ARTPICK {Passion project}

Personalised Art Discovery for E-commerce (Desktop Concept)

Overview

ArtPick is a desktop e-commerce concept focused on simplifying the decision-making process when purchasing art prints online.

The goal of this project was to design a guided selection experience that reduces choice overload and increases user confidence through structured personalisation.

I approached this as a product thinking exercise, combining UX strategy, interaction design, and a cohesive visual system.

Context

Online art marketplaces typically offer thousands of products across styles, formats, and price ranges. While variety is valuable, it often creates decision fatigue.

Users struggle with:

• defining their own style

• imagining how artwork fits their space

• narrowing down overwhelming options

Most platforms rely heavily on filtering and search, but lack guided discovery. This creates friction, hesitation, and abandoned sessions.

Core Challenge

How might we help users discover art that fits their taste and space without overwhelming them with excessive browsing?

The challenge was to design a structured yet engaging flow that:

• supports self-discovery

• feels lightweight and intuitive

• integrates naturally into a traditional e-commerce environment

Key Problems, Solutions, and Outcomes

Problem
Users experience decision paralysis when browsing large art catalogues.

Solution
I introduced a guided recommendation quiz that translates subjective preferences into structured inputs.

Outcome
The experience shifts from passive browsing to active guidance, reducing cognitive load.

Problem
Traditional filtering systems require users to know what they are looking for.

Solution
The quiz reframes the journey into simple, emotionally driven questions about mood, colour, and space.

Outcome
Users can express preferences without needing design terminology, making the experience more accessible.

Problem
Personalisation often feels disconnected from the main shopping experience.

Solution
The recommendation results were designed as a natural extension of the product listing page, not as a separate tool.

Outcome
The flow feels integrated into the overall e-commerce journey, supporting conversion rather than distracting from it.

DESIGN Process

Research & Discovery

I analysed existing online art stores to identify common UX patterns and friction points.
Key findings included overwhelming product grids, unclear filtering hierarchies, and limited emotional guidance.

Target Audience

• Gen Z & Millennials (18-35 years old)

• Urban creatives, renters, and first-time homeowners

• People who love aesthetics but don’t consider themselves "art experts"

• Users who prefer digital-first, mobile-friendly experiences

User research

For user research, I focused on understanding why people struggle to choose art online. I explored common frustrations, such as decision fatigue and the overwhelming number of options. I also analyzed competitor websites to identify gaps in personalization and ease of use. These insights helped shape ArtPick’s quiz-based approach, making the art selection process more intuitive and engaging.

Quantitative research

For quantitative research, I analyzed data from online surveys and existing market reports on art-buying behavior. I looked at statistics on how users browse and purchase art, focusing on decision-making patterns and common drop-off points. This data reinforced the need for a guided shopping experience, leading to the development of ArtPick’s personalized quiz.

Survey Data (Hypothetical Example):

• 68% of users said they feel overwhelmed when choosing art online.

• 52% abandon their purchase because they’re unsure if the artwork will fit their space.

• 75% prefer personalized recommendations over browsing large catalogs.

Industry Insights (Real Data):

• According to Artsy’s 2023 Art Market Report, 35% of online art buyers say they hesitate due to too many choices.

• A Baymard Institute study found that 69% of online shopping carts are abandoned, often due to indecisiveness.

• E-commerce brands using quizzes and guided selling see a 20-40% increase in conversions.

User personas

Goals

• Zuzka wants to decorate her apartment with stylish art that reflects her creative personality.

• She values personalized shopping experiences and prefers quick, curated recommendations.

Frustrations

• She often feels overwhelmed by the sheer number of art options available online.

• She struggles to find art that suits her taste and matches her modern home decor style.

Needs

• Personalized art suggestions based on her aesthetic preferences and apartment layout.

• A simple, time-saving shopping experience with intuitive navigation.

Behavior

• Zuzka frequently shops online for home decor and enjoys discovering unique, modern art pieces.

• She engages with brands that offer clear and minimalistic designs, as well as curated recommendations.

Goals

• Janko is in the process of decorating his new home and wants to find artwork that complements his minimalist interior design.

• He is not an art expert but is interested in finding modern art that fits his space.

Frustrations

• Janko finds it hard to choose the right art that matches his home’s design without feeling uncertain.

• He doesn’t have much time for browsing countless websites or galleries.

Needs

• Simple, curated art recommendations based on his preferences.

• A straightforward online shopping process with recommendations tailored to his style and home design.

Behavior

• Janko prefers shopping online for convenience, particularly for home decor.

• He values functionality and clarity in online shopping experiences and looks for reliable guidance when making decisions.

Empathy MAP

COMPETITIVE ANALYSES

Customer journey map

I defined the primary user journey:

Landing → Quiz Entry → Preference Selection → Recommendation Results → Product Exploration

The focus was on creating a linear but flexible flow that remains transparent and predictable.

WIREFRAMING & FLOW DEFINITION

Low-fidelity wireframes were used to:

• test quiz length and pacing

• validate information hierarchy

• ensure seamless transition between quiz and product results
  
  

Special attention was given to:

• progress indicators

• clarity of choice states

• visual feedback

PROTOTYPING & REFINEMENT

• flow clarity

• micro-interactions

• transitions between quiz and results

• emotional tone of the interface
  
  

The design was iterated to ensure the quiz feels lightweight rather than time-consuming.

Impact & Learnings

This project demonstrates my ability to:

• design structured decision-support flows

• balance guidance with user autonomy

• build a coherent desktop UI system

• think beyond aesthetics and focus on interaction logic

It also strengthened my understanding of how personalisation can be embedded into traditional e-commerce models without increasing complexity.

Responsibility : UX research, UI design

Tools: Figma, Miro, Adobe Illustrator