Luxa
Luxa Overview
Luxa is an AI-powered tool designed to help B2B product managers gain insights from sales calls automatically. It integrates with Gong to analyze sales and customer success call transcripts, extracting feature requests, complaints, and praise. Luxa combines these insights with CRM account data, allowing managers to prioritize based on facts, not opinions. It is built specifically for sales-led B2B product management, aiming to capture and analyze essential feedback for fueling B2B sales-led growth.
Luxa Highlights
- Luxa uses AI to auto-extract insights from customer calls, saving time and effort for product managers.
- It integrates with CRM data to provide a reality-based prioritization, helping to make smart product decisions.
- Luxa aligns Product, Sales, and Success teams around the same data, promoting efficiency and agility.
Use Cases
A B2B product manager uses Luxa to analyze customer feedback from sales calls. The AI-powered tool extracts feature requests and complaints, providing valuable insights into what customers want and what they are not satisfied with. The manager then uses this information to guide product development, ensuring that the product meets customer needs and expectations.
The product is improved based on customer feedback, leading to increased customer satisfaction and sales.
A sales manager uses Luxa to gain insights into what customers are praising about the product. The manager then uses this information to refine the sales strategy, focusing on the product's strengths that customers appreciate. The AI tool also integrates with CRM data, providing a reality-based prioritization that helps the manager make smart sales decisions.
The sales strategy is improved, leading to increased sales and revenue.
A company uses Luxa to align the Product, Sales, and Success teams around the same data. By providing a single source of truth, the tool promotes efficiency and agility, helping the teams work together more effectively. The teams can then focus on their core tasks, rather than spending time and effort on data extraction and analysis.
The teams work more efficiently and effectively, leading to improved performance and results.