Opt-in e-mail marketing influence on consumer behaviour: A Stimuli–Organism–Response (S–O–R) theory perspective

Abstract

The paper examines the influence of opt-in e-mail marketing on consumer behaviour. The study attempts to extend the Stimuli–Organism–Response (S–O–R) theory that has been broadly explored in consumer research. Following a critical review of the literature organisation approach, a hypothetical model has been proposed for this study, based on identified factors, such as, informational value, entertainment-based message content, layout, visual appeal, attitude toward e-mail advertising and intention towards the sender in the context of opt-in email marketing. Data were collected in South Africa through an online survey of 436 opt-in e-mail marketing subscribers. Structural equation modelling (SEM) was employed to measure the proposed hypotheses of the study. The research results suggest that even during a pandemic, e-mail marketers could employ certain features in promotional and informational e-mail marketing communication, particularly informational value, entertainment-based message content, layout, visual appeal, as a means to design their e-mail marketing messages and plan e-mail advertising campaigns. The findings of the study are intended to advance the e-mail marketing knowledge base to help marketers during a pandemic, such as COVID-19. The paper provides marketers with relevant insights on how to effectively engage with e-mail subscribers.

Keywords:

• Consumer behaviour
• opt-in e-mail marketing
• e-mail marketing
• subscribers
• COVID-19 pandemic
• South Africa

1. Introduction and contextualisation

The COVID-19 (coronavirus) pandemic was first reported in Wuhan city, China, in December 2019. The pandemic spread rapidly across the world (Fernandes, 2020). At the time of the first draft of this article, almost 21,000 cases of the virus had been recorded in South Africa, and more than 400 people had died. The global e-mail marketing market was forecast to grow at 19.6% from 2017 to 2025 (Transparency Market Research, 2019), it was valued at US$4.51bn in 2016; and is expected to be valued at US$22.16bn by the end of 2025 (Transparency Market Research, 2019). E-mail users were approximately 3.9 billion in 2019 and are expected to grow to over 4.4 billion users by year-end 2023 (Statista, 2018). According to Kotler and Armstrong (2018), p. 72% of adults prefer that organisations communicate with them though electronic mail. Approximately 66% of e-mails are now accessed on mobile devices (Kotler & Armstrong, 2018); this means that many people read their e-mails on their mobile telephones, and this number is expected to increase (Chaffey, 2018). The Direct Marketing Association (DMA) observed that 66% of consumers had made online purchases as a result of an e-mail marketing message (J. Wu et al., 2018). In 2015, 85% of retailers in India reported e-mail marketing as their primary channel for customer engagement (Retail Snapshot, 2015). Numerous researchers (Hartemo, 2016; Holtrop et al., 2017; Kingsnorth, 2019; Martin et al., 2003) and companies (Nath & Gupta, 2013), have echoed that e-mails are a tool of Customer Relationship Management (CRM). E-mail marketing can be very specific and can be tailor made to suit a target segment; this means that each client could receive marketing that is more personalised to their specific needs and wants (Bhujwala, 2019; Kotler & Armstrong, 2018).

In South Africa, severe lockdowns were implemented in order to try to curb the spread of COVID-19. A result of the lockdowns led to a drop in consumption, and interruption to consumers’ everyday lives (Cullen et al., 2022). The reason why the study focused on the COVID-19 time period was due to the fact that during this time, there was more online e-mail marketing as the customers and companies could not afford free movement during the lockdown (Cullen et al., 2022; Koch et al., 2020). This clearly showed the super interconnection between e-mail marketing and conditions during COVID-19, such as the lockdown and social distancing measures (Pham et al., 2020). Online platforms were the most convenient ways of doing efficient shopping and marketing of goods and services (Ali, 2020; Dannenberg et al., 2020). The COVID-19 global pandemic resulted in an increase of numerous advertising and marketing approaches, such as e-mail marketing (Cullen et al., 2022; Dannenberg et al., 2020). This means that companies had to rely on digital marketing strategies, especially e-mail marketing, during the COVID-19 pandemic, as brands strove to remain front-of-mind for consumers (Gilliland, 2020). The social distancing measures and stay-at-home orders imposed as a result of the COVID-19 crisis had a large impact on how marketers engage with consumers through online platforms such as e-mail marketing (Dannenberg et al., 2020; Koch et al., 2020).

