Master Thesis:
There’s an app for that: How can
interactive mobile marketing raise
engagement in the NGO sector
Jessica Bailey 10863958
Graduate School of Communication Political Communication Supervisor: Dr Sanne Kruikemeier
Abstract
Mobile marketing has been used in the commercial sector for several years now, however the use of mobile marketing by NGOs has only recently started, with some large international NGOs making their own mobile applications and smaller NGOs working in collaboration with existing mobile applications. However, most of the previous research in this area has been focused on the adoption of mobile media and the content it hosts. However, what is missing is research on whether or not campaigns shown on mobiles are more effective than when shown on traditional media. It is for this reason that this thesis will look at whether NGOs can increase engagement (awareness, empathy, engagement and donation intention) using existing mobile applications to showcase their campaigns. This question will be answered by an experiment which has three conditions. One group will be exposed to the campaign displayed on a traditional media channel and two groups will experience the campaign via a mobile application. However, because it is important to also take the interactivity one has with the mobile application into account, one of these two groups will experience the campaign passively and the other group will be able to physically interact with the campaign on the mobile application. The results showed that although engagement was not directly affected by media channel, it was mediated by perceived interactivity, except in the case of donation intention. These results are important as they show that NGOs can use interactive techniques to boost engagement with younger audiences and that this will work better than just passively showing their campaign via an app.
Introduction
Advertisers and other organisations, such as political parties and NGOs are increasingly using new media and techniques to enhance engagement amongst their audiences. They hope that this will, in turn, lead to more sales, votes and customer loyalty (Kaplan, 2012). Following this increase in adoption of new media by businesses, politicians and society is academic research focusing on mobile marketing and interactive engagement. These studies found that the mobile phone is an increasingly powerful tool to reach and engage audiences, especially younger generations (Gao, Rau & Salvendy, 2006; Kaplan, 2012; Mirbagheri & Hejazinia, 2010; Shankar & Balasubramanian, 2009; Third Sector Insight, 2014; Yu, 2013). This engagement can be found in mobile applications (apps) which are downloaded onto smart phones and considered the future platform for marketing (Kaplan, 2012; Mirbagheri & Hejazinia, 2010). Research by Pew suggests that by 2020, the mobile device will be the primary internet connection tool for most people around the world (Kaplan, 2012). Currently, global mobile penetration rate stands at 70%, with 5 billion phones for 6.9 billion people, yet in some countries, such as Germany and Italy, mobile penetration is already over 100% (Kaplan, 2012).
The above shows that the mobile phone is ever-gaining importance in all aspects of life, including advertising. Therefore, this study will look specifically at how mobile apps, and the level of interactivity accompanying them, produces the different levels of
engagement among younger generations in relation to an NGO campaign, compared to traditional media channels. This is an important area to research because, compared to the for-profit sector, NGOs typically lag behind in their adoption of new media due to the perceived technical complexity and financial resources needed to build effective mobile campaigns (Fussell Sisco & McCorkindale, 2013; Jensen, 2012; Obar, Zube & Lampe, 2012; Quinton & Fennemore, 2013). Currently, mobile marketing is limited to large international
NGOs such as Greenpeace and UNICEF, who have both launched their own apps (Jensen, 2012). However, these are expensive to maintain and would only be downloaded by those who are already interested and engaged with the cause. Nevertheless, a small number of NGOs have acknowledged the benefits of mobile marketing and have subsequently teamed up with corporate organisations (who have the technical expertise and financial capabilities to make mobile applications) to make joint mobile apps. One example of this is a German children’s charity, ‘Ein Herz für Kinder’, who with the help of the confectionery company Haribo created a gaming app which also allowed the user to donate between three and five Euros to the charity whilst playing a Haribo based game. Over the three month period that the app was in circulation, it was downloaded 168,000 times and over €1 million was donated to the charity (Jensen, 2012). Another, more recent example comes from Medicins sans
Frontieres. They integrated a campaign which allows users of ‘Whatsapp’ to download ‘Refugee emojis’ into the existing text-based messaging app. Every time this keyboard extension is downloaded, 70% of the cost (€2.11) goes to Medicins sans Frontieres (Refugee Emojis, 2015). These examples show that charities can adopt mobile marketing in a cheap way by launching their campaigns on existing mobile platforms.
Taking the above examples into account, this academic study aims to distinguish if and why campaigning via mobile applications leads to increased engagement among young audiences. This is important for two main reasons, firstly NGOs, in comparison to politicians and the for-profit sector, have less money to spend on marketing as the majority of their funds come from donations and it is expected that this money is spent on the work they do, not on their advertising (Hibbert & Horne, 1996). This in turn means that the return on investment is crucially important when choosing a campaign channel, and often, online campaigns are viewed as the cheaper more efficient option (Obar et al., 2012; Phethean, Tiropanis & Harris, 2013). However, there is a gap in the academic literature associated with
the effectiveness of online/mobile campaigns as a large amount of the research connected to mobile marketing focuses on its adoption and content rather than the effect it has on the audience. This leads to the second reason as to why this study on the effectiveness of mobile applications is necessary. Many studies have shown that the above examples of mobile marketing by NGOs are rare and even though the majority of NGOs have Facebook pages, often they are not used in an interactive way. Instead research shows that NGOs continue to focus on one-way communication and information dissemination rather than engaging with their audiences or encouraging eWOM (Fussell Sisco & McCorkindale, 2013; Quinton & Fennemore, 2013).
Accordingly, due to this study’s focus on engagement, effective engagement will be operationalised by three factors based on research by Phethean, Tiropanis and Harris (2012; 2013). Firstly, it is expected that the campaign will be successful if it raises awareness of the cause. Secondly, the engagement of a campaign can be measured by the interaction the audience has with the campaign. Phethean et al believe that if audiences interact with the campaign, they will process the message on a deeper level, which in turn may lead to the last level of effective engagement, which is defined as the action people take such as making a donation to the charity. This level is expected to be the smallest of all three as it requires the most effort on behalf of the viewer (Obar et al., 2012; Phethean, Tiropanis & Harris, 2012; Phethean et al., 2013).
Taking into account these three levels of effective engagement, and the information above, this study proposes the following research aim: To what extent does the use of an integrated campaign from an NGO into a pre-existing mobile application lead to more engagement among users (awareness, engagement and donation intention)?
One further reason as to why it is important to study this topic is to see what role interactivity has on the engagement of the audience. Mobile phones and apps are interpreted
as being highly interactive as they allow the audience to play an active role in viewing the campaign (Pavlou & Stewart, 2000). Apps also allow faster and easier interaction and
communication with the mobile device, the sender and other users (Kiousis, 2002), than both traditional media and traditional online channels such as websites. Because of this, it is necessary to see whether this interactive element of the app increases the persuasion and goal of the campaign.
To test these research aims, this study will focus on younger citizens aged 18-34, as this age group are the highest users of interactive media and are the most likely to use their mobile phones for social networking (Moore, 2012). The pre-existing app that will be used is Snapchat because it is the third most popular social app among young people, trailing only Facebook and Instagram (Virgillito, 2015). Snapchat also focuses on imagery and allows photos to be sent to a wide number of people with a limited amount of text. This style works well for NGO campaigns, as their campaigns are frequently image based in order to raise empathy and grab attention (Basil, Ridgeway & Basil, 2008; Phethean et al., 2013). Moreover, Snapchat has already been used by several corporations such as Audi and
McDonalds as a marketing tool and also by the World Wildlife Fund (Hsu, 2015). The NGO campaign that will be used is the #Traffikfreechocolate campaign from Stop the Traffik (Stop the Traffik, 2015). This campaign aims to raise awareness and stop children from being trafficked and taken to work on cocoa plantations in the Ivory Coast. The campaign will be shown both via the Snapchat application and in a magazine, because magazines are still a common traditional media format which displays still images.
