasise the role of a

formalised strategy to craft a competitive social media programme.

The primary purpose of a social media strategy is to align social media with ﬁrms’

strategic marketing goals and chart a viable pathway towards achieving those goals

JOURNAL OF MARKETING MANAGEMENT 5

(McCann & Barlow, 2015). Social media strategy development contributes to social media

eﬀectiveness in multiple ways. First, social media strategy helps to establish clear goals

and performance expectations, which reinforce goal commitment and better decision-

making (Habibi et al., 2015; McCann & Barlow, 2015). As previously noted, social media

goals are primarily derived from ﬁrms’ strategic marketing goals (Eﬃng & Spil, 2016).

Second, social media strategy helps to coordinate organisational actions and mobilise

resources around identiﬁed marketing goals. Adopting a formalised strategy circumvents

the duplication of resources and synergises ﬁrms’ social media eﬀorts by deﬁning a

coherent structure and line of communication (Mergel & Bretschneider, 2013; Valos

et al., 2017). Finally, social media strategy is important for establishing and institutionalis-

ing policies and procedures that govern channel choice decisions, content development

and interactions with customers (Felix, Rauschnabel, & Hinsch, 2017). Such policies and

procedures are particularly useful in minimising the risk of improper communication in

social media (Tuten & Solomon, 2015; Valos et al., 2017). For the aforementioned reasons, a

formal social media strategy is anticipated to contribute to social media performance.

Hypothesis 1: The development of social media strategy will lead to higher social media

performance.

Active presence

Once ﬁrms decide to implement social media, they need to be actively present on the

platforms by creating content, testing diﬀerent campaign ideas and engaging with custo-

mers on a regular basis (Kaplan & Haenlein, 2010). Social media marketing is built on the

content, community and technology inherent to each platform. As such, to make it success-

ful, ﬁrms must be active in the space by developing customised content and interacting

with customers in a manner best suited to that speciﬁc technology (Tuten & Solomon, 2015).

Content is the main vehicle through which ﬁrms can inﬂuence the conversation in social

media (Kietzmann et al., 2011). By developing content regularly, ﬁrms can drive online

conversations that are purposeful and aligned with their objectives (Mangold and Faulds,

2009). As Gensler et al. (2013) noted, ‘ﬁrm-generated brand stories [in social media] aim to

create and strengthen consumers’ relationship with the brand by providing a theme for

conversations between consumers and ﬁrms and among consumers themselves’ (p. 242).

Although ﬁrms cannot directly control customer conversations in social media, they can

provide guidance and inﬂuence by way of appropriate content (Mangold and Faulds, 2009).

Active presence is anticipated to contribute to social media performance by driving

incremental customer reach and brand exposure. By regularly communicating content

on social media, ﬁrms can potentially reach and appeal to diﬀerent segments of their

customer base (Hanna et al., 2011; Tuten & Solomon, 2015). Similarly, active presence

can foster brand connections and mutual trust by facilitating opportunities for frequent

interactions between ﬁrms and their customers (Kaplan & Haenlein, 2010; Valos et al.,

2017). Finally, active presence can prove crucial to countering competitors’ inﬂuences in

social media. Firms that are actively present on social media can swiftly respond to

competitive actions. Therefore, the relevant hypothesis is as follows.

Hypothesis 2: Active presence will lead to higher social media performance.

6 W. TAFESSE AND A. WIEN

Customer engagement initiatives

Customer engagement is a multidimensional concept manifested in customers’

emotional, cognitive and behavioural responses with a ﬁrm focus (Dessart et al.,

2016). It is a motivational state that leads customers to a heightened i nvolvement

with interactive, brand-related responses and experiences (Harrigan et al., 2015;

Tafesse, 2 016). Of particular importance in social media is behavioural engagement,

which represents customers’ proactive, ﬁrm-directed eﬀorts that go beyond trans-

actions (Van Droon et al., 2010). Behavioural engagement is an extra-role behaviour

in which customers make voluntary resource contributions to a ﬁrm, such as

knowledge, time, network resources and social inﬂuence (Jaakkola & Alexander,

2014).

