Marketing digest: Calibrating the influence of user-generated content

Social media is transforming how customers interact with companies globally, where user-generated content is having a massive influence on what we buy. But how people engage with brands and make decisions via the creator economy is not fully understood, new research hopes to address this issue.

Globally the creator economy is expected to be worth US$ 500 billion by 2027, with over 50 million creators worldwide.¹ These online influencers are reshaping modern marketing and how brands build loyalty. The audience is vast and growing, with billions of users and influencers on TikTok, YouTube, WeChat and Facebook across the world.² It’s crucial for marketeers to understand this medium.

“What’s interesting about user-generated content is that businesses don’t have much control over it. They can motivate people to post, but they don’t have much influence on whether it’s positive or negative, or if the right brand image is conveyed. It’s also difficult to measure impact,” explains Melanie Clegg, Assistant Professor of Marketing at HEC Lausanne.

The assistant professor and other researchers have found that there is a lot of research on the pre-purchase stage for products, but there is less understanding of how customers engage with brands while they are purchasing, or after they’ve bought an item.³

“This is because it is harder to determine the influence of user-generated content (UGC) on actual purchases and post-purchase loyalty. It is also relatively easy to acquire engagement data, such as clicks and likes, on a post, but it is harder to attribute actual purchases to a specific type of content,” she states.

Her research concludes that businesses should encourage UGC generation from customers who have recently made a purchase, in order to boost engagement. Companies could also monitor purchasers and develop response strategies, particularly for addressing negative content once purchases have been made and reviewed.³

“Another issue is that there is limited research on UGC that contains video. This is because videos are more complex to analyse than text. There is audio, moving images and the data is richer. This is why we have developed a video analytics tool in order to evaluate how engaging content really is,” states Clegg.

After the analysis of over 57,000 TikTok videos, researchers found that atypical videos, which includes those that follow a trend, but adds deviations and modifications, received more engagement than those that did not. Their video analytics tool was used to make this assessment. This research advances our understanding of what makes trend-following content successful.⁴

The next frontier that Assistant Professor Clegg is researching involves artificial intelligence and generative AI, so-called gen-AI, since it has the potential to produce its own content at very low costs. This has implications for real-life content creators.

“Gen-AI could impact the sector. But if businesses decide to only rely on generative-AI only in order to produce content. Then it could end up being generic and look similar to existing videos. This could become a competitive disadvantage because we know that unique content is what stands out and influences people,” details Clegg.

She concludes: “it is also worth considering how AI influences creators. Tiktok has a centre where creatives work together with a Gen AI assistant. They are given tips on how to create content. The question is how far will people be guided by AI affecting peoples’ creativity? How can gen-AI be calibrated so it helps generate unique content, not hinder it? This is a big question.”

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