Most customer experience goals miss the mark, focusing on vanity metrics that don't genuinely help customers. Executives often pursue a single 'magic number,' ignoring service complexity. There’s a disconnect between leadership and frontline teams, with automation optimizing metrics but frustrating customers. AI can be a game changer for analyzing issues, yet poor goal-setting can distort success and punish effective automation. The hosts suggest shifting to customer-impactful outcomes to align goals with actual needs.
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insights INSIGHT
Goals Chosen For Optics, Not Impact
CX goals are often picked because they sound respectable, not because they solve customer problems.
John Goodman calls out how leaders choose arbitrary targets like a '3% increase' without customer evidence.
insights INSIGHT
Attention Drives Metric Choices
Attention and reward determine what teams optimize, so vanity metrics get prioritized.
Executives want a single magic number and prefer simple green/red reporting over complex truth.
insights INSIGHT
The Executive–Customer Incentive Gap
Customers and frontline agents align on wanting real human resolution while executives prioritize automation and cost.
This incentive gap explains why automation often frustrates customers despite executive approval.
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Most customer experience goals are meaningless. In this episode, Bob Furniss and Amas Tenumah dismantle the way contact centers set annual CX metrics and explain why leaders keep optimizing numbers that customers neither notice nor value.
Using insights from a John Goodman article on CX goal-setting, the conversation exposes the disconnect between executives, customers, and frontline teams—and why automation, deflection, and "respectable" percentage improvements often make service worse, not better.
This episode is about shifting from internally convenient metrics to customer-impactful outcomes.
What You'll Hear
Why CX goals are often chosen because they sound reasonable, not because they solve customer problems
How executives chase a single "magic number" instead of understanding service complexity
The fundamental incentive gap between customers and senior leadership
Why customers and frontline agents are aligned—but executives aren't
How automation and bots optimize company metrics while frustrating customers
Where AI actually helps: analyzing volume, root causes, and systemic friction
Why average metrics (ASA, AHT) distort reality and reward the wrong behavior
How poor goal-setting punishes leaders who successfully automate the "easy" work
The risk of letting someone else define your goals if you don't take control
A real-world example of automation done right—and how bad metrics mislabel it as failure
Key Takeaways
Vanity metrics don't fix customer experience
Deflection and containment may look good internally while actively harming trust
CX leaders must own the narrative or be trapped chasing numbers they don't believe in
AI should surface customer pain, not just reduce contact volume
Goals should reflect customer outcomes, not executive convenience
Resources Mentioned
John Goodman's article on CX goal-setting (referenced in discussion)
HOLD: The Suffering Economy of Customer Service by Amas Tenumah
Available on Amazon
Signed copies at waitingforservice.com
Who This Episode Is For
Contact center and CX leaders setting 2026 goals
Executives relying on NPS, ASA, AHT, or deflection as proxies for success
Practitioners tired of fixing the wrong problems
Anyone responsible for explaining service performance to leadership
Contact Center Show 