In South Africa, e-mail marketing sits at the epicentre of digital marketing (Everlytic, 2017). E-mail marketing works (McKinsey & Company, 2014)! In recent times, e-mail marketing has been on the rise (Bhatia, 2020; Chang et al., 2013; Fariborzi & Zahedifard, 2012; Geyer, 2005; Harms, 2018; Kotler & Armstrong, 2018; Todor, 2017). E-mail marketing is used to market a commercial message through the use of e-mail (Andersson et al., 2014; Bawm & Nath, 2014; J. Wu et al., 2018), where consumers are targeted using electronic mails with e-newsletters, business updates, advertisements, promotions and discounts, etc., in order to attract consumers to buy products or services (Khan & Iftikhar, 2017; Pooja, 2018). Globally, 16% of online adults find information regarding new brands and products through branded e-mails or letters (Trifonova, 2019), and 60% of consumers admit they have made immediate purchases from e-mail marketing messages (Mullen & Daniels, 2011). Commercial e-mails sent without the permission of the receiver are referred to as SPAM (Morimoto & Chang, 2006). Spam is referred to as unsolicited, unwanted commercial e-mail messages that congest users’ e-mailboxes (Kotler & Armstrong, 2018). Spam has produced consumer irritation and frustration as it now accounts for 70 percent of all e-mail sent worldwide (Kotler & Armstrong, 2018). It is therefore crucial to note that Opt-in e-mail is more effective as compared to spam e-mail advertising (Chang et al., 2013). Marketers want to add value for consumers but not be intrusive and annoying (Kotler & Armstrong, 2018). It is important to make sure that the receiver wants to receive the e-mail before sending out the e-mail.

A marketing e-mail becomes a success only if the e-mail receiver opens and reads it (Miller & Charles, 2016). In South Africa, the e-mail average open rate is 25.83%, while the average click-through rates is at 3.46%, which indicates that subscribers want to engage (Everlytic, 2017).

Numerous studies have reported that permission e-mails increase the chances of purchase (Bhatia, 2020; Chang et al., 2013; Kumar et al., 2014; Martin et al., 2003; Reimers et al., 2016). Researchers such as Ellis-Chadwick and Doherty (Ellis-Chadwick & Doherty, 2012) and Mahmoud (2015) have indicated that the selection of studies regarding attitudes toward e-mail advertising is quite narrow. Billions of e-mails continue to be sent and people spend a lot of time managing e-mails (Amin & Bengtsson, 2017). The key for successfully advertising e-mails is to have permission to send the e-mail.

This research investigates the influence of opt-in e-mail marketing on intention towards the sender in South Africa during the COVID-19 pandemic crisis. Using the Stimuli-Organism-Response theory (S-O-R), this study addresses the informational value, entertainment-based message content, layout, and visual appeal, attitude towards e-mail advertising and intention towards the sender in the context of opt-in e-mail marketing.

2. Theory

2.1. Stimuli-Organism-Response (S-O-R) theory

Rooted in environmental psychology, the Stimulus-Organism-Response theory (SOR) describes the individual behaviour through the stimuli generating cognitive and emotional states, which, in turn, lead to response (Mehrabian & Russell, 1974). In this study, we further extend the model by understanding antecedents of attitudes towards permission based e-mail marketing with the final outcome being customer response. In the e-mail marketing context, stimulus factors include informational value, entertainment-based message content, layout, and visual appeal. Organism refers to attitude towards e-mail advertising, and response includes factors, such as intention towards the sender. Dawson and Kim (2010) found that e-mail marketing can influence impulse buying (R) on online websites. Similarly, in this study, the stimuli are the touch points, constituting informational value, entertainment-based message content, layout and visual appeal, the e-mail subscribers can form positive and favorable attitudes towards e-mail advertising, leading to a positive intention towards the sender arising of organism and response of e-mail subscribers. This is how the SOR framework is deemed appropriate to be used as a platform to develop and manage opt-in e-mail marketing and intention towards the sender in the context of opt-in e-mail marketing.

