How Connectivity and AI Suggestion Algorithms Influence Marketing Strategies and Media Presence of Entrepreneurs
- Daniel Farah
- Oct 9, 2024
- 16 min read
Analysis of purposeful viral content creation
Chapter 1: Introduction
Technology and Connectivity as a Megatrend
In 2005, there were around 1 billion Internet users worldwide, whereas currently, there is almost 4 billion.
Due to big investments, growing Internet of Things sector of market and Fourth Industrial Revolution, “connectivity” is becoming a forceful expression of political power and global ambition, far surpassing mere economics (Mettler, 2021). By 2030, 90% of the world population will be able to read, 75% will have mobile connectivity, 60% should have a broadband access. (Mettler, 2021).
Connectivity acts as a multiplier of human behaviour more than anything else. In this sense, any human pattern, whether detrimental or beneficial, will be strengthened by connectivity.
One of especially vivid changes in the current world caused by high connectivity should be perceived in marketing field and its digital working principles, influencing both consumers as well as producers of goods.
AI Based Marketing - New Social Media Standard
Entrepreneurs tend to locate more and more budget in online activities, that promote their products and services due to high connectivity. There was almost 22 billion dollars spent on advertising in 2017 in USA and it is expected to reach 82 billion dollars by the 2025. (Statista, 2021).
Due to wide spread of social media and development of AI, new ways of online presence are being exercised among brands. Taking advantage of suggestion algorithms delivered by biggest social media platforms is becoming a new standard, when it comes to create branded content online.
Viral content creation, is a new approach utilizing AI and generating cost-efficient organic traffic. This phenomena can be observed on Social Network Services (SNS), that implements AI based recommendation engines (Reco-engines), that to some extend dictates what every user watches online.
In this understanding connectivity considered as a megatrend and AI based social media existence being one of its immediate aftermath could be seen as a subtrend, might have a strong influence on both, society’s online activity and the way brands promote their products.
AI Marketing Working Principles
There are multiple approaches of utilizing AI in marketing such as:
The use of advanced voice analysis capabilities, an AI agent might be able to infer from a customer’s tone that an unmentioned issue remains a problem and provide real-time feedback to guide the (human) salesperson’s next approach (Davenport et al., 2019).
The use of AI bots, which - in some cases - would function as a human salesperson, to make initial contact with sales prospects. (Davenport et al., 2019).
The use of AI based algorithmic recommendations, to reach wider audience by its viral capabilities and get access to clients, who are in fact interested in a product.
This research concentrates on the last of those approaches taking TikTok as an example, that is currently the fastest growing platform on the internet and relies mainly on suggested content consumption, rather than search engines.
Why Suggestion Algorithms Took Over Social Media?
Recommendation algorithms in social media platforms are highly exercised and rising because they enable:
Marketers to create relatively cost-effective campaigns, build society among products, and personal brands, that provides an opportunity to reach enormous audience by becoming viral.
Users, to be provided with relevant content, that in fact lays in their interests.
Social media platforms monetize their existence by data collection and analysis.
Servion Global Solutions report predicts that by 2025, 95% of customer interactions will be powered by AI (Mishra, 2021).
Chapter 2: What is a Viral Content?
There are multiple definitions of a viral content however, the main aspect that lets content to be perceived as viral its wide and fast spread among social media users. We should understand viral content as a figure (video, photography, text, etc.) that is posted online, which generates big traffic in a short period of time. (Berger & Milkman, 2012).
"Content goes viral for various reasons. Entertainment value is a common characteristic; others include usefulness, information, artistic merit, promotion of viewpoints and shock value." (Viral Content, 2016).
"Research in this field so far has highlighted that the key element in the message that might light the fire of virality is the emotion that content generates in the audience." (Dafonte-Gómez et al., 2020).
What Becomes Viral?
Content that is appealing for the audience which is expressed in various forms, that is being picked up by the algorithm, resulting in suggesting it to other similar users, that would generate a snowball effect in views of certain media.
TikTok as a specific SNS is strongly based on AI suggestion algorithm, that significantly affects the possibility of viral content creation, by analysing viewers’ interests and attentions.
In contrast to non-AI media era, nowadays, there is no need for content to be shared to one user by another. Thanks to suggestion algorithms, this happens automatically. But how does it exactly work?
How TikTok’s AI Decides a Video to Become Viral?
The app prioritizes who is recommended with what, based on two ways of filterings:
Collaborative Filtering (CF)
“User-user type”: “People who are similar to you liked this item, so you also might like it.” (Schafer et al., 2007, p.295).
“Item-item type”: “People who liked this item, usually like that item as well” (Sarwaret al., 2001).
