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Which Message? Which Channel? Which Customer? - Exploring Response Rates in Multi-Channel Marketing Using Short-Form Advertising

Published Online: 24 Sep 2021
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Received: 15 Apr 2021
Accepted: 30 Jul 2021
Journal Details
License
Format
Journal
First Published
30 Mar 2017
Publication timeframe
4 times per year
Languages
English
Abstract

Formulating short-form advertising messages with little ad content that work and choosing high-performing channels to disseminate them are persistent challenges in multichannel marketing. Drawing on the persuasive systems design (PSD) model, we experimented with 33,848 actual customers of an international telecom company. In a real-life setting, we compared the effectiveness of three persuasion strategies (rational, emotional, and social) tested in three marketing channels (short message service (SMS), social media advertising, and mobile application), evaluating their effect on influencing customers to purchase international mobile phone credits. Results suggest that companies should send rational messages when using short-form advertising messages regardless of the channel to achieve higher response rates. Findings further show that certain customer characteristics are predictive of positive responses and differ by channel but not by message type. Findings from crowdsourced evaluations also indicate that people noticeably disagree on what persuasive strategy was applied to these short messages, indicating that consumers are not well-equipped to identify persuasive strategies or that what advertisers see as a “pure” strategy actually involves elements from multiple strategies as interpreted by consumers. The results have implications for the theoretical understanding of persuasive short-form commercial messaging in multichannel marketing and practical insights for advertising within a limited amount of space and attention afforded by many digital channels.

Keywords

Introduction

Message formulation to persuade customers and encourage purchase behaviors has been noted as a persistent challenge in multichannel marketing (C.-W. Chen, Liu, Chen, Hsu, & Tang, 2021; Sinisalo, Salo, Karjaluoto, & Leppäniemi, 2007). To this end, persuasive technologies can be of assistance. Persuasive technologies are defined as “interactive technologies that change a person's attitudes or behaviors” (Fogg, 1998, p. 225); they are widely used in various contexts in users’ everyday interactions with computers and mobile phones (Fogg, Grudin, Nielsen, & Card, 2003). In commercial communication, persuasion can take the forms of notifications and messages aimed at leveraging consumer emotional responses to motivate action; such notifications and messages can be used in branding management and brand promotion (Mingli Zhang, Hu, Guo, & Liu, 2017). Persuasive technologies are used in many application areas, including advertising and marketing (Edwards, McDonald, Zhao, & Humphries, 2014; Kimura & Nakajima, 2011; King, Lazard, & White, 2020; Orji, Reilly, Oyibo, & Orji, 2019; Paay et al., 2020; Ruijten, 2020).

In the multichannel context, where users’ attention is both fragmented and sporadic (Nakano & Kondo, 2018), each message must surpass the communicative noise online users face (Jiang, Liu, & Chi, 2015) and persuade the users to take action (Saleem & Mustafa, 2020) with only a marginal share of their overall attention (Bawden & Robinson, 2009). Persuasive messages have been important communicative means for promoting desired effects on customers. Messages can be disseminated on a variety of platforms, including interactive applications, mobile applications, hand-held devices, and electronic games (C.-H. Chen, Lee, & Hwang, 2018; Khaled, Biddle, Noble, Barr, & Fischer, 2006). These platforms or channels are pathways by which persuasive messages reach customers to change their attitudes and behaviors (Rosenbloom, 2012). Channel selection, therefore, is another core element of online marketing success (Kollmann, Kuckertz, & Kayser, 2012).

Persuasive communication (Dillard & Nabi, 2006; Kwon, King, Nyilasy, & Reid, 2019; C. Y. Li, 2013) is commonly viewed as composed of elements within which the interaction occurs, including the sender, message, channel, receiver, effect, and context (Lasswell, 1948; McQuail & Windahl, 2015; Shannon, Weaver, & Burks, 1951). The persuasive systems design (PSD) model identifies three basic elements of persuasion: intent, event, and strategy (Oinas-Kukkonen & Harjumaa, 2009). This research interprets advertising and marketing communication concepts using the PSD framework, as the research is directly composed of the three basics elements of the PSD model. Therefore, we deem it ideally suited for this research.

A systematic review of the literature under this framework suggests that tailoring, tunneling, reduction, and social comparison have been the most studied methods for persuasion (Torning & Oinas-Kukkonen, 2009). Prior research shows that (a) message effectiveness includes source credibility and argument impact on affective, cognitive, and behavioral responses (C. Y. Li, 2013; S. Teng, Khong, Goh, & Chong, 2014; Yu, 2012); (b) communication channel effectiveness includes factors such as type and characteristics of the communication pathway (Fogg, 1998; Fogg et al., 2003); and (c) audience-related factors affect effectiveness include personality traits (Hirsh, Kang, & Bodenhausen, 2012). To develop persuasive content, copywriters use strategies to elicit responses from users, including direct requests, flattery, and social norms (Eckles et al., 2009).