3. Literature review

3.1. Opt-in e-mail marketing

Opt-in e-mail marketers can initiate campaigns for targeted audiences based on their interest and relevancy (Bawm & Nath, 2014). They allow marketers to share messages on e-mail with customers at low cost (Zhang et al., 2017); it is also a more effective medium to acquire customers (McKinsey & Company, 2014). Opt-in e-mail marketing software enables the sending of bulk e-mails to subscribers and also makes important data available to marketers (Bawm & Nath, 2014; Maziriri et al., 2022), thus having the potential to improve marketing success as well as brand image (Hsin Hsin Chang et al., 2013). Permission is the commencement of two-way e-mail communications between the customer and the e-mail marketer. Opt-in e-mail marketing can stimulate impulse buying (Chaffey et al., 2009). According to Kent and Brandal (2003), the purpose of opt-in e-mail marketing is to develop a relationship with the recipient over time, and thereby increase the number of loyal and profitable customers. Chaffey and Ellis-Chadwick (Chaffey & Ellis-Chadwick, 2016, p. 523) define opt-in DEM as “the form of e-mail direct marketing where “an individual agrees to receive e-mail communications”.

Opt-in e-mail marketing messages are effective targeting which may result in lower costs (Andersson et al., 2014; Bonfrer & Drèze, 2009; Kotler & Armstrong, 2018). They let marketers send messages that are inviting, and interactive (Kotler & Armstrong, 2018), and can produce a higher response rate than mass mailings accomplished in the traditional manner (DuFrene et al., 2005; Nyagadza, 2022; Pooja, 2018). Opt-in e-mail marketing has been recognized as one of the most effective marketing tools in brand building, improving relationships with customers, as well as getting new contacts and driving sales (Hudák et al., 2017). The increase in the adoption of smartphones is predicted to increase the e-mail marketing platform as recipients will not be limited to opening laptops in order to get access to their e-mails (Transparency Market Research (TMR), 2019). According to Amin and Bengtsson (2017), despite the increased use of e-mail advertising, studies regarding digital marketing seldom examine e-mail advertising. Zhang et al. (2017) also echo that even though e-mail marketing is profitable and increasingly used by marketers, it has received very little attention in literature.

3.2. Linking opt-in e-mail marketing to permission marketing

When customers give permission to joining permission marketing programmes, organizations share marketing messages with recipients in order to influence their decision-making and choice (Kumar et al., 2014). Opt-in marketing predominantly has its background in the 1990s direct marketing literature (Krafft et al., 2017) with the term “permission marketing” which is based on consumers giving their consent to receive marketing information. Opt-in e-mails are powerful because the consumer requests the information from the advertiser rather than having random exposure to it (Martin et al., 2003; Nyagadza, 2020). Opt-in e-mail campaigns are becoming a vital marketing component for customer relationship management (Geyer, 2005). Opt-in e-mail advertising has been recognized for offering consumers lower search costs and an increased level of precision to advertisers (Martin et al., 2003).

4. Hypotheses development and conceptual model

4.1. Information value and attitude towards opt-in e-mail marketing

People subscribe to e-mails because they are interested in receiving content that is relevant and interesting to them, therefore marketers need to pay attention to what their audience is interested in (Charest, 2016). According to Mahmoud (2015), the value of information positively influenced consumers’ attitudes toward e-mail advertising. It is important for marketers to highlight relevant information on products and special promotions which can save customers information search costs, time and money (Chaffey et al., 2009; Martin et al., 2003). Marketers should tailor e-mail content for the audience and offer high-value pieces (Cochran, 2014). Effective content marketing can influence consumer attitudes and purchase intentions (Milhinhos, 2015). Thus, the following hypothesis was formulated:

H1: Information value has a positive impact on attitude towards opt-in e-mail marketing.