“item-user type”: “It combines both approaches to generate recommendations. The simplest ones are based on matrix decomposition techniques. The goal is to create low-dimensional vectors (“embeddings”) for all users and all items, such that multiplying them together can uncover if a user likes an item or not (Figueroa, 2020).
(Maruti Techlabs, 2022)
Content Based filtering (CBF)
It takes into consideration features of the video, both given by the creator (description, hashtags etc.) and associated to it by AI (content analysis) “Based on training data a user model is induced that enables the filtering system to classify unseen items into a positive class c (relevant to the user) or a negative class c (irrelevant to the user).” (Meteren & Maarten, 2019).
(Maruti Techlabs, 2022)
By merging both types of filterings, AI based video content platforms (including TikTok) create a content rating matrix, that then is being tested on users and updates itself basing on viewers response. (Hybrid recommendation method)
How People Can Increase Their Chance to Go Viral?
- Emotion/Trends Led Creation
TikTok is a specific platform that emphasized AI usage to the extreme, more than 75 % of content watched there is being AI suggested rather than searched. (TikTok for Business, 2022b).
According to Semrush study on previous viral videos:
Happiness was the most common emotion triggered by viral TikTok videos.
More than 1 in 3 viral TikTok videos focused on a person speaking within the first three seconds.
More than half of viral TikTok videos used music as their primary backing sound in the first three seconds. (TikTok for Business, 2022a).
There are multiple publications by TikTok, that suggest how to behave when creating content, for it to be favored by the algorithm and go viral - among them we can read: “Join trends and be part of culture” (TikTok for Business, 2022a).
Therefore creators exercise specific content creation, that follows the so-called “trends” in purposeful viral content creation.
(TikTok for Business, 2022a)
Chapter 3: Current AI Led Viral Content On Social Media
(How to Go Viral on TikTok, 2022)
Brands use various trending (often for unknown reasons) viral content to stay trendy and relevant to eventually connect and build their audience on the social media. Viral content pieces help the brand to tap into the cultural nuances of their target audience which is a “win-win” scenario. They are being used to build a campaign, launch a collection, or just to keep their social media platform a fun and relevant place for the audience to visit and increase their engagement. Some examples of trending viral content nowadays are ASMR, food exaggeration, various dance trends, and many more.
The following examples might be some of the most vivid use cases of viral content productions, that shape today's social media consumption and creation.
3.1: Main Trends Nowadays: ASMR?
Autonomous Sensory Meridian Response (ASMR) is defined by a pleasant tingling feeling that begins at the scalp and progresses to the neck and spine. Although the word ASMR may appear to be technical, the phenomenon is not supported by science or research.
Whispering, quiet and sluggish speaking, breathing sounds, and smacking lips and tongue are some of the most common vocal triggers. Noises caused by object interaction, crushing, tapping, scraping, rough surfaces, and page rustling. Visual-tactile, demonstrating the application of makeup, hair care, combing, smooth hand movements, and soft substance contact.
The term was first coined in 2010 by a woman named Jennifer Allen who created the first ASMR Facebook group. Since then popularity exploded where millions of ASMR videos were created on social media with a response of billions watching it.
Through the concept of ASMR, brands are discovering new ways to genuinely describe and convey their product experience. The origins of ASMR can be traced back to sensory marketing. This tool assists in reaching the customer's mental space. As companies increasingly seek to reach out to more hyper-saturated consumers, eliciting reactions that appeal directly to the senses has shown to be more effective than traditional marketing tactics. In this instance, ASMR's job has been to break new ground in terms of reaching customers through aural and visual impacts.
There have been several reports that watching strangely pleasant videos helps people feel “relaxed and peaceful", according to researchers. It's no secret that stress and anxiety have skyrocketed and watching these videos provide rapid stress relief and relaxation from the convenience of your phone, at any time and in any location,which is one of the reasons for the spike of the trend.
Oddly Satisfying Cutting Trending Viral Content
A lot of people on Instagram have watched videos of soap or vegetable cutting, slime crunching, or frozen paint smashing. They are part of a social media craze that has gone viral.
Oddly Satisfying was designated the fastest-growing Instagram specialty in 2018 by Instagram. Slime, according to Google, was the most popular DIY fad of 2017, resulting in a nationwide glue scarcity in the United States. Every minute, at least one video with the hashtag #OddlySatisfying is posted on Instagram, and Google searches for these films have increased dramatically in recent years.
(Paul Bryan TV, 2016)
Brands are banking on these trendy videos, as they feel satisfying videos resonate with the viewer’s emotional position and gives one of a kind relaxing experience to their audience which is long-lasting. Oddly Satisfying content when reaching wide audience, can be enriched by endorsements and branded content, that allow creators monetise on it, without changing the main purpose of the video - to be relaxing for the viewers.