With the rapid change of technological communication and the shift in behaviors of people employing these technologies, the effectiveness of persuasive messages in the multichannel context is unclear. Prior research suggests rational and emotional persuasion techniques each have benefits. Still, it is unclear which strategy works better with one-way messages on different online channels, as previous results are mixed (Kwon et al., 2019). Instant messaging (Tseng & Hsieh, 2019), social media, and mobile application notifications are popular channels for interpersonal and mass communication of persuasive messages (Mubin, Wijayarathne, Ahmad, Ginige, & Hewapathirana, 2016; Sohn & Lee, 2007; Westermann, Wechsung, & Möller, 2016). However, prior research has not fully understood the effectiveness of messages via these emerging channels, especially when the effect is mixed with different message types and customer characteristics within an organizational setting. This last aspect is most compelling for our study, which focuses on an actual organization implementation rather than a survey or lab study.

Additionally, there is limited research investigating the possible effects of online communication technology on consumers’ receptiveness to advertising messages. Studies have discussed customers’ responsiveness to different persuasive strategies and communication channels (Caples, 1974; Danaher & Rossiter, 2011; Nelson, 2008; Shimp, 1997). These responses have been in various domains (e.g., health care, exercise, gaming); however, the authors could locate no previous research that evaluated messages and channels in a direct marketing experiment or examined the effectiveness of such messaging from the interplay of individual differences on message receptiveness. Also, especially with social media and many other online messaging, a crucial aspect is the shortness of the communication – many online channels are highly competitive and only get a small piece of consumers’ attention and a small amount of screen realestate. We refer to this type of advertising as “short-form advertising” (i.e., an advertising message that is short, simple, and without much substance).

Therefore, the research gap is how do the known persuasion strategies work in current digital channels characterized by short attention spans and limitations of length and scope of the ad content? That is, in the current media environment, in the best scenario, an advertiser can hope for only a glimpse of the consumer's time. This situation creates a lot of pressure on the selection of persuasion strategies. As a step toward understanding the effects of persuasive techniques in the online short-form advertising communication environment, this research poses the following research questions (RQs):

RQ1 (focus: message): Do customer response rates vary based on persuasive message types in short-form advertising?

RQ2 (focus: channel): Do customer response rates vary based on communication channels in short-form advertising?

RQ3 (focus: receiver): Do customer response rates vary based on customer characteristics in short-form advertising?

We conducted a large-scale experiment with 39,000 customers of a major international telecom company to persuade the customers to purchase a mobile phone recharge for international calls. Messages were sent using three persuasion strategies (rational, emotional, and social) via three channels (short message service (SMS), social media advertising, and a mobile application), and the response rate of all customers exposed to the messages on all channels was calculated to determine the effectiveness of the multichannel marketing campaign.

The research contributions include evaluating three communication channels: social media advertising and mobile application notifications. Also, the experiment was implemented with a real product on real communication channels with real customers that directly impact the revenue of a real company. The authors also highlight the challenges of implementing an experiment in a real-life context as it has hurdles not present in controlled laboratory settings or other data collection methods, such as surveys.

Literature Review and Development of Hypotheses

This section reviews marketing communication from a persuasive technology perspective to develop the research hypotheses.

The Message Formulation
Emotion and Persuasion

Marketers use emotions as sources of leverage in persuasion (DeSteno, Petty, Rucker, Wegener, & Braverman, 2004), with advertising communication persuasive techniques often focusing on sex, greed, or fear (Caples, 1974). Research in marketing communication has examined several persuasion techniques to understand the effect of messages on customer behavior (Nelson, 2008; Shahbaznezhad, Dolan, & Rashidirad, 2021; Shimp, 1997). Wilson (2003) finds that emotional strategies are rated poorly in online communications due to the absence of non-verbal emotional cues; however, both emotional and rational strategies seem to work well in face-to-face communications. Studies have found that emotional strategies are more frequent than rational strategies, and positive emotional messages are the most persuasive (Adler, Iacobelli, & Gutstein, 2016; Mazzotta & De Rosis, 2006).

Research in psychology suggests that negative emotions, such as fear, disgust, and threat, can be very compelling (Nabi, 1999; Poong, Yamaguchi, & Takada, 2014; Tomkins, 1984). Prior work shows that commerce message has unique trust elements relative to non-commerce content (Wu, Zhao, Zhu, Tan, & Zheng, 2011), which makes brand advertising possibly effect in short form advertising (Mimi Zhang, Jansen, & Chowdhury, 2011). Fear-inducing messages can generate psychologically threatening situations and manipulate customers into less careful message processing (Nabi, 1999). Also, marketing campaigns have attempted to evoke disgust to convince customers of the need to purchase insecticides (DeSteno et al., 2004). Conversely, some prior research shows that rational messages lead to higher purchase intention (De Pelsmacker, Geuens, & Maison, 2002), and a positive word-of-mouth message has a greater effect on customers’ willingness to use a service (Sweeney, Soutar, & Mazzarol, 2014).