4.2. Entertainment-based message content and attitude towards opt-in e-mail marketing

An increase in the perception of entertainment increases the attitude of consumers to permission based marketing (Bhatia, 2020). This has been seconded by numerous authors (Afzali, 2017; Chang et al., 2013; Shin & Lin, 2016; Wong et al., 2015). Le Roux and Maree (2016) confirmed the relationship between brand attitude and buying intention in social media contexts. When users consider an advertisement to have entertaining value, it raises the probability of consumer loyalty (Machi et al., 2022; Jamalzadeh, Behravan & Masoudi, 2012). Tsang et al. (2004) suggest that consumer attitudes, intentions and mobile marketing are all impacted by entertainment and granted permissions. Entertainment has proven to be associated with advertising value when engaging with consumers via e-mails (Haq, 2009; Mahmoud, 2015). Entertainment is a significant factor in e-mail marketing (Haq, 2009). This study therefore proposes the following hypothesis:

H2: Entertainment-based message content has a positive effect on attitude towards opt-in e-mail marketing.

4.3. Layout and attitude towards opt-in e-mail marketing

Manganari et al. (2011) established that simulated layouts, and the apparent straightforwardness of e-mail has a notable impact on consumers’ attitude. Layout design is defined as navigation in online store (Vrechopoulos et al., 2009). Marketers need to pay attention to the layout and content of e-mails (Andersson et al., 2014). A call to action on the layout can be an effective way of drawing attention and entice customer action (Gube, 2009). Based on these findings, the following hypothesis is proposed:

H3: Layout has a positive effect on attitude towards opt-in e-mail marketing.

4.4. Visual appeal and attitude towards opt-in e-mail marketing

In order to gain and keep loyal consumers, permission marketers must produce appealing, relevant communications (DuFrene et al., 2005). Findings by Dang and Pham (2018) postulate that an online presence is essentially necessary in online retailing, making it a key issue for consumers to know whether it is worthwhile to purchase products online. Marketers need to design e-mails to be adaptable to mobile devices so that reach is not limited to desktop only (Sedani et al., 2019). Getting the design of the e-mail right is a difficult task for marketers since the e-mail must look professional on every single device and browser (Gaille, 2016). As such, the following hypothesis is proposed:

H4: Visual appeal has a positive effect on attitude towards opt-in e-mail marketing.

4.5. Attitude towards opt-in e-mail marketing and intention towards the sender

Attitude mediates the relationship between beliefs and behavioural responses towards opt-in e-mail marketing (Mahmoud et al., 2019). The proposed relationship of attitude and purchase intention is informed by the theory of reasoned action (Ajzen & Fishbein, 1980). Chang et al. (2013) revealed a positive relationship between attitudes and intentions toward the sender and consumer response. In their study, Yang et al. (2019) indicated that personalization, interactivity and financial features were significant predictors of revisit intention based on customers’ involvement levels, while attitude was shown to be a significant mediator. Online opt-in e-mail marketing has become a significant source of revenue for retailers (Limbu & Jensen, 2018). This study therefore proposes the following hypothesis:

H5: Attitude towards opt-in e-mail marketing has a positive effect on intention towards the sender.

Based on the review of literature, the following conceptual model in Figure 1 is proposed:

Figure 1. Conceptual model.

Source: Researchers’ conception (2021)

5. Methodology

5.1. Study design

The research used a positivist approach and quantitative methodology in order to examine opt-in e-mail marketing influence on consumer behaviour. A deductive logic and approach was applied in order to test the model’s theoretical application, followed by practical statistical inferences.

5.2. Data sources

Data were collected via the distribution of a self-administered structured questionnaire. A web-based survey method, using Google Forms, was employed to collect data in order to validate the research model.

5.3. Data collection strategy, population, sampling and sample size

A stratified random sampling technique was applied (Alexander et al., 2016) in the study. The sample consisted of both undergraduate and postgraduate students enrolled at a university located in South Africa, as well as working professionals via WhatsApp. The reason for selecting only postgraduate students was due to the nature of the research and related objectives for the study. Recruitment of respondents was based on the requirement that in the past 12 months, the participant had received permission-based/opt-in e-mail (promotional or informational communication). Questionnaires were administered to 436 participants using an online survey hosted by Google Forms. The collection period was from 2 April 2020 to 21 May 2020 during the COVID-19 pandemic in South Africa. Participants were asked to respond to the questionnaire based on their latest permission-based/opt-in e-mail received. Out of the 436 completed questionnaires, 37 were excluded, as they had not received permission-based/opt-in e-mail (promotional or informational communication) in the past 12 months. The final sample of 399 consisted of 155 males, 243 females and one prefer not to say. Study participants were aged between 18 to 55 years. The majority of the respondents were postgraduate students. There was a difference between the way undergraduates and postgraduates respond to e-mail marketing, due to the knowledge differences between the two levels of study, and this had effects towards their responses. Gender differences further fuelled this issue.

