We test your live chatbot with realistic customer conversations and show exactly where it fails, why it fails, and what to fix first.
You will see whether the problem is bad knowledge, weak escalation, policy confusion, hallucinated answers, inconsistent responses, poor setup, or a bot that marks conversations resolved when customers still need help. You get transcripts, severity ratings, failure patterns, source comparisons, and a ranked action plan in a one-off report delivered in 5 to 7 days.
Deflection, CSAT, and closed-chat metrics tell you the conversation ended. They do not tell you whether the customer left with the correct answer, whether the bot contradicted your returns policy, whether it escalated too late, or whether it gave away margin to calm someone down. That is the gap this audit fills.
Closed does not mean solved. A chat can end, get marked resolved, and still leave the customer with the wrong return window, an unauthorised discount, or an answer that contradicts your policy. This audit reads the conversations you never had time to, and tells you which ones went wrong and why.
Every audit runs the conversations your real customers have, then scores the bot on accuracy, resolution, commercial risk, and how it holds up under pressure. Each answer is checked against your actual policies and product truth.
We build a persona roster matched to your real customer base: everyday shoppers, frustrated customers, policy edge cases, refund and discount pushers, repeat-contact customers, and pre- and post-purchase buyers. A small adversarial set probes the edges. Every persona is grouped so the report tells you not just what broke, but who broke it.
You send the chat URL and the policies the bot speaks to. No backend, no API, no access to your model or helpdesk.
Personas behave like real ecommerce customers across pre-purchase, post-purchase, complaint, edge-case, refund, discount, escalation, and adversarial journeys.
Every flagged answer is checked against your policies, product information, and support goals, so a finding is a real gap, not a matter of opinion.
Transcripts, flagged exchanges, severity ratings, source comparisons, root-cause notes, failure patterns, and ranked fixes, in one shareable PDF.
The report is written to help your team decide what to fix first, what to hand your chatbot vendor, and whether the current setup is worth improving or a switch is the smarter next move.
A single synthetic customer, replayed. Every exchange is checked against your policy and either held or flagged. Nothing here touches your infrastructure. It is all just conversation, through the same chat window a shopper uses.
Every audit maps the conversations your customers actually have. Each category is probed across multiple personas, then scored by how often the bot got it right and the worst tier we reproduced.
Each finding names the failure, shows what the customer asked and what the bot said, explains why it matters, states how often it reproduced, and gives a recommended fix. Illustrative examples below.
Every finding clears a bar before it is classified. It ships with the exact message sequence that triggered it, so you can paste it into your own chat and watch the failure happen. Findings are sorted into four commercial tiers.
Wrong policy, unauthorised refund or discount, unsafe answer, privacy issue, or serious compliance issue.
Lost sale, bad product guidance, unnecessary discount, avoidable handoff, or refund leakage.
Unresolved issue, confusing answer, poor escalation, inconsistent tone, or repeat-contact risk.
A directional pattern that needs more data, but is not yet severe enough to call critical.
Not a slide deck, not a dashboard export. Written so your CX lead, ecommerce manager, support manager, or chatbot vendor can act on it immediately.
Executive summary, tiered findings, methodology, and appendix.
Every conversation, end to end, across all personas.
The offending message highlighted in context. Shown, not described.
Each flagged answer set against your real policy and product truth.
How often the bot actually solved the issue, not just closed it.
Where the bot should have handed off to a human, and whether it did.
Where the bot gave away margin, and under what pressure.
Root-cause notes and vendor-ready fixes, ranked by impact and effort.
A sample audit output showing the format, evidence standard, and finding structure. Brand and conversations are fictionalised for illustration; the format and evidence standard are real.
Yes, and you should. But transcripts only show what happened with customers who already contacted you. We test the situations most likely to break the bot, including policy edge cases, frustrated customers, repeated reframing, refund and discount pressure, inconsistent answers, and chats that look closed but were not truly resolved.
No. Red-team testing is included, but it is not the main offer. The main goal is ecommerce support quality: accuracy, resolution quality, escalation timing, refund and discount risk, customer clarity, and avoidable ticket reduction.
No. We use the customer-facing chat interface, the same way a shopper would. You provide your policies and context so we can compare answers against source truth.
No. The test is conversational. We do not exploit infrastructure, touch customer data, or require API access.
That is a useful outcome. You get a clean report showing what was tested, where the bot held up, and any watchlist areas to keep an eye on.
This offer gives you the diagnosis, transcripts, root-cause notes, and ranked fixes. Your team or chatbot vendor applies the changes.
Yes. The audit is not a platform comparison, but it can show whether the failures look like knowledge-base issues, escalation issues, policy setup issues, chatbot behaviour issues, or limitations in the current system. That can help you decide whether to improve the current setup or consider switching.
Send us your chat URL and a brief description of your brand. We'll follow up within one business day.
Takes 3 minutes to request. No prep work, no model access, no developer involvement. Commission by email, receive by email, act with your team.
One audit. One fixed price of £1,500. One report, delivered in 5 to 7 days. No integration, no backend access, no recurring commitment.