Long-form guides for CX leaders evaluating, deploying, or migrating to AI customer service. Grounded in production data from 1,000+ Richpanel customers — not category-survey theater.
Ungrounded LLMs hallucinate in 15–30% of customer service responses. Air Canada, DPD, and a Chevy dealer all paid the price. Here's the four-layer architecture — pre-launch evals, QA AI, deterministic tool execution, human fallback — that keeps production rates under 1%. Includes eight evaluation questions for your next AI vendor RFP.
A weighted 40-question RFP plus anchored 0 to 3 scoring across six dimensions (security, accuracy, workflow fit, implementation, support, pricing) and eight instant-disqualifiers. Built for mid-market CX teams running a formal evaluation across three to five vendors. Calibrated against roughly 1,000 Richpanel onboardings and 69 mid-market demo calls.
A chatbot generates text. An AI agent resolves the ticket. The five axes that separate the two (memory, retrieval, action, escalation, learning), why 25 of 69 demo prospects told us their incumbent AI does not work, and six verification questions for your next AI vendor demo.
Audit, pilot, data move, validation. The 2-week migration most mid-market teams expect to take 2 months. Covers triggers, automations, organizations, custom fields, attachments, and the integration reconfiguration nobody warns you about.
DTC subscription brands lose 4 to 8% of subscribers every month. Static save flows in Recharge, Skio, and Stay AI ceiling around a 5% save rate. The four-mechanism AI architecture in this playbook (intent inference, policy-bounded save offers as typed tool calls, contraindication detection, clean fallback) converts 10 to 15% of click-cancels into saves, pauses, or downgrades, without a dedicated CRO team. Includes a four-metric scorecard and eight pre-launch checks.
One email per published guide. No newsletter padding, no "10 ways to improve your CX." Just the next long-form best-practice piece when it goes live.
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