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Abstract

While the social media app Snapchat has increasingly attracted the attention of millennials around the world, there is limited empirical research dealing with Snapchat marketing. For businesses, it is imperative to know how effective Snap Ads are at reaching millennials. Based on the uses and gratifications theory (UGT), this study aims to fill this research gap by identifying millennials’ motives for using Snapchat and analyzing how they affect their attitudes toward Snap Ads and the subsequent behavioral intentions. Some 265 Saudi, Snapchat-using students aged between 18 and 35 completed an online survey. Our data analysis employed exploratory and confirmatory factor analyses, as well as structural equation modeling. The results indicate that respondents seek four forms of gratification from using Snapchat, namely information seeking, self-expression, entertainment, and social interaction. Of these, only information seeking and entertainment were found to have significant positive influences on attitudes toward Snap Ads, intentions to share then, and purchasing intentions. This research contributes to the theory by proving that the UGT is suitable for gaining knowledge about consumer behavior on social media in general, as well as by proposing a framework for studying the persuasive effectiveness of Snap Ads in particular. From a practical perspective, this study offers guidelines on how customized Snap Ads can be conceived for millennials, so they will not irritate them.

Keywords

millennials uses & gratifications intention to share Snap Ads persuasion

Introduction

Having a strong presence on social media presents opportunities to create value for customers and enhance the brand–consumer relationship. This is why more than 80% of marketers invest hugely in social media in general and in digital advertising in particular (Faruk et al., 2021; Ganguly, 2015; Gao & Feng, 2016; Gil-Or, 2010; Lipschultz, 2017; Smith, 2011; Stelzner, 2016; Tucker, 2016). At the same time, researchers are continually investigating how digital advertising in general, and social media advertising in particular, can help persuade consumers (Faruk et al., 2021).

Snapchat’s marketing potential has gained particular attention among many practitioners and scholars. Well-known brands like Sony, Sperry, Victoria’s Secret, Universal Studios, and GoPro maintain continuous contact with their customers through Snapchat’s Discover feature (Sashittal et al., 2016). Over the years, Snapchat has grown impressively in terms of its number of users and daily views on mobile devices (Frier, 2016; Hatch, 2018; Heine, 2016a; Murphy, 2018; Richter, 2016), and maintaining this relies upon constantly satisfying users’ needs through this platform (Quinn, 2020). This has led to Snapchat increasing its net worldwide revenues from advertising (Snap Ads) to an estimated 2.62 billion US dollars in 2021 (Statista Research Department, 2021a).

Snapchat engagement is driven by the fear of missing out (FOMO), which is defined as “a pervasive apprehension that others might be having rewarding experiences from which one is absent,” so it arouses “a desire to stay continually connected with what others are doing” (Przybylski et al., 2013). In the Snapchat app, users’ interactions with brands are ephemeral in nature, but they are constantly renewed as brands offer time-limited promotions and photo/video collections that are only available for 24 hr. Due to this short-lived content, Snapchatters continually follow their favorite brands to explore their updates, and they more quickly and frequently share those brands’ content (Utz et al., 2015). This new Snapchat experience is attractive to businesses, because it provides opportunities to differentiate and customize offers and customer relationships, whether to trigger a desired behavior or just provide information. Furthermore, compared to traditional and other forms of digital advertising, Snap Ads appears to be more efficient at generating revenue (Hutchinson, 2021), so it will be interesting to investigate the persuasiveness of Snap Ads.

Due to its relatively young population, which is mostly aged between 26 and 34 years old, the Kingdom of Saudi Arabia (KSA) has the highest annual growth rate for social media users of anywhere in the world (Radcliffe & Bruni, 2019). About 72.38% of its population is rated as active users of social networking sites (SNSs), with a daily average of 3 hr of use (Alhubaishy & Aljuhani, 2021). In 2019, global statistics classified Snapchat’s monthly active audience in the KSA as the largest in the world (Fonteneau, 2019), and in 2021, the country was ranked fifth with a total of 19.7 million Snapchat users (Statista Research Department, 2021b). On the global level, Snapchat tends to attract women more than men, and it is most popular amongst millennials, who are typically, at present, adults aged 18 to 34 (Heine, 2016b; Trending Value, 2017). In the United States, for example, around 70% of Snapchat users are women and typically under 34 years old, with 53% of them being aged 18 to 24 (Aslam, 2021; MacMillan, 2013). Similarly in the KSA, of the 9 million active daily Snapchat users, 57.9% are aged 18 to 34 with 55% being women (Ampere Analysis, 2017; Saudi Gazette, 2018). This trend was observed around the world in 2021, with 61% of active Snapchatters being female (Statista Research Department, 2021c), and 12.5% of them being aged 18 to 20 (Statista Research Department, 2021d).

The increase in the number of Snapchat users and growing investment in Snap Ads in the KSA highlight the powerful motives for adopting this application, as well as the effects that these motives have on the persuasiveness of Snap Ads. From a marketing perspective, Snapchat can help engage customers and drive purchases, especially when Snap Ads cultivate emotional connections and positive attitudes (Phua et al., 2017b; Pavelle & Wilkinson, 2020).

Taking into account the uses and gratifications theory, this present research sought to determine millennials’ motives (i.e., the gratifications sought) for using Snapchat and examine their impact on attitudes toward Snap Ads and behavioral intentions.

The following section provides an overview of Snap Ads’ relevance for marketing to millennials. It also discusses the importance of Snapchat users’ motivations when investigating Snap Ads’ persuasiveness. It also proposes some hypotheses to link these motives with attitudes toward Snap Ads and behavioral intentions. The second section then presents the research design, before the third section details the statistical analyses. The fourth and final section then presents the findings and discusses their major implications on both the theoretical and practical levels.

Literature Review, Theoretical Framework, and Hypotheses Development

The strong potential of Snap Ads for promoting products has attracted several brands in recent years, yet there is a lack of research into the effectiveness of Snap Ads, particularly when it comes to exploring motives that lead to sharing Snap Ads and how these motives influence consumers’ attitudes and purchasing intentions.

Snap Ads

Snapchat offers different advertising products with specific marketing objectives, such as Snap Ads, Filters, Lenses, and Discover, thereby offering an interesting alternative to TV advertising and other major social media platforms.

A Snap Ad is a full-screen video advertisement with customized attachments (e.g., web view, app install, long-form, and article) based on the advertiser’s objectives (Felicitas, 2022; L. Johnson, 2016; Snap Inc. Internal Data, 2017). It offers interesting opportunities for advertisers and a new experience for customers. Snapchat makes it easier to target particular clientele because it “takes context into account to serve up the Ad most relevant to the user.” Furthermore, Snapchatters “can view a product’s Snap Ad, can swipe up on the Snap Ad to buy the product instantly from the advertiser’s website without leaving the Snapchat application” (McAlone, 2017). Overall, Snapchat advertising represents a relevant tool for marketers due to its potential to acquaint users with brands through emotional connections (Sashittal et al., 2016).

Nevertheless, sponsored Snapchat advertising can also irritate users. A survey among 2,500 millennials and gen Zers found that 74% of them hate seeing advertising in their social media feeds, such that 56% of these audiences decreased their social media usage time. This highlights an interesting conundrum about how to advertise online without annoying consumers (Whitman, 2016). There is no doubt about the challenge of targeting the right audience with attractive and engaging content (W. Wang et al., 2021). The uses and gratifications theory (UGT) of E. Katz et al. (1973) offers a marketing perspective for understanding customers’ motivations for engaging with specific types of social media content (Malthouse et al., 2013; Smock et al., 2011), so marketers can avoid annoying users and enhance the effectiveness of their Snap Ads.

