Case study: B2B SaaS co. sees 400% increase in leads with AI prospecting

A prominent B2B SaaS company in the project management space was facing a classic growth-killer: their highly-paid sales team was spending over 20 hours per week, per rep, on manual, soul-crushing prospecting. The process was slow, the leads were often low-quality, and morale was suffering. This case study details how our 3-Day AI Sprint transformed their top-of-funnel, resulting in a 400% increase in qualified leads and a 90% reduction in manual prospecting time.

The challenge: a leaky bucket of wasted talent

The client's sales team was their most expensive asset, yet they were operating like manual data miners. Their process involved:

• Endless hours scraping LinkedIn Sales Navigator and industry directories.
• Manually verifying company information and trying to find correct contact details.
• Building lead lists in spreadsheets, a process prone to errors and duplication.

The result was a pipeline filled with poorly qualified leads, reps who were too burnt out to be effective, and a lead acquisition cost that was spiraling out of control. They were trapped in a cycle of inefficiency, unable to scale without hiring more reps to do the same manual work.

The solution: the AI prospecting agent

During our 3-Day AI Sprint, we deployed a custom AI Prospecting Agent designed to automate their entire top-of-funnel workflow. The agent was tasked with a clear directive based on the company's Ideal Customer Profile (ICP):

"Continuously find and qualify B2B tech companies with 50-1,000 employees that are currently hiring for 'product manager' or 'engineering lead' roles and are using competing project management software."

The agent executed a multi-step plan 24/7:

1. Monitoring: It continuously scanned job boards, LinkedIn, and tech news sites for signals that a company matched the ICP.
2. Enrichment: Once a target company was identified, the agent enriched the record with key data points, including firmographics, technographics, and key contacts.
3. Qualification: It scored and verified each lead, ensuring it met the strict qualification criteria before being passed to a human.
4. Delivery: High-intent, fully-qualified leads were delivered directly into a dedicated Salesforce queue for the sales team, complete with research notes on why the lead was a good fit.

This entire process was built on a Human-in-the-Loop model, where reps had final approval, ensuring quality and control.

The results: a high-performance sales engine

The impact was immediate and transformative. Within the first month of deploying the AI Prospecting Agent, the client achieved:

• A 90% reduction in time spent on manual prospecting, freeing up over 20 hours per rep per week to focus on selling.
• A 400% increase in the number of qualified leads generated per month.
• A 75% decrease in their lead acquisition cost.
• A significant improvement in sales team morale and a reduction in rep burnout.

By automating the top of their funnel, the company was able to build a predictable, scalable pipeline and empower their sales team to do what they do best: build relationships and close deals. This case study is a testament to how the modern sales engine can turn operational drag into a significant competitive advantage.