However, other research indicates that both emotional (G. Li, Lin, Yu, & Guo, 2020) and rational messaging (i.e., message based on reason, logic, or facts without emotional embellishment) have an impactful role, with the emotional component appearing preeminent (Nicolini, Cassia, & Bellotto, 2017). Several factors are found to be relevant to the effects of persuasive messages (Dutta, Das, & Chakraborty, 2020). Individual differences exist in reactivity to emotion-inducing messages. Certain types of messages may produce persuasive or counter-persuasive effects depending on the characteristics of the customer receiving the messages (Dillard & Nabi, 2006). Other factors, such as what mood or emotional state the customer is in prior to getting the message (DeSteno et al., 2004; Kahn & Isen, 1993), add levels of complexity to the persuasiveness of messages (Sarma, Singh, & Goswami, 2019). Message-relevant emotions are found to be more likely to influence engagement in message processing than message-irrelevant emotions (Nabi, 1999). However, real-world evaluation of emotional versus rational messaging is lacking in short form advertising; therefore, it is an open question about which is more persuasive.

This research focuses on message-relevant emotions from the baseline of a rational message, as prior work seems to lean more toward the use of emotion than toward rationality for persuasive messaging. Therefore, the hypotheses are:

H1:Emotional messages result in a higher response rate than rational messages in short-form advertising.

H1a:Positive emotional messages result in a higher response rate than negative emotional and rational messages in short form advertising.

H1b:Negative emotional messages result in a higher response rate than rational messages in short-form advertising.

Social Influence

Research in social psychology demonstrates that individual judgments are subject to social influence (Deutsch & Gerard, 1955). Prior research recognizes the importance of social psychology theories to provide systematic analysis and design methods that can help develop persuasive system solutions (Oinas-Kukkonen & Harjumaa, 2009). Sometimes appearing in the form of peer pressure, social influence seems to play a role in encouraging certain behavior (Midden, Kimura, Ham, Nakajima, & Kleppe, 2011). For instance, previous research finds that persuasive messaging that uses normative social influence by suggesting social approval or disapproval has stronger persuasive effects than rational feedback (Vossen, Ham, & Midden, 2009), with negative social feedback, in particular, having the strongest effect (Vossen et al., 2009).

Research also finds that personal recognition, facilitation of group activity, feedback, and less intrusive alerts are all effective ways to promote social influence through instant messaging systems (Sohn & Lee, 2007). Social messages reportedly generate more favorable outcomes than rational messaging (Z. Li & Li, 2014). However, social influence may be culturally sensitive (Sheldon, Herzfeldt, & Rauschnabel, 2020). Research finds that positive feedback at both the individual and group level is effective for people from a collectivistic society; for people from an individualistic society, only positive individual feedback appears effective (Earley, Gibson, & Chen, 1999; L. Teng, Zhao, Wu, Fu, & Wang, 2019). However, there are several under-investigated areas concerning social influence in short form advertising.

To control for possible cultural differences, this research selects customers of one nationality (Egyptian) as the research population (Heba, 2021) for evaluating the effect of social messaging relative to rational messaging, with the hypothesis:

H2:Social messages result in a higher response rate than rational messages in short-form advertising.

The Channel Selection

Marketing researchers have studied influence strategies using various communication channels (Boyle, Dwyer, Robicheaux, & Simpson, 1992; Frazier & Rody, 1991; Frazier & Summers, 1984). Communication strategies need to consider channel conditions, including channel structure, climate, and power (Mohr & Nevin, 1990). Prior research shows that the strength of the seller-customer relationship, trust, and dependence factors influence satisfaction and commitment to the channels (Andaleeb, 1996; Boyle et al., 1992) and the frequency of recommendations, promises, and information. This indicates that channels, where the consumer opts-in, might be fruitful communication channels (Ming, Chen, & Tu, 2020).

Previous research reports that customers have distinct channel preferences to receive certain types of messages (Flanagin & Metzger, 2001; Westmyer, DiCioccio, & Rubin, 1998). The channel seems to affect the receptiveness of the messaging (Nicolini et al., 2017), and customers leverage social media channels for finding product information (Phua, 2019). Meanwhile, companies often have their own preferences communication channels based on accessibility, cost, and other factors (Rice, D’Ambra, & More, 1998).

Marketing communications are more effective when companies transmit their message via channels that the customers prefer (Danaher & Rossiter, 2011; Rice et al., 1998), and the more communications a customer receives from a channel, the less likely the customer is to respond to an offer made in that channel (Danaher & Rossiter, 2011). The research argues that coordination of various communication channels is needed for effective communication to happen (Holm, 2006). A comparison of eleven channels suggests that customers use social media and short message services (SMS or text messaging) extensively (Danaher & Rossiter, 2011). Also, the rapid penetration of smartphone app technology (Panova, Carbonell, Chamarro, & Puerta-Cortés, 2020; Renner et al., 2020) and extensive use of social network sites (Jin Jeong, Suh, & Gweon, 2020) highlight the need to focus on communication channels through mobile phones.

This research focuses on three online communication channels for short-form advertising: text messaging using SMS, social media using Facebook advertisements, and notifications using a company mobile app. Based on prior work on channels and interaction with messaging, the researchers hypothesize:

H3:Mobile app notification has a higher response rate than Facebook advertisement and text messaging in short-form advertising.