Advertising on social media and apps
Advertising on mobile phones is becoming increasingly popular and originally started with SMS marketing (Mirbagheri & Hejazinia, 2010). Yet after the introduction of the IPhone in 2007 a mobile marketing revolution began and since then more than 250,000 apps,
which have become part of the standard communications repertoire for corporate
organisations, have been created (Kaplan, 2012). Mobile marketing is crucial to commercial communication strategy plans as mobile phones have become essential in the everyday life of the general public meaning messages and marketing penetrates into the lives of the users in a way that computer based, television based and newspaper based marketing does not.
Marketing on mobile phones also differs to traditional marketing as it is interpreted as more personalised because mobile phones usually belong to just one person and are not shared. They are also more often used for entertainment, and to communicate with friends (Gao et al., 2006; Kaplan, 2012) which allows advertising and viral campaigns to blend in and be
accepted.
Mobile marketing is an especially popular marketing strategy used to reach younger generations (between 12 and 34) who are somewhat fragmented and absent when it comes to traditional media (Kaplan, 2012; Mirbagheri & Hejazinia, 2010). These young people are constantly surrounded by their mobile phones and use them primarily for gaming and instant messaging (Yu, 2013). They are digital natives who have grown up with social media and mobile applications and are therefore considered the best target group for applications as they take instant communications and wireless technology for granted whilst thriving on sharing and creating their own content (Mirbagheri & Hejazinia, 2010).
Other evidence that mobile marketing has become more popular is the increase in budgets allocated to mobile marketing. This spending has increased considerably in the last decade (Shankar & Balasubramanian, 2009) and because of this, it is important to understand what successful mobile marketing looks like. Previous research has shown that the mobile phone has several unique characteristics which make it a successful communication channel with response rates from mobile advertising reaching 31% compared to between 0.15% and 0.6% for traditional media (Mirbagheri & Hejazinia, 2010). For example, mobiles allow
two-way or multi-two-way communication at fast speeds meaning that all users can create content and distribute it (Shankar & Balasubramanian, 2009). Additionally, a lot of mobile advertising is considered ‘interactive’ (Gao et al., 2006; Shankar & Balasubramanian, 2009; Yu, 2013), with one study finding that 69% of cases of mobile marketing could be classed as interactive (Mirbagheri & Hejazinia, 2010) and another finding that ‘playfulness’ was a key element that allowed for interactivity which mobile phones provide and other channels do not (Gao et al., 2006). Furthermore, the price companies must pay for mobile advertising is much lower than for traditional advertising (Phethean et al., 2012; Shankar & Balasubramanian, 2009). Finally, a content analysis of 45 mobile marketing cases showed that the main objective of mobile marketing was to enhance brand awareness, followed by improving brand attitude, and an increase in both of these would hopefully lead to the third intention which was increasing purchase intention (Mirbagheri & Hejazinia, 2010).
NGOs and advertising
Turning to research focusing on online campaigns by NGOs, it has been claimed that the forerunners in traditional online social media (Facebook, Twitter, blogs) are large scale international NGOs such as Save the Children, Plan UK (Cooper, 2014) and the American Red Cross (Briones, Kuch, Fisher, Liu & Jin, 2011). Yet, with the rise of viral campaigns and hashtags, and the increase in literature which shows that the most successful campaigns involve the user somehow (Kaplan, 2012), smaller NGOs are slowly beginning to understand the benefits of user-generated content and user participation (Cooper, 2014; Fussell Sisco & McCorkindale, 2013; Quinton & Fennemore, 2013). In addition, NGO campaigns have realised that posts on social media containing photos are the most successful in terms of interactions (Phethean et al., 2013), which is beneficial because most NGOs rely on images and emotional story-telling. In order for their campaigns to be successful they need to spread virally and, like any viral campaign they need to attract the audience by building an
emotional connection between the campaign and the recipient (Dobele, Lindgreen,
Beverland, Vanhamme & Van Wijk, 2007). Images used by NGOs often produce empathy and guilt and these have been shown to enhance pro-social behaviour and donation intention, as empathy reduces perceived social distance and enhances personal relevance, and guilt increased the sense of responsibility of the viewer (Basil et al., 2008). Nevertheless, following the stages of engagement as previously mentioned, the main aim of online NGO campaigns is not to increase donations but to raise both NGO brand awareness and awareness of the problems they tackle (Phethean et al., 2012; Phethean et al., 2013).
The theoretical research presented here focuses on the content and adoption of online campaigns by NGOs, yet it is still unknown how effective NGO online campaigns are in terms of engaging their audiences with reference to a specific a cause.
Interactivity
The question as to whether or not apps are more effective platforms for campaigns than traditional media in terms of creating engagement must also take into account the level of interactivity user’s experience. To understand how successful organisations are in effecting audiences by using apps as campaign tools, an important theoretical line of research that needs to be discussed is the interactivity literature. Traditionally, advertising has been seen as one-way communication whereby advertising is something an organisation ‘does’ to a
passive customer (Pavlou & Stewart, 2000). However, new media and apps in particular, are viewed as more interactive than traditional channels as they allow the consumer to play an active role in choosing what to view and when to view it (Pavlou & Stewart, 2000).
Before this thesis discusses the effects of interactivity on user engagement, it must first define what interactivity is. Though there is no set definition for the term and the concept has confused and intrigued scholars for decades (Bucy & Tao, 2007), what is agreed is that interactivity can lie in the message (i.e message centred interactivity), the structural features
of a device (i.e structural interactivity) or lastly, interactivity can be perceived by users (i.e perceived interactivity) (Bucy & Tao, 2007; Kiousis, 2004). However, because the message will remain the same across all conditions, and the structural features of the channel will be purposefully manipulated, this study will focus on the level of interactivity perceived by the user.
This perceived interactivity is characterised by how the consumer interprets the activity, not by what marketers do or how the channel itself works (Pavlou & Stewart, 2000) and therefore it focuses on the degree to which the user perceives that the interaction is two-way, controllable and responsive to their actions (Mollen & Wilson, 2010). Research on perceived interactivity has shown an improvement in the effectiveness of campaigns and an increase in user satisfaction (Pavlou & Stewart, 2000). For this reason, perceived interactivity is often viewed as the most stable predictor of attitude responses (Gao et al., 2006).
Nevertheless, one negative aspect of focusing on perceived interactivity is that it often fails to acknowledge the structural characteristics of systems which are required to evoke a sense of perceived interactivity in the first place (Bucy & Tao, 2007).