Motives for Using Snapchat

In the social media context, investigations have applied various social psychology theories and concepts—such as social identity theory (e.g., D. Lee et al., 2011; H.-L. Yang & Lai, 2011), social capital theory (e.g., Choi & Scott, 2013), and the need to belong theory (e.g., Ma & Ma & Chan, 2014; Ma & Yuen, 2011)—in order to learn about users’ sharing behaviors. Nevertheless, UGT has been the dominant social science theory for studying how and why individuals use a specific medium (Smock et al., 2011), and it is touted as being one of the most influential theories in the field of communications research (C. A. Lin, 1998). For many decades now, UGT has served as a cutting-edge theoretical approach for studying mass communications media, starting with those currently regarded as traditional (e.g., newspapers, radio, and television) and moving onto the emerging internet-based media (Hossain, 2019; Ruggiero, 2000). UGT seeks to identify the needs and desires that drive an individual to use a particular media channel (Smock et al., 2011). Its primary strength lies in its ability to facilitate investigations of “mediated communication situations via a single or multiple sets of psychological needs, psychological motives, communication channels, communication content, and psychological gratifications within a particular or cross-cultural context” (C. A. Lin, 1998).

Given that UGT is the most effective approach for identifying the motivations underlying media channel usage (Hossain, 2019; LaRose & Eastin, 2004; C. A. Lin, 1998; Ruggiero, 2000; Smock et al., 2011), as well as its extensive application to examining the various motivations in social media (e.g., Kujur & Singh, 2020; Malthouse et al., 2013), it should serve as a relevant theoretical foundation for this present study.

Motives for using the internet are key to understanding users’ reactions to internet advertising (K. C. Yang, 2004). Gratification emerges from satisfying various needs by using a specific medium (C. S. Lee & Ma, 2012). According to the UGT, media users have a goal-driven approach in that they search out a medium that will best meet their needs and reflect their specific motives (Haridakis & Whitmore, 2006; Leung, 2013; McLeod & Becker, 1981; West & Turner, 2007). The UGT explains “how antecedent conditions lead to felt needs, motives, attitudes, and behaviors, which produce outcomes” (Cortese & Rubin, 2010), so motives for using Snapchat depend on the user’s needs, and understanding these motives will help to adapt communications and products to meet customers’ specific needs.

The available literature deals mainly with Facebook and identifying the specific motives for using it. N. Park et al. (2009) discovered four primary needs in the Facebook context, namely information seeking, entertainment, socialization, and self-status seeking. In contrast, Hunt et al. (2012) found only three major predictive motives for frequent Facebook use, namely entertainment, interpersonal communication, and self-expression. Krause et al. (2014) also highlighted three motivations in the form of entertainment, communication, and habitual diversion. Sheldon et al. (2021), meanwhile, posited that the main reasons for using Facebook among baby boomers and traditionalists are diversion, entertainment, relationship maintenance, companionship, and the desire to meet new people. Based on a review of 49 studies related to sharing behavior in social media and other online contexts, as well as 53 studies that applied the UGT in the social media context, Plume and Slade (2018) highlighted six motivations for sharing tourism-related sponsored advertising on Facebook: information seeking, entertainment, socializing, self-expression, information sharing, and altruism. LaRose and Eastin (2004) revealed that information seeking, entertainment, and social needs are the most common use and gratification factors in relation to SNSs. Similarly, C. S. Lee and Ma (2012) found that the main factors are information seeking, entertainment, socializing, and self-status seeking.

Regarding the popular social media platforms of Facebook, Twitter, Instagram, and Snapchat, researchers have found that the motives for using SNSs are associated with the features and functions offered by each medium (Phua et al., 2017a, 2017b; Quan-Haase & Young, 2010). In addition, users remain engaged with SNSs for as long as their gratifications and needs are satisfied (Y.-C. Ku et al., 2013).

Phua et al., 2017a, 2017b; Quan-Haase & Young, 2010) compared Facebook, Twitter, Instagram, and Snapchat in terms of six gratifications: showing affection, following fashion, demonstrating sociability, passing time, sharing problems, and improving social knowledge. In terms of following brands, Snapchat scored higher than the other platforms according to the last three motives. The authors therefore posited that Snapchat is the most useful for entertainment, relaxation, and escape from everyday life. Furthermore, due to its synchronous and personal nature, Snapchat offers a means for forgetting problems and getting more involved in the social community. The comparison also revealed that individuals use Instagram more frequently than Snapchat for showing affection, following fashion, and demonstrating sociability.

By synthesizing the several studies that have applied UGT to social and traditional media, Gao and Feng (2016) classified gratifications from social media into five main categories: information seeking, entertainment, social interaction, self-expression, and impression management. They found that social interaction with friends through social media and impression management for maintaining one’s self-image in a social group were perceived as being interconnected by respondents.

The above literature review has found that the four dominant motivations are information seeking (IS), entertainment (ET), social interaction (SI), and self-expression (SE), and these antecede intentions to share Snapchat Ads and the development of attitudes and purchasing intentions (Gao & Feng, 2016; C. S. Lee & Ma, 2012; N. Park et al., 2009).

Hypotheses Development

The dominant motivations that drive Snapchat use represent a starting point for examining users’ attitudes toward Snap Ads (ASA), their intentions to share Snap Ads (ISSA), and their purchasing intentions (PI).

The Impact of Information Seeking

Information seeking (IS) refers to the search for information and the act of learning how to make sense of things (Shao, 2009). By navigating through social media, people can track information about sales, deals, products, events, and businesses (Al-Adwan & Kokash, 2019; J. W. Kim, 2014; Kwak et al., 2010; Whiting & Williams, 2013). IS is a motivation that embodies a need for resources and helpful information (Ashley & Tuten, 2015). Thus, information obtained directly from brands can be a major form of gratification when involving consumers in online brand communities, such as those on Snapchat (H. W. Kim et al., 2011; Dholakia et al., 2004; Dunne et al., 2010; C. S. Lee & Ma, 2012; K.-Y. Lin & Lu, 2011; Muntinga et al., 2011; N. Park et al., 2009; Pavelle & Wilkinson, 2020; Raacke & Bonds-Raacke, 2008). This leads to the following hypothesis:

H1: IS is a significant motive for using Snapchat.

Information about products and events that is presented through advertisements on social media affect consumers’ attitudes and influence their decisions (Raacke & Bonds-Raacke, 2008; Rotzoll et al., 1996). Gratification with social media information is therefore positively related with attitudes toward product messages (C. Chung & Austria, 2010, 2012), such that consumers who use social media to search for information are likely to feel positively about native advertising (J. Lee et al., 2016). When IS is the motive for using Snapchat, it is expected to lead to a favorable ASA. Indeed, Tiany (2017) confirmed that social IS has a positive impact on ASA. This leads to the follow hypothesis:

H2: IS as a motive positively affects ASA.

With the exception of the study of Hanson and Haridakis (2008) that dealt with news sharing on YouTube, most studies in online and social media contexts have confirmed that IS promotes sharing behavior (Kairam et al., 2012; J. W. Kim, 2014; J. Lee et al., 2016; Oh & Syn, 2015; Raacke & Bonds-Raacke, 2008).

H3: IS has a positive effect on consumers’ intentions to share Snap Ads.

IS increases a customer’s knowledge about a brand promoted on social media, and this helps the customer to make better decisions and reinforces the PI (Al-Adwan & Kokash, 2019; Hao et al., 2019; E. Katz et al., 1973; Turcotte et al., 2015), leading to the following hypothesis:

H4: IS has a positive effect on PI.