5.4. Measures

Data or questionnaire responses were analyzed by coding them using a seven-point Likert scale from 1 = strongly disagree to 7 = strongly agree. The study derives four items relating to informational value from Reimers et al. (Reimers et al., 2016), three items for entertainment were taken from Bhatia (2020); four items relating to layout were taken from Wolfinbarger and Gilly (2003); five items of visual appeal were taken from Cai and Jun (2003). Three items relating to attitude toward opt-in e-mail marketing were also taken from Bhatia (2020); and four items of intention towards the sender were taken from Chang et al. (2013).

5.5. Data analysis

In analysing quantitative data, descriptive as well as inferential statistics were used. Structural Equation Modelling (SEM) was used to test the proposed hypotheses. To assess adequacy of the measurement model, the researchers applied Confirmatory Factor Analysis (CFA; Worthington et al., 2010).

6. Results

6.1. Respondents’ profile

The profile of the participants is displayed in Table 1:

Table 1. Sample Characteristics

Male	155	38.8%
Female	243	60.9%
Prefer not to say	1	0.3%
Total	399
Age
18–25	101	25.3%
26–35	163	40.9%
36–45	99	24.8%
46–55	30	7.5%
55 and above	6	1.5%
Total	399
Very well-off	59	14.8%
Somewhat well-off	216	54.1%
Not so well-off	103	25.8%
Not well-off at all	21	5.3%
Total	399
Matriculation	3	0.8%
Diploma/Certificate	8	2.0%
Undergraduate degree	148	37.1%
Postgraduate degree (Honours, Masters, Doctorate)	240	60.2%
Total	399
What do you do when you receive “permission-based/opt-in” promotional or informational e-mail marketing messages?
Disregard it completely	55		13.8%
Read it occasionally	212		53.1%
Delete it after accumulating too many of them	24		6.0%
Delete it when I get time	85		21.3%
Delete it right away	23		5.8%
	399
Which sender do you mostly receive “permission-based/opt-in” promotional or informational e-mail messages from?
Vodacom	55		13.8%
Ster-Kinekor	6		1.5%
Pick n Pay	42		10.5%
Woolworths	71		17.8%
Edgars	9		2.3%
Discovery Insure	20		5.0%
Makro	22		5.5%
Estee Lauder	3		0.8%
Samsung	23		5.8%
BMW	3		0.8%
ADT Security	5		1.3%
Pam Golding Properties	3		0.8%
Additional	137		34.3%
	399

Source: Primary data (2021)

The number of respondents was fairly distributed, with 60.9% female and 38.8% male respondents, while the remaining 0.3% preferred not to say. The majority of the respondents were from 26 to 35 years in age, and the majority had either a postgraduate degree (60.2%) or undergraduate degree (37.1%). Regarding their financial situation, 54.1% considered themselves somewhat well-off. The most popular e-mail marketing sender amongst the participants was Woolworths (17.8%). In terms of what participants do when they received e-mails 53.1% indicated that they read it occasionally. According to Merisavo and Raulas (Martin et al., 2003), regular contact with consumers by e-mail has a positive effect on brand loyalty.

6.2. Inferential analysis

SEM technique was used to assess the model and the proposed hypotheses among six constructs.

6.3. Scale accuracy analysis

The table below presents descriptive, reliability and validity statistics.

7. Testing for scale reliability and validity

Cronbach’s alpha coefficient was used to analyze reliability, the analysis revealed that Cronbach’s coefficients of variables ranged between 0.786–0.953 with the lowest and the highest being attitude toward e-mail advertising and visual layout, respectively, which were higher than the standard of 0.7 suggested by Henseler et al. (2009). The questionnaire items had good internal consistency (Table 2). This study utilized AMOS 26. Table 2 displays the reliability of various constructs. The CRs were higher than the recommended 0.70 cutoffs (Hair et al., 2009). Furthermore, all factor loadings in Table 2 are greater than 0.5. Thus, the convergent validity of the model is confirmed.