In relation to structural interactivity, which usually influences perceived interactivity, research has shown that the more engaged the viewer is with the medium, the more
responsive they are to advertising (Cader et al., 2009) as this involvement plays a key role in determining whether people process information on the central or peripheral route, according to the elaboration likelihood model (Petty, Cacioppo & Schumann, 1983). For example, the higher the number of interactive features on a political candidate’s website, the more likely respondents are to think positively of that candidate (Bucy & Tao, 2007; Sundar & Kim, 2005). This could be taken in the case of NGOs too. If the viewer is physically engaged in the task, or at least perceives the task to be physically engaging, they may wish to donate more.
This interactivity relies on viewers processing the interactive information via the peripheral route of the elaboration likelihood model (Sundar & Kim, 2005).
Taken together, what can be seen for both definitions is that interactive media should lead to higher involvement and engagement (Sundar & Kim, 2005). This means interactive media may be more persuasive (Pavlou & Stewart, 2000) as it has been positively associated with advertising effectiveness (Calder, Malthouse & Schaedel, 2009; Gao et al., 2006; Sundar & Kim, 2005). Moreover, although most studies are based on the interactivity of websites (Gao et al., 2006), interactive advertisements on mobile phones are also processed on the peripheral route (Shankar & Balasubramanian, 2009) making mobile phones and in particular mobile applications effective platforms for interactive campaigns. Furthermore, because the mobile phone is a personal device and can be used anytime and anywhere, users are often more engaged (Shankar & Balasubramanian, 2009) than they are on websites.
To differentiate between the two forms of interactivity mentioned above, both will be measured. Firstly and most obviously, the channel itself will be manipulated (independent measure), and then secondly, the level of interactivity user’s experience (mediating measure) will be measured. This will be explained further in the next paragraph.
One problem often encountered when examining how apps affect engagement (compared to exposure to a campaign in a magazine), is that the factor which is examined, (whether it is the app or not) is not clear. Because this study compares modalities, it is not conceptualized what it is in the modality that is affecting users. It could be for example, the use of images, video, or text rather than physical interaction the user has with hyperlinks, or the possibility to communicate with others. However, to make sure that it is really the interactivity that explains the rise in awareness, engagement and donation intention, an extra condition will be introduced as a control condition. Participants in this condition will watch a video of the app in use, therefore experiencing a passive interaction with the app rather than
being allowed to physically interact with it. It is hoped that this group will then show whether the effects on the dependent variables are due to the channel, or caused by the level of
interactivity the user experienced. Moreover, taking previous research on interactivity into account, it is presumed that there will be a stair-step increase in the level of interactivity felt by participants, with the magazine being viewed as the least interactive, followed by the video condition, and finally it is presumed that the app will be considered the most interactive.
Perceived interactivity as a mediator
According to Bucy and Tao (2007), some studies show that changes in dependent variables are not a direct effect of the independent variable, instead they may be caused by third variables which mediate (or moderate) the relationship. In this study the mediation could be ‘perceived interactivity’. The idea of perceived interactivity as a mediator originates from research on media effects studies of television which showed that even though
television as a medium has no interactive attributes, it may elicit a sense of perceived interactivity derived from the one-sided techniques employed in communication (Bucy & Tao, 2007). If the results of perceived interactivity as a stand-alone concept do not yield statistically significant results, it could be that perceived interactivity should be instead positioned as a mediator variable. Hoffman and Novak through Bucy and Tao wrote that “a consumer’s perception of behavioural control over [information technology] use and its impact on intentions and actions is more important than real control” (2007, p658). This means that, for example, although exposed to a video of the app in use, participants may still perceive this condition to be highly interactive.
Hypotheses
Taking into account all the information above the following hypotheses can be formulated:
Hypothesis 1: Viewing the campaign on different media channels leads to different levels of awareness, empathy, engagement and donation intention with a) the magazine leading to the lowest scores in awareness about the problem, empathy towards the cause, engagement with the campaign and donation intention, followed by b) the video of the app in use and c) the actual app, which has the highest scores in terms of awareness about the problem, empathy towards the cause, engagement with the campaign and donation intention.
Hypothesis 2: Viewing the campaign on different media channels leads to different levels of perceived interactivity, with a) the magazine leading to the lowest scores of perceived interactivity, followed by b) the video of the app in use, and c) the actual app, which has the highest scores of perceived interactivity.
Hypothesis 3: The level of perceived interactivity in response to the magazine, video and app positively affects a) awareness about the problem, b) empathy, and c) engagement and d) donation intention
Below is a visual representation of hypothesis 3, showing how perceived interactivity could lead to an indirect effect on the dependent variables.
Case Study
For the purpose of this study an already established online (and offline) campaign against child trafficking in the cocoa industry from the existing NGO ‘Stop the Traffik’ will be used. This campaign has been running since 2007 and is mostly aimed at pressuring large companies to use Fairtrade cocoa by educating the general public about child-trafficking (Stop the Traffik, 2015). Their online campaigning involves the use of a hashtag,
‘#Traffikfreechocolate’ (Stop the Traffik, 2015) which has been used widely on their social media channels since around 2014. There also seems to be a rise in the promotion of the campaign around the times of holidays associated with chocolate such as Christmas and Easter (Stop the Traffik, 2015). Finally, the social media outlets they are active on are Facebook, since 2010 (Facebook, 2015), Twitter since 2009 (Twitter, 2015) and YouTube since 2010, however they were last active on this site over one year ago (YouTube, 2015), thus showing that this NGO underutilises their online communication channels.
In relation to Stop the Traffik, NGOs on a wider scale, and the for-profit sector, social media, online campaigns, and mobile marketing (where used) are usually targeted at younger generations. However, when looking just at the NGO sector, young people on average, donate less than their older counterparts (Midlarsky & Hannah, 1989). Many NGOs claim that fundraising has not been a central part of their social media strategies and is often just an indirect side effect of the relationship building effort (Phethean et al., 2013). Nonetheless, it is evident that NGOs, including Stop the Traffik, need to embrace social media and other innovative methods of recruitment and loyalty building which are suited to the fluidity and reactivity of younger generations (Urbain Gonzalez & Le Gall-Ely, 2013).
Snapchat
Snapchat was created in 2011 as a free social photo/video sharing mobile-only application whereby the photos (more commonly referred to as ‘snaps’) are automatically
deleted after a maximum viewing time of 10 seconds. Although a limited amount of
characters can be typed onto each snap, users have the option to draw over their photos with a range of different coloured paints (Virgillito, 2015). Multiple photos can be taken over a 24 hour period and collated to create a Snap story which can be repeatedly viewed for 24 hours (Snapchat, 2015). Snapchat currently has over 200 million subscribers (Aslam, 2015), 86% of whom are under 34 years old (Snapchat, 2015). 65% of subscribers contribute on a daily basis (Virgillito, 2015) and over 800 million photos and videos are uploaded every day (Aslam, 2015). The short time-span in which the receiver can view the picture/video leads to a sense of urgency and can trigger a fear of missing out (Virgillito, 2015). It can also cause people to pay more attention to the messages because they know they are unable to see them again, which creates excitement, prompting more effective marketing (Kaplan, 2012) than say on Facebook or Instagram, where the content will last forever (Virgillito, 2015). Nonetheless, Snapchat as a marketing tool is a relatively new concept and the effects of Snapchat campaigns have not been explored to a great extent (Virgillito, 2015).