Despite being a voluntary response behaviour, ﬁrms can inﬂuence customer beha-

vioural engagement using diﬀerent engagement tactics (Pansari & Kumar, 2017).

Harmeling, Moﬀett, Arnold and Carlson (2017) collectively referred to these engage-

ment tactics as customer engagement marketing, deﬁning it as ‘a ﬁrm’s deliberate

eﬀort to motivate, empower and measure a customer’s voluntary contribution to the

ﬁrm’s marketing function beyond the core, economic transaction’ (p. 6). Firms can use

engagement marketing to drive customers’ active participation in and contributions

towards their marketing eﬀorts (Harrigan et al., 2015; Pansari & Kumar, 2017). In a

social media environment, a critical source of customer engagement is the content

and experiences that ﬁrms facilitate on the social media platforms. Research shows

that customers engage more actively with content and experiences that are interest-

ing, novel and transformational (Ashley & Tuten, 2015; Tafesse, 2015; Tafesse & Wien,

2017). Similarly, interacting with customers at a personal level and being responsive to

their comments and questions can boost customer engagement and brand value

(Choudhury & Harrigan, 2014; Harrigan et al., 2015). Finally, ﬁrms can use material

incentives, such as special oﬀ

ers, competitions and rewards, to stimulate customer

engagement

(Pansari & Kumar, 2017). In short, an integral deployment of customer

engagement tactics in social media can motivate customers to interact with ﬁrms on

favourable terms.

Hypothesis 3: The use of customer engagement initiatives will lead to higher social

media performance.

Social media analytics

The vast interactions that occur in social media generate an unprecedented volume of

behavioural data that can be translated into actionable managerial insights (Wedel &

Kanna, 2016). Social media analytics deals with the compilation, analysis and interpreta-

tion of part of this behavioural customer data to inform marketing decisions (Peters,

Chen, Kaplan, Ognibeni, & Pauwels, 2013).

One of the deﬁning features of social media marketing is that it enables ﬁrms to

develop and track a range of metrics that quantify customer responses to given market-

ing actions (Peters et al., 2013). Among the most frequently employed metrics in social

media include follower base, reach, engagement, web traﬃc, brand mention, brand

sentiment, conversion and ROI (Hoﬀman & Fodor, 2010; Mintz & Currim, 2013;

JOURNAL OF MARKETING MANAGEMENT 7

Smallwood, 2016). Some of these metrics, such as reach, engagement and web traﬃc,

measure the magnitude and quality of customer responses to ﬁrms’ marketing actions.

Other metrics, such as brand mention and brand sentiment, measure the magnitude and

valence of consumer-generated content. Still, other metrics, such as conversion and ROI,

measure the eﬀectiveness of social media in driving sales and ﬁrm proﬁtability.

An eﬀective metrics system should reﬂect a shared deﬁnition and understanding of

key marketing drivers and outcomes, diagnose marketing performance, enable organi-

sational learning and support decision-making to improve performance (Jarvinen and

Karjaluoto, 2015; Peters et al., 2013). When applied proactively, social media analytics

and the range of metrics that it produces empower ﬁrms to understand their customers

and competitors and make evidence-based decisions (Hoﬀman & Fodor, 2010; Mintz &

Currim, 2013), oﬀering them the insight they need to devise an eﬀective social media

programme (Mintz & Currim, 2013). Therefore, the relevant hypothesis is as follows.

Hypothesis 4: The use of social media analytics will lead to higher social media performance.

Firm performance

Firms implement social media to advance their strategic marketing goals, such as

acquiring new customers and driving customer satisfaction. However, the interactivity

and engagement attributes of social media mean that ﬁrms must ﬁrst reach and engage

with customers in order to attain their strategic marketing goals (Hanna et al., 2011).