Table 2. Accuracy analysis scale

Research Construct		Descriptive Statistics				Cronbach’s Test		C.R. Value	AVE Value	Factor Loading
		Mean Value		Standard Deviation		Item -total	α value
INV	INV1	4.510	4.358	1.655	1.716	0.775	0.848	0.833	0.745	0.888
	INV2	4.510		1.670		0.779				0.892
	INV3	4.710		1.610		0.756				0.825
	INV4	3.700		1.930		0.482				0.526
ENT	ENT1	3.710	3.727	1.803	1.798	0.751	0.838	0.812	0.818	0.828
	ENT2	4.360		1.633		0.681				0.806
	ENT3	3.110		1.957		0.681				0.766
LYT	LYT1	5.070	5.058	1.528	1.486	0.856	0.953	0.898	0.912	0.881
	LYT2	5.090		1.517		0.902				0.923
	LYT3	5.060		1.463		0.894				0.927
	LYT4	5.010		1.435		0.893				0.916
VAL	VAL1	5.010	5.090	1.492	1.437	0.827	0.924	0.923	0.820	0.871
	VAL2	5.260		1.391		0.761				0.795
	VAL3	4.910		1.482		0.822				0.868
	VAL4	5.000		1.446		0.869				0.913
	VAL5	5.270		1.372		0.732				0.771
ATT	ATT1	4.020	4.540	1.976	1.815	0.667	0.786	0.793	0.740	0.847
	ATT2	5.240		1.611		0.594				0.647
	ATT3	4.360		1.859		0.629				0.727
INT	INT1	4.180	4.320	1.822	1.714	0.744	0.881	0.823	0.780	0.785
	INT2	3.740		1.878		0.719				0.758
	INT3	4.710		1.508		0.791				0.871
	INT4	4.650		1.648		0.734				0.838

Source: Primary data (2021)

7.1. Inter-correlations values

Key: INV: Informational Value, ENT: Entertainment, LYT: Layout, VAL: Visual, Appeal, ATT: Attitude Towards Email Advertising, INT: Intention Towards The Sender

Table 3 and 4 above present the correlations and model fit indices respectively. It is observed that all correlations are accepted as they are below 1 and indices are above 0.9. The root measure standard error approximation (RMSEA) is also accepted as it is below 0.08, confirming model fit.

Table 3. Correlation Matrix

Correlations Matrix
	INV	ENT	LYT	VAL	ATT	INT
INV	1
ENT	.730**	1
LYT	.517**	.518**	1
VAL	.491**	.555**	.742**	1
ATT	.542**	.637**	.477**	.477**	1
INT	.615**	.719**	.569**	.593**	.705**	1
** significance is at 0.01

Source: Primary data (2021)

Table 4. Model fit indexes

Model	Goodness of fit	Normative Fit	Relative Fit	Incremental Fit	Tucker Lewis	Confirmatory Fit	RMSEA
Default model	0.920	0.941	0.921	0.964	0.951	0.963	0.061

Source: Primary data (2021)

7.2. Hypotheses testing and path coefficients

Table 5 presents the results of the hypotheses and path coefficients, followed by a discussion thereof.

Table 5. Hypotheses results and path coefficients

			Hypothesis	Estimate	P Value
INV	→	ATT	H1	−0.021	0.518	Not Supported
ENT	→	ATT	H2	0.897	***	Supported
LYT	→	ATT	H3	0.189	***	Supported
VAL	→	ATT	H4	0.083	0.009	Supported
ATT	→	INT	H5	0.977	***	Supported

Source: Primary data (2021)

Information value is not related to attitude towards e-mail advertising (path coefficient = −0.021). Thus, the hypothesis is not supported. Contrary to the existing literature (Khan et al., 2016; Mahmoud, 2015; Haq, 2009; Siau & Shen, 2003), informational value had no relationship with the attitude towards e-mail advertising. The findings could also indicate that marketers need to personalize their content and messages according to their subscribers’ preferences and buying patterns (Scher, 2018; Standberry, 2019), so that the right message is personalized to the right person (McKinsey & Company, 2014).

