How Instagram data will get you on the best dressed list
What does one wear to the Met Ball?
When celebs like Anne Hathaway and Naomi Watts get ready for major red carpet events like the Met Ball, there’s a lot of strategy that goes into nailing the right look. Is the starlet more DVF or Prada? Play it cool or go bold? All of this thought is warranted when you think of the millions of impressions that a star could rack up if she hits it out of the park and lands on several "Best Dressed" lists. Not to mention the embarrassment that ensues when one ends up on a “Worst Dressed” compilation. Stakes are so high in the age of social media, what if celebs and stylists let the data do the styling to optimize looks for the most positive engagement?
As I flipped through my Instagram feed last night, on the prowl for #MetBall coverage, I came across this photo of actress Liu Wen in a Zac Posen dress. Incidentally, a photo of that same dress was one of the most-liked posts on the @MBfashionweek feed during February’s #NYFW, when we managed the account.
By analyzing the contents of the Mercedes-Benz Fashion Week Instagram feed, we discovered that full gowns, in green and/or metallics, garnered many more likes than any other posts. That knowledge enabled us to tailor #MBFW’s social content and increase the number of likes-per-photo by 97%, from the first day to the last (according to data pulled from Keyhole and our proprietary tool, Daily Density).
How smart would it be for an actress to look at analytics like these during the dress decision process? No wonder Liu Wen made every best dressed list, including Refinery29, Glamour and Buzzfeed, to name a few. While the dress seems over the top and a risky choice, it's in fact an extremely safe bet; the fashion fans of Instagram had already given it a glowing review months ago. Big data is already being harnessed by advertising agencies, newsrooms and The White House. Perhaps fashion will be the next industry to bring data scientists on board.
Mae Karwowski is founder and CEO of Obviously Social. Follow her on Twitter: @maewow.