Exaggeration of food/Puffery Advertising With Use of Viral Content Spreading
Exaggeration is one of the most prevalent strategies used by advertising agencies to market a product on social media nowadays. Now, it can't just be a little exaggeration, because it could be mistaken for reality. No, it has to be a "full-on, out there" exaggeration. Also, known as “Puffery advertising”.
Restaurant menu items rarely, if ever, resemble those in professionally set and retouched images. In digital advertising, exaggeration of food is all about exaggerating and stretching the truth about a product or service in a harmless way. The bigger issue arises when brands actively misrepresent their products or establishments on the internet.
The pursuit for virality and algorithm favorability often leads to exceed the boarders and leads to miscommunication in endorsements.
Red Bull, were found guilty of misleading advertising in a $13 million lawsuit in 2014. The corporation claimed that their product increased users' concentration and reaction times, which the brand dismissed as "false advertising." Courts, on the other hand, disagreed, stating that those statements could not be scientifically demonstrated to be true, even if they were accurate in certain consumers for a limited length of time. Red Bull made the classic puffery advertising error of being too precise. The commercial transitioned from subjective to objective by making specific statements about the benefits their product could provide.
Original Sounds/ Music Usage
Another phenomenon that is being observed among SNSs led by suggestion algorithms (especially TikTok) is spreading original music/ sounds by the use of hashtags.
Brands create a music/ sound to encourage other users adapt their videos with the interpretation of sound while adding a hashtag, to eventually make videos searchable and easily recognizable by the AI. That way brands are able to create a community, at the same time go viral with their sound and hashtag achieving higher brand awareness and widespread brand exposition.
"Consumption and creation of videos on SNS nowadays is strongly led by what has a potential to go viral with the help of suggestion algorithms. Therefore, we will take a closer look on how brands and entrepreneurs has utilized an era of automatically spreading content in order to achieve marketing goals and shape current video consumption" (Naveen, 2018).
3.2. Trends Utilization and Outcomes of Viral Content Creation
An Example of Marketing With the Use of Viral Content Spreading in restaurants
Many restaurateurs and food related entrepreneurs take advantage from the fact that exaggeration of food is a topic that has a strong viral potential on social media.
By implementing current trends that AI based suggestion algorithms are favoring, they open their personal brands and businesses for the wide audience.
In past years, there have been multiple attempts to monetize on food exaggeration on social media, resulting in enormous growth of personal brands and recognizability of restaurants.
Nusret Gökçe can be treated as a good example of an entrepreneur that has understood the working principles of suggestion algorithms, and have been using them for marketing purposes.
This is how exaggeration of food content works, from AI perspective:
Klug, D., Qin, Y., Evans, M., & Kaufman, G. (2021). Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm. 13th ACM Web Science Conference 2021.
Nusret Gökçe
Nusret Gökçe has been effectively utilizing the fact that TikTok and Instagram’s suggesting AI favors entertainment and food exaggeration. By a specific way of salting meats, and covering food with gold videos, Nusret has become known by utilizing the algorithms.
Thanks to suggested algorithms, such an entrepreneur was able to open multiple restaurants around the world, serving meals presented on social media.
Why is this important?
Suggestion algorithm enabled this individual to reach large audiences to the extent that was not possible before AI implementation in SNS. By high connectivity and reaching wide audience Nusret’s way of preparing food is shaping restaurant trends around the world.
By constant creation of new trends containing videos, restaurants keep being occupied and create revenue. The persona of Nusret became a brand itself, and has opened a lot of other possibilities for monetizing on media presence like paid endorsements for others on social media.
Gucci
Gucci is one of the brands, that included an original sound on TikTok created by one of the users in order to promote their brand. The sound was explaining how to dress as a Gucci model.
The #GucciModelChallange was spread by AI and became popular which influenced other users to create their own interpretation of this hashtag using the original sound (Marine, 2020). Gucci’s official account sourced some of the TikToks that utilized the challenge and re-posted them to their own TikTok page.
What is more, Gucci has selected a few TikTok creators and offered to get them featured in their next campaign.
(Marine, 2020)
Why is this important?
Trends that are being spread on SNS with the help of AI are enabling brands to interact with their clients and enthusiasts, which shapes a new era of brand communities, that according to Hsu-Hsien Chi is more effective than advertising (Chi, 2011). Individuals are more empowered due to viral features of social media and the fact that creating content is being picked up by the algorithm they could be noticed and offered a job by Gucci in this case. “In the moments I am online I will be able to choose how I am seen and experienced.” (Pew Research Center, 2022, p. 56). Fashion brands like Gucci has the potential to reach a large audience that is attracted to the entertainment part of Social Media, not specifically fashion.
