melis.ai

Maybelline New York · product discovery

A better way to find your foundation shade.

A guided product experience in Facebook Messenger, designed to help customers choose a Fit Me foundation with more confidence.

Launched / past client project

Delivered as bot•hello, now called melis.ai.

Sean’s role
Leading conversation design and writing with the brand team and project partners.
What we built
A personalised Fit Me product journey in Facebook Messenger.
Client-reported result
18,000+ users · 96% completionFigures shared by Maybelline’s marketing leader in a written recommendation.

The Maybelline experience

Product guidance, inside Messenger.

Four original phone mock-ups from the Canva lookbook showing Maybelline’s earlier eyebrow-product campaign: questions, product preferences, recommendations and sharing.
Earlier Maybelline eyebrow campaign, from the 2022 lookbook. The Fit Me foundation project is described below.

The challenge

Choosing foundation online means judging shade, skin type and finish without a beauty advisor beside you. Maybelline wanted to make that decision easier through a conversation in Facebook Messenger.

What we did

We designed the conversation and wrote its responses with the brand team and delivery partners. Research into Maybelline’s social channels informed the language and personality. Sean joined testing at L’Oréal’s Melbourne office, helping the team refine questions that caused hesitation.

How it works

Within Facebook Messenger, the conversation explored each customer’s foundation use, skin type, tone and preferred finish. Earlier answers shaped the next question, leading towards a Fit Me recommendation without making everyone follow the same path.

The results

Maybelline’s marketing leader reported more than 18,000 users and 96% completion. The relationship led to introductions across the L’Oréal group, including Lancôme, Kiehl’s, SkinCeuticals and CeraVe.

What we learned

Relevant questions and a recognisable brand voice helped make the experience coherent. Observing customers use it showed where the conversation needed refinement.

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