AI Product Recommendation Chatbot for Your Website

What is an AI product recommendation chatbot?

An AI product recommendation chatbot uses your product information and the preferences shoppers share in chat to suggest relevant options and explain the differences.

• Narrow the choice — Help shoppers find suitable options without reading every product page.
• Make comparisons clearer — Explain differences in features, materials, sizes, or intended use.
• Answer questions before purchase — Clarify whether a product meets the customer’s requirements.
• Make products easy to find — Point shoppers to the relevant page when they are ready to explore or buy.

Skills for your product recommendation chatbot

Give shoppers a way to explore a recommendation or get more advice.

• Action buttons — Show relevant buttons that open a product page, category, or buying guide. Give shoppers a clear next step after explaining their options.
• Human handoff — Offer contact with your team when a shopper needs specialist advice or a detail is missing from the chatbot’s knowledge. Configure options such as email, phone, or WhatsApp.
• Lead form — Collect a name, email, or phone number when a shopper wants personal advice or a quote. Keep contact details linked to the conversation so your team can review the products and requirements discussed.
• Booking — Let shoppers schedule a product consultation or demonstration through Calendly or Cal.com. Offer booking when choosing the right product calls for a longer conversation.
• Follow-up message — Send a message after a pause in the chat, such as “Would you like help comparing these options?” Customize the delay and wording to invite further questions.

Set up your chatbot to recommend your products

1. 1.

   Start with your product pages. Enter your website address to prepare your chatbot’s initial knowledge and profile. Review the product information it has gathered and add pages or files for any missing items. Include product links so shoppers can find the options discussed.

2. 2.

   Add the details that help shoppers choose. Provide specifications, prices, size guides, materials, and intended uses through website pages, files, or Q&A. Explain meaningful differences: which backpack fits a laptop, which chair suits a smaller desk, or what an upgraded model adds.

3. 3.

   Define what to ask before recommending. Instruct your chatbot to clarify the shopper’s intended use, budget, and must-have features. For example: “Before suggesting a backpack, ask what they carry and whether it is for commuting or travel.” Keep questions relevant to the product category.

4. 4.

   Set rules for comparisons and alternatives. Ask the chatbot to suggest a short list and explain why each option fits the stated needs. Define how it should handle trade-offs, such as a lower price versus an extra feature. Tell it to acknowledge missing specifications and offer human contact when suitability is uncertain.

5. 5.

   Test recommendations before publishing. Try requests with different budgets, conflicting preferences, and requirements your products do not meet. Check that suggestions are supported by your product information and lead to the right pages. Update the knowledge and instructions where explanations are incomplete.

6. 6.

   Learn from shopping conversations. Review which products customers compare and what details they struggle to find. Add answers to recurring questions and update sources when products, specifications, or prices change. Use saved conversations and contact details to prepare for requests that need personal advice.