Useful AI service depends on accurate sources, clear permissions, and an accountable review process.
Understand the job you are hiring it to do
Write down the customer problems the assistant should solve. Product discovery, policy questions, and order support each rely on different information and actions. A specific brief makes it easier to judge the result.
Gather example conversations from your store and remove personal details where they are unnecessary. Use these as evaluation scenarios rather than relying entirely on a vendor’s demonstration.
Check where the answers come from
Ask which catalog, policy, and knowledge sources the assistant can access and how updates reach it. Test conflicting information and missing information. A responsible answer should reflect uncertainty when the source is incomplete.
Decide what the assistant may do
Reading order information is different from changing an order. Map each action to the required verification and permissions. Make the distinction visible in your setup and your test plan.
Ask about data processing, retention, and subprocessors. Your team should know where conversation data goes and how a deletion request is handled.
Keep a person responsible for quality
Choose an owner for conversation review, policy updates, and escalation testing. Track answer quality as well as operating metrics. When a question is answered incorrectly, improve the source or the boundary and retest the scenario.
Try the idea in your own store.
Explore the assistant and see how a useful conversation feels.
Experience Convi