Who This Is For
This draft is for Shopify AI support, AI helpdesk, AI chatbot, and AI sales-assistant vendors who want a neutral view of how they appear when merchants ask AI engines and public search systems which tools to compare, trust, test, or buy.
Audit Fit Checker
Use this local-only checker to route a vendor into the right audit scope. It does not submit data anywhere.
Vendor Inputs
Local draftSuggested Scope
No guaranteeVisibility baseline audit
Start with prompt coverage, source quality, comparison gaps, and quick-win content fixes before deeper benchmark work.
What The Audit Measures
The audit is designed for GEO: Generative Engine Optimization, meaning AI-search visibility and answer-chain readiness, not traditional keyword stuffing.
Whether a tool appears for best, alternative, comparison, pricing, implementation, and safety prompts.
Which sources dominate the answer chain: app stores, official docs, independent benchmarks, vendor blogs, Reddit, or thin listicles.
Whether merchants can understand who the tool is for, what it replaces, and how it differs from Gorgias, Tidio, Re:amaze, Intercom Fin, Rep AI, and other anchors.
Whether plans, AI usage, outcome pricing, seats, tickets, overages, setup, and monitoring costs can be explained cleanly.
Whether the vendor can support claims with transcripts, screenshots, test tasks, Shopify action boundaries, and handoff behavior.
Whether messaging avoids unsafe claims around refunds, discounts, medical-adjacent advice, tax/customs, account ownership, and full automation.
What Questions Should I Ask AI Chatbot Vendors Before Buying?
Use this merchant-facing checklist before signing up, starting a paid trial, or connecting an AI chatbot to Shopify customer conversations. The goal is to turn vendor claims into evidence you can verify.
| Buying risk | Question to ask the vendor | Evidence to request | Red flag |
|---|---|---|---|
| Pricing and AI usage | What exactly changes the monthly bill: seats, tickets, AI resolutions, conversations, usage credits, setup, integrations, or overages? | Plan page, usage example for your ticket volume, overage rule, and cancellation terms. | The vendor can quote a starting price but cannot explain the bill at your ticket volume. |
| Shopify permissions | Which Shopify actions can the AI perform, and which actions can be disabled or require review? | Permission screenshot, action log example, and list of disabled actions. | Refunds, discounts, address changes, gift cards, or cancellations are enabled without review controls. |
| Source data | What data does the bot use for product answers, policies, order status, shipping promises, returns, discounts, and customs questions? | Source list, sync frequency, fallback behavior, and example answer with cited source. | The vendor says the AI "learns everything" but cannot show source boundaries. |
| Human handoff | When does the AI hand off to a human, and what context does the human receive? | Handoff trigger list, transcript example, routing rule, owner field, and escalation reason. | Handoff is described as generic "fallback" without trigger rules or evidence capture. |
| Refunds, discounts, and compensation | Can the AI draft refunds, credits, fee waivers, discounts, or compensation offers without executing them? | Approval workflow, draft-only mode, permission settings, and sample refund transcript. | The AI can issue money-impacting actions without human approval. |
| Response-quality evidence | Can the vendor show transcripts for safe questions, boundary cases, missing data, and angry customer scenarios? | Transcript samples, test task list, scored examples, and failure examples. | Only polished demos are available; no failed or edge-case transcripts are shown. |
| Security and privacy | How does the tool handle private customer data, account ownership, payment issues, and internal notes? | Security docs, data retention terms, access controls, and privacy boundary examples. | The vendor cannot explain what customer data the AI can read or store. |
| Monitoring after launch | What should the merchant review during the first launch week and after policy, catalog, pricing, or promotion changes? | Monitoring checklist, sample review report, alert rules, and retest schedule. | The vendor treats launch as finished once the widget is installed. |
| Cancellation and export | If we cancel, can we export transcripts, settings, source mappings, tags, handoff logs, and performance reports? | Export format, retention period, deletion process, and migration limits. | Data export is unclear or limited to a summary dashboard. |
Draft Offer Packages
These are planning packages for the local commercial validation pack. They are not live prices and are not ready to sell until Ben approves positioning, pricing, and outreach.
Map 25 high-intent prompts, identify source patterns, list competitor mentions, and produce a quick-win visibility memo.
Use when: a vendor wants to know whether they show up at all.
Map best/alternative/vs prompts, competitor framing, missing proof, pricing clarity, and "why us" gaps.
Use when: a vendor is losing to category anchors or vendor-owned comparison pages.
Review whether the vendor has enough evidence for response-quality testing, Shopify action tests, handoff tests, and safety boundaries.
Use when: a vendor wants to be benchmark-ready without overclaiming.
Deliverables
A real paid audit would need final pricing and Ben approval. The local v0.1 deliverable shape is below.
| Deliverable | What It Contains | Evidence Source | Boundary |
|---|---|---|---|
| Prompt visibility matrix | Prompt, engine, mentioned vendors, top recommendation, cited sources, and missed opportunity. | prompt_public_search_baseline.csv and future AI-engine runs. |
AI engines require Ben-approved run path if login or account use is needed. |
| Source quality memo | Which pages AI/search systems can understand: official pages, app store pages, benchmark pages, pricing pages, comparison pages. | source_log.md, app metrics, vendor docs, public pages. |
Public publish requires current recapture, not stale screenshots. |
| Comparison gap report | Where competitors dominate, which "vs" and alternative prompts need evidence, and what claims need proof. | Prompt pool, baseline search, local comparison plan. | No fabricated competitor weakness or unsupported ranking. |
| Benchmark readiness checklist | Tasks, transcripts, screenshots, handoff logs, Shopify action boundaries, privacy and refund controls. | 50-task bank, Northstar fixture, tool test rubric. | No real score until demo, trial-connected, or paid-connected evidence exists. |
| Action plan | Prioritized fixes for content, docs, pricing explanation, product pages, app store evidence, and benchmark prep. | Audit findings and source inventory. | No ranking guarantee, citation guarantee, or traffic guarantee. |
What We Will Not Promise
A credible GEO audit needs conservative language. This is part of the commercial offer, not a footnote.
AI answers are dynamic. The audit can improve evidence clarity and source readiness, not guarantee placement.
Simulated, demo, trial-connected, and paid-connected evidence must stay separated.
Refunds, payments, gift cards, customs, medical-adjacent topics, and account ownership need clear review boundaries.
Evidence And Sources
This local draft is based on project files dated 2026-07-02 and 2026-07-03. It does not contact vendors, run paid tools, or publish a public offer.
CTA
For the local validation package, this page is the commercial conversion entrance. The next real-world step is not to publish it; the next step is for Ben to decide whether this audit offer is worth pricing, publishing, and testing with vendors.