Generating favourable customer interactions on social media, such as a customer sub-

scribing to a ﬁrm’s social media page, engaging with its content or clicking on a link, is a

critical prerequisite to achieving favourable, customer-based market outcomes. In

essence, social media implementation produces two distinct customer-based outcomes,

which we formalised into social media performance and marketing performance draw-

ing on Katsikeas et al.’s(2016) comprehensive marketing outcome framework.

Social media performance captures customer-based social media outcomes that result

from customers’ favourable perceptions, feelings or actions towards ﬁrms’ activities on

social media and includes such outcomes as customer reach, customer engagement,

follower base and web traﬃc. Marketing performance, on the other hand, captures

customer-based market outcomes that result from customers’ purchase and post-pur-

chase behaviours that are facilitated by social media and includes such outcome as new

customer acquisition, customer satisfaction, customer services, sales and customer loyalty.

Mapping these two outcome measures on Katsikeas et al.’s(2016) marketing out-

come framework, social media performance matches what the authors called ‘realised

marketing outcomes’, which capture consumers’‘pre-purchase behaviour interest indi-

cators (e.g. website visits, signing up to receive catalogs or email oﬀers)’. On the other

hand, marketing performance matches customer mind set outcomes, which capture

‘customer purchase and post-purchase behaviours (e.g. repurchase, word of mouth)’ (p.

3). Just as realised marketing outcomes drive customer mind-set outcomes, customer-

based social media outcomes are expected to drive customer-based market outcomes.

Accordingly, the following hypothesis is proposed:

Hypothesis 5: Higher social media performance will lead to higher marketing performance.

8 W. TAFESSE AND A. WIEN

Methodology

Sample and data collection

We gathered data from two sources. Our primary source was the 2017 version of Kapittal

500, an annually updated list of the largest 500 ﬁrms in Norway. The ﬁrst step in the

sampling process was to determine how many ﬁrms in the list maintain a social media

presence. Inspection of the ﬁrms’ corporate websites indicated that 460 ﬁrms have an

active social media presence.

The second step in the sampling process involved identifying appropriate respon-

dents from each ﬁrm. We deﬁned appropriate respondents as senior executives who are

close to the ﬁrms’ social media and marketing operations. We began our online search

for appropriate respondents with those closest to the social media marketing operation,

such as social media marketing managers and digital marketing managers. When these

positions were unavailable, we searched for senior managers who were closest to the

marketing operation, such as marketing managers, brand managers and commercial

managers. When both of these were unavailable, we turned to communication and

information directors. Using this approach, we compiled the name, position and e-mail

address of 420 respondents. Despite numerous eﬀorts, we could not obtain the e-mail

addresses of respondents from the remaining 40 ﬁrms.

Subsequently, we emailed the questionnaire to the identiﬁed respondents. The

original e-mail was followed up by two rounds of reminders, each sent 10 days apart.

At the end of the three rounds, we obtained 113 fully completed responses (27%

response rate). We augmented this data set with new data gathered from a Facebook

group in Norway. At the time of data collection, the group’s membership stood at about

20,000 digital marketing professionals and enthusiasts. After securing the permission of

the group’s moderators, we shared the questionnaire on the group’s timeline, which

generated 28 fully completed responses. Since we were only allowed to share the

questionnaire once, we had no way of increasing the response rate.

The ﬁnal sample was, therefore, composed of 141 responses. We compared the

responses from the e-mail list (three rounds) with the responses from the Facebook

group based on the primary constructs of the study (i.e. social media implementation,

social media performance and marketing performance) and found no signiﬁcant diﬀer-

ences. As such, non-response bias was not an issue in our study.