The Impact of Entertainment

ET in social media serves to satisfy various consumer needs (Hung, 2014), such as a desire to pass time, evade life’s daily routine, vent negative feelings, browse content, share experiences, and engage in entertaining activities (P. R. Johnson & Yang, 2009; N. Park et al., 2009; Plume & Slade, 2018; Quan-Haase & Young, 2010; Raacke & Bonds-Raacke, 2008; Whiting & Williams, 2013; Zhao & Rosson, 2009). Social media can be a source of ET, with individuals playing games, listening to music or jokes, and watching humorous videos (Whiting & Williams, 2013). Furthermore, interacting with others in an online network can be fun and enjoyable (Y. C. Ku et al., 2013; Pai & Arnott, 2013). Due to the interactive resources on the platform, ET via social media can be an immersive experience that provides significant gratification (C. S. Lee & Ma, 2012; N. Park et al., 2009; Yu et al., 2020). A comparison between Facebook, Twitter, Instagram, and Snapchat found that the last of these was the most useful for ET (Phua et al., 2017b). This leads to the following hypothesis:

H5: ET is a significant motive for using Snapchat

ET is positively related to attitudes toward advertising (Ducoffe, 1995). The greater the enjoyment that is perceived from watching advertising, the more positive the consumer’s attitude toward advertisements will be (Blanco et al., 2010; Chowdhury et al., 2006; Tsang et al., 2004). However, C. Chung and Austria (2010, 2012) found that ET needs do not significantly influence attitudes toward the advertising content on social media. In some real-life contexts, using social media has become a common practice in everyday life, and this has weakened its ability to provide ET (C. Chung & Austria, 2012). The literature also confirms the existence of a significant relationship between ET motives and attitudes toward sponsored advertising (Celebi, 2015; Ducoffe, 1995, 1996; J. Lee et al., 2016; Mukherjee & Banerjee, 2017; Oh & Syn, 2015; Plume & Slade, 2018; Turcotte et al., 2015; Zhou & Bao, 2002), although the findings have been contradictory about the direction of this relationship. On Snapchat, users can discover innovative entertaining content (Manjoo, 2016), but if they are seeking to satisfy ET needs when they are suddenly interrupted by Snap Ads, it can cause an adverse effect (Dehghani et al., 2016). In this case, ET has a negative impact on ASA (Tiany, 2017). Nevertheless, Plume and Slade (2018) demonstrated that ET has a positive effect on consumers’ intentions to share tourism-related sponsored advertisements on Facebook. This finding is consistent with previous results that have shown that consumers who are motivated by ET express positive attitudes toward internet advertising, and this in turn stimulates their intention to share it (Celebi, 2015; Zhou & Bao, 2002). Overall, ET helps explain online advertisement-sharing behaviors (Kujur & Singh, 2020; Taylor et al., 2012). In SNSs, brands exploit a platform to diffuse entertaining content (e.g., sponsored advertising) that enhances interaction, increases word-of-mouth among users about it (C. S. Lee & Ma, 2012), and drives the motivation to share it (Hsieh et al., 2012; Rohm et al., 2013). The present research adopts the dominant opinion that ET has a positive relation with attitudes toward sponsored advertising on social media and sharing behaviors, as expressed in the following hypotheses.

H6: ET positively affects ASA.

H7: ET has a positive effect on consumers’ ISSA.

An entertaining experience on social media is easily memorized and positively influences attitudes and PI (Abadi et al., 2011; Cruz & Mendelsohn, 2010; Topaloğlu, 2012; Zamzuri et al., 2018). In addition, entertaining online content establishes a positive emotional connection between brands and users (Hudson et al., 2015; Sheth & Kim, 2017), and this causes users to share it with their peers and favorably affects their PI (Dobele et al., 2007). Entertainment-based motives therefore positively affect consumer purchasing behaviors (Arbabi et al., 2022; Ebrahimi et al., 2022a), as expressed in the following hypothesis:

H8: ET has a positive effect on PI.

The Impact of Social Interaction

Satisfying the need to belong to a group and engage in SIs represents the main motivation that drives individuals to use social media (Alghamdi & Plunkett, 2021; Baek et al., 2011; Hennig-Thurau et al., 2004; Muntinga et al., 2011; N. Park et al., 2009; Whiting & Williams, 2013). Through interactions, social media platforms like Snapchat offer the opportunity to build and maintain relationships with people, groups, and communities. During these interactions, individuals often share information, knowledge, and resources, both of a personal nature and in reference to specific brands. In this sense, social media cultivates trust and reciprocity among users as well as between users and brands (Phua et al., 2017a, 2017b; Shipps & Phillips, 2013). This leads to the following hypothesis:

H9: SI is a significant motive for using Snapchat.

Social capital facilitates the SIs of users through social media (Ghahtarani et al., 2020), leading to strong relationships that feature emotional kinship, trust, and social support among individuals. This bonding social capital has been found to be most prevalent in Snapchat, followed by Facebook, Instagram, and Twitter (Phua et al., 2017a). SI also represents a way to generate online content and share experiences and information (Leung, 2009), and this process cultivates engagement, emotional attachment, and cognitive involvement among a brand’s virtual community (Brodie et al., 2013). It also encourages individuals to develop positive attitudes toward social network advertising (C. Chung & Austria, 2010; de Gregorio & Sung, 2010). Thus, SI gratification through social media has a positive relationship with attitudes toward media content (Chu, 2011; C. Chung & Austria, 2010), such that the stronger the interaction with a brand on an online platform, the greater the level of participation and engagement with the content (Hamilton et al., 2016; F. Y. Wang et al., 2007). According to Plume & Slade (2018), SI has a positive effect on consumers’ intention to share tourism-related sponsored advertisements on Facebook. All the above lead to the following hypotheses:

H10: SI positively affects ASA.

H11: SI has a positive effect on consumers’ ISSA.

SI, as an antecedent of emotional and behavioral outcomes, influences consumers’ attitudes and PIs (Coyle & Thorson, 2001). In social commerce, users observe and learn from their peers’ behaviors, and such activities affect an online platform’s use and influence PIs (Al-Adwan & Kokash, 2019; L. Chen et al., 2021; Ebersole, 2000; Isa et al., 2016; D. C. Li, 2011; Li et al., 2018; Stafford & Stafford, 2001; Y. Wang & Yu, 2017). Any gratification of the social interaction motive favorably influences consumer purchasing behaviors (Arbabi et al., 2022; Ebrahimi et al., 2022a). In reality, the SI motive can be a tool for both producing value and favorably impacting buying decisions. In a social network, the stronger the SI, the stronger the purchasing intention will be (Ebrahimi et al., 2021), leading to the following hypothesis.

H12: SI has a positive effect on PI.

The Impact of Self-Expression

Sharing opinions can be a motive for using SNSs (X. Chen et al., 2015). A. L. Williams and Merten (2008) found that several students engaged in SNSs when they perceived them as a means for SE. In reality, digital platforms enable users to express their ideas, opinions, and preferences without constraint, so they facilitate SE (van Dijck, 2013). The following hypothesis is therefore proposed:

H13: SE is a significant motive for using Snapchat.

To convey their personalities to others and thereby satisfy their need for SE, consumers associate their self-image with specific brands’ online images (Cătălin & Andreea, 2014), leading to positive attitudes (Pelham et al., 2005). Furthermore, it has been shown that when online advertising content is perceived to enhance a person’s self-image, it is more likely to be regarded positively and accepted by that person (Taylor et al., 2012). In addition, if an advertisement’s content allows for self-referencing, it can satisfy the need for self-expression, and favorable feelings are formed that improve the evaluation of that advertisement (Sujan et al., 1993). Overall, if a brand’s image in Snap Ads is perceived to match with the user’s self-image, that user’s attitude toward these advertisements will be favorable, so:

H14: SE affects positively ASA.

