Author’s note: One of my main goals as a marketing and communications specialist is to maximise the impact of a brand’s promotional and communicative contents, while investing the fewest number of hours and smallest amount of money into their design and creation. In support of that, the effectiveness of the content should regularly be assessed in order to optimise content conceptualisation and implementation. Although experienced marketing specialists might be able to infer probable trends by “looking” at quantitative data retrieved from analytics tools, conclusions drawn from a statistical analysis are generally more credible. The following article describes the design of a conceptual model that can help managers and specialists at spectator sports organisations assess the causal relationships between content categories and engagement behaviour, as well as a possible association with the number of viewers on network television and streaming services. The article is meant as a pilot study to test the model. It focuses on one social media channel, i.e. the official NHL TikTok channel, and findings can only be applied to that channel. However, the research offers noteworthy results and a good foundation for further development of the model and the conceptualisation of respective content.
The following pilot study explores how individual categories of social media content affect user engagement behaviour on the official TikTok account of the National Hockey League (NHL). The article further assesses possible causal relationships between content categories and engagement behaviours and the number of viewers who watched the Stanley Cup 2022 final series on network television (TV) and via streaming. Structural equation modeling was applied to a sample of 83 TikTok videos published on the official NHL account between 12 and 26 June 2022, the time period when the final series took place. Findings suggest that content revolving around people (in-game and not in-game), as well as content leveraged from the NHL TikTok community, positively influence all engagement behaviours, whereas the content categories game highlights and information have only partial effect on user engagement behaviour. Furthermore, the content categories game highlights and people (in-game and not in-game) have a significant and positive effect on the number of viewers that watched the final series on network TV or streamed it. On the other hand, no significant causal relationship was found between any engagement behaviour variable and viewership numbers.
Background to this pilot study
Social media has transformed the way viewers consume and experience spectator sports (Sanderson, 2011). Fans can engage with their favourite teams, athletes, or leagues through various social media channels in order to feel close to them before, during, and after the game (Sutera, 2013). Such user engagement can be incited through different kinds of media contents, which might be informative, affective, social, or aesthetic in nature (Chen et al., 2021; Gómez-Suárez & Veloso, 2020). These characteristics form the foundation of a brand experience, which can foster consumer satisfaction and loyalty (Schmitt, 1999; Brakus et al., 2009; Pine & Gilmore, 2020). Consequently, social media experiences are characterised by what is published on a given channel through content that may follow a conscious or unconscious strategic categorisation (Hu et al., 2014; Geurin-Eagleman & Burch, 2016) and seek to achieve an array of communication and engagement objectives (Baetzgen & Tropp, 2013; Batra and Keller, 2016).
Content categories can drive uses and gratifications for users to follow a brand or organisation on social media and to engage in specific behaviours (Whiting & Williams, 2013). The uses and gratifications theory is a considerable choice for the categorisation of media contents in mass communication (Blumler & Katz, 1974). However, various contemporary studies propose an adaptation of its categories to the context of the respective research or business application (see Cvijikj & Michahelles, 2013; De Vries et al., 2014; Dolan et al., 2016; Vale & Fernandes, 2018). This might include combining or excluding certain categories or altering them to fit the context. Although TikTok, the social media platform examined in this research, is often portrayed as mainly being used for entertainment purposes (cf. Zuo & Wang, 2019; Su et al., 2020), extant literature suggests that the platform offers a wider range of content types (cf. Basch et al., 2021; Huebner, 2022; Jiang et al., 2022). This is a legitimate argument given that TikTok content is created and consumed by more than 1 billion monthly active users by April 2023 (Demandsage.com, 2023). Furthermore, it can be argued that the degree to which video content is attractive to its targeted audience may be influenced by factors such as a video’s visual appeal, emotional reference, informative value, or engaging properties (cf. Yang & Kang, 2021).
The proactive conceptualisation and planning of social media content for different categories helps organisations such as the NHL coordinate the creation of its content more efficiently and effectively (Klimsa, 2017). Moreover, strategically organising and delivering different types of content across a variety of communication channels maintains consistency in how the brand story is told to the target audience and, hence, strengthens brand associations (Fetchko et al., 2018). Yet, organisations should examine how audiences use available communication channels and respectively deliver the type of content appropriate for a specific channel; not all content categories might be suitable for all channels (Ryan, 2020).
