iliza: the personal fashion assistant

by post_author

Findings from Challenge 6:

In Challenge 6, we designed a survey to discover the fashion habits of millennials. The goal of the survey was to test whether a personal dressing app would be well-received. We asked participants about their process in picking out outfits; how long it took them to select outfits, how much they enjoyed choosing outfits, and what occasions they have most difficulty dressing for. Additionally, we gathered data on individual’s shopping habits, their laundry habits, their familiarity with personal shopping apps, and sought open-ended feedback about what an ideal app would look like.

The findings of the survey were incredibly useful in designing our app. We discovered that individuals moderately enjoy the process of picking out outfits as well as the activity of shopping. However, almost everyone thought that they spent too much time selecting their outfits, and often had difficulty selecting outfits for work or nights out with friends. While people generally didn’t want an app that simply told them what outfit to wear each day, through the open-ended feedback we found that many wanted suggestions for outfits as well as recommendations on potential items to purchase that would complement their wardrobe. Further validating the idea that individuals want some help selecting their outfits, just last week Amazon announced it will be offering outfit advice to their Prime members.

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In our prototype, we will walk you through a quick user journey for Angela. Angela is a busy young professional in her mid-20’s living in New York. When Angela downloads the app, she will be asked to give us an overview of her wardrobe (survey participants indicated high levels of willingness to share their wardrobe).

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Angela can either upload pictures or she can select pictures in the app that look like her own items. This initial phase is necessary so that the app can learn about Angela’s wardrobe and her style, and personalize all outfit and shopping recommendations.

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When Angela opens the app on Tuesday morning, she will see a maximum of 3 options for outfits to wear to work. Angela will be able to swipe through them and select the one that she likes the most. These suggestions will be tailored to Angela’s style (taken/learned from her existing clothes), and will also take into consideration Angela’s schedule that day. Today is a casual work day and she has no client meetings.

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The other main feature of the app revolves around shopping. Many survey respondents indicated that they need help keeping up with new fashion trends, and would love for the app to suggest “cute pieces”. Because the app knows Angela’s style, her wardrobe, and what pieces she actually wears, the app will be uniquely positioned to help her find pieces of clothing within her price range that would also go well with what she already owns. When most people shop, they often fail to consider how the new purchase goes with what they already have, leading to unnecessary purchases. This feature of the app will address this issue.

Link to InVision

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