The SE of users through SNSs acts as a means for users to disclose themselves to others. This in turn increases their inclination for online content sharing (N. Chung et al., 2012; Trammell & Keshelashvili, 2005). R. Yang (2018) showed that when advertisements on Snapchat can satisfy SE, the sharing of them increases. Flecha et al. (2019) demonstrated that gratifying millennials’ need for SE through Snapchat has a positive impact on the sharing of content (e.g., product images, promotional videos and events, filters, etc.) and participation. Plume and Slade (2018), meanwhile, suggested that the sharing of tourism-related sponsored advertisements on SNSs is a way for users to express their personalities, although their empirical findings showed SE to be the only motivation that did not influence the intention to share tourism-related sponsored advertisements on Facebook. They speculated that this could be explained by the nature of the sponsored advertising examined. When looking to satisfy their need for SE, individuals do not perceive the sharing of marketing generating content (MGC) to be appropriate, and they prefer to share their own tourism experiences. In general, consumers are motivated to share an advertising message when they perceive it as supporting their own concepts (Taylor et al., 2012).

H15: SE has a positive effect on consumers’ ISSA

Individuals satisfy their need for SE by buying brands that they perceive as being appropriate to their self-image (Cătălin & Andreea, 2014). R. Yang (2018) found that the perceived self-expressiveness of brand Filters on Snapchat favorably stimulates PIs, while Flecha et al. (2019) posited that SE through Snapchat increases ephemeral user–brand interactions and triggers purchasing actions. Within social media communities, a user’s SE has a positive relationship with the purchase of digital goods. Hence, the more engagement there is in satisfying SE, the greater the PI will be (Y. Kim et al., 2011; H. Chen & Chen, 2020; J. Lee et al., 2012).

H16: SE has a positive effect on PI.

Relation Between Attitude and Behavioral Intentions

A viewer of an online advertisement who experiences a strong positive attitude toward the content will feel a greater desire to share it with others. Thus, the attitude toward an online advertisement is a key determinant of the intention to share that ad (Huang et al., 2013; J. Lee et al., 2013; Hsieh et al., 2012; J. Lee et al., 2016).

H17: ASA has a positive effect on ISSA.

No previous studies have examined the relationship between attitudes toward advertising and PIs for Snapchat. However, H. Chen and Lee (2018) found that young customers tend to have a positive attitude toward Snapchat that in turn generates favorable feelings toward the brands advertised on this platform, including for PIs. More generally, a significant and positive relationship between attitudes toward online advertisements and PI has been confirmed in various studies (Chu et al., 2019; Geetika et al., 2018; Lin & Kim, 2016; C. A. Meghisan-Toma et al., 2021).

H18: ASA has a positive impact on PI.

By helping users to share positive experiences, a social media platform can stimulate the purchase of products (Kaplan & Haenlein, 2010). When an SNS delivers a high degree of satisfaction, the engagement and participation of users increase along with their motivation to make an online purchase (Aluri et al., 2016; Hall et al., 2017; Hossain & Kim, 2020; Veloutsou et al., 2017). According to Dones et al. (2018), when users are gratified through Snapchat, it increases their satisfaction, and this in turn encourages the quick sharing of Snap Ads and impulsive purchasing decisions. The sharing of ephemeral Snap Ads expresses the Snapchatters’ engagement and positive experiences, potentially leading to an impulsive purchase (Ho et al., 2019; Marjanovic, ; Dones et al., 2018; Flecha et al., 2019; Wakefield & Wakefield, 2016).

H19: ISSA has a positive impact on PI.

In light of the hypotheses proposed above, a conceptual framework was developed (Figure 1). This model involves four exogenous constructs (i.e., IS, ET, SI, and SE) and three endogenous ones (i.e., ASA, ISSA, and PI).

Figure 1.

The conceptual model.

Research Methodology

To address the research objectives, a quantitative study was conducted, with a survey being used to identify people’s motives for using Snapchat and assess their impact on attitudes toward Snapchat Ads, their intentions to share them, and their buying intentions.

Sample Selection and Data Collection

The investigation was conducted among three Saudi universities located in Riyadh, the kingdom’s capital, between April 15 and April 30, 2020. A convenience sample of students was therefore selected from King Saud University (KSU), Al-Imam University (IMAMU), and King Saud bin Abdulaziz University for Health Sciences (KSAU-HS).

The population for this study was Saudi millennials (Generation Y) aged 18 to 35 (Nur’afifah & Prihantoro, 2021; Palacios et al., 2021; Petruch & Walcher, 2021; Yasri et al., 2020). According to Debevec et al. (2013), the millennial generation is not homogeneous, because it includes young and old subgroups. He suggested that the first group covers those aged 18 to 24 years and the second one includes those aged 25 to 34 years.

Data were collected through a questionnaire, with the participants being assured about the confidentiality and anonymity of their data before being asked to give verbal consent. The questionnaire was written in both English and Arabic, and each respondent received links to these two versions through Survey Monkey and Google Forms. Despite respondents having the choice to answer in Arabic or English, all the respondents completed the Arabic version. Note that the Arabic versions of the measurement instruments resulted from a meticulous translation and back-translation procedure (McGorry, 2000).

A total of 265 valid responses were returned. In terms of the ages of respondents, 92.4% were between 18 and 22 years old, and only 7.6% were aged between 23 and 35. For gender, 62.6% of the respondents were female (N = 166) and 37.4% were male (N = 99). The proportions of students from the KSU, IMAMU, and KSAU-HS universities were 66%, 19.3%, and 14.7%, respectively. The questionnaire included three questions that dealt with the use of social media in terms of familiarity, frequency of use, and seniority of use. Respondents were also invited to express their degree of familiarity with five social media platforms, namely Snapchat, Twitter, YouTube, Instagram, and Facebook. All the respondents identified as Snapchat users, and familiarity with Snapchat was relatively high across all participants compared with the other social media platforms. The percentage of respondents claiming to be “very” to “extremely” familiar with Snapchat was 92%, which was higher than with Twitter (91%), YouTube (90.6%), Instagram (86.8%), and Facebook (42.3%). Only 14% of the participants used Snapchat at least once a day, while 65% used it several times a day. Regarding their seniority with using Snapchat, 73% of the respondents cited having a Snapchat account for 3 years or more.

Measures of Reliability and Validity

The measurements for all the constructs were taken from the literature, and their wordings were adapted to reflect the use of Snapchat. The 33 items related to the current research’s variables were assessed on a seven-point Likert scale that ranged from “1 = strongly disagree” to “7 = strongly agree.” The list of statements together with their corresponding constructs is shown in Table A1 (see Appendix).

To ensure accurate results, it was necessary to evaluate the dimensionality, reliability, and validity of the research scales (Furr, 2011; Tavakol & Dennick, 2011). As a first step, the dimensionality and the reliability of the measurements were verified by performing a descriptive analysis with the SPSS software. Next, the validity of the measures was assessed through a first-order confirmatory analysis with the Amos software (Roussel et al., 2002), and this supported the results of the first step.

Principal component analysis (PCA) then confirmed the unidimensionality of the seven scales. The extractions of all items were mostly greater than 0.5, with the exception being the SE-related item “I can keep a record of my life.” This had a communality equal to 0.448, so the item was removed from the analysis (Evrard et al., 2003). The scales’ reliability was measured using the Cronbach’s alpha coefficient to indicate the level of internal consistency among the items, with a Cronbach’s alpha greater than .8 being preferred in a confirmatory study (Evrard et al., 2003). Its values for the IS, ET, SI, SE, ASA, ISSA, and PI variables were 0.889, 0.860, 0.907, 0.878, 0.944, 0.931, and 0.949, respectively, so the scales used in this study could be considered reliable (DeVellis, 2012).