Based upon the discussion above and in consideration of the practicability of the chosen sample in the context of the NHL, the TikTok content categories highlights, people in-game, people not in-game, community, and information are proposed and accordingly defined in the following paragraphs:
The game highlights category refers to any video that focuses on a play that occurred during in-game action. A highlight can be defined as “the best, most important, or most interesting part” of an occurrence (Cambridge.org, 2023). For spectator sports, Merler et al. (2018) define highlights as “the most interesting moments of a game” and determine them by considering “players’ reactions (action recognition such as high-fives and fist pumps), players’ expressions (aggressive, tense, smiling and neutral), spectators (crowd cheering), commentator (tone of the voice and word analysis) and game analytics” (p. 2520). Such moments are based upon recognisable game aesthetics and familiar affective situations. In order to foster excitement among viewers, highlighted moments should offer an aesthetic logic that documents and celebrates the sports product, i.e. NHL games, instead of seeking to inform viewers with a fast-paced video, as it is often the case with contemporary journalistic video highlights (Vogan, 2014). Figure 1 refers to an example of an NHL highlight video on TikTok that follows the above-mentioned format.
The NHL TikTok channel offers two different types of videos that focus on people: The people in-game category refers to any video that focuses on people (e.g. players, fans, etc.) that is not related to in-game action, but where the scene occurs during a game (incl. shortly before and after the game). This could include, but is not limited to, videos showing how people enjoy the atmosphere at the game, how fans try to get players’ attention with cardboard signs or similar, or how players, coaches, or referees interact with each other while the game is stopped; see an example in Figure 2.
The people not in-game category also refers to any video that focuses on people (e.g. players, fans, etc.) that, however, is not directly related to a current game. Examples include outfit-of-the-day videos (i.e. #OOTD), moments from an event other than a game with focus on people and not on the event, whimsical videos with fans or players, or moments from past games; Figure 3 illustrates an example of a behind-the-scenes video from a photoshoot with NHL players. People are an essential component of the marketing mix; this includes people working for the product-delivering company, i.e. the NHL, as well as people consuming the product, i.e. spectators and fans (see Kotler & Keller, 2012). Personalities like players, coaches, executives, and broadcasters can be classified as marketing assets of the brand, as they directly or indirectly deliver the sports product to spectators and connect them to the product (Fetchko et al., 2019). On the receiving end, spectators in the venue or online may contribute with any kind of behavioural engagement (e.g. voicing emotions in the venue, contributing comments while second-screening, etc.) towards the co-creation of the game or brand experience alongside the above-mentioned personalities or other spectators; this can then strengthen the bond with the product-providing brands, i.e. the team(s) or league (cf. Schmitt, 1999).
The community category refers to any video that leverages content sourced from a fan or creator (i.e. user-generated content). Pegoraro (2013) notes that “sport media production is increasingly driven less by formal publishers and more by sports fans or the general public” (p. 254) and adds that “it is important for sport organizations to know what drives individuals to participate and create content, what types of content sport fans are producing and how is this changing the world of online sport fandom” (p. 255). This is highlighted by the notion that online content is necessary in order to engage, interact, and influence target audiences in respective online communities (Ryan, 2020). Subsequently, communities on social media are found to positively affect its members’ identification with the team (Sutera, 2013). Moreover, asking members for specific contributions to co-create the experience might trigger a feeling of investment in the product or brand (Yocco, 2016). It is further noteworthy that user-generated content about a product or brand can lead to higher behavioural engagement from other like-minded users as compared to brand-created content (Mayrhofer et al., 2020). Thus, empowering community members by offering them the opportunity to share their content through the official NHL channel can intensify the loyalty towards the product and brand (cf. Yocco, 2016). Figure 4 depicts an example of a video that was shot by a spectator and shared on the NHL account.
The information category refers to any video that informs people about something happening within the NHL or hockey community. In spectator sports, this could include informing followers about final scores of games and other game statistics, player trades, new products or services (e.g. new app, new website, new merchandise, etc.), and similar. People follow a brand’s social media activities, because they want to stay informed about various aspects of the brand and, possibly, learn from other followers (Vale & Fernandes, 2018). Although informational content can be considered an important element for the creation of a holistic brand experience (Pine & Gilmore, 2020), it may only motivate users to consume content and is less likely to incite higher degrees of interaction (Cvijikj & Michaelles, 2013). Framing content to be more informative than informational (e.g. conveying fascinating information or data) by including elements of surprise and exclusivity can raise the level of interaction, as users might perceive it as more valuable (cf. Schmitt, 1999). Figure 5 shows an example of how the NHL informed TikTok users about a new immersive augmented reality experience for fans.
Ryan (2020) defines social media as “the umbrella term for web-based software and services that allow users to come together online and exchange, discuss, communicate and participate in any form of social interaction” (p. 220). This definition highlights the importance of user engagement behaviour in social media. Vale and Fernandes (2018) suggest three levels of social media engagement behaviour: consumption, the most frequent behaviour, refers to the lowest levels of engagement (e.g. viewing posts, watching videos, reading comments, etc.); contribution refers to functional interactions such as liking, commenting, saving, and sharing, which are activities that require more effort than solely consuming content and show stronger user interest in the product or brand; lastly, creation requires most effort from users and refers to the active production and delivery of brand- or product-related content that might stimulate other users to consume, contribute, or create content (e.g. informative reviews, commentary, etc). As of May 2023, the main functional user engagement possibilities with a TikTok post include viewing, liking, commenting, saving, and sharing; see Figure 6 for reference. These will be used as variables in the conceptual model of this research.
