The World’s most famous egg could well be more than just an Instagram stunt as marketers worldwide are holding their breath trying to figure out what comes next, as the egg started… hatching.
It started as a joke: how could an egg – a simple stock photography of an egg – could become the most liked post ever on Instagram? Yet, within a few days, the egg beat Kylie Jenner’s baby announcement and, yes, became the most liked ever post on Instagram.
Many were left wondering if this could have been the works of a brand. It seemed too good to be true. It seemed too good an opportunity to simply be a fun challenge someone’s clever brain had come up with. Well, as it happens, it could well be one of the most elaborate marketing stunt of the social media marketing era.
People of the Internet, hear this: the egg is hatching.
And no-one knows what is inside. We still don’t even know who is behind the egg.
So what will happen? What will come out of the egg? The account now counts nearly 10 million followers and generates record breaking engagement. And now every brand in the world wishes it had been involved. Nik Sharma, Head of DTV at Vayner Media, estimates that the brand which would come out of the egg could generate as much as $10 million worth of free media.
The account has now posted 4 new photos, all showing the hatching progress. The latest one might give us a clue…. the egg now looks like a football. Are we about to witness one of the best Super Bowl ad campaign ever?
Hulu is reported to be behind the media buy.
Fifth (and latest) post
Somehow, I am convinced we will find out tonight as the Super Bowl begins…. and we will likely be talking about this for a long long time.
So, what is your best guess? Who’s behind the egg?
UPDATE (in video)
More from Featured
Advertisers can now target Spotify listeners based on the type of podcasts they stream on its platform.
In an effort to make public post comments more meaningful, Facebook is updating the factors that determine how comments are …
Pinterest is working on a new scene-based complementary recommendation system that identifies the context in a scene, to make better recommendations.