H3a:Mobile app notification has a higher response rate for emotional and rational messages than other channels in short-form advertising.

H3b:A Facebook advertisement has a higher response rate for social messages than other channels in short form-advertising.

The Customer Segmentation

Market segmentation strategies disaggregate the total market into segments of distinct demands (Dickson & Ginter, 1987). Customer characteristics such as age, education, mobility, income, and attitudes toward technology are used in a latent class analysis to estimate the likelihood that those customers will adopt a telecommunication service (Green, Carmone, & Wachspress, 1976). Researchers have further realized that customers should not be viewed as members of a homogeneous market segment but rather as individuals seeking personalized experiences and communications (Fuat Firat & Shultz, 1997; Pires, Stanton, & Rita, 2006). Consumer personality attributes (Y. Zhang, Sun, & Kim, 2017) have been reported to impact e-commerce behavior with a moderating effect (Leong, Jaafar, & Sulaiman, 2017).

The rapid development of Web and mobile communications has introduced a new transaction channel and unique abilities for increased communication among consumers of the product (Peterson, Balasubramanian, & Bronnenberg, 1997; Pires et al., 2006). These abilities allow tailored offerings to suit individual needs within market segments (Simmons, 2008). Demographic, social characteristics, information exposure, and customer preferences to different channels (H. Kim, Lee, & Oh, 2020) are said to be related to communication effectiveness (Scott, Schmidt, Aunger, Garbrah-Aidoo, & Animashaun, 2008). Therefore, it is essential to identify individual customers to target persuasive communications.

Research has studied techniques that identify correct customers to target in direct marketing campaigns (Gutierrez & Gérardy, 2017). This type of modeling helps for understanding and predicting the communication impact on each customer. It also enables the campaign manager, for example, to divide the customers according to their responses and push the offer to those customers who will most likely react positively to messaging. The effect of customer characteristics on response rates to short-form advertising is an under-researched area.

For this research, based on the prior work of the effect of both demographic and behavioral individual differences on reactions to persuasive messaging, the hypotheses are:

H4:There are customer characteristics that indicate response rates in short-form advertising.

H4a:There are customer characteristics that indicate response rates based on the message type in short-form advertising.

H4b:There are customer characteristics that indicate response rates based on the channel in short-form advertising.

For H04a and H04b, we specifically investigate the following customer characteristics, which are normal collected by the company:

Demographic variables (customer gender, age on network, customer value, smartphone flag (y/n), smartphone technology).

Behavioral variables (average recharge internal, average data balance, total interval minutes, data usage).

Methodology

To test these hypotheses, the authors conducted a between-subjects experiment, as part of a marketing campaign of a large telecom company, measuring the response rate of persuasive messages across channels.

The persuasive messages were sent via three communication channels: (a) text message (SMS), (b) Facebook advertising (FB), and (c) a mobile app notification. The messages were sent to mutually exclusive segments of a targeted customer population. The customers, who were all of the same nationality, were stratified into experimental segments that were as demographically similar as possible in terms of gender, age, length of time with the company, and so on.

The dependent variable was the response rate, which refers to the number of people who positively respond to a message divided by the number of those to whom the message was sent. Customers were given a limited time to respond to the offer or discard it, as required by the company's guidelines.

The authors designed the messages with three persuasion techniques, based on the literature review, and each had the same offer of free international minutes to buy a specific mobile credit recharge option

Mobile prepaid lines count on different type of recharges where customers can buy a specific benefit (credit, calling minutes, or data allowance) in advance.

:

Rational: contain factual statements and descriptions of the offer.

Emotional: contain elements evoking affective responses (Positive: causing a nostalgic feeling of missing home. Negative: causing fear of losing the limited offer).

Social: causing peer pressure to conform to social norms and expectations of others.

Since the experiment was conducted in a telecommunications company, where such message crafting and advertising occur nearly daily, the company has its own internal ethical review process. First, the experiment was run as a normal course of business operation that sought to enhance methods of communicating with customers and improve the contexts and content of messages. Second, the authors involved expert team members in formatting the content of the messages to ensure it abided by the company's policies. Third, the company ensured that proper communication was delivered to the customers involved in the experiment without unnecessary disturbance to service. In addition, the extracted customer data were anonymized before being supplied to the researchers.

Data Collection

The experiment involved 39,000 customers of the telecommunications company and focused on the Egyptian customer population. The offer was 15 free international calling minutes to Egypt with a data recharge equivalent to $27 USD. The choice of Egyptian customers was based on both a sufficiently large segment of customers to run the experiment and low-cost consideration for the free value given in the communicated offer in the host country of the telecom company. The host country has a substantial Egyptian expatriate population, and this customer segment is users of international calling minutes to reach families, friends, and others in their home country.

