Our social media platforms are a great way for us to educate and connect with our audience. However, with an audience of over 10 million across our social platforms,it can be difficult to educate our users on an personalized case by case basis. Makeup and beauty are highly tailored to the individual as everyone has different skin tones, skin types, and concerns. Our audience has widely expressed wanting to try out our best-setlling Fenty Beauty PRO FILT'R Foundations but not knowing where to start for shopping their shade.
We posed this problem that we wanted to tackle— how do we help give personalized recommendations by foundation shade and educate users in an accessible way that feels true to our brand?
We decided that using a Facebook Messenger chat bot would be the best platform to help provide a personalized educational experience to our audience as it is instant, robust, personalized, and accessible across any device.
We found that most branded Facebook Messenger bots are used for customer service (tracking orders, answering customer's inquiries, etc.). We wanted to do something unique by creating a robust tool for personalized product suggestions tailored to every individual user.
We were faced with the challenge of creating a well-rounded education tool which included 1) a shade finder tool to help users find their Fenty Beauty PRO FILT'R Foundation shade plus personalized product recommendations and 2) the ability to learn about our full product catalog.
1) To help our audience get personalized product recommendations, we decided to create a Shade Finder quiz with our Facebook Messenger bot to help users find their Fenty Beauty PRO FILT'R Foundation shade. With 50 different shades of foundation that we offer with a wide range of depth, shades, and undertones, we knew that the Shade Finder quiz would have to be extremely robust and complex. Foundation shopping is distinct due to unique undertones and shade depths that vary per person. We utilized model photography to show our shade range, having users select which shade range they thought they most closely resembled to get them in the right shade range bucket. From there, our users would select their undertone from "cool", "neutral", "warm", and "warm golden". To further incorporate education into our Shade Finder quiz, we integrated an undertone finder quiz within the tool for users who are not sure what their undertone is. Once users inputted their shade range and undertone information, we would show a few PRO FILT'R Foundation shades that we believe would fit them best based on their answers.
2) In addition to the shade finder quiz, we incorporated further product and brand education tools. From the shade finder quiz, users can continue to learn about every step of the "Fenty Face" makeup routine and get personalized recommendations based on the results of their Shade Finder quiz. We suggested complementary shades of our PRO FILT'R Concealer and PRO FILT'R Setting Powder based on their PRO FILT'R Foundation shade number. Users were also able to select and expand other product categories such as highlighters, lip, and eye categories to learn more about Fenty Beauty products. We also linked to our YouTube channel where users could further learn about application tips and tutorials.
Once we finished creating our Fenty Beauty Facebook Messenger Bot, the next step was creating awareness about the tool. We shared videos of our Facebook Messenger Shade Finder quiz functionality in action across our social platforms including Instagram, Instagram Stories, Twitter, and Facebook encouraging users to use the Messenger bot find their Fenty Beauty Foundation shade and share their results.
We launched our Fenty Beauty Facebook Messenger chat bot, and posted about its launch across social. Our social posts promoting our Messenger bot have received over 5000 comments/replies of users sharing screenshots of the results from their Shade Finder quiz.
Users love how easy the Shade Finder is to use and how educational it is:
Accuracy of the recommendations is important, and we found that users trusted their results with users who already knew their shade taking the quiz and getting accurate results as well:
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