Conversational gift-finder assistant that recommends products for an online florist
Company: Shopify
Role: Product Manager
Category: Product Design & Strategy
Difficulty: medium
Interview Round: Other
An online store sells flowers and gifts. Design a product recommendation experience for this store that works through chat: the shopper talks with an assistant, and the assistant suggests what to buy.
Explain whom it serves, how the conversation works, how the recommendations are chosen and how you would measure success.
```hint Start from what the shopper knows
Someone buying flowers as a gift often knows the recipient, the occasion and when it has to arrive, but not which product to pick. Which of these facts rule out the most products, and what can a conversation learn that a filter panel on a category page cannot?
```
### Clarifying Questions
- Is the assistant for this one store, or a tool that many merchants could add to their own storefronts?
- What is the business goal: more visitors buying, larger orders, or fewer shoppers leaving without a purchase?
- Does the store deliver locally on the same day, ship nationally, or both, and what does it sell besides flowers?
- Where does the chat appear: on the website, in a mobile app, or inside messaging apps?
### What a Strong Answer Covers
- A business goal for the assistant and a clear reason why a conversation beats browsing and filters for this kind of purchase.
- Gift-buyer segments (for example last-minute occasion buyers, planned-holiday buyers, sympathy senders, people buying for themselves) with a justified focus and that segment's pain points.
- The conversation design: what it asks, in which order, how many questions before the first suggestions, how it handles delivery date and address, and how it hands off to cart and checkout.
- How recommendations are produced from the real catalog: delivery and stock feasibility, occasion and recipient fit, personalization, and a cold start for a store with little order history.
- Metrics that show the chat causes extra purchases, with guardrails for delivery misses, complaints and abandoned chats.
### Follow-up Questions
- On Valentine's Day traffic spikes and popular arrangements sell out. How should the assistant behave?
- Should the assistant ask for a budget? How would you avoid steering shoppers toward pricier items in a way that costs their trust?
- Shoppers who open the chat may have been more likely to buy anyway. How would you measure the chat's real effect?
Overview: A product design question about building a chat assistant that recommends flowers and gifts to shoppers of an online store. It tests segmenting gift buyers, designing a short conversation, producing recommendations that respect delivery dates and inventory, and choosing metrics that show whether the chat drives incremental purchases.