The customers were representatively split into equally sized combinations of communication channels and persuasive strategies. A total of twelve groups were formed, each containing approximately 3,000 customers. The experiment also designated a control group of approximately 3,000 customers for benchmarking the experimental effects. This control was sent no message, a common benchmarking in the industry to see the effect of any advertising.

A common process in telecom and other companies, called contact strategy, was performed before sending any customer campaigns. The contact strategy process determines whether each customer is eligible for receiving an offer. This contact strategy includes the exclusion of blacklisted customers, do-not-disturb customers, and customers who have already received the maximum number of offers in a given period. Hence, after the contact strategy exclusion process, the number of contacted customers in the experiment was reduced to approximately 2,600 customers in each group, resulting in a total of 33,848 customers, including the control group, as shown in Table 1.

Number of Customers in Each Group by Persuasive Techniques and Communication Channels

ChannelRationalEmotional (pos.)Emotional (neg.)SocialTotal
Facebook ads2,5792,5342,5632,55010,226
Text messaging2,5782,5622,5652,58810,293
Mobile app2,5872,5732,5592,61310,332
Total7,7447,6697,6877,75130,851
No message
Control2,99733,848

Note. There is a control group of 2,997 receiving no message. Bold represents headings and totals.

Construction and Manipulation Check of the Messages

With the assistance of marketing communication experts within the telecom company and prior work (Sohn & Lee, 2007), the rational message was tweaked and modified to produce the required message text for the other techniques. The message texts, translated from Arabic into English, of the offer to the customers using the different persuasive techniques are shown in Table 2. The rational message is the simplest and shortest form of the message that delivers the offer in the minimum number of words with the minimum triggered sentiments.

Text Used for the Persuasive Techniques

Persuasive strategyMessage text (translated from Arabic to English)Number of Words and Characters
RationalRecharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 20No. characters: 90
Emotional (positive)Missing home? Talk more with your family and friends in Egypt. Recharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 31No. characters: 142
Emotional (negative)Do not miss the limited time amazing offer to call Egypt. Recharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 31No. characters: 137
SocialAre your friends calling Egypt more than you? Here is your chance to join them and call more to Egypt. Recharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 40No. characters: 173

Although we would ideally select explicitly positive emotion, negative emotion, or social terms for each message, organizational guidelines prohibit the messages from appearing “too spammy”. So, none of the explicit messages were deemed appropriate. In the end, these were the messages that passed organizational quality control. Additionally, each message contained a reward asset, which is a component of the PSD model (Oinas-Kukkonen & Harjumaa, 2009).

To validate the sentiment triggered by each of the text messages, the researchers conducted a manipulation check on each message on 50 Egyptian crowd workers for each message using Appen, a crowdsourcing platform that enables the collection of user responses according to a constructed message format. The text was presented to each crowdworker, who was asked to choose the sentiment that best corresponded to the text. Table 3 presents the number and percentage of crowdworkers who had a certain sentiment triggered as a result of each message.

Sentiment Votes Collected by Each Strategy, with the Highest Category (Displayed in Bold)

StrategySentiment votes (%)
RationalEmotional (pos.)Emotional (neg.)Social
Rational16 (32)8 (16)17 (34)9 (18)
Emotional (positive)4 (8)25 (50)14 (28)7 (14)
Emotional (negative)7 (14)7 (14)24 (48)12 (24)
Social9 (18)11 (22)12 (24)18 (36)

As shown in Table 3, the majority of votes generally aligns with the intended persuasive technique. The crowdworker findings were in line with the chosen sentiment, and the telecom marketing experts also considered the messages on target with the intended strategies. The persuasive messages were then sent to customers in each group. Figure 1 shows the snapshots of how customers received the message on each communication channel.

Figure 1

Snapshots of the persuasive messages sent via SMS, Facebook Ads, and mobile app notification (see Table 2 for the English translations). SMS, short message service.

The authors collected a variety of anonymized data for each customer, including the dependent metric of interest, response to the offer, and a variety of additional data, as shown in Table 4.

Demographic and Behavioral Variables of the Customers

Demographic variableDefinitionReason for inclusion
Customer genderMale/FemaleCommon demographic attribute for segmentation
Age on networkHow long with the companyExpected impactful demographic attribute based on discussions with domain experts
Customer valueRevenue rating of High, Medium, or Low valueExpected impactful demographic attribute based on discussions with domain experts
Smartphone flagYes/NoExpected impactful demographic attribute based on discussions with domain experts
Smartphone technology2G/3G/4G technology supported by the handsetExpected impactful demographic attribute based on discussions with domain experts
Behavioral variableDefinitionReason for inclusion
Average recharge internalAverage interval in days between the rechargesExpected impactful behavior attribute based on discussions with domain experts
Average data balanceAverage data balance in megabytesExpected impactful behavior attribute based on discussions with domain experts
Total interval minutesTotal minutes calling Egypt in the last 30 daysExpected impactful behavior attribute based on discussions with domain experts
Data usageTotal data usage, megabytes, last 30 daysExpected impactful behavior attribute based on discussions with domain experts
Maximum rechargeThe highest recharge by the customerExpected impactful behavior attribute based on discussions with domain experts
Findings
Persuasive Messaging Techniques

Addressing RQ1 (message effect), Table 5 shows the results of the response rate of the different persuasive techniques. Each cell includes the number of customers who accepted the offer and the percentage of customers who accepted the offer through all channels.