The ﬁnal sample is broadly representative. Retail (12%), bank and ﬁnance (11%),

media and communication (9%), food products (8%), manufacturing (7%), transportation

and logistics (7%), oil and gas (7%), construction (6%) and technology (6%) were among

the major industry categories surveyed. In terms of size, ﬁrms with less than 500

employees accounted for 51% of the sample, ﬁrms between 500 and 1000 employees

accounted for 12% and ﬁrms with over 1000 employees accounted for the remaining

37%. We also asked respondents to indicate their ﬁrms’ experience with social media

and how many social media platforms they actively operate. The results indicate that the

average social media experience is 5 years (M = 4.99, SD = 2.62), suggesting that the

ﬁrms are fairly well experienced with social media. Likewise, on average, the ﬁrms

actively operate close to ﬁve social media platforms (M = 4.6, SD = 2.61), indicating a

robust and multiplatform social media presence.

JOURNAL OF MARKETING MANAGEMENT 9

Measure development

Social media implementation

In developing the measures, we signiﬁcantly relied on the conceptual domain of social

media implementation. Because social media implementation has not been operationa-

lised in prior literature, the opportunity to draw on extant measures was minimal.

Consequently, we followed a deductive process whereby we reviewed relevant literature

from marketing, information systems and practitioner sources to deﬁne the conceptual

domain of social media implementation.

The next step involved generating measurement items guided by the conceptual

domain. Consistent with established scale development procedures (Churchill, 1979;

Specter, 1992), we developed several items for each dimension of social media imple-

mentation (24 in total). Following the full speciﬁcation of the items, we carefully

examined the whole set to detect redundant items. We performed this task collabora-

tively and over several rounds to allow suﬃcient space for a substantive feedback loop.

Through this exercise, we reﬁned the items and reduced the total number to 19. Up to

this point, the items were written in English. Since respondents were Norwegians,

however, the items were translated to Norwegian. The Norwegian version was then

back translated into English, and the correspondence between the original and the

translated versions was checked.

The third step was to test the face validity of the items. For this purpose, we asked a

handful of social media marketing managers and an experienced marketing professor to

scrutinise and comment on the measurement items. Based on the resultant feedback,

we rewrote some items and deleted others, leaving 15 items for the next stage.

In the ﬁnal step, the items were tested on a sample of conveniently assembled social

media managers. However, the resulting responses were not large enough to enable

standardised statistical tests. Instead, we studied the response patterns to further reﬁne

the items and adjust the ordering and layout of the ﬁnal questionnaire. Following these

adjustments, we incorporated the ﬁnal 15 items into the questionnaire.

Firm performance

Our procedure to generate, reﬁne and validate the measurement items for ﬁrm perfor-

mance partitioned into social media performance (four items) and marketing performance

(ﬁve items) is identical to the one we employed to develop the measurement items for social

media implementation. In order to develop the measures for social media performance, we

drew on relevant academic and practitioner discussions to identify key customer-based

social media metrics such as customer reach, follower-base and customer engagement

(Jarvinen and Karjaluoto, 2015; Peters et al., 2013) and converted them into standardised

measurement items. Likewise, the development of the measurement items for marketing

performance was inspired by core academic texts on the topic (Katsikeas et al., 2016;Mintz&

Currim, 2013). The items cover key aspects of customer-based market outcomes, such as

customer acquisition, customer satisfaction, customer services and sales.

We employed a reﬂective measurement approach and a 5-point Likert rating scale for

all the items (1 = completely disagree, 5 = completely agree). Table 1 summarises the

items and their respective factor loadings. All the items loaded on their intended

dimensions/constructs with factor loadings greater than .75.

10 W. TAFESSE AND A. WIEN

Measure validation

Having established the adequacy of the factor loadings, we turned to testing the

reliability and validity of the proposed dimensions/constructs. Convergent validity was

assessed using composite reliability and Cronbach’s alpha values. For all the dimensions/

constructs, the composite reliability values substantially exceeded the .60 cut-oﬀ recom-

mended by Bagozzi and Yi (2012), and the Cronbach’ s alpha values substantially

exceeded the .70 cut-oﬀ recommended by Nunnally (1978), thereby providing evidence

of convergent validity. Discriminant validity was assessed by comparing the average

variance extracted (AVE) for a given dimension/construct with its squared correlation

with all other dimensions/constructs in the model. In no case was the AVE lower than

the squared correlations, thereby oﬀering evidence of discriminant validity (Fornell &

Larcker, 1981). Results of these tests are summarised in Table 2.