The PCA revealed the existence of seven factors, and the confirmatory factor analysis (CFA) validated this factorial structure. Through the CFA, the reliability was re-verified with the Jöreskog’s Rhô, where 0.7 or above is regarded as an acceptable value for a construct (Fornell & Larcker, 1981; Didellon & Valette-Florence, 1996). The standardized regression weights for all the items were greater than 0.5, and the critical ratio (CR) associated with each factorial contribution was above 1.96, as recommended by Byrne (2001). The convergent validity was assessed by calculating the rhô of convergent validity. According to Fornell and Larcker (1981), this index must be greater than or equal to 0.5 for each construct. The conditions for reliability and validity were respected, as shown in Table A1 (see Appendix), so the dimensions obtained for all the constructs were deemed to be reliable and valid.

Hypotheses Verification Methodology

Hypotheses H1, H5, H9, and H13 state that IS, ET, SI, and SE are relevant motives for using Snapchat. First, a Varimax rotation was performed to evaluate the internal structure of Snapchat’s gratification by integrating items from the scales purification. This procedure adjusts the coordinates of data produced by a PCA (Allen, 2017). Second, CFA was performed using the Amos program to analyze the reliability, convergent validity, and discriminant validity of the model of Snapchat’s gratification.

Finally, structural equation modeling was used to test the empirical model with the partial least squares technique (Hair et al., 2014) in the Smart PLS 3.3 software. We then tested the remaining hypotheses by linking the motives for using Snapchat to the endogenous variables (i.e., ASA, ISSA, and PI) (see Figure 1). The partial least squares structural equation modeling (PLS-SEM) approach suited this study’s objectives because it is a causal modeling method that aims to maximize the explained variance of the dependent latent constructs. Furthermore, “it provides more flexibility to explore and experiment, in contrary to the Covariance-Based Structural Equation Modeling’ objective that is to reproduce the theoretical covariance matrix, without focusing on explaining variance” (Hair et al., 2017; Hair et al., 2011). Additionally, the PLS-SEM approach supports data testing in medium samples (Chin, 2010) and evaluates the results of the measurement model in addition to those of the structural model. This method was therefore appropriate for testing this research’s framework.

Results

Validation of Snapchat’s Gratification Structure

After purification and validation of the scales, 19 statements that reflected reasons for using Snapchat were kept. These items were subjected to PCA using Varimax rotation, with the results indicating that two statements deviated from the theoretical structure. Almost all items included in one factor had loadings greater than 0.60 in that factor and below 0.40 in any other factor, with the exception being the item “I can get opinions and advice from my friends.” For this item, a cross-loading (0.618–0.525 = 0.093) with a difference of less than 0.15 from the item’s highest factor loading was observed, so it was removed from the analysis (Worthington & Whittaker, 2006). The second item of “I can express my ideas and advice to friends” was expected to load on the SI factor, but it had a higher loading on the SE one. This could be because respondents consider that SE gratification happens not just by expressing their own ideas or opinions but also when they are perceived as advice by others on the social platform. In other words, by expressing their thoughts through Snapchat, individuals hope to convey a positive self-image. This behavior secures greater gratification when these thoughts are appreciated and considered as valuable advice.

After the structural purification, the KMO measure of sampling adequacy (KMO = 0.908) and Bartlett’s Test of Sphericity (χ² = 3193.536, df = 153, p = .000) indicated that the sample had an appropriate size for the factor analysis. The analysis yielded four factors that contribute to explaining motives for using Snapchat, with these explaining 72.64% of the variance. More specifically, the “IS” factor (α = .089) explained 43.905% of the variance, while the “SE” factor (α = .901) accounted for 14.464% of the overall variance. The “ET” factor (α = .860) represented 7.840% of the variance, while the “SI” factor (α = .912) only explained 6.435% of the overall variance. We can therefore deduce that the motives for using Snapchat follow this hierarchy: IS > SE > ET > SI.

CFA was used to validate the model that integrated the four identified gratifications. The structural model is shown in Figure 2. The results (Chi square/degree of freedom = 1.771 < 2, p = .000) yielded the standardized regression weights that linked items to gratifications. The RMSEA was around 0.05 (0.054), thus reflecting a good fit (MacCallum et al., 2001; Steiger, 1990). The GFI (0.913) was above 0.90, which again corresponds to an acceptable fit (Jöreskog & Sörborn, 1989). The CFI (0.969) was above the threshold of 0.9 (Bentler, 1990), while the NFI (0.932) was greater than 0.8 (James et al., 1982). In addition, the standardized root mean residual value (0.048) was less than 0.08 (Hu & Bentler, 1999). All these results confirm that the factor structure for users’ motivations fits with the empirical data.

Figure 2.

Confirmed factor structure for Snapchat’s gratification.

The reliability and the convergent validity of the two modified factors were satisfactory. Indeed, the Jöreskog’s Rhô was 0.917 and 0.896 for SI and SE, respectively, whereas the Rhô of convergent validity was 0.786 and 0.635 for the same motives. Table A2 (see Appendix) shows how the discriminant validity was confirmed by verifying that the square root of every average variance extracted (AVE) for each latent construct (in the diagonal) was greater than any correlation coefficient (i.e., off-diagonal) for any couple of latent constructs (Fornell & Larcker, 1981). IS (F1), SE (F2), ET (F3), and SI (F4) were found to represent significant motives for using Snapchat, so H1, H5, H9, and H13 were accepted.

Effect of Snapchat’s Gratification on Persuasion

Assessment of the Measurement Model

The level of adequacy between the latent variables and their corresponding measurement items was assessed through individual item reliability analysis, the convergent validity, and the discriminant validity. The results in Table A3 (see Appendix) demonstrate that all items except the “I use it to entertain” item have loadings greater than 0.70. In reality, however, when a scale is adapted from another setting, a loading of 0.5 can be regarded as acceptable (Chin, 1998), so all the items demonstrated a satisfactory level of individual reliability (Fornell & Larcker, 1981).

The Cronbach’s alpha (CA), the composite reliability (CR), and the reliability coefficient (Rho-A) were then used to assess the measures’ reliability. Table A3 shows that the CA and CR values were higher than the threshold value of 0.7 (Evrard et al., 2003; Nunnally, 1978) and that the Rho-A statistics were greater than 0.8 (Henseler et al., 2009), so all the constructs demonstrated good reliability.

The average variance extracted (AVE) was then used to assess the convergent validity of the latent variables. The AVE values (see Table A3 in the Appendix) are above 0.5 for all latent variables, thus confirming convergent validity (Fornell & Larcker, 1981).

Three tests were conducted to assess the discriminant validity: First, an analysis of the cross-loading (Table A4, Appendix) indicated that all the measurement items have a higher correlation with the latent variable being measured than with any other latent variable in the model (Chin, 1998). Second, AVE analysis (Table A5, Appendix) demonstrated that each latent variable shares a greater variance with its own measure than it does with the measures of other latent variables (Fornell & Larcker, 1981). Finally, the Heterotrait–Monotrait criterion values, which represent the similarity between latent variables, are below 0.90 (Table A6, Appendix), thus confirming discriminant validity (Hair et al., 2022; Henseler et al., 2015).