The Response Rates by Message Type and Channel

StrategyControlFBSMSMobile appOverall by message
Rational15 (0.58%)15 (0.58%)15 (0.58%)45 (0.58%)
EmotionalPositive19 (0.75%)9 (0.35%)16 (0.62%)44 (0.57%)
Negative13 (0.51%)5 (0.19%)12 (0.47%)30 (0.39%)
Social (peer pressure)14 (0.55%)7 (0.27%)10 (0.37%)31 (0.40%)
Control response rate12 (0.40%)Overall by Platforms
Target response rate by platform61 (0.60%)36 (0.35%)53 (0.51%)150 (0.49%)

SMS, short message service.

Given the overall response rate of the campaign (0.49%) compared to the control group (0.40%), the overall effectiveness of the messaging in the various channels is, at first glance, minor. In a comparison of the persuasive strategies, the rational message yielded the highest response rate (0.58%). Also, the positive emotional message resulted in the second-highest response rate (0.57%). The lowest response rates were found for the negative emotional message (0.39%) and peer pressure (0.40%) messages. The response rate of the SMS channel was the lowest overall, even lower than for the control group. It is not clear why, as one would expect the response rate to at least match the control group. This aspect would require further investigation. Results of logistic regression analysis indicate that there was no significant association between the message types and response rates. Therefore, H1a, H1b, and H2 are not supported. Positive emotional, negative emotional, or social messages do not result in higher response rates relative to rational messages in short form advertising.

Communication Channels

Moving to RQ2, Table 5 (last row) shows the response rates of the different channels. FB and mobile app channels had better response rates (0.60% for FB and 0.48% for the mobile app) compared to the SMS channel (0.38%). The response rate of the SMS channel was <0.47% of the control group. Results of the binary logistic regression indicate that there was a significant association between the channel type and response rate (b = 1.39, OR = 4.02, CI: 0.24–2.87, p = 0.03 for FB and b = 1.31, OR = 3.69, CI: 0.14–2.79, p = 0.05 for the mobile app). Therefore, H3 is fully supported. The mobile app platform has a higher response rate than FB and SMS channels, and FB also has a significantly higher response rate than the SMS channel for short-form advertising.

We explored the interaction effect between the message type and the communication channel. Results of the logistic regression indicated that there was a significant interaction effect between FB and all message types (χ2(7) = 1.3906, p = 0.0314) and the mobile app and all message types (χ2(7) = 1.3048, p = 0.0453). Interestingly, there is a significant but negative interaction effect between the social message and the mobile app (χ2(7) = −2.0095, p = 0.0183). Therefore, H3a is supported. The mobile app's response rate is higher than the responses of the other channels. H3b is partially supported as FB has a higher response rate for social messages in short form advertising that is significantly higher than that of SMS but not significantly different from that of the mobile app.

As shown in Table 5, most persuasive communication worked well on FB and the mobile app channel. Interestingly, negative emotional techniques did not work well on any channel, and the response rates of the negative emotional message and social pressure messages were lower than that of the control group. The SMS response rate was lower than that of the control group, indicating that commercial messages via this channel had an overall negative effect (i.e., it would be better not to advertise than to use SMS advertising).

Customer Characteristics

Addressing RQ3 regarding customer characteristics, the authors used separate Kruskal-Wallis tests on each continuous variable to test for differences among the groups to determine if customer characteristics influenced the response rates. The authors first examined the impact of customer attributes on each message type's response rate and found that there were no significant differences that depended on the persuasive message type among customers. Therefore, H4a is not supported. There is no indication that customer characteristics influence response rates based on the message type in short form advertising.

Examining the channel, there was a significant difference among communication channels for one of the customer behavioral characteristics, average data recharge interval2 (3) = 7.32, p = 0.05). The average data recharge interval indicates when a customer purchased a data recharge. Multiple comparisons were carried out with a Dunn test showing a significant positive difference between the FB and SMS groups, z = 2.24, p = 0.03, as well as between the FB and the control groups, z = −1.99, p = 0.05. So, H4b is partially supported. There is at least one customer characteristic that indicated response rates based on the channel.

Discussion and Implications
Theoretical Implication of the Research

In terms of specific findings, positive emotional and emotionally neutral (“rational”) messages work better than negative emotional and socially oriented messages. Theoretically, the contribution of this research is a comprehensive analysis for optimizing persuasive online communication with customers in direct marketing by identifying how, where, and who to target, which is conceptually shown in Figure 2.

Figure 2

Persuasion-based Optimization Advertising Model of the message, channel, and customer for short-form advertising.

However, fear of losing an opportunity and social messages did not result in a higher response rate than rational messages, suggesting negative and social messages harm response rates in this context (i.e., negative emotional messages on FB and social pressure on SMS), similar to the negative effects of persuasive messages found in other channels (Wang & Zhang, 2016).