Hypothesis testing

For two reasons, we employed partial least squares structural equation modelling (PLS-

SEM) to test the structural model. First, PLS-SEM relies on ordinary least squares estima-

tion to solve the models, thus relaxing the assumption of multivariate normality

Table 1. Measurement items and factor loadings.

Dimensions/Constructs

Factor

loadings

Values

Social media strategy

Our social media strategy clariﬁes key performance goals .90 46.59

Our social media strategy outlines directions for executing our social media programme .84 23.72

Our social media strategy is closely aligned with our marketing strategy .80 17.33

Our social media strategy oﬀers a clear deﬁnition of our target audience .79 14.93

Active presence

We have a regular posting schedule .87 29.00

We post frequently on our primary social media account .83 23.18

We produce suﬃcient content for our social media needs .82 21.61

Customer engagement initiatives

We encourage customers to interact with us in social media .83 26.60

We create interesting and engaging content to stimulate customer engagement .83 24.04

We respond actively to customer comments and questions .83 23.37

We acknowledge and reward customers who engage with us .75 14.20

Social media analytics

We use social media analytics to plan and execute our social media eﬀort .90 50.62

We use social media analytics to learn about our customers .90 44.86

We use social media analytics to measure our eﬀectiveness .89 42.08

We track and monitor relevant social media metrics .87 32.31

Social media performance

We reach more customers through social media .82 28.81

Our follower base in social media is growing .79 22.76

Web traﬃc from social media to our corporate/brand/product website is growing .76 16.72

Our key customer engagement metrics are improving (e.g. likes, shares, comments, and link

clicks)

.75 16.60

Marketing performance

We have improved customer satisfaction with the help of social media .89 36.37

We have acquired more new customers with the help of social media .83 23.20

We have improved customer services with the help of social media .83 21.62

We have increased sales with the help of social media .82 20.19

We have improved customer loyalty with the help of social media .78 19.09

Note: All t-values are signiﬁcant at p < .001.

JOURNAL OF MARKETING MANAGEMENT

underlying traditional covariance-based maximum likelihood procedures (Hair, Hult,

Ringle, & Sarstedt, 2017). This attribute makes PLS-SEM an ideal choice for our study,

which is based on a relatively small sample. Second, PLS-SEM is the preferred method

when the researcher is focused on optimised prediction of latent response variables, as

we are in this study. PLS-SEM seeks to maximise the relationship between speciﬁed

latent predictors and response variables (Hair et al., 2017).

PLS-SEM is conducted in two stages. In the ﬁrst stage, the researcher tests for the

reliability and validity of the constructs. After the adequacy of the measurement model

has been established, as we reported for this study earlier, the researcher proceeds to

estimate the structural model. The structural model is primarily assessed using R

and

Stone-Geisser’s Q

. While R

measures predictive accuracy, Q

measures the out-of-

sample predictive power (predictive relevance) of the structural model (Hair et al.,

2017). According to Hair et al. (2017), Q

values greater than zero suggest strong

predictive relevance. In our model, both of these values are signiﬁcant. For social

media performance, R

= .44 and Q

= .24; for marketing performance, R

= .32 and

= .21.

The hypotheses were tested using standardised path coeﬃcients (Hair et al., 2017).

We employed PLS-SEM’s bootstrapping procedure with 5000 subsamples to generate

t-values and conﬁdence intervals. The results indicate that social media strategy has a

signiﬁcant positive eﬀect on social media performance (β = .18, p < .05), which supports

Hypothesis 1. On the other hand, active presence lacks a signiﬁcant eﬀect on social

media performance (β = .06), which fails to support Hypothesis 2. Customer engagement

initiatives have a strong positive eﬀect on social media performance (β = .41, p < .001),

which supports Hypothesis 3. Likewise, social media analytics has a signiﬁcant positive

eﬀect on social media performance (β = .18, p < .05), which supports Hypothesis 4.

