From Blank Canvas to Sold Out: Designing a Direct-to-Consumer
Art Brand, 0 to 1
How designing every touchpoint of a new product — catalog, storefront, and go-to-market — drove 50% of inventory sold in a single day and an 8% conversion rate, roughly double the industry average
The Challenge
In 2022 I wanted to test something I couldn't answer from a desk: can original art become an everyday, ownable product - not just something that hangs on a wall? I had no team, no existing audience, and no capital runway. What I had was a body of hand-painted work and a 49-day window, working remotely from Goa, to design, build, and ship a complete commerce product before returning home.
How do you design, launch, and validate a new consumer product end-to-end - brand, catalog, storefront, and go-to-market - with no team, no ad budget, and one shot at a first impression?
Company
Deech (independent, founder-led)
Timeline
2022 (9 months)
Concept → Launch → Sustain
—
2025
Role
Founder, Product & UX Designer · User Research · Information Architecture · Brand & Visual Systems · Growth & Launch Design · Service Design
ISCOVERY & RESEARCH
Understanding trust before designing a single product
Before designing anything, I needed to understand two things: what makes someone buy art they've never seen in person, and how independent creators were already earning that trust online.
20 Days
Field Research
Days embedded in the market - sketching, testing motifs, and talking directly to buyers in Goa's art and tourist economy.
D2C
Competitive Scan
Benchmarked Instagram-native brands across fashion, home goods, and art prints - the pattern was consistent across all of them.
"Buyers didn't ask 'is this good art?' They asked 'do I understand the person who made this?'"
Across every conversation, the same behavior repeated - people decided to buy after watching the process, not after seeing the finished product.
COMPETITIVE SCAN
Instagram-native D2C brands,
benchmarked across three verticals
Fashion, home goods, and art prints - the same trust pattern surfaced every time.
Primary Driver
Not Primary
AP
Art &
Prints
HG
Home
Goods
FA
Fashion
Story-led captions & founder voice
Spec-first product listings
Process & behind-the-scenes content
Consistent across every vertical: story and process outsold specs.That confidence shaped how Deech's catalog and site content were built.
CORE INSIGHT
The product was never just the object.
Buyers weren't purchasing a scarf or a painting. They were purchasing proximity to a process, a place, and a person. A single original painting could only ever reach one buyer. The insight: the same imagery could become many products at many price points, extending one story into many formats without diluting it.
Don't sell the object. Sell the story - and let the story take many forms.
Core Insight
The system was built around the wrong question.
Librarians asked: "What is this work?" Researchers were asking: "What work feels like mine?"
Researchers don't search by classification. They search by resonance, what a work touches, who made it, what ideas it sits near. The old system couldn't answer that. It described objects. Researchers were looking for connections.
That became the principle behind every decision that followed: Stop describing works.
Start connecting them.
Design Principles
Before touching the architecture, I turned the core insight into four constraints. Not values, constraints. Each one came from something that had broken in the old system. Each one became a test: does this decision honour the principle, or compromise it?
Speak the researcher's language
Connections over containers
Built to be maintained
Flexible enough to hold what doesn't fit
Site Map
With the design principles set, the next step was mapping the full structure those principles would need to support - not just what content existed, but how every piece connects to every other piece. The sitemap below shows the shift: the old structure was flat, with 60+ standalone subject tags and no Creator, Material, or Method fields to connect records to one another. The redesigned structure adds those fields as first-class connectors, so every thesis record sits inside a web of related people, materials, and ideas instead of a dead-end category.
Content Model
With the taxonomy restructured, the next question was how content types related to each other - not just what they were, but how they connected. The Navigational failure pattern (users hitting a dead end at every record) was a schema problem, not just a UI problem. The content model was built to fix that at the data level.
I developed the content model diagram to map relationships between content types. The full taxonomy vocabulary and field-level audit was developed in collaboration with the content strategist.
Information Architecture
To restructure the subject taxonomy, I ran card sorting sessions with graduate students, asking them to group 40 subject terms into categories that felt natural. The guiding question for each term was: what does this mean in the context of your research? - determining, for instance, whether "Textiles" belonged under Materials & Making, Identity & Culture, or Social & Political. The clusters that emerged became the 8 parent categories in the redesigned taxonomy.