Results show that nonfactual persuasive messaging in the online context may not be an effective form of advertising communication relative to a factual approach for short-form advertising. Rational messages had a higher response rate than emotional messaging and social messaging. Although rational messaging works well, other strategies such as positive emotional messages can also be effective in channels that users trusted (Andaleeb, 1996), such as mobile applications (Renner et al., 2020). Contrary to findings from prior research, which studied social and emotional cues sent in more sophisticated contexts, our findings suggest that in a limited communication platform constrained by message length, emotional (especially negative emotional) messages and social messages may have adverse effects in convincing customers to buy a product.

Interestingly, our crowdsourced evaluations of the short form advertising messages indicated a mixed perception of persuasive strategies. Therefore, even though an advertiser may believe they are applying, for example, an emotional strategy, the customers may perceive this strategy differently than intended. This discrepancy between planned and realized effects should be explored in future work. We surmise several potential explanations for this finding. First, consumers may not be able to detect and identify persuasive strategies all too well, which confuses when the consumer is trying to interpret a given ad message. Second, it may be that persuasion is perceived differently altogether, meaning that what the advertiser perceives as a rational message may evoke an emotional reaction, and vice versa. It is, therefore, interesting to contemplate the idea that there may not be purely emotional or purely rational messages, but in reality, all short-form advertising messages may include components of each when interpreted by consumers.

Continuing this line of thought, from a theoretical point of view, the constraint in the number of characters of short-form advertising may negate portions of prior research on persuasive messaging (Adler et al., 2016; Dillard & Nabi, 2006), as customers may be more receptive toward simple, factual communication than to sophisticated peripheral cues, which are effective in communication channels with less constrained length. These findings add to prior research pointing to social media as an effective communication channel for companies. The factual aspect may be due to the character limitations in these forms of customer contact, a limitation that is not prevalent in some other forms of commercial advertising communications. From a practical perspective, this length restriction has become more common in online commercial communication.

Concerning communication channels, FB (with a 38 million user base in Egypt at the time of the study) advertising and the mobile app had higher response rates. This finding is most likely due to the greater degree of trust, opt-in, and loyalty aspects of these platforms, as customers, to some extent, accept commercial messaging via these channels. The interaction between message and channel appears to show that the latter has the most impact on the response rate, regardless of the message type. This, again, is most likely due to the contextual limitations on content with these channels. Increasingly considered a potentially spamming channel (Cloudmark, 2012), SMS underperformed the control group regarding the response rate.

The findings point to the value of organizational mobile apps, as the apps may indicate an acceptance of commercial and other communication from an organization by users based on the users’ perceived trustworthiness, relationship, and dependency toward these channels (Andaleeb, 1996; Danaher & Rossiter, 2011; Mohr & Nevin, 1990).

Finally, customer characteristics differences were limited (there were no demographic differences), and only one behavioral characteristic (interval from the last recharge) affected the response rate. This finding indicates that behavioral features and perceived usefulness of the offer are more important than demographics in predicting the response rate to persuasive messaging on these channels. This confirms earlier research that postulates a shift in marketing communications from demographic to intent-based targeting and the importance of a customer's historical behavioral data for communication effectiveness (Jansen & Booth, 2010; Salminen, Seitz, Jansen, & Salenius, 2017).

Practical Implication for Commercial Organizations

From our study, there are three core takeaways for organizations aiming to sell services or products via short online message targeting, which are:

Persuasive Messages: Given the results, it seems that the short form advertising message must contain some factual information, and, at least for this product, rational information is the most effective in generating high response rates relative to the other forms of messaging evaluated.

Communication Channels: Opt-in channels may be beneficial for companies using the short form advertising messaging format. The fact that the company mobile app as a channel has high response rates indicates that customers using these mobile apps may be more receptive to such marketing approaches. As such, the mobile app may be an effective communication channel for companies and worth the effort to recruit customers.

Consumer Characteristics: In the end, it is the customer needs that matter. The needs and wants of consumers appear to outdo other advertising efforts of short-form advertising messaging content and channel selection, and, despite leveraging a variety of consumer attributes, only one behavioral attribute (the need to recharge) was directly associated with the product seems to affect consumer response rate.

Limitations, Strengths, and Future Work

Regarding the limitations of this research, the study was confined to one industry and one product, international mobile phone credit. The finding that rational messages had higher response rates may be a factor of the nature of the product; perhaps employing a different product might lead to other message types performing higher. It remains to be seen if the findings hold in other contexts and for other types of commercial products. Also, the researchers tested a limited set of messaging and channels. Similarly, the implementation of the research in a real customer environment limited the options concerning messaging and making each message distinct. However, this is a limitation of working in a real environment with real customers. Finally, the experiment should be replicated with other nationalities for generalizability across cultural contexts.

As for strengths, the researchers evaluate three types of messaging across three different and popular communication channels using a sample in the tens of thousands of actual customers. Therefore, limitations asides, the authors believe the research provides important findings for online advertising and marketing domain concerning the transmission of pervasive communication across these channels for short-form advertising.