Method Participants
To test the hypotheses, an online experiment with a 1 x 3 (campaign shown either as a magazine or video of an app in use or the actual interactive experience with the app) between subjects design was conducted with 152 participants, of whom, 118 completed the entire study (Mage = 24.9 years, SD = 2.83). Participants were recruited through convenience snowball sampling via Facebook and friendship networks. The majority of respondents (64%) were women, and 65% of all respondents were still students, with 51% holding or studying for a master’s degree. Participants were randomly assigned to one of three conditions, (n = 43, n = 36, n= 39).
Stimulus Material and Procedure
The stimulus material is Stop the Traffik’s #Traffikfreechocolate campaign which was presented in the style of a photo story. Because the experiment was launched in December, the campaign focused on the increase in sales of chocolate during the Christmas period and linked this to child trafficking. The images and text shown in the campaign are the same across the conditions (see Appendix A for stimulus material).
The photo story will be presented in the following way. The first snap will show images of chocolate with the following text overlaid, “Christmas is coming” and “I love chocolate”. The second snap will show more chocolate and the following text “do you want to give child-made chocolate?” The third snap will say “many children are trafficked onto cocoa farms” along with “1 million just like him” and “Ivory Coast”, the text will be shown with the image of a small child carrying cocoa beans. The fourth snap will show an image of Fairtrade cocoa beans, chocolate, and the Fairtrade logo and the text supporting it will say “buy #Traffikfreechocolate this Christmas”. The fifth snap of the photo story will show a photo of a girl with a bar of Fairtrade chocolate, the text accompanying it will read “snap us your selfie using #Traffikfreechocolate”. The sixth snap will have the text “and we will share it to Facebook” and show a number of these photos on the Stop the Traffik Facebook page. The seventh snap will show an image of the Stop the Traffik website and have the text “then please visit our website and donate the cost of your chocolate” overlaid. The final snap of the photo story will show a photo of an advent calendar with a piece of chocolate that shows a child being abused and will have the text “so that we can STOP child trafficking today. Thank you” as well as the website address.
For the magazine condition, the images described above were photo-shopped into a double page spread from a magazine and viewers were shown a full screen image of the
magazine. Participant were only able to click onto the rest of the survey after they have seen this image for a minimum of 25 seconds.
In regards to the app and the video of the app in use, it was not possible to use the real Snapchat app due to the fact the experiment was conducted over the internet. For that reason an app was created (using the web application framework, Ruby on Rails) in order to look, feel and work like Snapchat in order to obtain the best results possible. If participants were assigned to the interactive app group, they were redirected to a new webpage which showed the app and allowed the respondent to interact with the campaign and other snaps on a mobile phone. These other snaps were added in order to make the Snapchat app more realistic. The participants were free to watch however many of the four snap stories as they wanted in whichever order, and when they felt they had completed the task, they could close the app and return to the survey.
For those in the video condition, a video was made showing the app in use on a mobile phone. The video showed someone playing with the phone and going from the home screen to clicking on the Snapchat application, to then viewing all four snaps including the campaign. The video was created using Adobe Premiere Pro and lasted 1 minute 30 seconds. Moreover, it was only after this time that participants could click to continue with the survey. These minimum time limits were imposed in all conditions to ensure participants actually viewed the campaign.
Pilot study
A pilot study was conducted among 21 students studying at the University of Amsterdam. Although participants were found using convenience sampling, none of them were aware of the purpose of the study before hand and none studied Communication
Science. The participants were split into the three experimental groups and exposed to one of the stimuli. They were then asked one question related to interactivity; that question being
‘how interactive was your campaign viewing experience?’ This question was coded on a 7-point scale (1 = not interactive at all, 7 = very interactive). The results of the pilot showed that the magazine was seen as the least interactive, (M = 2.57, SD = 1.13), followed by the video of the Snapchat campaign, (M = 4.29, SD = 0.49) and the most interactive was the actual interactive experience with the app (M = 4.57, SD = 1.72).
Measures
The dependent variables for this experiment are awareness and empathy, willingness to engage in the campaign and willingness to donate. These four variables have been chosen because they fit into the three sequential outcomes which Phethean, Tiropanis, and Harris (2012) suggest NGOs aim for when creating their campaigns. Phethean et al (2012) presume that there is a stair-step decrease in the number of people at each stage. In this experiment, empathy can be interpreted as part of awareness.
Awareness: Participants will be asked to rate on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree) how much they agree with the statements: ‘after seeing the
campaign, I was more aware of child trafficking in the cocoa industry’ (M = 4.54, SD = 1.64), ‘I was surprised by the information presented’ (M = 3.82, SD = 1.78) and ‘after seeing the campaign, I will be more wary of whether chocolate is Fairtrade’(M = 4.42, SD = 1.68). The results from this are then computed into a new variable called awareness (Eigenvalue = 2.07, explained variance = 69.02%, α = .77, M = 4.26, SD = 1.41).
Additionally, awareness will be operationalised as recall, due to the fact participants undergo forced exposure to the campaign and this is how Phethean et al (2012)
operationalises NGO awareness. Participants will be asked, at the end of the survey, if they remembered the name of the NGO used in the campaign, this will later be recoded into a binary variable, referred to as recall (0 = correct, 1 = incorrect). A level of error will be allowed for in terms of spelling. With this variable, 54% got the NGO name correct. This
question will be asked at the end of the experiment to avoid priming participants.
Subsequently at the end of the survey, participants will also be asked if they were aware of Stop the Traffik before taking part in the experiment (9% were aware of Stop the Traffik), this will check for familiarity bias.
Empathy: The extent to which participants were empathic with the campaign would
be measured by examining to what extent participants agree with certain statements, answered on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), such as whether they would feel guilty if they did not buy Fairtrade chocolate (M = 3.66, SD = 1.63), donate (M = 2.53, SD = 1.48), or take part in the campaign (M = 2.92, SD = 1.63) or if they would feel regretful if they did not buy Fairtrade chocolate (M = 3.64, SD = 1.76), donate (M = 2.83, SD = 1.53) or take part in the campaign (M = 2.76, SD = 1.48). Following this, the results would be computed into a new variable called regret (Eigenvalue = 4.10, explained variance = 63.35%, α = .90, M = 3.06, SD = 1.30).
Participants would also be asked about whether they feel bad about themselves for not normally buying Fairtrade chocolate (M = 3.08, SD = 1.60), feel sad for the children that are trafficked (M = 5.59, SD = 1.57), whether they can imagine what it is like for the child involved in the campaign (M = 4.63, SD = 1.87) and whether they feel empathy towards the campaign (M = 4.97, SD = 1.72). Finally they would be asked if they trust the information presented (M = 4.75, SD = 1.52). The answers from these questions represent guilt and are again computed into a new reliable guilt scale (Eigenvalue = 2.93, explained variance = 58.64%, α = .82, M = 4.60, SD = 1.27).
All the above questions were taken from pre-defined theoretical empathy scales used by Basil et al (2008) and adapted to this study. Empathy has been chosen as a dependent variable because NGO campaigns need to play on people’s emotions in order for them to become aware of the cause and want to help (Basil et al., 2008).
