Accelerating Commercial Conversion with Virtual Assistants: More Leads, Less Effort
Region
Spain
Sector
Food Industry
Duration
2 months
Technologies Used
Scrapers for extracting company profiles and information
AI-based matching model
Generative AI
Workflow management
What We Solved
In companies with large sales teams and long commercial cycles, manual lead management leads to wasted time, classification errors, and missed opportunities.
We identified that sales teams were investing too many resources in prospecting, initial contact management, and intent analysis, making it difficult to scale their sales processes and reduce their customer acquisition costs.
How We Solved It
We implemented a complete solution based on customizable virtual assistants that automate the entire lead management cycle:
1.
1. Automated Lead Scraping and Identification
We used advanced scraping techniques to capture qualified leads.
2.
2. Smart Classification and Enrichment
We applied AI models trained with CRM and ERP histories to automatically classify and enrich leads.
3.
3. Automated Initial Contact and Nurturing
Virtual assistants handled the first contact with personalized messages and continued nurturing if no response was received.
4.
4. Intent Detection and Efficient Closing
Automatic detection of lead intent to route it to a salesperson or continue with the virtual agent.
5.
5. Seamless CRM and Channel Integration
All activity was logged and integrated into the client’s systems with no manual intervention.
What Results We Achieved
Scalable and Effective Prospecting Automation
75% reduction in time spent on initial lead searches by the sales team.
Improved Initial Conversion
40% increase in response rate for outbound campaigns thanks to personalization and automated follow-ups.
Optimización del embudo de ventas
30% reduction in cost per qualified lead (CPL) by eliminating repetitive manual tasks.
More Accuracy, Fewer Errors
90% of leads were correctly classified and enriched without human intervention, reducing errors and management time.
Greater Traceability and Continuous Learning
All interactions were logged and analyzed to continuously improve the recommendation engine.