Assessment of the Structural Model

With the robustness of the measurement model having been confirmed, the next step was to evaluate the structural model. This involved examining the model’s predictive abilities and the relationships among the latent variables. The path coefficient (β value) and t-statistic value, the coefficient of determination (R²), the effect size (ƒ²), and the predictive relevance of the model (Q²) were employed as standards for evaluating the structural model (Hussain et al., 2018).

The model was validated by using a resampling method to test the significance of the t-value of the path coefficients through the nonparametric significance test known as bootstrapping (Chin, 1998). The results of this are presented in Table 1, and they reflect the significant structural relationships among the study’s constructs. Overall, of the 15 proposed hypotheses, five were confirmed at various significance levels.

Table 1.

Path Coefficients and t-Statistics.

Hypothesis	Relationship	Standardized Beta (β)	t-Statistic (T)	p-value (p)	Inference
H2	IS → ASA	.327	4.283	.000	Supported (S)
H3	IS→ ISSA	−.007	0.108	.914	Non supported (N.S)
H4	IS→ PI	.090	1.484	.138	N.S
H6	ET→ ASA	.229	2.204	.028	S
H7	ET→ ISSA	.095	1.154	.249	N.S
H8	ET→ PI	.017	0.253	.801	N.S
H10	SI→ ASA	−.268	2.763	.006	S
H11	SI→ ISSA	−.004	0.050	.960	N.S
H12	SI → PI	.036	0.594	.553	N.S
H14	SE → ASA	.035	0.336	.737	N.S
H15	SE → ISSA	−.042	0.455	.649	N.S
H16	SE → PI	−.116	1.502	.133	N.S
H17	ASA → ISSA	.772	16.567	.000	S
H18	ASA → PI	.870	12.325	.000	S
H19	ISSA → PI	−.043	1.484	.593	N.S

Hypotheses 2, 3, and 4 posit that IS has a positive effect on ASA, ISSA, and PI, respectively. The results showed IS to have a significant direct effect on ASA (β = .327; T = 4.283; p = .000) but not on ISSA (β = −.007; T = 0.108; p = .914) or PI (β = .090; T = 1.484; p = .914). Thus, H2 was accepted, while H3 and H4 were rejected.

Hypotheses 6, 7, and 8 suggest that ET influences ASA, ISSA, and PI, respectively. The results revealed that ET significantly and positively affects ASA (β = .229; T = 2.204; p = .028) but not ISSA (β = .095; T = 1.154; p = .249) or PI (β = .017; T = 0.253; p = .801). Consequently, H6 was accepted, but H7 and H8 were rejected.

The findings also revealed that SI has a significant negative influence on ASA (β = −.268; T = 2.763; p = .006) but not on ISSA (β = −.004; T = 0.050; p = .960) or PI (β = .036; T = 0.594; p = .553). Thus, H11 and H12 were rejected, while H10 was also rejected because SI as a significant motive for using Snapchat was expected to have a positive impact on ASA.

H14, H15, and H16 link SE to ASA (β = .035; T = 0.336; p = .737), ISSA (β = −.042; T = 0.455; p = .649), and PI (β = −.116; T = 1.502; p = .133), respectively, but these were all rejected due to a lack of significance.

H17 and H18 assert that ASA has positive relationships with ISSA and PI, respectively, and the results did indeed demonstrate that ASA positively and significantly influences ISSA (β = .772; T = 16.567; p = .000) and PI (β = .870; T = 12.325; p = .000), so H17 and H18 were accepted.

Finally, no significant relationship was found between ISSA and PI (β = −.043; T = 1.484; p = .593), so H19 was rejected.

To evaluate the predictive power of the structural model, the R² value, which is also called the coefficient of determination, was employed. This value explains the variance in the endogenous variable(s) in the model through its exogenous variable(s). R² values of .75, .50 and .26 are considered substantial, moderate, and weak, respectively, when determining the predictive capacity of a structural model (Hair et al., 2013). Results indicated R² values of 15.8% (p = .000) for ASA, 55.4% (p = .000) for ISSA, and 66.4% (p = .000) for PI. According to Hair et al. (2013), the proposed research model demonstrated the weakest predictive power for attitudes to SnapAds and the strongest predictive power for behavioral intentions. Nevertheless, it has been suggested that a model where the R² values are equal to, or greater than, 10% has adequate predictive power (Falk & Miller, 1992).

The effect size F² is the change in the R² when an exogenous variable is removed from the model (Chin, 1998). Cohen (1992) suggested that the effect size is weak when the value is greater than 0.002, moderate if the value is greater than 0.15, and strong if the value is greater than 0.35. Table 2 shows that removing the relationship between ASA, ISSA, and PI has a substantial effect on the R² and improves the model greatly. Eliminating the relation between IS and ASA also has an impact on the R², albeit a weak one because the F² is 0.079 (<0.15).

Table 2.

Effect Size F².

Path	F ²	p-value (p)
IS →ASA	0.079	.025
IS→ ISSA	0.000	.969
IS→ PI	0.017	.411
ET→ ASA	0.029	.165
ET→ ISSA	0.007	.629
ET→ PI	0.000	.933
SI→ ASA	0.032	.235
SI→ ISSA	0.000	.968
SI → PI	0.000	.974
SE → ASA	0.001	.946
SE → ISA	0.002	.872
SE → PI	0.010	.551
ASA → ISSA	0.982	.000
ASA → PI	0.698	.000
ISSA → PI	0.004	.728

The predictive relevance of the proposed research model was calculated using the non-parametric Stone–Geisser test (Q²). The Q² value derives from a blindfolding procedure with an omission distance of 7, and it was calculated using the cross-validated redundancy approach (Hair et al., 2012) in order to establish the predictive relevance of the endogenous construct. If the Q² values are above zero, this indicates that the model is well reconstructed with good predictive relevance. Table 3 indicates that the research model has predictive relevance since all the Q² values are above zero.

Table 3.

Construct Cross-Validated Redundancy (Q²).

Construct	SSO	SSE	Q² (=1-SSE/SSO)
ASA	1325.000	1164.082	0.121
ET	1060.000	1060.000
IS	1590.000	1590.000
ISSA	795.000	405.670	0.490
PI	1325.000	603.121	0.545
SE	1060.000	1060.000
SI	795.000	795.000

Finally, the model fit was assessed by calculating the standardized root mean square (SRMS) residual. This index reflects the average degree of the differences between the observed correlation and the hypothesized covariance matrices. An SRMS value of 0.08 or lower indicates a good fit (Chen, 2007; Hu & Bentler, 1999), and the result in Table 4 indicates that the model has a good fit (SRMR = 0.051).

Table 4.

Model Fit.

	Estimated model
SRMR	0.051
d_ULS	1.192
d_G	0.697
Chi-Square	1084.153
NFI	0.847

Discussion and Conclusion

Key Findings

No previous study has proposed an empirical model for examining how the motives for using Snapchat relate to ASA, ISSA, and PI simultaneously. Thus, by adopting the UGT to identify the main motives for using Snapchat, this study has helped to gain a better understanding of how to promote products and increase sales through Snapchat, specifically by providing insights into how the motives for using Snapchat can predict ASA, ISSA, and PI.

The findings reveal that Snapchat users seek various forms of gratification to fulfill their needs and wants, and this is consistent with previous research (H. Chen & Lee, 2018; Dones et al., 2018; Phua et al., 2017a, 2017b; Tiany, 2017). We found that the main motive for using Snapchat is IS, followed by SE, ET, and SI.

With ET being placed in the third position, the respondents clearly did not consider it a priority when using Snapchat. This is somewhat surprising given that Phua et al. (2017a) found Snapchat to be more useful for ET than Facebook, Twitter, and Instagram. Nevertheless, our finding concurs with that of Tiany (2017), who found that “social IS” was ranked foremost by Snapchatters. For Saudi millennials, obtaining useful information quickly, easily, and at low cost is the leading form of gratification for this Snapchat community.