Engagement: The extent to which participants were engaged with the campaign
would be measured by asking two different styles of questions. Firstly, involvement would be measured and questions have been taken from the Personal Involvement Inventory scale which is a semantic differential scale (Zaichkowsky, 1985). This scale has been customized to measure involvement with the campaign and consists of fourteen statements. Participants are asked to state on a 7-point Likert scale how they feel the campaign was. Examples of these items are ‘interesting/boring (M = 4.73, SD = 1.63), ‘irrelevant to me/relevant to me’ (M = 4.74, SD = 1.54), not surprising/surprising’ (M = 3.91, SD = 1.84), ‘not needed/needed (M = 5.38, SD = 1.38). These statements were then computed into one involvement variable known as semantic engagement (Eigenvalue = 6.90, explained variance = 49.31%, α = .92, M = 4.71, SD = 1.10).
Following this, engagement was also measured by asking how likely participants would be to interact with the NGO. Answers were coded on a 7-point Likert scale (1 = very
unlikely, 7 = very likely). Participants would be asked how likely it would be that they would
visit the Stop the Traffik Facebook page (M = 3.81, SD = 1.92), look at a
#Traffikfreechocolate selfie posted to the Facebook page (M = 3.16, SD = 1.9), or ‘like’ Stop the Traffik on Facebook (M = 3.60, SD = 2.00). Participants would also be asked if they would ‘follow’ Stop the Traffik on Twitter (M = 2.44, SD = 1.82), or visit the Stop the Traffik website (M = 3.82, SD = 1.82). In addition, they would also be asked if they would buy Fairtrade chocolate for the purpose of taking a selfie for this campaign (M = 2.65, SD = 1.77) or if they would buy Fairtrade chocolate in the future (M = 4.52, SD = 1.76). These questions would then be computed into a new variable called involvement (Eigenvalue = 4.13, explained variance = 58.97%, α = .88 M = 3.43, SD = 1.42).
Donation intention: To gage the participant’s willingness to donate, they would be
months (33% yes), this will measure how charitable they are. Then, after viewing the campaign and at the end of the survey, participants would be asked if they are willing to donate the cost of Fairtrade chocolate to Stop the Traffik (53% yes), and if they would be willing to donate a larger amount (17% yes). Finally, the survey will end with the question ‘by clicking 'yes' below, you will be able to donate the amount of your choice to Stop the Traffik. Would you like to do this?’ (9% yes). This will determine whether or not participants are serious about donating money, as often this is different from their intention due to social desirability.
Perceived interactivity: The questions used to interpret perceived interactivity come
from the pre-defined theoretical scale used in Gao et al’s (2006) research on interactivity. All answers were coded on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Participants were asked to what extent they agree with the following statements, ‘the way the campaign is displayed enables two-way communications between myself and the NGO’ (M = 3.82, SD = 1.69), ‘the way the campaign is displayed enables instantaneous communication between myself and the NGO’ (M = 3.71, SD = 1.68), ‘I had control over the campaign viewing experience when it is displayed in this way’ (M = 4.04, SD = 1.65), ‘I feel connected to the NGO through this campaign as it was displayed to me’ (M = 3.44, SD = 1.63), ‘the campaign felt personal’ (M = 3.68, SD = 1.77), ‘I enjoyed viewing the campaign in this format’ (M = 3.81, SD = 1.84), ‘the campaign increased my curiosity about the NGO and topic’ (M = 3.97, SD = 1.76), and finally, ‘viewing the campaign in this way was interactive’ (M = 3.99, SD = 1.76). Following this, a confirmatory factor analysis was conducted in order to check that all items load onto a reliable perceived interactivity scale (Eigenvalue = 4.99, explained variance = 62.40%, α = .91, M = 3.83, SD = 1.33).
Control variables: Besides gender, age and education level, participants were asked
Snapchat they are asked to rate how frequently they use it in a week on a 7-point scale, 1 =
never, 7 = very often (M = 3.76, SD = 2.34).
Participants were also asked to fit the following statements to their character of a 7-point Likert scale in order to assess their personality in relation to the ‘big 5’ personality traits (openness, conscientiousness, extraversion, agreeableness and neuroticism). The statements are ‘I see myself as someone who:’, ‘is reserved/shy’ (M = 3.36, SD = 1.58), ‘people
generally trust’ (M = 5.71, SD = 1.2), ‘is relaxed and able to deal well with stress (M = 4.9,
SD = 1.47)’, ‘has little interest in art (M = 2.82, SD = 1.80)’, ‘is sociable’ (M = 5.51, SD =
1.04), ‘is quickly criticized by others (M = 3.05, SD = 1.43)’, ‘gets easily nervous (M = 3.8,
SD = 1.68)’, and ‘has a vivid imagination’ (M = 5.34, SD = 1.31).
Results Randomization check
The three experimental groups did not differ significantly from each other regarding
age, F (2, 115) = .844, p = .433; level of education F (2, 115) = .640, p = .529; gender,
2(2, N = 118) = .267 p = .875, and familiarity with Snapchat
2 (4, N = 118) = 8.71 p = .069.Manipulation check
The manipulation check was carried out again in the final study to ensure that respondents processed the material properly in relation to the levels of interactivity. The results showed that from the question ‘how interactive do you think your campaign viewing experience was?’ The magazine was considered the least interactive, (M = 3.56, SD = 1.60), followed by the video (M = 4.17, SD = 1.72) and again interacting with the app was seen as the most interactive (M = 4.72, SD = 1.17). This was both the expected and intended result. Subsequently a one-way between groups ANOVA was run to check for significant differences between the groups, yet because the Levene’s F test of homogeneity was not
satisfied, F(2, 115) = 3.89, p = .023 a robust Welch ANOVA was conducted which provided a significant difference between the three groups, F(2, 73.36) = 7.16, p = .001. Following this the Scheffe post-hoc test was run and the results show that the only significant difference was between the magazine group and the app group, p = .003.
Hypothesis 1
Hypothesis one assumed that participants exposed to the campaign via the app would have the highest levels of awareness about the problem, feel the most empathy, engage the most with the campaign and donate the most, in comparison to those who viewed it in the magazine, who would have the lowest scores in all measures, and those who watched the video, who’s scores would fall in the middle. Each of the following dependent variables, awareness, empathy (regret and guilt), engagement (semantic engagement and involvement), was tested using between groups one-way ANOVAs, with the condition of the experiment as the independent variable. None of the ANOVAs conducted on these dependent variables gave significant results, even though the Levene’s test of homogeneity was satisfied in all cases. Nevertheless, Table 1 shows the means and standard deviations of each dependent variable.
Table 1
A table showing the Means and Standard Deviations for the dependent variables used in Hypothesis 1
Awareness Regret Guilt Semantic
engagement Involvement Experiment condition M SD M SD M SD M SD M SD App 4.61ₐ 1.36 3.40ₐ 1.27 4.62ₐ 1.24 4.58ₐ 1.07 3.62ₐ 1.53 Video 4.20ₐ 1.41 3.02ₐ 1.40 4.46ₐ 1.31 4.71ₐ 1.10 3.35ₐ 1.25 Magazine 4.00ₐ 1.41 2.79ₐ 1.20 4.72ₐ 1.29 4.87ₐ 1.15 3.32ₐ 1.45
Note: Within each column significant mean differences (p < .05) are indicated by different subscripts.
