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A new user-centered kind of fashion

MA 2023
Artificial-Intelligence, Fashion, Cultural-Identity, Personalisation, Sustainability, Machine-Learning

Drip is a behaviour-changing service that enables more sustainable choices in fashion, developing people’s identity and supporting smaller, ethically focused fashion brands.

The team developed an alternative journey from current overconsumption and related environmental and personal financial consequences.

The use of smart image recognition, computer vision, and AI technology helps inspire, discover, and curate personalised fashion choices and is driven by a carefully targeted, designed, and intuitive system.


Throughout this project, we worked closely with fashion subject matter experts to guide our research and test and validate design propositions. We would like to thank our supporters for their time and valuable contributions: Orsola de Castro (Fashion Revolution), Julie Bornstein (Pinterest, Nordstrum, StichFix), Celine Chammas (Chanel, HBS) Zowie Broach (Fashion RCA), Savithri Bartlett (Fashion RCA), Harris Elliot (Harris Elliot Studio), Margarita Otaola Valdes (AllSaints, Harvey Nicholls), Robyn Smith (Edited)

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Challenging Norms


Less made, better made

Less consumed, better consumer

Through applying Service design to the fashion industry this project aimed to challenge the damaging status quo of fashion consumption and create new outlets for enjoying fashion. Our aim was to tackle three core problems:

  1. Disposable culture, convenience, and the lack of adoption of circular fashion.
  2. Decreased confidence among wearers and makers in creating clothes that last
  3. The underutilisation of fashion clothing.

To counter these problems DRIP exists to:

  1. Create new modes of consumption away from wear, dispose of and re-buy
  2. Increase consumer and maker confidence in investing in a fashion that lasts
  3. Nurture acceptance around re-wearing and maximising clothes' utility.


To shift the consumption norms we went in-depth into consumer behaviours and desires (say, do gap) and their relation to the fashion industries' modes of production and consumption - in order to find a specific solution to overcome a specific challenge.

Changing Behaviour


Through extensive research into consumer psychology and fashion consumption (including primary user research methods such as surveys, shopping shadowing, online blogs, and in-depth interviews - both structured and unstructured) we developed 4 behavioural archetypes with regard to users’ relationship to their clothing and shopping.

Like a coming-of-age movie, people evolve from freestylers in their teens to chameleons or expressionists in their 20s and eventually become orchestrators in their 30s and beyond. Changes tended to result from the trial and error of fashion products, life events - such as moving country, and/or societal demands (work, culture, religion). Real-life journeys though are much more complex, and we observe fluid interchangeability among archetypal behaviours, influenced further by day-to-day shifting factors such as mood, weather, or occasions. Ultimately, a fluid approach to designing a service was necessary to design in a complex network of choice reasoning.


Using our Archetypes we created 4 personas for each - focusing our behavioural archetypes on our target user group - young adults, fashion literate and trend-forward, that live in London or adjacent and consume fashion content and media on a daily basis

Debbie - She lives in Brighton as a student, Debbie is currently seeking out her unique style through TikTok and her friends.

PAT - whose casual work attire means a need for flexibility, choice, and change but their limited apartment space means clever interchange styling of clothes is essential

Michelle - the most assured of our users, as a time-short marketing manager needs a service that's quick and efficient in giving them that cool factor without the stress of finding it and knowing that it's ethically sourced.

Chris - moved to London to pursue a freelance creative career. Fashion is a part of their community and gives them a sense of belonging and identity. Furthermore, they use fashion as part of their job and feel the need to remain on top of trends.

The mission of DRIP is to foster a community of forward-thinking early adopters in fashion. Together, we promote confidence, and clarity in fashion choices while uplifting small community-based brands that challenge the fashion industry's norms.

Designing A Better Future

DRIP is like Spotify for fashion, offering a freemium service that empowers users to discover, curate, and manage their fashion style and identity. Fuelled by curatorial integrity and a personalised AI engine, in its simplest form users can search for fashion items and create playlists in our mobile or web app.

DRIP also helps fashion brands find potential customers organically online with a system where the customers come to them. No longer will brands struggle for exposure online or spend fortunes on marketing, with DRIP’s curated edits and personalisation, the customers find their products, style them together and purchase or rent with confidence.


