Expected output
The deliverable should include Draft response, Evidence used, Required lookups, Next step, and Escalation decision.
IntermediateCustomer Service & Retention AI
Online Customer Support | Diagnostic Analysis Prompt
Online Customer Support | Diagnostic Analysis Prompt is a copyable AI prompt for ecommerce sellers. Use it to answer pre-sales and common support questions quickly, accurately, and in line with policy from verified business inputs. Copy the full instruction, add your inputs and check the result before use.
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How the Online Customer Support | Diagnostic Analysis Prompt works
Answer pre-sales and common support questions quickly, accurately, and in line with policy from verified business inputs. The prompt identifies data gaps first, ranks findings by evidence strength, and ends with phased actions that require human review.
Key instructions and output
The points below describe the task and expected output in this prompt.
Parameter guide
Prepare the task information listed below and replace placeholders with verified details from the actual case.
[Knowledge base]
Replace this placeholder with verified, task-specific information before running the prompt.
[Product and order tools]
Replace this placeholder with verified, task-specific information before running the prompt.
[Brand voice]
Replace this placeholder with verified, task-specific information before running the prompt.
[Customer question]
Replace this placeholder with verified, task-specific information before running the prompt.
[Escalation conditions]
Replace this placeholder with verified, task-specific information before running the prompt.
Copy the complete prompt
The complete source is shown below. Copy it from the top right to use it.
You are an ecommerce support operations and AI service designer. Your objective is to answer pre-sales and common support questions quickly, accurately, and in line with policy. Analyze the following real inputs: [Knowledge base], [Product and order tools], [Brand voice], [Customer question], [Escalation conditions]. First list data gaps and definitions that need confirmation. When information is missing, mark it as 'To be confirmed' rather than guessing. Then provide: (1) key findings and supporting evidence; (2) prioritized root causes or opportunities using impact × evidence strength; (3) Draft response, Evidence used, Required lookups, Next step, Escalation decision; (4) executable actions for the next 7, 30, and 90 days; and (5) risks, counterexamples, and assumptions requiring human validation. Special requirement: Do not invent order status, inventory, or policy. Verify and escalate payments, identity, refunds, and exceptional commitments.Test this prompt on a real task
Copy a starter instruction, add the required inputs, then run one example and review the output.
01Online Customer Support | Diagnostic Analysis Prompt
The deliverable should include Draft response, Evidence used, Required lookups, Next step, and Escalation decision. Diagnose online customer support issues and prioritize evidence-backed action
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Online Customer Support | Diagnostic Analysis Prompt
The deliverable should include Draft response, Evidence used, Required lookups, Next step, and Escalation decision. Diagnose online customer support issues and prioritize evidence-backed action
You are an ecommerce support operations and AI service designer. Your objective is to answer pre-sales and common support questions quickly, accurately, and in line with policy. Analyze the following real inputs: [Knowledge base], [Product and order tools], [Brand voice], [Customer question], [Escalation conditions]. First list data gaps and definitions that need confirmation. When information is missing, mark it as 'To be confirmed' rather than guessing. Then provide: (1) key findings and supporting evidence; (2) prioritized root causes or opportunities using impact × evidence strength; (3) Draft response, Evidence used, Required lookups, Next step, Escalation decision; (4) executable actions for the next 7, 30, and 90 days; and (5) risks, counterexamples, and assumptions requiring human validation. Special requirement: Do not invent order status, inventory, or policy. Verify and escalate payments, identity, refunds, and exceptional commitments.Inputs to replace in this prompt
[Knowledge base]- Replace this placeholder with verified, task-specific information before running the prompt.
[Product and order tools]- Replace this placeholder with verified, task-specific information before running the prompt.
[Brand voice]- Replace this placeholder with verified, task-specific information before running the prompt.
[Customer question]- Replace this placeholder with verified, task-specific information before running the prompt.
[Escalation conditions]- Replace this placeholder with verified, task-specific information before running the prompt.
What to check before using the output
The generated result is a draft; check claims, numbers and operating conditions against source data before publishing, importing or acting on it.
Operating note 1
Replace every placeholder before running the prompt, and label key figures with their source, date range, and definition.
Operating note 2
Do not invent order status, inventory, or policy. Verify and escalate payments, identity, refunds, and exceptional commitments.
Operating note 3
Before uploading order, customer, contract, or supplier data, redact sensitive information and comply with platform terms, privacy policies, NDAs, and company data-governance requirements. Have the responsible operator review the result before it is published, sent, or executed.
Source & attribution
Compilation note and reference material
This section identifies the prompt’s creator and source, and marks details that could not be verified.
Vendolune
This Prompt was compiled by Vendolune from the scenario requirements and public reference material. The reference-page author is not credited as this Prompt's author.
Reference materialGorgias
This link is reference material and does not establish its page author as the author of this Prompt. The article provides prompts for analyzing low-CSAT causes, AI-to-human handoffs, customer friction, intents, and macro-coverage gaps from real tickets and support data.
The original page does not publish a rating, review, Product Hunt upvote, star, fork, install, or download count.
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