SE emerged as the second most important motive for using Snapchat, confirming that younger people frequently employ a higher level of self-disclosure on Snapchat (Bayer et al., 2016; Larsen & Kofoed, 2015). Saudi millennials, especially students, see Snapchat as a digital platform where they can convey their ideas, opinions, and preferences without constraints (van Dijck, 2013; A. L. Williams & Merten, 2008). According to the current research, expressing one’s personal information (e.g., interests, feelings, etc.) to others via Snapchat leads to SE-related gratification. This also occurs when users perceive that their friends are benefiting from their self-expressiveness (e.g., they find the advice useful). Consequently, Snapchat contributes to building a virtual self-identity through SE-related gratification, which is in turn crucial for gaining peer acceptance and exchanging social support (Shao, 2009).

The SI motive reflects a need to maintain contact with friends, interact with them, show concern, and give support. It remains a form of gratification that is sought out when using Snapchat, but the number of responses that cite it as a motive for using Snapchat is low compared to the three other motives. In reality, relationships on Snapchat are more restrictive than they are on Twitter, Instagram, and Facebook, because “snaps” are directed at a select group of individuals who maintain close, private relationships with the user (Phua et al., 2017b). Moreover, SIs on Snapchat are ephemeral in nature, because they are based on transient content (Bayer et al., 2016), such that users interact “for fun” (e.g., by sharing funny pictures and selfies) rather than for privacy-related or sexually motivated reasons (J. E. Katz & Crocker, 2015; Roesner et al., 2014; Utz et al., 2015).

In conclusion, the Saudi millennials conveyed that in order of importance, IS, SE, ET, and maintaining close SIs were the main gratifications they sought from Snapchat use.

In line with earlier studies (e.g., Celebi, 2015; J. Lee et al., 2016; Oh & Syn, 2015; Plume & Slade, 2018; Turcotte et al., 2015; Zhou & Bao, 2002), IS and ET have significant positive influences on ASA. In contrast, Dehghani et al. (2016) found that ET negatively influences attitudes toward advertisements displayed on YouTube. They explained this by saying that when users are motivated to use an SNS for an ET purpose, but they are interrupted by an irritating and irrelevant advertisement, they are more likely to reject that advertisement. Thus, the negative relation between ET and attitudes toward advertisements is due to the lack of congruency between the expected gratification and the advertising content. Tiany (2017) also found that ET negatively influences ASA. Nevertheless, the findings of these two studies cannot entirely dispute the dominant opinion that ET is positively linked with attitudes toward advertising for a couple of reasons. First, the ET being sought on YouTube differs in nature from that being sought on social media platforms like Snapchat. On YouTube, people look for a good video-viewing experience, and advertising interruptions can degrade this. Being aware of the irritation that advertising can cause, many social media platforms have introduced a “skippable” form of advertisements. Second, Tiany’s (2017) research found that the context combined with an advertisement’s content can unfavorably shape attitudes. In the current study, it was clear that the Saudi millennials have fun watching Snap Ads, and they are satisfied with the information provided by these ads.

In contrast to previous investigations (e.g., Celebi, 2015; J. Lee et al., 2016; Oh & Syn, 2015; Plume & Slade, 2018; Turcotte et al., 2015; Zhou & Bao, 2002), IS and ET were found to have no significant direct effect on ISSA or PI. However, when examining the indirect effects between these two gratifications and the dependent variables, the relationships were found to be statistically significant (Table A7, see Appendix), thus highlighting the mediating role of ASA. Furthermore, this is full mediation, such that the effects of IS and ET are fully transmitted by ASA.

This study found that SE does not affect ASA, which contradicts previous studies that have found that advertising content (e.g., brand image, a portrayed situation, etc.) is evaluated favorably when it stimulates self-referencing and thereby conveys a positive self-image (Y. Kim et al., 2011; Sujan et al., 1993; Taylor et al., 2012). Sujan et al. (1993) posited that when an advertisement’s content matches the recipient’s self-structure, it gratifies the SE motive and leads to strong positive feelings about the ad, which results in a favorable attitude. This process was not observed in our study, however, which suggests that Saudi millennials do not perceive Snap Ads as a means for self-expression.

In accordance with Plume and Slade (2018), no significant relationship was found between SE and the intention to share advertisements. When it comes to SE, Saudi Millennials do not like sharing MGC, preferring instead to share their own experiences with friends, brands, firms, or events on Snapchat.

We found that the SE motive does not influence PI, unlike in H. Chen and Chen’s (2020) study, where the authors found that in social network games (SNGs), the more that users are engaged in expressing their self-image, the greater their PI for digital goods will be. This is likely because the main way to express one’s self-image on SNGs is to create a virtual self-image known as an “avatar” (S.-B. Park & Chung, 2011). Users therefore invest in virtual goods to decorate their avatars, such as buying clothes, weapons, accessories, and so on (Schau & Gilly, 2003). In contrast, Snapchatters can satisfy their need for SE without intending to buy the promoted products.

Based on the above discussion, a plausible scenario could explain why the SE motive does not influence ASA, ISSA, or PI. Saudi millennials do not consider Snap Ads as a means for SE, so they do not share them or intend to buy the related product. To express themselves on Snapchat, Saudi Snapchatters prefer to share their own real-life experiences with brands through the use of other Snapchat features rather than Snap Ads: For example, they may use Snap stories to publish personal videos and images, sponsored geo-Filters to add information to stories by adding a specific geographical location (e.g., a restaurant, brand event, etc.), sponsored Lenses that allow linking a brand’s animation to personal images, and Discover, which offers compilations of personal “Snaps” at events and locations. Overall, SNSs users have many alternative means for expressing themselves: They can engage in online communications and conversations (Belk, 2013; Muntinga et al., 2011), voice opinions about a brand (Kokkoris & Kühnen, 2013), create personal content or contribute to a brand-related conversation online (Livingstone, 2008; Muntinga et al., 2011; Schau & Gilly, 2003), or publish selfies (Eagar & Dann, 2016; Kedzior et al., 2016; Pounders et al., 2016). In summary, the ephemeral nature of Snapchat’s content encourages a high degree of freedom and creativity. It offers a platform for users to experiment with themselves by trying different styles of presentation (J. E. Katz & Crocker, 2015; Kwon & Kwon, 2014). Thus, Snapchat has a significant capacity for gratifying users’ need for self-expression, but this does not contribute directly to the effectiveness of Snap Ads.

The present research confirms the divergence that has been observed in the prior literature with regards to the relationship between SI and attitudes toward sponsored content on social media. C. Chung and Austria (2010) found that gratifying the need for interaction on social media has a positive impact on attitudes toward social media marketing messages, while J. Lee et al. (2016) showed that socialization-based motivation was not a significant positive predictor of attitudes toward native advertising.

Our study found that the SI motive actually negatively influences ASA. In relation to this, Ko et al. (2005) posited that individuals with an SI motivation are more strongly attached to human–human interactions (i.e., communicating with friends and advertisers) than they are to human–message interactions (i.e., browsing and sharing messages). They therefore demonstrated that SI has a positive effect on human–human interaction but a negative impact on human–message interactions. This suggests that people using Snapchat for SI purposes are more focused on exchanging ideas and communicating with friends, so they are more likely to develop negative attitudes toward Snap Ads because they interrupt the SI process. Contrary to H11 and H12, SI was found to not affect either the intention to share Snap Ads or purchasing intention. These findings are consistent with those of J. Lee et al. (2016), who showed that socialization-based motivations do not affect the intention to share native advertising. They also concur with those of Harun and Husin (2019), which affirmed that SI does not influence millennials’ online purchasing behaviors. In conclusion, when Snapchat users are seeking to satisfy their need for information, the appearance of Snap Ads in their feeds leads to irritation and ultimately a negative attitude toward that ad. This in turn makes them disinterested in sharing the advertisement or buying the related product.

