Conversely AI

Case Study: How a Lead Generation Company Improved Cost Per Acquisition by 22% with Conversely AI

insurance lead provider case study

Lead generation (Call based)

Solution Used: Conversely Lead Insights Platform 

Time to Impact: <30 Days

 

Background

A national lead generation company was selling call-based leads to agencies. The team faced a critical challenge: to increase lead volume while simultaneously improving lead quality — all without true visibility into what was actually happening on the calls.

Despite a strong buyer network, the company lacked detailed insights into:

  • The quality of individual affiliates/publishers
  • Whether leads were qualified or sales-ready
  • The actual outcomes of calls (quote given, sale made, customer attitude, etc.)

To assess lead quality, the buyers of these leads had to spot-check calls manually, a slow and subjective process.

This lack of data transparency limited the lead provider’s ability to:

  • Optimize lead sources
  • Demonstrate value to buyers
  • Confidently price leads based on real outcomes

Solution

The lead generation company implemented the Conversely Lead Insights Platform, which uses AI to:

  • Transcribe and analyze 100% of calls automatically
  • Understand with remarkable precision:
    • Whether a quote or product pitch was given
    • Whether the customer was qualified
    • The skill set of the agents handling the volume
    • If the call converted into a sale
    • The intent of the lead to purchase
    • Specific ad or campaign feedback, including detection of the ad being misleading to the customer
  • Attribute all insights back to the original lead source

 

All this data was surfaced in the Conversely Lead Insights Dashboard, giving our client clear intelligence on which lead sources were outperforming others without any manual intervention.

Results

Within 30 days, our client saw measurable improvements:

  • 22% reduction in cost per acquisition (CPA) by optimizing the call routing strategy
  • Stronger buyer relationships by proactively offering higher-quality leads and pointing out under-skilled agents

 

Perhaps most importantly, the confidence provided by accurate call-level data allowed our client to move away from pricing leads on call duration, and instead offer performance-based pricing models:

  • Cost Per Acquisition (CPA)
  • Cost Per Qualified Lead (CPQL)

Conversely AI enabled this lead generation client to:

  • Turn subjective guesswork into objective call intelligence
  • Reduce waste in lead spend
  • Prove the value of every lead with hard metrics

With these tools, our client went from flying blind to becoming a trusted performance partner for their lead buyers — unlocking better revenue and buyer growth across the board.

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