Conclusion and Future Research

This research presents a conceptual framework of the message, channel, and customer within our Persuasion-based Optimization Advertising Model for short-form advertising. We based on a conceptual framework on implications from our empirical research that examined the influence of the interplay among messages, channels, and customers on the response rates of a commercial offer sent to >30,000 customers of a major telecom company. Findings showed that a rational message and trusted channels, such as mobile apps, work best, although there is an interplay between the two. There does appear to be an interplay among these three (i.e., message, channel, and customer), although, at least for this product, customers prefer just the facts over a trusted communication channel (the mobile app).

Concerning further work, examining more behavioral features may lead to improved response rate prediction. Also, expanding the experiment to other industries and contexts, such as product reviews, that can accommodate more persuasive techniques (Kim & Kang, 2018) would determine the generalizability of the findings to other domains other than telecommunications. It would also be insightful to investigate the context aspect of the message receiver (Peng, Qian, & Liu, 2020). An obvious area of future research would be investigating other product and service offerings via the same channels and using the same message formats. Finally, a fruitful area of future research would be to investigate the effects of richer message content and multimedia messages (Alamäki, Pesonen, & Dirin, 2019).

Figure 1

Snapshots of the persuasive messages sent via SMS, Facebook Ads, and mobile app notification (see Table 2 for the English translations). SMS, short message service.
Snapshots of the persuasive messages sent via SMS, Facebook Ads, and mobile app notification (see Table 2 for the English translations). SMS, short message service.

Figure 2

Persuasion-based Optimization Advertising Model of the message, channel, and customer for short-form advertising.
Persuasion-based Optimization Advertising Model of the message, channel, and customer for short-form advertising.

The Response Rates by Message Type and Channel

StrategyControlFBSMSMobile appOverall by message
Rational15 (0.58%)15 (0.58%)15 (0.58%)45 (0.58%)
EmotionalPositive19 (0.75%)9 (0.35%)16 (0.62%)44 (0.57%)
Negative13 (0.51%)5 (0.19%)12 (0.47%)30 (0.39%)
Social (peer pressure)14 (0.55%)7 (0.27%)10 (0.37%)31 (0.40%)
Control response rate12 (0.40%)Overall by Platforms
Target response rate by platform61 (0.60%)36 (0.35%)53 (0.51%)150 (0.49%)

Text Used for the Persuasive Techniques

Persuasive strategyMessage text (translated from Arabic to English)Number of Words and Characters
RationalRecharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 20No. characters: 90
Emotional (positive)Missing home? Talk more with your family and friends in Egypt. Recharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 31No. characters: 142
Emotional (negative)Do not miss the limited time amazing offer to call Egypt. Recharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 31No. characters: 137
SocialAre your friends calling Egypt more than you? Here is your chance to join them and call more to Egypt. Recharge with an Internet 100 card and get FREE 15 min for 7 days to call Egypt. Offer valid till DD/MM/YYYYNo. words: 40No. characters: 173

Demographic and Behavioral Variables of the Customers

Demographic variableDefinitionReason for inclusion
Customer genderMale/FemaleCommon demographic attribute for segmentation
Age on networkHow long with the companyExpected impactful demographic attribute based on discussions with domain experts
Customer valueRevenue rating of High, Medium, or Low valueExpected impactful demographic attribute based on discussions with domain experts
Smartphone flagYes/NoExpected impactful demographic attribute based on discussions with domain experts
Smartphone technology2G/3G/4G technology supported by the handsetExpected impactful demographic attribute based on discussions with domain experts
Behavioral variableDefinitionReason for inclusion
Average recharge internalAverage interval in days between the rechargesExpected impactful behavior attribute based on discussions with domain experts
Average data balanceAverage data balance in megabytesExpected impactful behavior attribute based on discussions with domain experts
Total interval minutesTotal minutes calling Egypt in the last 30 daysExpected impactful behavior attribute based on discussions with domain experts
Data usageTotal data usage, megabytes, last 30 daysExpected impactful behavior attribute based on discussions with domain experts
Maximum rechargeThe highest recharge by the customerExpected impactful behavior attribute based on discussions with domain experts

Number of Customers in Each Group by Persuasive Techniques and Communication Channels

ChannelRationalEmotional (pos.)Emotional (neg.)SocialTotal
Facebook ads2,5792,5342,5632,55010,226
Text messaging2,5782,5622,5652,58810,293
Mobile app2,5872,5732,5592,61310,332
Total7,7447,6697,6877,75130,851
No message
Control2,99733,848

Sentiment Votes Collected by Each Strategy, with the Highest Category (Displayed in Bold)

StrategySentiment votes (%)
RationalEmotional (pos.)Emotional (neg.)Social
Rational16 (32)8 (16)17 (34)9 (18)
Emotional (positive)4 (8)25 (50)14 (28)7 (14)
Emotional (negative)7 (14)7 (14)24 (48)12 (24)
Social9 (18)11 (22)12 (24)18 (36)

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