Store Visitors Qualification: Smart Pre-Sale Questions
Proactively ask 2-3 qualifying questions to understand customer needs and recommend the perfect product across all channels.
Overview
Most customers don't know what they need. They land on your site with vague ideas like "I need a laptop" or "looking for a gift." Without guidance, they browse without a goal, get overwhelmed by options, and leave. You need to narrow down their needs quickly, just like a skilled salesperson would in a physical store.
Zipchat's Visitor Qualification asks smart questions proactively to understand what customers actually need before recommending products. Instead of waiting for customers to describe their requirements perfectly, the AI jumps in with targeted questions: "What will you primarily use this for?" or "What's your budget range?" or "When do you need this by?" These questions speed up decisions by surfacing the most important factors: deadline, use case, and budget.
The AI adapts based on answers. If someone says "I need it by Friday," it will only recommend in-stock items with fast shipping. If they say "for professional photography," it filters out entry-level options. If they mention "under $500," it stays within budget. Every message from the AI ends with either a specific product recommendation or another qualifying question. This keeps the conversation moving toward a purchase instead of stalling in information overload.
Brands using visitor qualification see 40-60% higher conversion rates from engaged conversations compared to passive browsing. Average time to purchase drops by 25-35% because customers aren't wasting time exploring wrong options. More importantly, product return rates decrease by 20-30% because customers buy what actually fits their needs instead of guessing. For brands with complex catalogs, high-consideration purchases, or products requiring expertise to choose correctly, this ability transforms browsing into guided shopping that closes sales faster and more accurately.
Overview
Problem
Solution
Scenario description
Laptop Shopping Confusion
A customer lands on your electronics site and messages: "I'm looking for a laptop."
Instead of showing 47 laptop options, the AI asks: "I can help you find the perfect one! Quick questions: What will you mainly use it for—work, gaming, or everyday use?"
Customer: "Work, mostly video editing."
AI: "Got it. What's your budget range, and do you have a brand preference?"
Customer: "Around $1,500, no brand preference."
AI: "Perfect. For professional video editing at that budget, I'd recommend the MacBook Pro M2 or the Dell XPS 15 with dedicated graphics. The MacBook is better for Final Cut Pro users and has longer battery life. The Dell offers more ports and is better if you use Adobe Premiere. Which software do you use?"
Customer: "Premiere mostly."
AI: "Then the Dell XPS 15 is your best bet. It has the RTX 4050 GPU which handles Premiere renders really well, plus Thunderbolt ports for external monitors. Want me to send you the link?"
The AI went from 47 options to one perfect recommendation in under two minutes. The customer buys confidently because the AI understood her exact needs.
Gift Shopping Made Easy
A customer messages: "I need a gift for my girlfriend."
AI: "I'd love to help! What's the occasion, and what's she into—jewelry, fashion, tech, or something else?"
Customer: "Birthday. She loves skincare."
AI: "Nice! What's your budget, and does she have sensitive skin or any specific concerns like anti-aging or acne?"
Customer: "Around $80, and she's all about anti-aging."
AI: "Perfect. Our Retinol + Peptide Serum Set is exactly $79 and is our best-seller for anti-aging. Comes in beautiful gift packaging too. It's gentle enough for daily use and customers see results in 4-6 weeks. Want to add it to your cart?"
He orders it immediately. What could have been 20 minutes of browsing became a 90-second conversation with a perfect recommendation.
Setup guide

- Build your product knowledge base with detailed product information, use cases, and specifications
- Navigate to AI Training → Prompt & Tools → Additional Instructions
- Add instructions for the AI to proactively ask 2-3 qualifying questions at the start of conversations (use case, budget, deadline, preferences, experience level, etc.)
- Instruct the AI to always end messages with either a specific product recommendation or another qualifying question to narrow needs
- Test across different product categories to ensure qualification flows naturally
Ability statistics
Technical table
FAQs
What types of qualifying questions should the AI ask?
The most effective questions focus on use case ("What will you use this for?"), budget ("What's your price range?"), timeline ("When do you need this by?"), experience level ("Are you a beginner or experienced?"), and specific requirements ("Any must-have features?"). The AI adapts questions based on your product category. For technical products, it asks about compatibility. For fashion, it asks about style preferences. For gifts, it asks about the recipient's interests.
How does this work differently than showing all products with filters?
Traditional filtering requires customers to understand product specifications and know what they're looking for. Most don't. Visitor qualification is conversational—the AI translates customer needs into product specifications automatically. A customer doesn't need to know that "video editing requires 16GB RAM and dedicated GPU." They just say "I edit videos," and the AI handles the technical translation. This works especially well for non-technical customers or complex product categories.
Can the AI handle customers who don't know what they want?
Absolutely. That's exactly when qualification shines. When someone says "I'm not sure what I need," the AI asks exploratory questions to help them figure it out: "Tell me about what you're trying to accomplish" or "What problems are you trying to solve?" The AI guides discovery through conversation, helping customers clarify their own needs while simultaneously narrowing down products that fit.
Does this work across all customer touchpoints?
Yes. Visitor qualification works on bubble chat, WhatsApp, support emails, Instagram DMs, and Messenger. The AI adapts its questioning style to the channel. On chat, it's rapid-fire questions. On WhatsApp, it's more conversational. In email, it consolidates questions into fewer messages. The qualification logic is the same, but the delivery style matches the channel's natural communication patterns.
How much does qualification actually improve conversion rates?
Brands implementing proactive qualification see 40-60% higher conversion rates from engaged conversations compared to passive browsing. More critically, average time to purchase drops by 25-35% because customers aren't exploring dead ends. Product return rates decrease by 20-30% because customers buy products that actually fit their needs. For a store with 1,000 monthly qualified conversations, improving conversion by 50% can mean hundreds of additional sales without increasing traffic.
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