Social Media Marketing: A Game of Numbers
A statistical analysis by Sean Marie Prythyll A. Patnubay | August 1, 2020
Imagine the huge amounts of data available from a conservative estimate of 2.62 billion people who visit social media platforms at least once a month for you to access at the tip of your fingers. These people (or is it time to use the pronoun ‘we’ since I can identify with them?) even spend an average of 135 minutes per day in these sites and with this, one can collect and use their demographics, sociographics, and earlier website visits to target their brand communication content or even personalize advertising to cater to their wants and needs.
The ongoing evolution and proliferation of social media consumption has allowed for ubiquitous narratives of persuasion to pop up in these sites. This has led to the marketing industry to allocate a whopping 13.8% of brands’ total marketing budgets to social media alone. Numerous scholarship has also been produced as of late (2008- May 2018) on brand communication in social media by reputable journals such as the Journal of Advertising Research, Journal of Interactive Marketing, Journal of Interactive Advertising, International Journal of Advertising, Journal of Advertising, Journal of Marketing, and the Journal of the Academy of Marketing Science. There were 144 articles published on the said topic: the year 2017 had the highest number of papers published that being 25 between those years but it started to flourish as early as 2011 in these top advertising and marketing journals.
Among the platforms studied, almost 30% of the 144 papers (41 papers) focused on Facebook in particular which is not that surprising since it was launched in 2004 making it the first major global social media platform founded. Facebook, as an overview, is a social networking site with 2, 271, 000, 000 active users as of January 2019. It even begs the question of “who in this day and age doesn’t have at least one Facebook account?” This was followed by 19 papers published about social media in general and a considerable share of 18 papers focused on Twitter. These numbers can be attributed to the social networking sites’ characteristic of networking capacity and even I find myself getting out there because of this in these platforms.
Three of the key directions for future research stated in Voorveld’s (2019) research agenda include 1) research on social media influencers, 2) research on personalized brand content in social media, and 3) research focusing on platform characteristics rather than on Facebook.
Brands tapping on social media influencers has become a widespread phenomenon but very little academic research has been found with regards to this. The need to systematically compare them with other forms of endorsers is apparent since there are potential differences that may arise. After all, they give off a more authentic vibe since they are more similar to social media users than celebrities since users believe influencers produce more genuine content therefore more credible content. This can be linked to the second key direction that I would like to address.
I speak from experience that I would only follow social media influencers that I share the same interests with. I think that research on personalized brand content in social media can be gained also from the social media influencers they follow and not just on the hashtags, location, brands their friends have liked or shared in the past, the number of likes a brand-related post reaches, et cetera. However, I agree that marketers should also be wary of how they present this personalization that would appear as less intrusive especially amidst the privacy concerns.
Finally, with regards to research focusing on platform characteristics rather than on Facebook, I agree wholeheartedly. I, myself, spend more time on Twitter rather than on the aforementioned even if it is by far the most popular social media platform. This is in light of the barrage of fake news and other concerns related to that platform. I also find Twitter as a site with more engagements amongst a relatively more educated audience. It also helps that the ads are less intrusive but my no means ineffective.
Liu, Burns, & Hou (2017) investigated these three key directions I drew from Voorveld’s research. If I am not mistaken, then this specific article was one of the 25 articles on brand communication published in 2017 from earlier and one of the 18 articles published focusing on brand communication on Twitter. They studied brand-related user-generated content (USG) on Twitter. It ticks off two of those directions in our checklist from the title alone. Social media influencers and even users’ brand-related posts are in fact user-generated. It studied the content retrieved from Twitter as the title suggests as well and not from Facebook. As for the personalized brand content, we can get back to that later.
I also mentioned earlier that one can only imagine the big data we have at our disposal that can answer brand-management questions and its potential value towards brand managers. The write-up listed two of the most challenges obstacles we face in maximizing social media marketing that even grown to rival traditional promotion techniques. As an active Twitter user myself among 310 million per month, I am overwhelmed with the microblogging site’s deluge of tweets. I am not even surprised by the number works. Hello, 500 million new tweets per day is not a joke. One would have to spend so much time filtering through those alone even if a considerable number pertains to products and brands. So, the paper started investigating 1) the brand-related topics consumers discuss on Twitter, 2) the ranking of brand sentiments within and across industries, 3) how we can identify specific product and service issues that consumers complain about, and 4) the merits of products and services that consumers feel good about.
The answers to their research questions that are numbered above are in connection with the second key direction that I wanted to discuss from Voorveld’s findings. These answers, indeed provide brand managers with “actionable insights in targeted advertising, social customer relationship management (CRM) and brand management”.
Going back to why the researchers chose Twitter’s USG over Facebook, it is apparent that the primary motivation for complaints surfacing on Twitter is that users want the firms to resolve the issues and Twitter has eventually established itself as a space for such and as an effective consumer communication vehicle. In my personal opinion, those who air it on Facebook are just doing it for the clout and it is not necessarily making a call to action. Therefore, I agree with the third key direction from Voorveld which was to research on sites other than Facebook. This was done by Liu et. al as they likened Twitter’s influence to the “online equivalent if word-of-mouth (WOM) communications” or electronic word-of-mouth (eWOM) which is a type of marketing strategy employed.
Using the Global Industry Classification Standard (GICS), five industries were selected based on two criteria: 1) owned by an S&P 500 company and 2) closely related to consumers’ daily lives. I noticed that the negative brand sentiments average across industries, be it in fast-food restaurants, department stores, footwear, telecommunications, or electronics is higher than that of the positive sentiments broadcasted on Twitter. All of them getting above an 40% industry average. This means that these brands have a lower overall satisfaction especially since “dissatisfied customers engage in greater words of mouth than satisfied customers”. Imagine if these social media marketers fail to address this, then they would have lost terribly in this game of numbers and the 13.8% budget becomes questionable indeed. After all, with too much data to digest, it would seem as if they have bitten off more than what they can chew.
References:
Hilde A.M. Voorveld (2019) Brand Communication in Social Media: A Research Agenda, Journal of Advertising, 48:1, 14–26, DOI: 10.1080/00913367.2019.1588808
Xia Liu, Alvin C. Burns & Yingjian Hou (2017) An Investigation of Brand Related User-Generated Content on Twitter, Journal of Advertising, 46:2, 236–247, DOI: 10.1080/00913367.2017.1297273