Awareness was also measured by recalling the NGO name used in the case study, which was computed into a nominal binary variable (0 = correct, 1 = incorrect). A Chi-Square test was run to test for an association between experimental condition and NGO name recall. The Chi-Square test found that there was no association between experimental
condition and NGO name recall,
2 (2, N = 118) = 4.36, p = .113 (see Table 2 in appendix B).For donation intention, two Chi-Square tests were run in order to see whether there was an association between donation intention and the conditions assigned to each
participant. Firstly, a Chi-Square test was run based on donation intention, and the results for this Chi-Square test showed that donation intention did not differ by experimental condition,
2 (2, N = 118) = 0.19, p = .910 (see Table 3 in appendix B).Following this, participants were asked if they would like to donate ‘now’ to Stop the Traffik. Results from this differed greatly from the results from donation intention as 92% said no, in comparison to the 48% who said no originally, regardless of experimental
experimental condition and willingness to donate ‘now’,
2 (2, N = 118) = 0.48, p = .788 (seeTable 4 in appendix B).
Hypothesis 2
Hypothesis 2 presumed that the levels of perceived interactivity would increase in a
stair-step manner from the magazine condition, which would be perceived as the least interactive, to the video condition, which would be a control condition with a medium level of perceived interactivity, to finally the app condition, which should have the highest level of perceived interactivity. To see whether this hypothesis is supported, a one-way between groups ANOVA was run. Prior to this, the assumption of homogeneity of variances was tested and satisfied based on the Levene’s F test, F(2.118) = .991, p = .374.
The ANOVA showed a significant effect on perceived interactivity between
experimental conditions, F (2,118) = 5.88, p = .004, η2 = .093. To evaluate the nature of the differences between the three means further, the statistically significant ANOVA was followed by three Bonferoni post-hoc tests. These tests showed a significant difference in perceived interactivity between the magazine and the video (p = .037) and the magazine and the app (p = .005), but there was no significant difference in perceived interactivity between the video and the app condition (p > .05).
Hypothesis 3
Hypothesis three presumed that perceived interactivity by participants would mediate the relationship between experimental condition and the dependent variables. This mediation effect was formally tested with the SPSS macro PROCESS (Model 4) using 1,000 bootstrap samples to estimate the indirect effects (Hayes, 2013). Tests were conducted separately for each dependent variable.
The results showed a significant mediation effect so that the app when compared to the magazine had a significant effect on awareness via perceived interactivity, total effect b =
.61, p = .052, direct effect b = .18, p = .534; indirect effect .42, boot SE = .16, 95% bias corrected bootstrap confidence interval (BCBCI) [.15, .78]. The video, when compared to the magazine also showed a significant mediation effect on awareness via perceived interactivity, total effect b =.20 p = .520, direct effect b = -.14, p = .637; indirect effect .34, boot SE = .16, 95% bias corrected bootstrap confidence interval (BCBCI) [.08, .71]. However, a
non-significant mediation effect was found when the app was compared to the video, total effect b = .40, p = .214, direct effect b = .32, p = .280; indirect effect .08, boot SE = .14, 95% bias corrected bootstrap confidence interval (BCBCI) [-.18, .39]. Thus showing that perceived interactivity mediated awareness in terms of the app and the magazine and the video and the magazine but not between the app and the video.
Secondly, the same analysis was applied to the next dependent variable, regret. The results showed a significant mediation effect so that the app, compared to the magazine condition, had a significant effect on regret via perceived interactivity, total effect b = .61, p = .037, direct effect b = .10, p = .679; indirect effect .49, boot SE = .16, 95% bias corrected bootstrap confidence interval (BCBCI) [.19, .83]. In addition, the results showed a significant mediation effect that the video, compared to the magazine condition had a significant effect on regret via perceived interactivity, total effect b =.23 p = .436, direct effect b = -.18, p = .490; indirect effect .40, boot SE = .18, 95% bias corrected bootstrap confidence interval (BCBCI) [.07, .76]. Finally for regret, the results showed a non-significant mediation effect so that the app, compared to the video did not have a significant effect on regret via perceived interactivity, total effect b = .37, p = .211, direct effect b = .28, p = .270; indirect effect .10, boot SE = .16, 95% bias corrected bootstrap confidence interval (BCBCI) [-.21, .41].
The mediation analysis was then applied to the dependent variable, guilt. Firstly, the results showed a significant mediation effect so that the app, compared to the magazine, had a significant effect on guilt via perceived interactivity, total effect b = -.56, p = .722, direct
effect b = -.56, p = .032; indirect effect .46, boot SE = .15, 95% bias corrected bootstrap confidence interval (BCBCI) [.18, .76]. Next the video compared to the magazine showed a significant mediation effect, total effect b = -.26 p = .369, direct effect b = -.63, p = .016; indirect effect .37, boot SE = .16, 95% bias corrected bootstrap confidence interval (BCBCI) [.07, .69]. Lastly, a non-significant mediation effect was found when the app was compared to the video, total effect b = .16, p = .590, direct effect b = .07, p = .779; indirect effect .09, boot SE = .15, 95% bias corrected bootstrap confidence interval (BCBCI) [-.19, .38]. These results show that perceived interactivity mediated empathy (both regret and guilt) in terms of the app and the magazine and the video and the magazine but not between the app and the video.
Next, mediation analysis was conducted with semantic engagement as the dependent variable. The results showed a significant mediation effect so that the app when compared to the magazine had a significant effect on semantic engagement via perceived interactivity, total effect b = -.29, p = .239, direct effect b = -.15, p = .488; indirect effect .44, boot SE = .14, 95% bias corrected bootstrap confidence interval (BCBCI) [.17, .74]. Secondly, the results showed a significant mediation effect so that the video compared to the magazine had a significant effect on semantic engagement via perceived interactivity, total effect b = .14, p = .588, direct effect b = -.22, p = .310; indirect effect .35, boot SE = .15, 95% bias corrected bootstrap confidence interval (BCBCI) [.07, .67]. Lastly, results showed a non-significant mediation effect so that the app, compared to the video, did not have a significant effect on semantic engagement via perceived interactivity, total effect b = .15, p = .548, direct effect b = .07, p = .744; indirect effect .08, boot SE = .15, 95% bias corrected bootstrap confidence interval (BCBCI) [-.18, .39].
Then, mediation analysis was conducted with involvement as the dependent variable. The results showed a significant mediation effect so that the app, compared to the magazine
had a significant effect on involvement via perceived interactivity, total effect b = .30, p = .347 direct effect b = -.27, p = .326; indirect effect .57, boot SE = .20, 95% bias corrected bootstrap confidence interval (BCBCI) [.20, .98]. Following this, the results showed a significant mediation effect that the video when compared to the magazine, had a significant effect on involvement via perceived interactivity, total effect b = .03 p = .933, direct effect b = -.43, p = .120; indirect effect .46, boot SE = .21, 95% bias corrected bootstrap confidence interval (BCBCI) [.09, .89]. Finally, the results showed a non-significant mediation effect so that the app, when compared to the video, did not have a significant effect on involvement via perceived interactivity, total effect b = .27, p = .413, direct effect b = .16, p = .557; indirect effect .11, boot SE = .19, 95% bias corrected bootstrap confidence interval (BCBCI) [-.25, .49]. These results show that perceived interactivity mediated engagement in terms of the app and the magazine and the video and the magazine but not between the app and the video.