IF: We can increase the time spent by fashion consumers building self-confidence and experimenting pre-purchase, through digitally discovering, curating, and managing their style, identity, and clothing

AND: enable consumers to find and support small community-based brands

THEN: All stakeholders will be empowered to make more informed and responsible choices

AND: therefore consume, produce less, and contribute to a more sustainable future for the fashion industry.


To deliver the theory of change we created a refined list of features, that through testing formed our MVP


Home feed - a feed of curated and recommended racks based on your usage data and preferences

Style quiz - An onboarding quiz to figure out your style DNA is a gamified Tinder-esque fashion whereby you like and dislike fashion items. Analysed by machine learning, this helps better-fit products to your needs, values, and preferences.


Product search - Search for fashion products in two ways - one through a keyword search or two via a visual search where you can take an image of a product and find a match

Racks - Playlist-like dashboards to curate items together. Opinions include a generic rack, wishlist or wardrobe, and private and public access. Racks include a built-in custom field to enable auto-fill of playlists based on your data and your desired attribute such as a mood, item type, style, or colours. 

Product pages - Interactive product pages that enable you to tag and sort items into various racks, wishlists, or wardrobes. You can also click through to find the product purchase page on the brand's e-commerce website.


Your wardrobe - update, edit and sort your existing wardrobe items in custom templated racks for organising your closet around attributes from mood to the day of the week.

Size profiling - input accurate sizing through AI body image analysis to create a digital profile of your physique. Cross-reference this with preferences to get accurate sizing recommendations across products in DRIP.

Preference setting - Customise your entire DRIP experience by setting detailed preferences, from environmental values, to cost and style preferences.


DRIP is shaping a new fashion future. Doing away with fashion retail's ever-changing seasons and stock churn and encouraging iconic products, season-less collections, and sustainable business models - from made-to-order to second-hand and rental. With DRIP we hope to design a podium that ushers in systemic change.


Throughout the design process, we benchmarked features against best practices and unused emerging technology to push the boundaries of innovation. In order to bring value to users we tested out our features based on their importance to users then using the Kano model we prioritised what needs to be done first. During all testing, we offered a space for participants to brainstorm ideas and co-design as a source of further inspiration.

Bringing It To Life


DRIP utilises a matchmaking business model, connecting fashion early adopters with verified independent fashion brands. Like Selfridges or Dover Street Market, we offer a curated selection of fashion products and in-depth fashion storytelling to create a unique experience for our users - online.


As a Niche market offering DRIP leverages its distinctive user segment and its refined ethical assortment of brands & partners to remain viable in the highly competitive market of fashion e-commerce, media, and styling.

The 1.2 trillion dollar opportunity. DRIP brings to the e-commerce market its new-age, non-e-commerce design system, made-for-you AI, tribalistic curation, and anti-fashion mainstream rhetoric

DRIP also competes in the emerging digital styling market, offering a unique all-in-one service that focuses on long-term wardrobe digitisation, customisation, and adjustability.


DRIP customers: 

Early adopter fashion consumers

DRIP delivers its digital one-stop shop for free. And in return receives valuable engagement, activity data, and monetisation.

SME community-driven fashion brands 

DRIP serves as a stepping stone for brands to enter or scale their digital commercial presence. DRIP selectively works with brands that align with DRIP's values and meet the right pricing and size criteria. DRIP delivers brand customers and greater search engine positioning.

DRIP partners:

Indie fashion media outlets

DRIP collaborates with various media outlets, spanning from small independent zines to influential publications. These outlets produce progressive fashion content that promotes responsible consumption in the DRIP service.

Micro fashion social media influencers

DRIP also collaborates with progressive influencers who act as catalysts for change on the DRIP platform, generating content that fosters shared knowledge and empowerment.


If you are someone who loves the idea, a professional interested in developing the concept, a small fashion brand, a fashion influencer, or a cultural media outlet, reach out to Angus Bamford, Sara Alhajri, or Zoe Xiong to hear more about DRIP!


We would like to share a special thanks to the RCA tutors who helped guide the project across the 6 months of engagement: Nicollas Rebolledo Bustamante, Emily Boxall, David Eveleigh-Evans, Jonny Jiang & Judah Armani.

We would also like to thank our family and friends who supported us throughout the journey of working on this project.

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