About LoveSeen
LoveSeen is a collection of cruelty-free fake lashes that recognizes that people of different ages, ethnicities, eye shapes and beauty aspirations can’t wear one-size-fits-all false lashes.
Challenge
In order to build long-lasting customer relationships, LoveSeen knew that first, they needed a way to better understand the people visiting their website in order to make informed, 1:1 product recommendations.
And once customers made a purchase, LoveSeen wanted to make certain their subsequent communications were not just personalized, but relevant.
Solution
To achieve their first objective, LoveSeen partnered with BlueConic (formerly Jebbit) to build a beautiful, ‘Find My Lash’ quiz.
Featured prominently on their website homepage, LoveSeen’s quiz asks users about their eye shape, the look they’re going for, their experience in using fake lashes, and where they’re wearing them. At the end of the quiz, users are asked to submit their first name, email, and phone number. But the real beauty is how transparent LoveSeen is about how they’ll use the data that users provide.
To make the most of the first-party data they collect from users taking the quiz... LoveSeen sends it directly into Attentive, an Experiences by Jebbit technology partner, to power hyper-relevant emails and SMS messages like lash tutorials, for example.
Results
LoveSeen has seen some seriously stunning results. 35% of visitors to the LoveSeen website interact with the quiz and 47% of users who interact, opt-in to receive ongoing marketing communications. But when it comes to opt-in's, here's the real story:
LoveSeen's 'Find My Lash' quiz is powering a 6X lift in their communications opt-in rate from users who take the quiz versus users who opt-in via LoveSeen's website subscriber pop-up!
Plus, their quiz is driving a 60% increase in online conversion rates from users who take the ‘Find My Lash’ quiz. And finally, LoveSeen is seeing a 100% lift in email open rates and click-through rates from the personalized communications they're sending to thoughtfully segmented groups in their database.