Finally, social media performance is positively related to marketing performance (β = .57,

p < .001), which supports Hypothesis 5. Figure 1 visualises the standardised path

coeﬃcients, t-values and signiﬁcance levels.

Robustness checks

To check the robustness of the PLS-SEM estimates, we estimated the structural model

using OLS regression. As a further test of robustness, we added the number of actively

operated social media platforms as a control variable. The regression model is signiﬁcant

Table 2. Descriptive statistics, reliabilities and correlations.

Dimensions/Constructs Mean St. Dev CA CR 1 2 3 4 5 6

Social media strategy 3.74 .83 .85 .90 .69 .14 .09 .13 .14 .11

Active presence 3.81 .90 .79 .88 .37 .70 .29 .32 .19 .09

Customer engagement initiatives 3.71 .86 .82 .88 .30 .54 .65 .35 .32 .38

Social media analytics 3.51 1.03 .91 .94 .36 .57 .59 .79 .27 .22

Social media performance 3.97 .63 .78 .86 .38 .44 .57 .52 .61 .31

Marketing performance 3.56 .81 .89 .92 .33 .30 .62 .47 .56 .69

Notes: CA: Cronbach’s alpha; CR: composite reliability; AVEs are reported in the diagonal in bold. Correlations are

reported below the diagonal; squared correlations are reported above the diagonal. All correlations are signiﬁcant at

p < .01.

12 W. TAFESSE AND A. WIEN

(F = 17.55, p < .01), with R

= .41. The regression coeﬃcients are consistent with the PLS-

SEM path coeﬃcients. Social media strategy (β = .17, p < .05), customer engagement

initiatives (β = .31, p < .01) and social media analytics (β = .19, p < .05) are all signiﬁcant,

while active presence is not (β = .08, p = .39). Finally, social media performance, after

controlling for self-reported marketing budget relative to industry average, market share

position and ﬁrm size, has a signiﬁcant eﬀect on marketing performance (β = .62,

p < .01). Hence, the results of the PLS-SEM structural model are robust and stable.

Discussion

This study sought to gain a deeper understanding of the social media implementation

phenomenon. To this end, it conceptualised social media implementation, operationa-

lised it as a multidimensional construct and empirically assessed its eﬀect on ﬁrm

performance. The results indicate that all except the active presence dimension of social

media implementation positively contribute to social media performance. Further, social

media performance is strongly associated with marketing performance.

The positive eﬀect of social media strategy on social media performance is consistent

with Hypothesis 1 and demonstrates the critical importance of a well-developed strategy

for social media success. Social media strategy is essential to aligning social media with

ﬁrms’ strategic marketing goals (Eﬃng & Spil, 2016). It also plays an important role in

reinforcing goal commitment and facilitating optimal resource allocation decisions (Felix

et al., 2017). Finally, social media strategy is crucial to coordinating ﬁrms’ social media

Social

media

strategy

Active

presence

Cust.

Eng.

initiatives

Social media

performance

= .44

= .24

β = .18**

τ = 2.40

β = .06

τ = .74

β = .57***

τ = 10.36

β = .41***

τ = 5.25

β = .18**

τ = 2.06

Social

media

analytics

Marketing

performance

= .32

= .21

Figure 1. Structural path model.

Note: **p < .05; ***p < .01.

JOURNAL OF MARKETING MANAGEMENT

eﬀort by deﬁning a coherent structure and line of communication (Mergel &

Bretschneider, 2013).

Contrary to Hypothesis 2, active presence fails to contribute to social media perfor-

mance. This result suggests that active presence by itself may be incapable of driving

social media performance. First, for a brand, being overly active on social media might

be oﬀ-putting for its customers who often experience time pressure on social media.

