Spark playbook scenarios · Spark: AI Store Assistant

Structure a maintainable customer support knowledge base

Support repeatedly answers the same questions from inconsistent or outdated references. In this case, the immediate task is to structure a maintainable customer support knowledge base. The workflow should produce a support knowledge base outline and grounded FAQ answers, using the merchant's actual records and constraints.

Topic

Support FAQs and Knowledge Base

Target keyword

shopify customer support knowledge base

Copyable AI prompt

A prompt you can drop directly into Spark

First replace every [bracketed] placeholder with real store scope and constraints, then add any actual records or data you have, and paste it into your preferred AI assistant or Spark agent. Spark will follow this page's workflow to produce structured output and verification steps.

ai-prompt.txt

Act as a Shopify operations specialist.
Help me structure a maintainable customer support knowledge base.
My store context is [describe the business, products and target audience].

My scope is [specify the affected products, pages, customers or reporting period]. Use these inputs: [provide approved product and policy documents, repeated questions, document owners and update dates]. Organize answerable topics, resolve conflicting sources and define a fallback for unanswered questions.
Return a support knowledge base outline and grounded FAQ answers for the specified task.
Show the relevant evidence or before-and-after examples and explain how I can verify the result.
If essential data is missing, ask for it and mark unsupported conclusions as unknown.
Do not invent metrics, product claims or customer facts.
For any publication, message, account or store change, use only connected tools within my explicitly authorized scope and report success only after verification; otherwise provide the draft or proposed steps.

Use in Spark

Scenario & problem

When does this scenario usually come up?

Start with the business context, the trigger, and the expected output before moving into the execution steps.

How to solve

A recommended resolution workflow

Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.

Step 1

Start with approved product and policy documents, repeated questions, document owners and update dates.

Step 2

Organize answerable topics, resolve conflicting sources and define a fallback for unanswered questions.

Step 3

Deliver a support knowledge base outline and grounded FAQ answers; verify the result against the supplied records and identify unresolved inputs.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

Why record the source and update date?

Policies and product details can change. Traceability helps maintain accurate answers.

Can a knowledge base eliminate every support request?

No. Unusual orders and ambiguous situations still require individual investigation.

What information is needed to investigate this use case?

Start with approved product and policy documents, repeated questions, document owners and update dates. These inputs establish the relevant scope and help separate an actual issue from missing information or an unsuitable comparison. Without them, the result should remain a proposed approach rather than a confirmed diagnosis.

Related scenarios

Continue with adjacent or same-topic scenarios

Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.

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Open scenario

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