# Competlab Customer Voice Snapshot > Snapshots competitor presence on review platforms (G2 + Capterra + Trustpilot) and recent complaint themes. **Snapshot-only — limited coverage by design** because review-platform bot-blocking is universal (G2 + Trustpilot return 403 to all WebFetch attempts). Uses Perplexity-grounded answers as primary source, with URL verification for citations. Use when the user asks "what do customers say about competitor X", "G2 reviews for [competitor]", "complaint themes for [competitor]". For trend / velocity / sentiment-delta — requires dimension promotion (not this skill). Requires CompetLab MCP + Perplexity MCP + URL verification. - Skill: `competlab/competlab-customer-voice-snapshot` (Agent Skill) - Install (CLI): `npx skillmds@latest add competlab/competlab-customer-voice-snapshot` - Raw SKILL.md: https://api.skillmd.com/api/skills/competlab/competlab-customer-voice-snapshot/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - License: MIT - Author: competlab (https://skillmd.com/u/competlab) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/competlab/competlab-customer-voice-snapshot --- # Customer Voice — Snapshot You produce on-demand snapshot of competitor review-platform presence + recent complaint themes. **Limited scope by design.** ## Why limited scope - G2 product-page WebFetch → HTTP 403 universally (battletested 24+ product pages, 6/6 categories) - Trustpilot → HTTP 403 identically - Capterra → HTTP 200 sometimes but wrong-product redirects (catalog-ID collision) Perplexity recovers snapshot counts + ratings for 25-100% of vendors depending on category, but velocity / sentiment-trend / themes-delta is structurally invisible without persistent scraping. For: - Real-time review-velocity monitoring → dimension promotion required - Sentiment-trend reversal detection → dimension promotion required - Recurring complaint themes with monthly delta → dimension promotion required This skill: snapshot. Decision criteria for dimension promotion: customer demand signal post-skill-ship. ## Workflow ### Step 1: Identify competitors list_projects + list_competitors. ### Step 2: For each competitor, Perplexity-snapshot query ``` "For [Company] in [Category] in 2026: (1) G2: review count + average rating + 1-2 recurring complaint themes from recent reviews (2) Capterra: review count + average rating (3) Trustpilot: review count + average rating (if B2C-adjacent like Stripe, Klarna) (4) Any Reddit/HN/X recurring discussion themes Cite specific sources for each claim." ``` ### Step 2.5: Categorical-absence early-halt rule (banked from real-world validation) **If the first 2-3 Perplexity queries return "no data found" / "no G2 presence detected" for ALL 3 platforms** — the category likely doesn't review on standard B2B SaaS platforms. Examples of categorical-absence patterns: - **Hospitality / vacation rental tools** — buyers find these via Reddit r/AirBnB, r/Hosting, r/vacationrentals, STR Facebook groups, host conferences. NOT via G2 / Capterra / Trustpilot. - **Indie-developer tools** (early-stage AI tooling) — buyers find via Hacker News, Twitter, Reddit r/ChatGPTCoding. NOT via standard B2B SaaS platforms. **Action on categorical absence:** 1. Halt remaining Perplexity queries (don't waste budget on 9 identical null returns). 2. Document the finding in output: "Category absent from G2/Capterra/Trustpilot — buyers discover via [actual channels for this category]." 3. Optionally suggest alternative channels for customer-voice signal (Reddit search via Perplexity recency=month, conference-presence detection, etc.) but mark these as out-of-scope for the snapshot skill. 4. Return early — don't synthesize per-vendor docs with all "no data" cells. ### Step 3: URL-verify every cited source Per `PATTERN-url-verification.md`: every Perplexity-returned URL gets probed via `mcp__competlab__fetch_url` with `cleanHtml:true` before surfacing in output. Drop citations that 404. Validate count claims against source page where possible (G2 page may be 403-blocked even via fetch_url — flag honestly when can't verify). ### Step 4: For B2C-adjacent vendors, split B2B vs consumer reviews For a B2C-adjacent payments / fintech vendor, expect the typical signature: thousands of B2B G2 reviews + tens-of-thousands of consumer Trustpilot reviews + small Capterra tail. **Split the output** — B2B G2 numbers and consumer Trustpilot numbers represent different signal classes. The consumer-review tail is often orders of magnitude larger than the B2B count, AND consumer sentiment frequently runs lower (1-2★ Trustpilot averages are common for support-friction-prone vendors). When you see this pattern, the B2B signal is the procurement-trust read; the consumer signal is the brand-reputation read; both matter, neither substitutes for the other. ### Step 5: For developer-tool categories, Perplexity Reddit/HN For categories like AI-coding where G2 surface is thin (validation runs in this category yielded 0 of 8 vendors with G2 data), Perplexity Reddit/HN recovery is rich (specific dated discussion posts with upvote counts). Use as primary signal for those categories. ### Step 6: Synthesize per-vendor + cross-vendor Per vendor: - G2 count + rating (or "blocked, can't verify") - Capterra count + rating - Trustpilot count + rating (if B2C-adjacent) - Recent recurring complaint themes (1-2 max) - Recent recurring praise themes (1-2 max if useful) - Coverage gaps (which platforms had no data) Cross-vendor: - Review-volume comparison (e.g., "established competitor 5,000+ G2 vs new entrant 0 G2 reviews") - Highest-rated / lowest-rated competitor signal - Category complaint patterns (e.g., "all vendors in this category get complaints about admin complexity") ## Output Structure ``` # Customer Voice — [Category / Project] > Generated [date] | Snapshot only | Coverage: X of N vendors yielded G2 data via Perplexity ## Summary [Review volume range, top complaint themes across category] ## Per-competitor ### [Competitor] - G2: [count] reviews, [rating]★ | [main complaint themes — 1-2] - Capterra: [count] / [rating] | [if different from G2] - Trustpilot: [count] / [rating] | [if B2C-adjacent] - Reddit/HN: [recent discussion themes if developer-tool category] ## Cross-competitor patterns [Volume comparison, category-wide patterns] ## Coverage gaps [Which vendor × platform pairs returned no data] ``` ## Decision Questions 1. *"Should we run a G2/Capterra review-velocity campaign?"* — if we're under-represented vs category leaders 2. *"Are recurring complaint themes for top competitors something we can target in messaging?"* ## Error Handling - **Perplexity returns "no data" on first 2-3 queries for a vendor:** invoke the categorical-absence early-halt — stop further probing, record vendor as "no review-platform presence detected." Reflects either nascent vendor or category where reviews live elsewhere (Reddit / HN / conferences). - **G2 / Capterra / Trustpilot URLs bot-blocked (403/CloudFront on `fetch_url` verification):** expected behavior — review platforms reliably block automated scrapers. Record vendor as "G2 presence detected per Perplexity citation, count + rating not independently verifiable" rather than fabricating numbers from unverified output. - **Perplexity returns review count + rating without verifiable URL:** strip the unverified numbers; report only the qualitative complaint themes Perplexity surfaced (those are recovery-tolerant). Never publish a specific review count without URL verification — Perplexity often hallucinates plausible-sounding counts from category averages. ## What NOT To Do - Don't fabricate review counts. URL Verification is mandatory. - Don't claim sentiment trends from snapshot alone — say "current complaint themes" not "increasing complaints" - Don't include G2 numbers Perplexity returned without verifying against G2's actual page (Perplexity may overstate or invent based on category-association)