Following this, the mediation analysis was conducted with donation intention as the dependent variable, participants were asked if they would donate the cost of a Fairtrade chocolate bar to the NGO. The results showed a non-significant mediation effect so that the app, compared to the magazine did not have a significant effect on donation intention via perceived interactivity, total effect b < -.01, p = .991 direct effect b = .08, p = .868; indirect effect -.08, boot SE = .15, 95% bias corrected bootstrap confidence interval (BCBCI) [-.49, .15]. Following this, the results again showed a non-significant mediation effect that the video when compared to the magazine, had a non-significant effect on donation intention via perceived interactivity, total effect b = -.18 p = .70, direct effect b = -.11, p = .811; indirect effect -.07, boot SE = .13, 95% bias corrected bootstrap confidence interval (BCBCI) [-.43, .12]. The results also showed a non-significant mediation effect so that the app, when compared to the video, did not have a significant effect on involvement via perceived
interactivity, total effect b = .27, p = .413, direct effect b = .16, p = .557; indirect effect .11, boot SE = .19, 95% bias corrected bootstrap confidence interval (BCBCI) [-.25, .49].
Finally, the mediation analysis was conducted with the question asking participants whether they would donate now as the dependent variable. The results showed a non-significant mediation effect so that the app, compared to the magazine did not have a
significant effect on immediate donation intention via perceived interactivity, total effect b = -.11, p = .901 direct effect b = -.21, p = .810; indirect effect -.34, boot SE = .30, 95% bias corrected bootstrap confidence interval (BCBCI) [-.15, 1.05]. The results also failed to show a significant mediation effect when comparing the video to the magazine. There was a non-significant effect on donation intention via perceived interactivity, total effect b = .51 p = .523, direct effect b = .23, p = .783; indirect effect .27, boot SE = .27, 95% bias corrected bootstrap confidence interval (BCBCI) [-.10, 1.13]. The results also showed a non-significant mediation effect so that the app, when compared to the video, did not have a significant effect on involvement via perceived interactivity, total effect b = .41, p = .613, direct effect b = -.44, p = .584; indirect effect .06, boot SE = .16, 95% bias corrected bootstrap confidence interval (BCBCI) [-.13, .58]. These results show that perceived interactivity did not mediate donation intention among any of the conditions.
Therefore, hypothesis three is supported in relation to a) awareness, b) empathy and c) engagement as all dependent variable outcomes were mediated by perceived interactivity when there was a difference between traditional media (the magazine) and new media (the Snapchat video and app). However, d) donation intention was not mediated by perceived interactivity. This means that the app only had an effect on the outcome measures (awareness, empathy and engagement) when individuals perceived it to be interactive.
Discussion
The purpose of this study was to see to what extent mobile applications, as platforms for campaigning, and the level of interactivity which accompanies them, produces different levels of engagement among younger generations, when compared to traditional media. The levels of engagement were taken from previous research about the aims of NGO campaigns (Phethean et al., 2012; Phethean et al., 2013) and these were comparable to the reasons for campaigning in the for-profit sector (Mirbagheri & Hejazinia, 2010). This study has shown that the use of a mobile platform, in comparison to traditional media, has no direct effect on awareness, engagement or donation intention. This was a surprising find because previous studies had found that interactive media lead to higher levels of engagement (Sundar & Kim, 2005) and response rates (Mirbagheri & Hejazinia, 2010) in relation to corporate campaigns. Still, these non-significant results could have been due to the small sample size or type of campaign used.
Taking the above results into consideration, this study also investigated what role interactivity played. To begin with the findings from this paper aligned with the theoretical research on interactivity (Mollen & Wilson, 2010; Pavlou & Stewart, 2000), from which it was suggested, and subsequently proven that the magazine would be perceived as the least interactive channel and physically interacting with the app would be the most interactive.
Subsequently, because the results of this study proved inconclusive in relation to direct effects on engagement, yet echoed previous research in terms of interactivity levels, the role of interactivity as a mediator was tested, as suggested by Bucy and Tao (2007).
Regardless of a concrete definition, theoretical research and previous studies conducted in the for-profit sector have generally concluded that interactive media is more persuasive (Pavlou & Stewart, 2000) and positively associated with advertising effectiveness (Calder et al., 2009; Gao et al., 2006; Sundar & Kim, 2005). The results for this study are somewhat in agreement
with this as they show that when the audience perceives the advertising medium to be interactive, they become more aware of the problem, more empathic and more engaged with the campaign.
On the contrary though, this study failed to find a link between interactivity as a mediator and donation intention, a result which could possibly be explained by the research conducted by Phethean et al. (2012) which suggested not only that the smallest effect would be found in donation intention, but that also fundraising is often seen as an indirect side effect of the relationship building effort. However, practical research conducted into mobile
marketing by NGOs showed that donations increased for ‘Ein Herz für Kinder’ due to their collaboration with Haribo (Jensen, 2012). However, this is only one practical study looking into the increase in donation intention and no conclusions can be made from the other example mentioned, as the Medicins sans Frontieres and Whatsapp collaboration was only recently launched. Therefore, it can be assumed that a rise in donation intention occurs over time.
The most striking result from this study is that participants regard both the video of the app and the interaction with the app as highly interactive and levels of engagement increased among both conditions even though participants had no physical interaction with the video. This result echoes research conducted on media effects from television as mentioned by Bucy and Tao (2007) and shows that physical interactions and structural interactivity is not necessary for increasing engagement.
One major limitation for this study is that previous research conducted in relation to interactivity as a mediator and its effect on engagement related to NGO campaigns is non-existent. In addition, most other studies in relation to interactivity and engagement focus on the for-profit sector and on websites rather than mobile phones. For these reasons it is hard to know whether the results found in this study can be generalized. Consequently, what is
needed now is more research into the use of interactivity as a mediator and its effect on both for-profit and non-profit campaigns in order to see whether a pattern emerges and therefore, whether the results presented in this study fit with that pattern.
Another limitation can be found in the method of this paper’s experiment as it would have been better to use the real Snapchat app and conduct the experiment on a mobile phone. However, it is hoped that future studies would be able to use existing apps in order to conduct their research. One interesting line of research that could be looked into in the future is to compare of the levels of engagement found across different mobile applications. For
example, comparing Snapchat, a short term image-based platform, to Whatsapp, a text-based platform and also to Instagram, a long lasting image-based platform. In addition it could be interesting to compare mobile based viewing to computer based viewing, for example, does viewing a campaign on Facebook, Twitter, or on a website cause different levels of
engagement when viewed on a mobile phone, tablet, laptop or desk computer.
All the same, the results from this study have multiple theoretical and practical implications. First of all, this paper confirms that perceived interactivity is more important in assuming attitudinal and behavioural changes than structural interactivity and that it is the interactivity the audience believes is present that has the greatest effect on engagement rather than the medium used. What is more, this study is the first of its kind to measure interactivity as a mediator in relation to mobile campaigns and therefore opens a new avenue for future research. In terms of practical implications, the results found in this study and of further similar studies if they are conducted, can show why and how campaigns are successful when shown via mobile phones. This can benefit NGOs as they can better target their audiences and increase their return on investment, which means they will have more money to spend on the good work they do, rather than on marketing. For example, the results from this paper show that NGOs can increase levels of engagement simply by making their campaigns seem
interactive rather than actually having to be interactive, which should be cheaper (and easier) for them to create.
Finally, this study still brings into question whether or not NGOs should opt for mobile marketing as a strategy. It would seem that because mobile marketing on apps is only considered successful in raising awareness, empathy and engagement when it is deemed interactive, and yet is not considered successful in raising donation intention at all, interactive mobile marketing should be used to supplement existing communication strategies when the NGO aims to target young people.