H2 specifies a solid connection concerning entertainment-based message content and attitude towards e-mail advertising (estimate = 0.897). This result is in line with prior research (Le Roux & Maree, 2016; Jamalzadeh, Behravan & Masoudi, 2012; Mahmoud, 2015; Haq, 2009) that delivers strong confirmation that entertainment-based message content impacts attitudes concerning e-mail advertisements.

H3 supposes that the layout of the email positively affects attitude towards e-mail advertising. The hypothesis is confirmed because the outcome reveals a noteworthy association amid the layout of the e-mail that positively affects attitude towards email advertising (estimate = 0.189). Prior research underpins this result (Hasan, 2016; Pappas et al., 2014; Wu et al., 2014), thereby providing adequate evidence that design layout positively influences consumer attitudes towards email advertisements.

H4 indicates a strong relationship between visual appeal and attitude towards e-mail advertising (estimate = 0.083). This finding is consistent with previous literature (Dang & Pham, 2018; Hasan, 2016), which indicates that user attitudes towards the email sender are positively associated with the user’s intention towards the sender.

H5 designates a robust rapport concerning attitude towards e-mail advertising and intention towards the sender (estimate = 0.977). This outcome confirms prior literature on the issue (Ajzen & Fishbein, 1980; Chang et al., 2013), which indicates that user attitudes towards the e-mail sender are positively associated with the user’s intention towards the sender. If implemented effectively, it is able to deliver one of the highest returns on investments (Stokes, 2018).

8. Conclusion

The study aimed to investigate the effect of opt-in e-mail marketing on consumer behaviour in South Africa during the Coronavirus COVID-19 crisis. A conceptual framework proposed that informational value, entertainment-based message content, layout, visual appeal, attitude toward e-mail advertising influence intention towards the sender in the context of opt-in e-mail marketing. This article provides digital marketers with an understanding of e-mail marketing factors that could influence the intention towards the e-mail sender.

9. Implications

This study provides insights into important factors that need to be considered by opt-in e-mail marketing advertisers during a pandemic. These factors include informational value, entertainment-based message content, layout, visual appeal, attitude toward e-mail advertising and intention towards the sender in the context of opt-in e-mail marketing. Firstly, marketers should focus on the informational value of the e-mailer by providing content that is relevant to e-mail subscribers and personalized content. It is important for marketers to include content of the latest topics that interest e-mail subscribers. Subscribers could also benefit from special offers and opportunities to win prizes that they value. Secondly, marketers should focus on entertainment based message content by providing content that is enjoyable and pleasant to read. Thirdly, marketers should focus on making sure that the layout of the e-mail is laid out in a logical fashion, which is structured, easy to follow and a clear call-to-action. Fourthly, marketers should focus on the visual appeal of the e-mailer, as it needs to be aesthetically attractive with good use of colours so that it can attract subscriber attention. One of the key performance indicators for e-mail marketing is open-rate, marketers should aim at creating a high open rate where consumers read the e-mails “right away” upon receipt. In a country like South Africa, the concept of permission based e-mail marketing could still be a new concept, and it might be possible that some consumers, despite subscribing, still get irritated with receiving promotional or informational e-mails.

10. Limitations and areas of future research

This study is not without limitations. The present study used a quantitative approach to investigate factors that influence attitude towards opt-in e-mail marketing and intention towards the e-mail sender during the COVID-19 pandemic in South Africa. It provides e-mail marketers with relevant insights on how to effectively engage with e-mail subscribers. The present work leaves an opportunity for further research to consider the concept of informational value and whether factors like personalization might contribute to attitudes towards e-mail advertising. Empirical approaches have advantages and limitations, data were collected during the COVID-19 period in South Africa during a nationwide lockdown, meaning that results could be different if it were not during this period. Thus, future research could consider post COVID-19 data collection periods. Future studies could focus on the correlation between the open rate, subject line, and the click through rate.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors received no direct funding for this research.