Viewership on network television and streaming
The NHL season 2021-22 saw the organization entering a new broadcasting era in the United States with broadcasters ESPN and ABC, both owned by Walt Disney Company, after a 16-year partnership with broadcaster NBC (Sports Media Watch, 2021). The seven-year deal includes television, streaming, and media rights (NHL, 2021), which implies that the partnering companies recognise the importance of integrating different types of media channels for various consumption behaviours in order increase viewership (cf. Hutchins & Rowe, 2012). Thus, it becomes legitimate to hypothesize that social media content and its respective engagement behaviours can positively affect viewership numbers.
The conceptual model
The discourse above leads to the following hypotheses:
- H1: The TikTok content categories (a) game highlights, (b) people in-game, (c) people not in-game, (d) community, and (e) information have a positive effect on the number of viewers on TV and streaming.
- H2: The TikTok content categories (a) game highlights, (b) people in-game, (c) people not in-game, (d) community, and (e) information have a positive effect on TikTok engagement behaviours including (u) views, (v) likes, (w) comments), (x) saves, and (y) shares.
- H3: The TikTok engagement behaviours (u) views, (v) likes, (w) comments, (x) saves, and (y) shares have a positive effect on the number of viewers on TV and streaming.
A visualisation of the hypotheses is offered in Figure 7.
As mentioned above, this pilot study explores associations between the NHL’s TikTok content categories, users’ engagement behaviours, and the number of viewers on TV or streaming. A positivist approach was applied to investigate causal relationships between the proposed variables. In order to simplify the data collection process, focus was laid upon the Stanley Cup 2022 final series, because respective content on the official NHL TikTok channel would directly or indirectly promote the final series’ match-up. Hence, data for this research is based upon 83 videos that were published on the official NHL account between 12 and 26 of June 2022, the time period when the final series took place. All videos were manually categorised along the above-mentioned definitions and registered in a spreadsheet. Each video was allocated to only one category. Additionally, interaction metrics including the number of views, likes, comments, saves, and shares for each video were documented in the same spreadsheet. Lastly, viewership numbers for network and streaming on ABC and ESPN+ of the six Stanley Cup 2022 final series games were retrieved from Wikipedia (Wikipedia, 2022). No other openly available and consistent source for viewership of all final series games was found, hence the focus on the NHL’s American audience. Values for all variables were accessed on 3 December 2022.
In order to allow for an accurate analysis of the proposed associations, all values were standardised and converted to the same scale. Structural equation modeling was then applied in SPSS Amos to measure the causal relationships between the variables. Respective findings are discussed in the next section.
Findings and discussion
Of the 83 TikTok videos used in the analysis of this pilot study, 12 videos are attributed to the game highlights category, 20 videos to the people in-game category, 30 videos to the people not in-game category, 18 videos to the community category, and 3 videos to the information category. The statistical analysis of these 83 videos informs the following discussion. A visual representation of the findings is provided in Figure 8.
H1: Content categories and viewership. In regard to the association between TikTok content categories and the number of viewers on TV and streaming, this study finds that game highlights (H1a, β=.219, p<.05), people in-game (H1b, β=.456, p<.001), and people not in-game (H1c, β=.360, p<.001) have a significant and positive association with viewership numbers. Information (H1e, β=.116, p=.094) shows what is usually considered a non-significant relationship with a p-value of .094, but because this significance value is only slightly below the usually applied threshold, it is mentioned here for reference. If the sample would include more TikTok videos in the information category, its significance could improve. The strongest association with viewership numbers is recorded by the people in-game category. It can be argued that viewers enjoy a high level of curiosity when watching TikTok videos, as the videos offer situations that document how people experience an NHL game, which then connects them to the game and the protagonists in the videos (cf. Zuo & Wang, 2019). A similar argument applies to the video category people not in-game. Videos that show activities of NHL players, coaches, or fans, not directly connected to a game, offer a different perspective to spectators and fans, to which they usually do not have access; this brings them closer to their favourite athletes, team, or league and, thus, bolsters the respective attachment with the protagonists and the game (Sutera, 2013). Videos of game highlights also have a significant and positive association with viewership numbers, most likely because they raise excitement through aesthetic logic and vicarious achievement (Vogan, 2014). Information videos could influence viewership numbers, if they would convey essential information inciting more interest in the sports product, i.e. the game (Fetchko et al., 2018). Lastly, TikTok videos categorised as community are found to be irrelevant in the given context, as socialising and interacting with other NHL fans on TikTok does not seem to motivate people enough to watch the games; or, the sampled videos do not inspire enough socialisation and interaction among users.
