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Module 05 · Operations and Growth

AI-Assisted Customer Service Replies at Scale

20 minfocused lesson5practical steps5completion checks3source links
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On this lesson

Course outline

AI can draft consistent replies, but customer service is a decision system with privacy, policy and escalation boundaries. Automate preparation first. Keep refunds, safety issues, legal threats, account/payment disputes and unusual promises under human control.

// concept

Build an Approved Answer Desk

Create source cards for delivery, returns, warranty, sizing/specifications, payment, order changes and escalation. Each card needs an owner, approved wording, source/policy link and review date. When policy changes, update the card before the prompt.

Classify sanitized enquiries by intent and risk. Low-risk factual questions may receive a reviewed draft. Medium-risk cases require record lookup. High-risk cases go directly to a human.

// prompt — copy me4 lines
Draft a reply using only the approved answer cards and sanitized case facts.
Do not promise dates, refunds, replacements, stock, warranty or outcomes not present.
If evidence is missing, ask one precise question or output ESCALATE.
Return: intent, risk, draft, facts used, facts still needed.

// worked_example

Worked Example

Customer message: “My parcel has not arrived and I need it tomorrow.” The sanitized record contains order ID, platform status and the current courier event—no name, phone or address. The AI draft initially says “It will arrive tomorrow.” That is rejected.

The approved response acknowledges the delay, states only the visible status, explains the next permitted check and avoids a delivery guarantee. If the order is marketplace-managed, the reply follows the current marketplace flow rather than inventing a separate promise.

Sample replies belong in a test set. Keep expected risk, required facts and acceptable outcome for recurring cases, then review the prompt whenever a policy card changes. A fluent response that violates one condition must fail the test even if its tone is excellent.

// failure_cases

Failure Cases to Diagnose

5 cases to diagnose

  • Uploading full customer chats, addresses or payment screenshots.

  • Training templates from outdated policy.

  • Auto-sending an apologetic but false delivery date.

  • Treating sentiment as proof that a refund is owed or fraudulent.

  • Hiding escalation to keep response-time metrics low.

// pakistan_angle

Pakistan Angle

Offer English, Urdu or Roman Urdu where your team can review it accurately. Keep prices, dates, sizes and policy conditions literal. Voice notes may need human handling; do not upload them to third parties without a lawful, disclosed reason.

// hands_on

Hands-On Exercise

5 steps

  1. Create seven answer cards with owners and review dates.

  2. Define low, medium and high-risk routing.

  3. Test the prompt on delivery, return and product questions.

  4. Insert one missing fact and confirm the model escalates.

  5. Review five drafts for factual and tone errors.

// completion_rubric

Completion Rubric

5 checks — tick as you verify

0/5

// sources

Sources

3 official sources — check every claim yourself