Scroll Inside the box to view complete design.
Annotated Wireframes
With the architecture defined, wireframes were built to validate how the browse and search flows would work in practice - and to test the core hypothesis: that restructuring entry points around mental models, not metadata categories, would reduce abandonment.
Browse Flow
The Browse flow was for the researcher who arrives without a known destination. She has a theme, a feeling, a material - not a title or an author. Most the of users entered through the Topic facet but left without clicking a result.
Research finding that drives this: Users given a flat 60+ term list spent an average of 40 seconds scanning before giving up. Grid clusters reduced cognitive load and gave users a recognizable entry point.
Screen A - Browse Landing: 8 subject category cards displayed as a visual grid, each with a name and work count.
Screen B - Filtered Results: User selects "Materials & Making" then "Ceramics," with filter chips and a sort control shown.
Screen C - Results: Thesis cards for "Ceramics" display with the breadcrumb confirming the taxonomy path.
Search Flow
The Search flow was for precision. An advisor looking up a specific student.
A researcher who already knows the name.
Research finding that drives this: author-name was the most common search query, yet no Creator field existed. The search experience was redesigned around that reality - Creator surfaces as the first filter, not buried in an advanced options panel.
Screen A - Keyword entered: Results for "textile," with filters for Creator, Subject, Medium, Method, and Format on the left.
Screen B - Filtered Search: User expands Creator and selects a name; over-filtering caused abandonment, so filters are individually removable.
Screen C - Results: Both filters applied, breadcrumb confirms the path, and 10 results return as a card list.
Record View
Where the two flows converged was the record view - the individual thesis page. This became the most important screen in the system, and the place where the core insight had to show up most clearly: stop describing works. Start connecting them.
Research finding that drives this: users who reached a record either found what they needed immediately or abandoned entirely - there was no next step. Two design decisions responded directly to that dead end.
The Related Works module turns every record into a new entry point through shared tags. Rather than being a terminus, each thesis page becomes a continuation - a way to keep moving through the collection without returning to search. This was the single most important structural change in the system. It solved the Navigational failure at the UI level.
The clickable Author field surfaces every thesis by that creator from a single name. Finding one work by someone immediately opens their full body of work.
Screen A - Record Landing:Thesis title, creator name, and compound object preview above the fold.
Screen B - Persons & Affiliations: Advisor name is hyperlinked, surfacing all theses they supervised.
Screen C - Related Works: A card grid of theses connected by shared tags appears at the bottom.
Screen D - Related Works Expanded:Full view lets users keep browsing without returning to search.
High Fidelity Prototype
With interaction patterns validated in wireframe, the high-fidelity prototype brought the full visual system to life - typography, imagery, and spacing tuned to make dense archival metadata feel browsable rather than clinical. Built across desktop and mobile with working filters and a fully navigable grid, it translated every wireframe decision (breadcrumbs, filter chips, the Related Works module) into a real, clickable interface. This was the version tested with the 20 participants in the next phase.
Testing & Outcomes
User testing was conducted with 20 participants across graduate student and faculty profiles. Each session ran 90 minutes. Participants were given three tasks: find a thesis by a specific creator, explore works related to a given theme, and navigate from a single record to a connected work without returning to search.
Reflection
This project started as a migration. It ended as a rethinking of what discovery means in a creative archive.
The old system asked: what is this work? The new system asks: what does this work connect to? That shift - from description to connection - changed the schema, the taxonomy, the navigation, and ultimately the experience of every person who enters the collection looking for something they can't yet name.
What I would do differently: The taxonomy was rebuilt collaboratively through card sorting, but the maintenance model - how library staff sustain it over time - was documented but not tested with the people who will use it. The next phase of this work would be a staff-facing audit workflow that prevents the taxonomy from decaying back into the state we found it in.
What remains open: Personalization. The system now surfaces connections between works. It doesn't yet learn from individual researchers. That's the next layer of the discovery problem.
