Customer Support Coverage & Query Gap Report
Your help content might be live - but does it show up when it matters?
The Customer Support Coverage & Query Gap Report identifies where your customer service experience succeeds, where it fails, and where it’s completely missing — according to AI platforms like ChatGPT, Bing Copilot, Perplexity, and Gemini.
Today, users often turn to AI for answers before they visit your help center or contact support. If your support information isn’t discoverable or clearly structured, those users are getting the wrong answer — or no answer at all.
Who Is This For?
- CX and customer support leaders
- Operations and service quality teams
- SaaS and product-based companies with online help portals
- Brands aiming to reduce support friction and improve discoverability
What This Report Answers
- Which support questions are already answered correctly by AI?
- Where are users asking questions that your brand doesn’t appear for?
- Are your help topics structured and indexed properly?
- What common issues are repeated in LLM responses — and do they match your actual data?
- Where are there missed opportunities to preempt tickets or complaints?
What You'll See in the Report
We simulate real customer scenarios and service-related prompts across AI systems to identify support coverage, content visibility, and trust signals.
Key Data Points:
Answer coverage rate: % of key support prompts returning accurate, brand-aligned responses
Unanswered query log: Common customer scenarios where AI fails to provide a correct answer
LLM sentiment score for support mentions: Tone and confidence in AI-described service experience
FAQ and support page indexing audit: Schema completeness and prompt retrievability
Ticket deflection potential: Which issues could be solved if content were AI-discoverable
Brand mention trust markers: Is your brand cited as helpful, responsive, or unreliable?
Why It Matters
Customer experience doesn’t start on your website anymore.
When users ask AI for troubleshooting tips, setup help, or refund info — they expect fast, reliable answers. And if AI can’t surface yours, someone else’s (less accurate) answer might fill the gap.
This report helps you:
- Reduce support load by improving LLM-accessible help content
- Spot broken flows and outdated support data before customers do
- Build a reputation for service clarity and responsiveness — even in AI-driven channels
Data Sources
- Prompt simulations for top support scenarios (setup, billing, cancellation, etc.)
- Live testing across ChatGPT, Bing, Gemini, Claude, Perplexity
- Support content indexing audits (FAQ schema, sitemap coverage)
- Sentiment and trust scoring for support-related mentions
Deliverables
- 25–30 page AI support audit (PDF)
- Answer gap and misalignment report
- FAQ and help content schema checklist
- Ticket deflection opportunity list
- Optional workshop with CX strategist or documentation lead