INTL
Freelancer
전문가
외주
원격 가능
Outdoor Gear Recommendation Chatbot
예산
$30~$250 CAD
예상 기간
2~3개월
난이도
전문가
기술 스택
Shopify
JSON
API Integration
NLP
LangChain
AI Chatbot Development
Dialogflow CX
Rasa
GPT
Shopify API
Facebook Messenger API
Web Chat Widget Development
NLU Model Training
Data Annotation
AI 분석 요약
스포츠 용품 이커머스 스토어를 위한 AI 챗봇 개발 프로젝트입니다. 고객의 아웃도어 활동 장비 추천을 핵심 기능으로 하며, Shopify 재고 데이터를 실시간으로 연동하여 개인화된 제안을 제공해야 합니다. NLP, API 연동, 대화형 AI 개발 역량이 필수적입니다.
프로젝트 원문 설명
I run a sporting-goods e-commerce store and I want an AI chatbot that can act like a knowledgeable sales associate focused on recommending the right outdoor-activity equipment to each visitor. The core task is product recommendation, not general customer support or order processing, so every design decision should optimise for guiding shoppers toward the best-suited tents, backpacks, climbing gear, camping stoves, bikes, and similar items from our existing catalogue.
How I imagine the experience
• A shopper describes where they’re headed, their skill level, budget range, or brand preferences.
• The bot instantly analyses that input, checks our inventory feed, and responds conversationally with personalised gear suggestions, upsell add-ons, and concise feature comparisons.
• If an item is unavailable it offers close alternatives rather than dead-ending the chat.
Technical expectations
• You’re free to build with Dialogflow CX, Rasa, LangChain + GPT, or a comparable NLP stack—as long as it supports rich context, product-attribute filtering, and easy retraining when we introduce new SKUs.
• JSON or webhook integration must pull real-time data (price, stock, specs, images) from our Shopify store.
• Responses need to feel human: natural language, short paragraphs, emojis sparingly, no robotic repetitions.
Deliverables
1. A fully configured AI chatbot deployed to our website and Facebook Messenger.
2. Training dataset and intent/entity schema covering outdoor equipment queries.
3. Setup documentation plus a quick-edit guide so my staff can tweak copy or add new products without touching code.
4. A brief hand-off session (video or live call) walking me through dashboard controls and performance analytics.
Acceptance criteria
• At least 90 % of test conversations end with one or more valid product links.
• Average response time <2 s after user input.
• All recommendations originate from live inventory; no out-of-stock items suggested.
I’m happy to answer any follow-up questions about our catalogue structure or data endpoints—let’s build something that makes choosing outdoor gear easy and fun for our customers!
How I imagine the experience
• A shopper describes where they’re headed, their skill level, budget range, or brand preferences.
• The bot instantly analyses that input, checks our inventory feed, and responds conversationally with personalised gear suggestions, upsell add-ons, and concise feature comparisons.
• If an item is unavailable it offers close alternatives rather than dead-ending the chat.
Technical expectations
• You’re free to build with Dialogflow CX, Rasa, LangChain + GPT, or a comparable NLP stack—as long as it supports rich context, product-attribute filtering, and easy retraining when we introduce new SKUs.
• JSON or webhook integration must pull real-time data (price, stock, specs, images) from our Shopify store.
• Responses need to feel human: natural language, short paragraphs, emojis sparingly, no robotic repetitions.
Deliverables
1. A fully configured AI chatbot deployed to our website and Facebook Messenger.
2. Training dataset and intent/entity schema covering outdoor equipment queries.
3. Setup documentation plus a quick-edit guide so my staff can tweak copy or add new products without touching code.
4. A brief hand-off session (video or live call) walking me through dashboard controls and performance analytics.
Acceptance criteria
• At least 90 % of test conversations end with one or more valid product links.
• Average response time <2 s after user input.
• All recommendations originate from live inventory; no out-of-stock items suggested.
I’m happy to answer any follow-up questions about our catalogue structure or data endpoints—let’s build something that makes choosing outdoor gear easy and fun for our customers!
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