Deflection Rate Is the Wrong AI Metric. Heres What Replaces It
- E549
- 43:48
- August 5th 2026
If your company has implemented a chatbot or AI agent in the past two years, you may be focusing on the wrong objectives, potentially resulting in significant revenue loss. In this episode of Predictable B2B Success, we interview Dvir Ginsberg, founder and CEO of Encore, whose innovative approach challenges traditional AI deployment strategies.
Many organizations rely on deflection rate, which measures how many customers an AI handles without human intervention. However, as Dvir Ginsberg explains, this metric can undermine customer satisfaction and obscure growth opportunities. Focusing solely on deflection rate overlooks more meaningful outcomes such as conversion and value.
Encore’s approach, known as “interaction mining,” analyzes real customer conversations before any automation occurs. This process uncovers hidden revenue, process gaps, and compliance risks, enabling AI to learn from top human performers and deliver more effective results.
This episode examines how compliance concerns differ across industries such as finance, retail, and manufacturing. It also explores the distinction between chatbots that only “sound” human and those that truly “act” human. We outline essential steps every business should take before their next AI rollout and offer new perspectives on achieving AI success.
Some topics we explore in this episode include:
- Deflection rate as a flawed metric
- Importance of interaction mining
- Revenue leakage from missed opportunities
- Training AI on top performer behaviors
- Compliance and liability risks of AI
- Shortcomings of prompt-based deployment
- AI unlocking new business models
- Need for continuous post-launch improvement
- Regulation accelerating AI adoption
- Organizational and cultural change for AI success
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