A client-facing conversational agent that engages website visitors or callers to qualify leads, answer FAQs, and schedule demos. It acts as a 24/7 pre-sales assistant, ensuring no inquiry is missed and filtering serious leads from casual browsers.
Retail and service brands lose sales when shoppers cannot get quick answers. Someone comparing products late at night, unsure which option suits them, often leaves rather than emailing a question. Sales teams, meanwhile, spend time on enquiries from casual browsers while serious buyers wait. International or multilingual customers face an extra barrier when support only operates in English.
An AI sales chatbot acts as a pre-sales assistant on the website, WhatsApp or other messaging channels. It answers product and policy questions, runs short quizzes that recommend suitable products, qualifies higher-value enquiries and books demos or consultations. Leads and quiz answers flow into the CRM and Mailchimp for follow-up, so staff can focus on customers ready to buy.
Product information, policies and common questions are loaded into the chatbot's knowledge sources, with Dialogflow handling structured flows and an LLM handling open questions.
Visitors can ask questions freely or take a short quiz about needs and preferences; the bot matches answers to products using rules the merchandising team sets.
The bot detects the visitor's language and responds in it, drawing on approved translations for key policies.
For high-value or B2B enquiries, it asks qualifying questions and offers booking into a sales consultant's calendar.
Contact details, quiz answers and consent choices are sent to the CRM, such as Salesforce, and marketing-consented contacts are added to Mailchimp audiences.
A premium haircare brand deploys a multilingual chatbot that uses a short quiz to recommend products for each customer's hair type, helping shoppers choose with confidence and move to checkout.
Google Dialogflow, OpenAI GPT models, Custom UI, CRM Integration (e.g., Salesforce), Mailchimp, WhatsApp
Product recommendations and claims are covered by the Australian Consumer Law, so the bot must not overstate benefits or suggest results a product cannot deliver; beauty and health-adjacent products need particular care, and therapeutic claims can fall under TGA advertising rules. Adding chat contacts to Mailchimp requires consent under the Spam Act 2003, so ask explicitly rather than assuming. WhatsApp messages sent for marketing also need consent. Quiz answers can reveal personal information, such as skin or hair conditions, which may be sensitive, so collect only what the recommendation needs and explain how it is used under the Privacy Act 1988.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
Recommendations come from rules and product data the business controls, such as matching quiz answers about needs and preferences to product attributes. The LLM phrases the explanation naturally but should not invent reasons. Keeping recommendation logic explicit makes it easier to test and adjust as the range changes.
Yes. The same conversation design can be deployed on the website and WhatsApp through the WhatsApp Business Platform. WhatsApp has its own rules about templates and when businesses can message users, so follow-up messages need to fit those rules and your consent records.
It handles early-stage questions and filters enquiries, but people still close larger sales, handle complex needs and build relationships. Most businesses find the bot changes what staff spend time on rather than removing roles. It also creates better notes, so conversations pick up where the bot left off.
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