H2: Content categories and engagement behaviours. Videos categorised as people in-game (H2b), people not in-game (H2c), and community (H3d) have a significant and positive effect on all engagement behaviour variables and have the strongest influence overall. This could be explained by the aesthetic and emotional proximity offered by the people in-game video category to the NHL product, combined with the identification of the viewing user with the people portrayed in the video; another factor to consider is the degree to which users following the NHL’s TikTok channel are invested in the product, as fans with a stronger attachment to the product might be more inclined to engage with the content (Onwumechili, 2017). Illustrating how people enjoy the game, positions the brand as more personal and less commercial and can evoke the desire to join the experience by engaging with the content and like-minded others (Rein et al., 2006). Similarly, TikTok users might find videos categorised as people not in-game appealing and interesting, because they portray real-life situations otherwise not accessible to them, hence, satisfying their curiosity and offering an escape from daily life (Nabi et al., 2003). Videos leveraged from the community highlight the opportunity for fan integration and offer a certain level of empowerment to fans (cf. Vale & Fernandes, 2018). This can be fostered by emphasising the broader social and cultural meaning of the brand in various videos (Schmitt, 1999). Game highlights videos (H2a) do not have a significant influence on views (H2au), but they have a significant and positive influence on likes (H2av), comments (H2aw), saves (H2ax), and shares (H2ay). However, game highlights videos have an overall weaker effect on engagement behaviour when compared to the people in-game (H2b), people not in-game (H2c), and community (H3d) categories. A possible explanation is that NHL highlights videos on TikTok do not offer distinct value. This could be improved by strengthening the aesthetic logic that documents and celebrates NHL games (cf. Vogan, 2014). Videos categorised as information have a significant and positive influence only on likes (H2ev) and saves (H2ex), and they record the weakest influences in comparison to the other associations. In order to reinforce that effect, content could be framed to include elements of surprise and exclusivity and make such videos more informative than informational, thus, increasing their perceived importance (cf. Schmitt, 1999).
H3: Engagement behaviours and viewership. This pilot study did not find significant causal relationships between any of the engagement behaviours and viewership numbers. Nevertheless, significant correlations were found between the above-mentioned variables, which explains that there are significant associations between these elements in the sampled data, but no cause-and-effect relationships. One reason could be that functional engagement behaviours on social media might need to be mediated by social presence and commitment of other fans before influencing viewing intention (Lim et al., 2015; Mereu, 2021). These causal relationships can be stimulated by emphasising second-screening characteristics of the NHL TikTok experience. Given its wide reach and the various purposes TikTok can be used for, it is legitimate to consider the platform for social TV/second-screening when watching spectator sports (Oelrichs & Leinfelder, 2022).
This pilot study examined how individual social media video categories influence user engagement behaviour on the official TikTok channel of the NHL; it further examined how these content categories and engagement behaviours influenced the number of viewers who watched the Stanley Cup 2022 final series on network TV and streaming. The sample included 83 TikTok videos published on the official NHL account during the time period when the final series took place, from 12 to 26 June 2022. The analysis found that videos focusing on people (in-game and not in-game) and videos leveraged from the NHL TikTok community have a significant and positive impact on all engagement behaviours; videos categorised as game highlights and information have partial and generally weaker influence on respective engagement behaviours. Additionally, videos of game highlights and people (in-game and not in-game) report a significant and positive impact on the number of viewers that watched the final series on network TV and streaming, whereas no significant influence was found between any user engagement behaviour and viewership numbers.
This research underlines the importance of strategically categorising content in order to plan and improve engagement behaviour more effectively and strengthen viewership. Furthermore, categorising social media content provides managers with an editorial overview of content that is published, planned, in production, drafted, and to be conceptualised. The task should be overseen by a content producer or social media manager, as it requires a mix of creative and analytical thinking. The categorisation process for this study was done manually, as no appropriate artificial intelligence tool was easily available.
The proposed model is tested with a specific convenience sample that allows control over possible interferences, e.g. promotional and communicative objectives of the published content. Nevertheless, future research should tackle that challenge and expand the dataset with further NHL TikTok videos and respective data from other time periods and about other games. This could be taken even further by including videos from team channels and other NHL media partners; however, consideration needs to be given to the extra layer of complexity that comes with it, as contents from different channels might differ in quality, quantity, as well as marketing and communication goals and, thus, complicate the analysis. This study refrained from including videos from other TikTok channels for simplicity reasons.
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