Reference List
Aslam (2015). Snapchat by the numbers: Stats, demographics and fun facts. Retrieved from: http://www.omnicoreagency.com/snapchat-statistics/.
Basil, D. Z., Ridgway, N. M., & Basil, M. D. (2008). Guilt and giving: A process model of empathy and efficacy. Psychology & Marketing, 25(1), 1-23.
Briones, R. L., Kuch, B., Liu, B. F., & Jin, Y. (2011). Keeping up with the digital age: How the American Red Cross uses social media to build relationships. Public Relations
Review, 37(1), 37-43.
Bucy, E. P., & Tao, C. C. (2007). The mediated moderation model of interactivity. Media
Psychology, 9(3), 647-672.
Calder, B. J., Malthouse, E. C., & Schaedel, U. (2009). An experimental study of the relationship between online engagement and advertising effectiveness. Journal of
Interactive Marketing, 23(4), 321-331.
Cooper, G. TEXT APPEAL? NGOS AND DIGITAL MEDIA. In eds: Cooper, G., Cottle, S., Doucet, L., Duncan, S., Gormley, B., Joye, S., Klein, A., Newton, J., Scarff, L., Thorsen, E., Wardle, C., Watkins, R. & Wynne-Jones, R. (2014). The Future of Humanitarian Reporting. London: City University London.
Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & Van Wijk, R. (2007). Why pass on viral messages? Because they connect emotionally. Business Horizons, 50(4), 291-304.
Facebook (2015) Stop the Traffik. Retrieved from:
Fussell Sisco, H., & McCorkindale, T. (2013). Communicating “Pink”: An analysis of the communication strategies, transparency, and credibility of breast cancer social media sites. International Journal of Nonprofit and Voluntary Sector Marketing, 18(4), 287-301.
Gao, Q., Rau, P. L. P., & Salvendy, G. (2010). Measuring perceived interactivity of mobile advertisements. Behaviour & Information Technology, 29(1), 35-44.
Hayes, A. F. (2013). My Macros and Code for SPSS and SAS. Retrieved from Andrew F. Hayes, PhD.: http://www.afhayes.com/spss-sas-and-mplus-macros-and-code.html
Hibbert, S., & Horne, S. (1996). Giving to charity: questioning the donor decision process. Journal of Consumer Marketing, 13(2), 4-13.
Hsu, T. (2015). Top 5 Snapchat campaigns by innovative brands. Retrieved from: http://keyhole.co/blog/top-5-snapchat-campaigns-by-innovative-brands/
Jensen, O. (2012). Use of New Mobile Media by Nonprofits and Development of Societal Mobile Apps.
Kaplan, A. M. (2012). If you love something, let it go mobile: Mobile marketing and mobile social media 4x4. Business horizons, 55(2), 129-139.
Kiousis, S. (2002). Interactivity: a concept explication. New media & society, 4(3), 355-383.
Midlarsky, E., & Hannah, M. E. (1989). The generous elderly: naturalistic studies of donations across the life span. Psychology and aging, 4(3), 346.
Mirbagheri, S., & Hejazinia, M. (2010). Mobile marketing communication: learning from 45 popular cases for campaign designing. International Journal of Mobile
Mollen, A., & Wilson, H. (2010). Engagement, telepresence and interactivity in online consumer experience: Reconciling scholastic and managerial perspectives. Journal of
business research, 63(9), 919-925.
Moore, M. (2012). Interactive media usage among millennial consumers. Journal of
Consumer Marketing, 29(6), 436-444.
Obar, J. A., Zube, P., & Lampe, C. (2012). Advocacy 2.0: An analysis of how advocacy groups in the United States perceive and use social media as tools for facilitating civic engagement and collective action. Journal of Information Policy, 2, 1-25.
Pavlou, P. A., & Stewart, D. W. (2000). Measuring the effects and effectiveness of interactive advertising: A research agenda. Journal of Interactive Advertising, 1(1), 61-77.
Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of consumer
research, 135-146
Phethean, C., Tiropanis, T., & Harris, L. (2012). Measuring the performance of social media marketing in the charitable domain.
Phethean, C., Tiropanis, T., & Harris, L. (2013, May). Rethinking measurements of social media use by charities: a mixed methods approach. In Proceedings of the 5th Annual
ACM Web Science Conference (pp. 296-305). ACM.
Quinton, S., & Fennemore, P. (2013). Missing a strategic marketing trick? The use of online social networks by UK charities. International Journal of Nonprofit and Voluntary
Sector Marketing, 18(1), 36-51.
Shankar, V., & Balasubramanian, S. (2009). Mobile marketing: a synthesis and prognosis. Journal of Interactive Marketing, 23(2), 118-129.
Stop the Traffik (2015). Stop the Traffik. Retrieved from: http://www.stopthetraffik.org/campaign/chocolate
Sundar, S. S., & Kim, J. (2005). Interactivity and persuasion: Influencing attitudes with information and involvement. Journal of interactive advertising, 5(2), 5-18.
Third Sector Insight. (2014). Transforming your fundraising: Boosting engagement and donations through mobility.
Twitter (2015). Twitter. Retrieved from: https://twitter.com/stopthetraffik
Urbain, C., Gonzalez, C., & Gall‐Ely, M. L. (2013). What does the future hold for giving? An approach using the social representations of Generation Y. International Journal of
Nonprofit and Voluntary Sector Marketing, 18(3), 159-171
Virgillito (2015). 5 ways to rock at Snapchat marketing. Retrieved from:
https://www.elegantthemes.com/blog/tips-tricks/5-ways-to-rock-at-snapchat-marketing
YouTube (2015). YouTube. Retrieved from:
https://www.youtube.com/user/STOPTHETRAFFIKglobal
Yu, J. (2013). You’ve got mobile ads! Young consumers’ responses to mobile ads with different types of interactivity. IJMM. 8(1).
Zaichkowsky, J, L. (1985). Measuring the Involvement Construct, JCR, 12 (December), 341-352. In eds: Bruner II, G, C. (2009). Marketing Scales Handbook: A Compilation of Multi-Item Measures for Consumer Behaviour & Advertising Research (5th ed.). Illinois: GCBII Publications.
Appendix A
Screen shots of each experimental condition
Image 2: Screenshots from the video condition (not all images from photo story are shown
Appendix B
Tables referred to in the results section
Table 2
A table showing NGO name recall per experimental condition
What was the name of the NGO used in the campaign?
Experimental condition Incorrect answer Correct answer Total
Magazine 58% 42% 100%
Video 36% 64% 100%
App 41% 59.% 100%
Total 46% 54% 100%
Table 3
A Crosstabs showing the percentages for donation intention per experimental condition
Would you be willing to donate the cost of Fairtrade chocolate to Stop the Traffik?
Experimental condition Yes No Total
Magazine 51% 49% 100%
Video 56% 44% 100%
App 51% 49% 100%
Table 4
A Crosstabs showing the percentages of those willing to donate ‘now’ per experimental condition
Below you have the option to donate directly to Stop the Traffik, would you like to?
Experimental condition Yes No Total
Magazine 7% 93% 100%
Video 11% 89% 100%
App 9% 91% 100%