Nevertheless, our results indicate that ASA has a positive influence on the intention to share ads and purchasing intention, which concurs with the findings of a number of authors (e.g., Flecha et al., 2019; Geetika et al., 2018; Huang et al., 2013).

Moreover, it was expected that the more that individuals favorably evaluate advertisements, the more willing they will be to share them with their online peers, as well as intend to purchase the related product (Kenneth & Kelly, 2020). Nevertheless, our results imply that sharing Snap Ads does not influence purchasing intention. Considering that brand identification is defined as “the extent to which the consumer sees his or her own self-image as overlapping with the advertised brand’s image” (Tuskej & Podnar, 2018), the persuasion occurs through a peripheral route for people with a low level of brand identification. Under such conditions, the advertisement is evaluated based on its peripheral characteristics, such as the background music or the celebrity endorsing the product, rather than the message content in itself (Kenneth & Kelly, 2020). This assumption is plausible because the results demonstrated that the SE motive does not affect the persuasiveness of Snap Ads (H14, H15, and H16). Additionally, the attitudes formed through the peripheral route are less strong and less consequential for persuasion than those created through the central route (Petty & Hinsenkam, 2017). Consequently, a favorable ASA directly and positively influences the intention to share ads and purchasing intention. However, this impact is not transferred to PI via ISSA, because no significant indirect effect was found to exist between ASA and PI (T = 0.526; p = .599, see Table A7, Appendix), so ISSA clearly does not mediate the relationship between these two variables.

In summary, having been tested with empirical data, the proposed theoretical framework of our study offers both theoretical and practical implications, and it also opens up further opportunities for researching the effectiveness of Snap Ads as a commercial tool.

Implications, Limitations, and Future Directions

This study makes a theoretical contribution to the literature by adopting the UGT in order to propose a model for examining the motives that drive people to use Snapchat and explaining how various forms of gratification impact the ASA, ISSA, and PI of users. This model can now be applied by researchers and practitioners to better understand how sponsored advertisements can succeed in the social media environment. Furthermore, this study validates the UGT for the social media context in addition to identifying four motives for using Snapchat. The results here demonstrate that not all these motives influence the effectiveness of Snap Ads, so to effectively promote their products, marketers should focus on Snap Ads that satisfy the IS and ET needs of users. What is more, users searching for information through Snapchat can be irritated by Snap Ads and therefore develop a negative attitude toward them, so identifying the motives of the target customers can help brands to customize their Snap Ads in order to avoid such irritation.

Organizations nurture their relationships with their audiences through social media platforms in general and particularly Snapchat. They need to develop a dialog that is perceived as being vibrant and dynamic, and this can be achieved through the continual use of new and/or creative input (Kodish, 2015). Our study has revealed that the content diffused through Snap Ads should fit with users’ motives if they are to be successful. In reality, young adults recognize that Snapchat facilitates congruent communication at the interpersonal level because it allows for more privacy than other social media platforms (Vaterlaus et al., 2016), and this advantage should be exploited by practitioners. Thus, to enhance the persuasiveness of Snap Ads, brands should create close, private relationships with users to facilitate congruent communication, and this could be further reinforced by customizing Snap Ads. This will be key to influencing consumer behavior (Salamzadeh et al., 2022).

Marketers should also consider adopting co-creation behaviors on Snapchat to create effective advertisements. Moghadamzadeh et al. (2020) demonstrated that co-creation with customers on social media offers an opportunity to understand these customers and develop innovative services and products together with them. This process can also be used to design innovative and appropriate Snap Ads that will contribute to improving the brand experience on Snapchat. Rather than creating advertisements on its own, a brand can ask Snapchatters to propose ideas that will help its marketers to shape their advertising. During the co-creation process, users can express their motives for using Snapchat and enjoy opportunities to enhance the brand experience and people’s willingness to share Snap Ads, as well as reinforce buying behaviors. In effect, social media users engaged in a co-creation process are participating as co-marketers. By contributing to the promotion of the brand, these users make it more credible for their peers, and this in turn increases purchasing intentions (Ebrahimi et al., 2022b).

From a practical perspective, satisfying IS- and ET-related needs seems to be crucial to the success of Snap Ads among Saudi millennials. This observation agrees with previous findings that have indicated that Snapchat addiction derives from its ability to satisfy IS and ET (Noë et al., 2019; Punyanunt-Carter et al., 2017). Since millennial Snapchatters believe that Snap Ads gratify these two needs, we expect that brand addiction can be achieved by providing useful, informative, and enjoyable Snap Ads. Brand addiction is defined as a “self-brand relationship in daily life and involving positive affectivity and gratification with a particular brand and constant urges for possessing the brand’s products/services” (Mrad et al., 2020).

Snap Ads should attract customers’ attention, both cognitively and emotionally, so marketers are urged to target more effort at ensuring the quality of the delivered information and the creative aspect of the message. They should communicate up-to-date information and focus on offering valuable propositions while applying entertaining techniques. The Snap Ads should then be perceived as a useful source of information and pleasure. Indeed, Snapchat users need to feel that novelty and creativity are attached to the cognitive message being delivered. Snap Ads can therefore be useful for creating an experience that provides both utility and joy, which in turn will nurture positive attitudes and behaviors.

While this study has brought some clarity about how the main motives for using Snapchat can shape customers’ attitudes and behavioral intentions, some limitations have affected this study, and these could be addressed in future research. First, our study focused on four important motives for using social media that were extracted from the literature, but an exploratory investigation could have determined motives that are specific to the Snapchat context. By the same token, the validated model could be applied to other contexts in order to investigate the effect of cultural differences among millennials. In addition, this study did not consider the impact of demographic factors (e.g., gender, ethnicity, and socioeconomic status), so it would be worthwhile to test whether such factors have a moderating influence.

Finally, this study considered only a limited number of Saudi millennial students, so caution is needed in generalizing the results to all the millennials in the Saudi population. A future study could improve the external validity by recruiting a larger and more representative sample.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors extend their appreciation to the Deanship of Post Graduate and Scientific Research at Dar Al Uloom University for funding this work.

Ethics Statement

All participants were fully informed why the research is being conducted, that the anonymity is assured, and that the collected data will be used exclusively for the research purpose. All participants gave verbal consents to fill out the questionnaire.

ORCID iD

Mohamed Nabil Mzoughi

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Do Millennials’ Motives for Using Snapchat Influence the Effectiveness of Snap Ads?

Abstract

Keywords

Introduction

Literature Review, Theoretical Framework, and Hypotheses Development

Snap Ads

Motives for Using Snapchat

Hypotheses Development

The Impact of Information Seeking

The Impact of Entertainment

The Impact of Social Interaction

The Impact of Self-Expression

Relation Between Attitude and Behavioral Intentions

Research Methodology

Sample Selection and Data Collection

Measures of Reliability and Validity

Hypotheses Verification Methodology

Results

Validation of Snapchat’s Gratification Structure

Effect of Snapchat’s Gratification on Persuasion

Assessment of the Measurement Model

Assessment of the Structural Model

Discussion and Conclusion

Key Findings

Implications, Limitations, and Future Directions

Footnotes

Appendix

Declaration of Conflicting Interests

Funding

Ethics Statement

ORCID iD

References