Second, social media algorithms prioritise and serve content to users based primarily on

engagement considerations. If a brand’s content cannot garner some initial level of

engagement, its chances of reaching a wider audience organically will be limited. As

such, producing content actively with little concern for engagement can hardly lead to

success.

Customer engagement initiatives have a strong positive eﬀect on social media

performance, demonstrating their value for social media success. Social media repre-

sents deeply engaging platforms in which human connection and social relationships

take centre stage (Hanna et al., 2011; Kaplan & Haenlein, 2010). It is therefore essential

that ﬁrms infuse their social media eﬀort with engagement orientation (Pansari & Kumar,

2017). Research shows that engagement tactics such as interacting with customers at a

personal level or facilitating transformational experiences trigger favourable aﬀective

responses (Harmeling et al., 2017; Tafesse, 2016) which in turn readily translate into

concrete behavioural outcomes (Harrigan et al., 2015). Our results validate these ﬁndings

from an organisational perspective.

Social media analytics is an integral part of social media marketing that involves the

compilation, analysis and interpretation of behavioural customer data to inform market-

ing decisions (Wedel & Kanna, 2016). Most social media platforms oﬀer some form of in-

built analytics that allow marketers to set up, monitor and analyse a range of perfor-

mance metrics (Peters et al., 2013). When performed proactively, social media analytics

fosters a culture of data-driven decision-making, thus enabling marketers to prioritise

their actions and allocate resources eﬃciently. Our results substantiate conceptual

arguments in the literature that analytics represent a crucial source of social media

competency and success (Peters et al., 2013).

Finally, social media performance is positively related to marketing performance,

which is consistent with Hypothesis 5. Social media performance represents customer-

based social media outcomes that arise from customers’ favourable perceptions, feelings

or actions towards ﬁrms’ activities on social media, while marketing performance repre-

sents customer-based market outcomes that arise from customers’ purchase and post-

purchase behaviour facilitated by social media. The strong positive association between

these two performance measures signiﬁes the transferability of favourable social media

responses to market-based behavioural responses.

Theoretical contributions

Taken together, the study makes a threefold contribution to the literature. First, it posits social

media implementation as a synchronous organisational process by which ﬁrms leverage social

media to drive strategic marketing actions. This ap proach departs fromstages-of-growth

models, which aim to develop a social media growth model based on sequential stages

(Chung et al., 2017;Eﬃng & Spil, 2016). Our conceptualisation draws on a set of clearly deﬁned

14 W. TAFESSE AND A. WIEN

and operationalised social media processes that are essential for social media success. While

the stages-of-growth models accentuate social media maturity, our conceptualisation accent-

uates social media eﬀectiveness, whereby social media strategy and analytics serve as instru-

ments of strategic (business) alignment and learning.

Second, although marketing research has begun to address the eﬀects of social media

on ﬁrm performance (e.g. De Vries et al., 2017; Srinivasan et al., 2016), these works are

largely conﬁned to using social media spending as a measure of ﬁrms’ social media eﬀort.

Important social media processes that shape ﬁrms’ social media eﬀort beyond spending,

such as social media strategy, customer engagement initiatives and social media analytics,

are overlooked (Lamberton & Stephen, 2016; Valos et al., 2017). The second contribution of

this study is to document the eﬀects of these core social media processes on ﬁrm

performance. Our results oﬀer novel insights into how core social media processes con-

tribute to marketing performance through enhancing social media performance.

A ﬁnal contribution of the study lies in the development of a reliable and valid

measurement scale for social media implementation. To our knowledge, no prior mea-

surement scale for social media implementation has appeared in the literature. The

measurement scale developed in this study meets all the requirements of a reliable and

valid scale (Churchill, 1979). With a total reliability score of .84, the proposed scale can be

readily employed in future research to measure social media implementation and

examine its organisational antecedents and outcomes.

