Title | STYLE SCANNER |
Brand | EE |
Product/Service | EE |
Category |
A09. Use of Advanced Learning Technologies |
Entrant
|
POKE London, UNITED KINGDOM
|
Idea Creation
|
POKE London, UNITED KINGDOM
|
PR
|
M&C SAATCHI PR London, UNITED KINGDOM
|
Production
|
SNAP TECHNOLOGY London, UNITED KINGDOM
|
Additional Company
|
HAVAS LONDON, UNITED KINGDOM
|
Credits
Angus MacKinnon |
POKE |
Group Creative Director |
Jamie Ingram |
POKE |
Technical Director |
Tim Fletcher |
POKE |
Account Director |
Alvaro Ojeda |
POKE |
Strategist |
Rachel Adelson |
POKE |
Senior Producer |
Warren Lewis |
POKE |
Senior Creative |
James Laurel |
POKE |
Designer |
Yohan Lebret |
POKE |
Developer |
Background
EE sponsor the BAFTA ceremony every year. With the acute draw on attention that A-list celebrity brings, the brand has a moment to shine, providing they can capture people’s imagination with a novel twist on the standard ceremony fare. And even if they grab more than their fair share of attention, how do they make the spectacle ladder up to something the brand wants to be known for- the superior speed of their network?
Describe the creative idea
BAFTA Style scanner turns red carpet couture into affordable fashion in the swipe of a thumb.
It worked like this… We shot celebrities on the red carpet using our rig and cameras in the press pit. Those images were quickly formatted into mini fashion story spreads, pulling out interesting details as well as the full length shot. Simultaneously, a technology search compiled a list page of related garments across thousands of ecommerce sites. This match list was then published as a page and linked to from that celebrity story. A lot of tech behind the scenes, but for the user a compelling, intuitive journey delivered straight to their Instagram feed from our influencers Lydia Bright and Markus Butler.
Describe the strategy
We researched the chatter around gala’s like the Oscars and BAFTA’s and to no-one’s surprise discovered that fashion was the main topic of conversation. Celebrities of course exploit this interest and natural connection point with fans and media, as the right outfit pumps their presence. Following this journey to the end however, we discovered a weak spot. With many celebrity outfits being supplied by couture houses, these coveted garments are completely out of reach for most people, so the engagement comes to an abrupt and dissatisfying end.
But what if we could find affordable fashion, similar to that being paraded on the red carpet? And what if we could search high and low and return within that fleeting moment when we could rely on the user’s excitement and attention?
We’d just need some pretty impressive tech to pull this all off…
Describe the execution
EE Style Scanner was a campaign built exclusively for Instagram. It used linkable stories to match celebrity fashion images, straight from the red carpet to affordable garments gathered from across the web. The stories went out on fashion influencer Lydia Bright and Marcus Butler’s channels. So a pure-play social campaign with novel utility.
We integrated with a technology that uses machine learning to constantly analyse and index items across a huge volume of ecommerce sites. The technology hunts for matches and associations between designs, colours and styles, whilst also monitoring live price and availability to avoid disappointing purchase journeys. We plumbed this into a front-end page, optimised for mobile display, so each specific celebrity garment posted on stories, would link to a specific search return landing page, listing all the related garments instantly.
List the results
Our influencers stories got viewed by over 3.7 million people with a whopping 25,000 swiping up to check out the styles and make a purchase. The EE network message reached over 600,000 and more than 250 media articles devoted to our stunt were published in the UK. Our launch partnership with celebrity Rochelle Humes and the video introducing the Style Scanner was also picked up by Daily Mail and Daily Online. Overall the project generated over 300k in earned media value.