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11.9 hours. That is how long it takes for the internet to hyperfixate on the next trending topic.

In Stolen Focus, Johann Hari introduces a concept called collective attention. Defined by how long a large group of people can remain interested in the same thing. In 2016, a hashtag spent an average of 11.9 hours in Twitter’s global top 50. Hashtags may be less prevalent than they were in 2016, but this concept still applies to media cycles today. Whether it is a viral TikTok video, a brand campaign or even an Instagram story, media circulates at a rapid rate.

For brands trying to participate in those conversations, 11.9 is an especially small window. A trend could emerge in the morning, get talked about during lunch and be old news by bedtime. 

Also, for brands, remaining culturally relevant is more important than ever. If you go into the TikTok comments on any viral video, you will most likely see a thread of blue checkmarks from new brands to legacy brands, all trying to gain likes, reposts and shares by interacting with the video. 

But there is another side to real-time marketing. Brands have to move at the speed of the internet and most approval processes simply do not.

There is a lot happening behind a single TikTok comment you wouldn’t necessarily think about, and by the time an idea is written, reviewed by legal, gone through revision rounds and approved, the conversation may have already moved on and that video’s engagement may already be declining.

This creates an interesting tension. Moving quickly can make a brand feel culturally aware, but moving quickly can also lead to missteps as well as feeling forced, especially to an audience that automatically screens for authenticity. Not every trending conversation needs a brand response, especially when the race to participate can lead to an overload. But consistently missing the moment could cost the brand its voice, especially when so much of today’s social content revolves around timing. So, maybe the challenge isn’t figuring out how to make an approval process fit inside a 11.9 hour window, but rather learning to recognize which 11.9 hour windows are actually worth it.