AI Wine Sommelier

Shipped in 2024 | Proof of Concept | Google Gemini AI

Taiwan wine sales growth hit 60-year low🔻

Carrefour tapped AI chatbot for turnaround

THE PRODUCT

It democratizes wine expertise for beginners, aiming to revive market growth through personalized guidance

The chatbot guides customers through Taiwan's largest wine collection with conversational AI and everyday language. Through this approachable interaction, the sommelier demystifies wine selection, turning confusion into confidence for customers navigating Taiwan's most extensive wine collection.

Project Overview

I shipped the first Gemini AI chatbot in Taiwan retail by leading end-to-end design

Role

UX Designer
UX Researcher

Type

E-commerce
Conversational AI
B2C

Team

UI Designer
UX Researcher
PM

Stakeholder

CTO
Data Team Lead
Dev Team Lead

Platform

Web App

Duration

2023.09 - 2023.12
(Design Phase)

Numeric Scales & Everyday Language

Illustrations & Clear descriptions

Result & Impact

My design delivered measurable business impact

+0%

Wine sales Increase within 2 months of launch

0%

Users added wine to cart in ≤3 searches

0st

Google Gemini AI application in Taiwan retail

"AI sommelier can give you the right wine in just a few seconds."

Henry Ting

Digital Technology Officer, Carrefour Taiwan

Research

To ship fast, I explored mature AI applications and market demands.

AI application assessment

I analyzed 14 deployed AI applications to extract workable design and interaction patterns.

Sommelier and seller interviews

We interviewed 2 liquor store owners and 1 Carrefour sommelier to understand wine selection challenges.

Online forum threads analysis

I analyzed wine community forums to uncover beginner barriers and purchasing behaviors efficiently.

Insights

We uncovered two critical findings

Sommelier's 3-step guidance framework

Expert sommeliers consistently used three questions to guide customers: purpose (gifting, gathering, or personal enjoyment), flavor preferences (taste, origin, grape variety), and budget. This structured approach made wine selection approachable, but required expert availability.

Knowledge barriers blocked wine beginners

Technical wine terminology scared beginners away. Terms like 'dry,' 'oaky,' 'notes of leather,' 'full-bodied with firm tannins,' 'musty,' and 'enology' felt like a foreign language, making wine culture feel exclusive and inaccessible.

Key Feature 1

Expert-informed AI conversation flow

Before

Customers overwhelmed by selection and buy nothing

Carrefour's extensive wine selection intimidated beginners who lacked the knowledge to navigate options. Without accessible expertise, customers left stores without making purchases.

Challenge

How to balance providing personalization, AI costs, and tight deadlines?

Generating full AI responses and translating them consumed too many tokens, driving up costs and slowing response times. The MVP timeline didn't allow time to extensively test and guarantee AI predictability.

Key Decision 1

I created step-by-step conversation flows based on sommelier expertise

I transformed sommelier expertise into guided conversation flows with choice-based interactions. This approach made professional wine guidance accessible to beginners while ensuring accurate recommendations, controlled costs, and on-time delivery—all without requiring model fine-tuning

Key Decision 2

I designed choice-first interactions to ensure accuracy and delivery timeline

To guarantee accuracy and meet the 4-month deadline, I designed structured choice flows instead of free-form input. Guided selections ensured reliable recommendations without model training, while reducing decision anxiety for wine beginners.

The Design

Expert-guided conversation flow for reliable MVP accuracy

I transformed sommelier expertise into guided conversation flows with choice-based interactions. This approach made professional wine guidance accessible to beginners while ensuring accurate recommendations, controlled costs, and on-time delivery—all without requiring model fine-tuning

Key Feature 2

AI-simplified wine profiles in everyday language

Before

Expert wine language confused beginners, creating a critical barrier

Technical terms like 'pencil lead,' 'sundried rocks,' and 'medium-bodied palate' excluded wine beginners rather than guiding them. This expert language reinforced intimidation, turning potential customers away without purchases.

Challenge

How to maintaining accuracy and credibility while simplifying wine language

Expert wine language ensures accuracy but excludes beginners. I needed to make descriptions accessible without oversimplifying—maintaining enough detail for trustworthy description while removing intimidating jargon that prevented purchases.

ACCESSIBLE LANGUAGE

Translate expert terminology into everyday words

EXPERT CREDIBILITY

Maintain trust and authority while being approachable

Description accuracy

Ensure descriptions genuinely match wine favors

The Design

I used numeric scales and everyday language make wine expertise approachable

Simple descriptors like 'micro-bubbles' and 'fruit aroma' paired with numerical scales transformed complex wine attributes into scannable, relatable information.

The Design 2

I use plain language and food pairing icons to simplified wine profiles

I combined three elements to make wine expertise accessible: numerical scales (Acidity: 3) for quick comparison, everyday descriptions ('fresh and smooth' instead of 'medium-bodied'), and food pairing icons (beef, cheese, sweets) that relate to real dining experiences

Key Learnings

AI flows evolved as users became more confident and direct

After launch, user behavior evolved. Initially, beginners needed structured guidance through choices, but as they became familiar with the system, they started entering complete requests upfront. I adapted by allowing direct input alongside guided flows and added 'I don't know' options for uncertain beginners

Multilingual AI requires cultural adaptation, not just word translation

Direct Chinese translation reduced recommendation accuracy significantly. I learned that multilingual AI needs culturally appropriate concepts and examples to maintain accuracy and relevance.

Smart Warehouse System

Smart Warehouse System -

I transformed fragmented datas into a unified dashboard.

I delivered impact in 12-week internship at Salesforce