Landing Page Critique Chat

Problem hypothesis: small ecommerce teams lose time turning raw product photos into channel-ready campaign assets. Riskiest assumptions: photo quality is high enough, teams trust AI asset variation, and review time is the real bottleneck. Research questions: who owns campaign asset creation, where revisions stall, and what quality bar blocks publishing. Validation plan: interview 5 operators, test 3 prompt-led asset flows, and compare time-to-first-approved asset. Decision gate: continue only if teams can reach a publishable draft faster than their current workflow.

Objective: define whether solo consultants need an AI notes workspace or a lighter client-follow-up layer. Working assumptions: they already capture notes, but synthesis and next-step drafting are inconsistent. Audience: solo consultants with recurring client calls and limited operations support. Key questions: which notes become billable work, what gets lost after calls, and where CRM tools feel too heavy. Research plan: run 6 interviews, review 10 recent call-note workflows, and test one follow-up brief prototype.

Issue type: repeated export failure plus refund request. Customer-facing reply: acknowledge the failed attempts, apologize plainly, and confirm you will help recover the export path first. Policy boundary: explain refund eligibility only from the provided policy notes; do not promise an exception. Next step: ask for export format, browser, and timestamp, then route to billing if the account meets refund criteria. Internal note: tag as product reliability risk because the same export failed twice.