MIRA BEAUTY is the world's first universal store and collaborative library for makeup and skincare. It's made up of over 100,000 products and counting-- that can be sorted and compared based on what you look like and what you're looking for.
At MIRA BEAUTY, I had the opportunity to grow our community from a small group of 12 beta users to 50k MAU. Our community was not just a place to chat about beauty, it was a place of learning and information exchange. Mira's community played a crucial part of our product and search ecology.
This is a high level walkthrough that strives to capture the major stages of growth within Mira’s community over the span of 2-3 years. In this brief we’ll cover:
To see an example of a project that takes a closer look at my design process, check out my Low-Intent Community Exploration design sprint here.
Prototyping & Testing
I was employee #1 and first designer at MIRA BEAUTY. During my term, my role focused on the overall community building efforts. I led most design initiatives for the community and grew the product from a data-driven search tool to a holistic beauty community and platform.
At first, Mira was a search engine for beauty products. We quickly realized community engagement is a necessary part of Mira because product hunting happens across multiple touchpoints and beauty research at its core, is a highly social activity.
To better evaluate Mira’s community and product ecology, we created journey maps that follow beauty users' experience from product exploration to purchase and beyond.
We first started by listening and learning about our community with two How Might We questions:
We started with a co-creation session with 16 participants. In this session, we guided our participants through different sacrificial concepts that illustrated different online and offline community concepts (i.e. guided shopping, quizzes, AMA Q&A sessions, etc.) and topics of conversation.
From our discussion, we generated five topic areas to organize the community around, which were Beauty Advice, Best of the Best(products), Beauty&identity, Looks, and Beauty Deals). In my first design iteration, I made each topic a "group" within the app where people could join to talk about the assigned topic.
In our pilot, the most active conversation channel by far is Beauty Advice where people talked and asked about products, their skin, how products interact with skin. Of 200+ posts generated by our early users, over 70% of them were posted in Beauty Advice.
The most engaged posts were ones that were product focused and problem driven. This provided validation for our design research and we started to focus on making it super easy for people to share, find and answer questions.
In reality, there was no special functionality or algorithm that surfaced personalized posts. These questions were just the most recent posts--nothing changed on the back-end-- but engagement skyrocketed!
We knew that people responded well to personalization and this quickly became a grounding mechanism in Mira's mobile app experience.
At the same time, another seemingly insignificant change that let to big gains was product tagging in comments and posts. Initially we used icons like "@" above the keyboard to tag products, brands, or users. However when we eperimented with a large dedicated product tagging button, we saw a significant increase in product tagging. This not only helped the poster and commenter reference products more easily, it also changed the way clickers/lurkers interacted with product pages and posts. Through features like QFY we realized how powerful and consequential microinteractions can be.
People in high intent mode who asked product focused, problem driven questions actively engaged people who were in low-intent mode.
There was a significant group of community members in high intent mode looking for answers and a similar cohort of people looking to give answers. This not only created a true value exchange but also crystallized our value proposition.
It should be blatantly clear on every page what we want the users to do. There should be no question as to what the most important jobs are on a page.
After the success of QFY, Mira was able to help community members address each others' problems in high intent mode by prompting people to ask problem-driven, product-specific questions and creating affordances that allowed them to further explore Mira’s data catalogue.
Mira lacked the proper mechanics to provide seamless exploration between the product catalogue and community space. There were many “dead ends” in Mira’s flows. We called this "branch-like" exploration. There was no trace of community content within our product catalogues and barely any traces of product pages within our community space. Most posts funnel under “Beauty advice” making topics obsolete as a personalization tool (an important aspect of surfacing the most relevant questions and answers). An opportunity here would be to link all of our product content and UGC content in a way that felt more "web-like" - in a graph-like structure similar to that of Pinterest.
As we found from QFY about personalization, community members expressed how comfortable they felt posting and answering questions because they didn't have to be "credible" or "influential" to add value, they just had to relate to the question asker in some way through shared traits or experiences. This was a core community value that was foundational for question asking and answering (QFY) on Mira. There is an opportunity to connect people more intimately by bringing forward similar traits, interests or experiences by surfacing questions or conversations where they can actionably contribute.
In a big A-ha! Moment, we realized that people are essentially looking for the same thing whether they were query searching or asking questions to the community. Engaging with the community can be thought of as the "multiplayer" mode where you ask more open ended questions, receive follow up feedback, and collect personalized and anecdotal data. Query searching is then the "single player" mode where one might receive many more results and collect more quantitative data.
Either way, the user is looking for more context. What started as a design exploration led to production as we merged the two verticals (community + search) together by rolling out Topics-- thus tackling both opportunities in IA and personalization.
In the past, we only had nodes in Mira which were essentially just brand or product pages. To organize both our catalogue and discussions, we created Topic Pages, which were a set of 30 topical tags that were used to organize and further enhance some of our existing taxonomy (i.e. brands and skin attributes). Topics ranged from skin type (oily, dry, etc.), skin concerns (large pores, eczema, rosacea, etc.) to subcategories(foundation, serums, etc) to attributes (drugstore, cruelty-free, etc).
Topic tags allowed UGC content to self-organize in unstructured spaces. People are able to follow tags, find content that they are interested in, and create posts with topic tags so that it’s easily discovered by others who follow those tags. These tags became the backbone to our IA and our personalization features.
This allowed UGC content to surface in the right contexts no matter what you were searching whether it was for Maybelline foundation, eczema or date night makeup inspiration.
Along with topics being a primary method in cataloguing and repopulating content within Mira, each topic has its own page with its own content-- meaning you could explore Mira’s community AND search in a multitude of ways. This not only made Mira’s search and product browsing experience much more fluid and rich, it was also key to the success of Question for You.