The world has truly gone Emoji mad. (And, for the record, I’m one of the maddest!) With recent announcements that Twitter can now target you by Emoji use and Apple’s ability to auto-replace words with Emoji in iOS 10, will we reach the tipping point and lose words altogether to create content and engaging conversations?
Emojis have inspired fashion, influenced politics, chosen contest winners and can have a pizza delivered to your front door. How did we get to this Emoji-centric world? New technology yields new case studies. As Emoji accessibility scaled up, so did the Emoji content by marketers.
Brands & Emojis
You may have read that Kim Kardashian has bespoke Emojis for your downloading pleasure. Yes, it’s true. The many iconic moments from Keeping Up with the Kardashians forever emblazoned in our minds are now in Kimoji form. She is just one of the latest brands going Emoji.
There’s a literal cost of entry into the branded Emoji game. Twitter is rumored to charge upwards of one million dollars for brands to have official Emojis. Without any additional action by the user, Emojis appear in tweets when using a branded hashtag. You’ll see a lot of this during television events, sometimes with the Emoji creative updating in step with each episode.
For this year’s All-Star Game, the NBA rolled out custom Twitter Emojis for all 24 players. Using those hashtags during the fourth quarter was the only way for fans to vote for the Game’s MVP. It was not only an awareness play, but a fan utility.
In 2015, Chevy launched a campaign called #ChevyGoesEmoji. Their official press release was written entirely in Emoji. No words. They extended this further by creating Emoji-driven content whereby unhip adults were schooled by influencers at an “Emoji Academy.”
Even the Pope has his own Popemoji. (They’re infallible.)
So…what’s next? More Emojis! And who determines these updates? The UTC.
The Notorious UTC
Only the Unicode Technical Committee (UTC) determines new Emojis.
The Unicode Emoji Subcommittee “takes input from various sources and reviews requests for new Emoji characters.” Facebook, Adobe, Yahoo and Apple are just a few of the voting members of the UTC. This year new Emojis were green-lit for Unicode 9.0, but then we play hurry-up-and-wait for it to hit our devices’ keyboards in 2017. (If you, dear reader, are looking to live the Emoji dream, individuals can apply for membership at unicode.org, but you can’t vote.
Now, how can we as content creators authentically deliver with Emoji?
Hillary Clinton, famously wanted to connect with Millennials about their student loan situation via Emojis. She has over seven million followers on Twitter. It may have backfired (the student loan struggle is far too real for mere symbols to articulate), but she quickly learned from this exercise and reacted accordingly. Biggest lesson? Authenticity is key if you’re going to play in the Emoji content sandbox.
The most recent iteration of the Always “Like A Girl” campaign asserts the need for Emoji diversity for young women. My aggravation is that Generations Y & Z will always find ways to communicate what they want to be heard. They don’t need the UTC to take a year or two to answer the call. They’ll string a series of symbols together to get their sentiment across until the technology can catch up with society. But how can technology speed that process up? Is the answer data?
In February, Facebook pushed out Emojis called “Reactions,” an extension of the Like button. For over a year, the social network “conducted global research, including focus groups and surveys, to determine what types of reactions people would want to use most.” They landed on Love, Haha, Wow, Sad and Angry. Now, there’s a lot of evidence that people aren’t even using these, which may just be a user experience issue, IMHO, but Facebook “sees this as an opportunity for businesses and publishers to better understand how people are responding to their content.”
Still, think of how powerful that data could be in terms of targeting the right audience with the right content. Learning how we all react to content in a much more granular way than Like. It could inform what content creators make in 2016 and beyond.