Managerial implications

Our results hold valuable implications for managerial action. First, based on the result that

social media strategy positively contributes to social media performance, we encourage ﬁrms

to develop a formal strategy that deﬁnes their goals for social media and formulates a clear

execution plan in terms of target audience, channel choices, policies and structure. A well-

developedstrategyshouldalignwithanddrivestrategic marketing actions. Managers can ﬁnd

detailed guidance on the social media strategy development process from such authoritative

sources as Sproutsocial.com and Hootsuite.com.

Second, although the result that active presence makes no signiﬁcant contribution to

social media performance should encourage ﬁrms to pay greater attention to the quality

of their social media content, decisions regarding active presence should best be

considered on a platform-by-platform basis. For instance, on Twitter, where daily

updates from brands are commonplace, active presence can be valuable, while on

Facebook, a level of presence on par with Twitter is uncommon and might even be

counterproductive. As such, ﬁrms should decide their level of presence according to the

characteristic and dynamics of each social media platform.

Third, we encourage ﬁrms to cultivate initiatives that stimulate customer engagement in

social media. Customer engagement comprises a diverse set of favourable customer actions

with a ﬁrm focus, such as giving referrals, producing positive WOM and providing constructive

feedback (Harrigan et al., 2015). Firms can apply a range of tactics to motivate such behaviour,

such as producing content that is emotionally and experientially resonant, listening and

responding to customer concerns and feedback in a timely manner and motivating and

rewarding customers to regularly interact with the ﬁrm.

JOURNAL OF MARKETING MANAGEMENT

Finally, we encourage ﬁrms to become analytics oriented in their social media eﬀorts.

Social media analytics empowers marketers to quantify customer responses to speciﬁc

marketing action and allocate resources more eﬃciently. It enables them to concentrate

their eﬀorts where they can achieve the greatest impact. To this end, ﬁrms should

develop a relevant metrics system that provides a clear picture of the eﬀectiveness of

and improvement in their social media eﬀort (Peters et al., 2013). The metrics that ﬁrms

track need to be closely aligned with their strategic marketing goals.

Limitation and future research

The present study is among the ﬁrst attempts at conceptualising and operationalising

social media implementation as a multidimensional construct. As such, the proposed

framework opens up several avenues for future research. First, future research can

examine the antecedents of social media implementation. This study was focused on

the performance consequences of social media implementation, and given the contri-

bution of social media implementation to ﬁrm performance, it is worthwhile to identify

the organisational factors that foster (or hinder) it, such as resources. Second, it is

plausible that social media implementation may vary by industry, ﬁrm size and customer

type (e.g. B2C vs. B2B). Certain dimensions of social media implementation could be

more impactful within certain industry and ﬁrm-level contexts. Future research might

examine such industry- and market-speciﬁceﬀects. The small data set we employed

precluded us from performing this sort of granular level analyses. Third, future research

might explore factors that moderate the relationship between social media performance

and marketing performance, such as ﬁrms’ e-commerce capability. Such works can

provide a better understanding of the circumstances under which social media perfor-

mance contributes to marketing performance.

The limitations recounted in prior paragraphs notwithstanding, the present study oﬀers a

valuable initial framework to understand social media implementation. It can be reﬁned and

extended in the future to reﬂect diﬀerent organisational realities as well as changing social

media habits and practices.

Disclosure statement

No potential conﬂict of interest was reported by the authors.

Notes on contributors

Wondwesen Tafesse is a post-doctoral researcher at the School of Business and Economics, UiT–

The Arctic University of Norway. His research interests include social media marketing, branding

and consumer experiences. His works have been published in Industrial Marketing Management,

European Journal of Marketing and Journal of Product & Brand Management, among others. He has

teaching responsibilities and supervises graduate students.

Anders Wien is an associate professor of marketing at the School of Business and Economics, UiT–The

Arctic

University of Norway. His research interests include word of mouth, consumer behavior and social

media marketing. His works have been published in journals such as Psychology & Marketing and

European Journal of Marketing. He has teaching responsibilities and supervises graduate and MBA

students

16 W. TAFESSE AND A. WIEN

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