Chapter 4: The Future of AI and Connectivity
Uses of AI are way broader than those connected with suggestion algorithms in SNS. This market is in quickly growing age, therefore in the following slides there are some additional vivid use cases and future predictions concerning AI in general.
(Technavio, 2022)
Users’ connectivity and companies’ AI can play a key role in aiding companies predict what customers would purchase, so using AI can lead to substantial enhancements in predictive ability.
Depending on the levels of predictive accuracy, brands may even substantially change their business models, providing goods and services to customers regularly based on data and predictions about their needs. AI is expected to also take an important role in forecasting not only what clients wish to purchase, yet also what price to charge, and whether special offers should be presented - since price and price promotions are dominant drivers of sales and brands’ marketing strategies.
Recommender Systems for Business With Regards to AI and
Connectivity
Brands are using the technology of machine learning, and deep learning specifically to get to understand a vast number of clients solely online simply via their entered data. By using a data model to filter through users' favorite products and behaviours, it is easier than ever to make recommendations of what they would enjoy to benefit from the most or purchase.
Types of Recommender Systems
- Memory Based Approaches (as mentioned earlier)
- User User
- Item Item
- Content-Based Filtering Systems
- Collaborative Filtering Systems
- Demographic-Based Systems
- Hybrid System
Recommender systems help businesses improve customer loyalty, efficiently analyze the market, increase sales, and enhance the overall user experience.
Filter Bubbles Phenomenon: Negative Impact of Suggestion Algorithms
Among all the possibilities that recommender systems give us, there are some downsides of popularization of them. One of them being a phenomenon called Filter Bubbles when discussing SNS.
Due to the fact that the recommender system tries to suggest the closest possible content to the previous liked ones, it is possible that content that is being presented to an SNS user is just another version of the thing that he/she has already watched. “Users could be trapped in a self-reinforcing cycle of opinion, never being pushed to discover alternative genres or viewpoints” (Zhang et al., 2012, p. 1).
This is a vivid thread, while looking in the future of AI. Closing societies in their own bubble of information and entertainment content zone can lead to narrowing perspectives of a society.
(Weinbrecht, 2021)
The impact of AI and Connectivity on The Future of Industries
Transportation industry:
The existence of driverless, connected, and AI-enabled cars may be sooner than we thought, impacting the alteration of both business models and customer behavior. For example, driverless vehicles could impact the attractiveness of real estate in terms of the following:
Driverless cars can move at faster speeds, and so commute times will reduce.
Commute times will be more productive for passengers, who can safely work while being driven to their destination.
Online Retailing Industry:
With AI and Connectivity, online fashion retailers may be able to predict what clients would need; assuming that these predictions achieve high accuracy, retailers might transition to a shipping-then-shopping business model.
Fashion brands might use AI to identify customers’ preferences and deliver pieces to their doorsteps without an official online purchase, with customers having the option to return what they do not need.
This might revolutionize retailers’ marketing strategies, business models, and customer behaviors. Businesses like Birchbox, Stitch Fix and Trendy Butler already use AI to try to predict what their customers want, with varying levels of success.
Although such global trends are argued to push some jobs out of the market, yet research shows the emergence of new ones created by AI and Connectivity
TRAINERS
Customer-language tone and meaning trainer:
Teaches AI systems to look beyond the literal meaning of a communication. For example, detecting sarcasm.
Smart-machine interaction modeler:
Models machine behavior after employee behavior so that, for example, an AI system can learn from an accountant’s actions how to automatically match payments to invoices.
Worldview trainer:
Trains AI systems to develop a global perspective so that various cultural perspectives are considered when determining, for example, whether an algorithm is “fair”.
EXPLAINERS
Context designer:
Designs smart decisions based on business context, process task, and individual, professional, and cultural factors.
Transparency analyst:
Classifies the different types of opacity (and corresponding effects on the business) of the AI algorithms used and maintains an inventory of that information.
AI usefulness strategist:
Determines whether to deploy AI (versus traditional rules engines and scripts) for specific applications.
SUSTAINERS
Automation ethicist:
Evaluates the non-economic impact of smart machines, both the upside and downside.
Automation economist:
Evaluates the cost of poor machine performance.
Machine relations manager:
“Promotes” algorithms that perform well to greater scale in the business and “demotes” algorithms with poor performance.
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Titel der Vorlesung
Mishra, A. M. (2021). Role of Artificial Intelligence in Social Media Marketing. International Journal of Business Analytics and Intelligence, 9(1 & 2), 34–40. http://publishingindia.com/ijbai/
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Authors
Daniel Frah
Mani Raj Rathore
Maksymilian Czyżykowski
© Macromedia University of Applied Sciences. All rights reserved.
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