Area Bis
Área Bis, an online office equipment retailer, faced the challenge of managing a high volume of diverse customer inquiries through WhatsApp while maintaining speed, accuracy, and personalization. The team needed a system capable of processing multiple types of requests — from product specifications to quote generation — while capturing key data from potential clients and connecting them efficiently with the sales team. The main difficulty was ensuring that all customer interactions were handled swiftly and consistently, providing the commercial team with the necessary information to create tailored quotes without increasing operational workload.
Year
2024
Industry
E-commerce
Scope of work
/
Agents
/
Automation
/
AI
/
ecommerce
Timeline
1 month
To address these challenges, Lumen designed a network of AI-powered customer support agents specifically tailored for Área Bis’s WhatsApp channel. The system includes several coordinated agents that automate data collection, qualification, and internal routing, while maintaining natural and personalized conversations with users.
Key components include: - Intelligent Information Collection: The primary agent interacts naturally with customers via WhatsApp, asking targeted questions about product needs, company size, and budget considerations. - Unified Data Management: All collected data is automatically stored in a centralized database, generating complete client profiles accessible to the sales team in real time. - Real-Time Notifications: The system proactively alerts the sales team whenever a new qualified lead is detected, ensuring immediate follow-up. - Multi-Agent Architecture: Behind the scenes, specialized AI agents collaborate to process complex requests, maintain context, and prioritize leads based on business criteria. - CRM Integration: The assistants are integrated with Área Bis’s CRM platforms, streamlining workflows and eliminating redundant data entry. Together, these features allowed Área Bis to automate client interactions, accelerate response times, and improve data accuracy — transforming their customer support operations into a scalable, AI-driven ecosystem.
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