NM Signals vs Verity Score: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of NM Signals and Verity Score — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
NM Signals
Nyman Media
Audits whether AI crawlers and assistants can actually read your website, then tracks how often they mention your brand.
Key features
- AI Readiness Audit: Scores a public URL across 106 checks in six categories — crawlability, structured data, entity clarity, content structure, answerability and trust signals — for a readiness score out of 100.
- Served-vs-Rendered Comparison: Measures how much of the browser-rendered page survives a fetch-only request, flagging JavaScript-dependent content that non-rendering AI crawlers never see.
- AI Crawler Access Checks: Reports robots.txt, canonicals, redirects and status codes specifically for AI crawlers such as OAI-SearchBot, not just traditional search bots.
- UX Review with Developer Brief: Runs a separate usability pass with visual layout analysis on paid plans and produces a copyable brief a developer can work straight from.
- Saved Action Plans: Keeps an audit as a private baseline, lets you rank findings by priority, and records implementation progress against it.
- Generated Fixes and Verification: Premium plans generate implementation guidance for a selected finding and verify the change against a fresh audit rather than trusting a checkbox.
- AI Answer Snapshots: Asks the same five core questions weekly with three samples each, deciding by majority whether the brand is named, and charts the trend against tracked competitors.
- Programmable Surface: A public REST API, CLI and MCP server let audits run inside CI/CD pipelines or be called directly by AI agents.
Best for
- AI Search Readiness: Find out why an AI assistant summarizes a competitor's page instead of yours and fix the specific access or rendering issue behind it.
- Pre-Launch QA: Audit a new marketing site before launch to catch blocked crawlers, missing markup and unreadable server-rendered content.
- CI/CD Regression Guards: Call the REST API or CLI on every deploy so a rendering change that hides content from crawlers fails the build.
- Brand Monitoring: Track weekly whether AI assistants name your brand in answers to the questions your buyers actually ask.
- Agency Reporting: Produce white-label PDF audits and score comparisons for client sites on the Partner plan.
- Content Restructuring: Use heading/body agreement and attribution checks to rewrite pages into retrievable, quotable sections.
Verity Score
Kamil Kaderbay
Shopify app that audits how ChatGPT, Perplexity, Gemini and Claude read your products, then generates and applies the exact fixes.
Key features
- Prompt Tracking: Regularly asks ChatGPT, Perplexity, Gemini and Claude the questions your buyers ask before purchasing, storing each answer verbatim with its sources so you can see your proposal rate per assistant and which competitor gets cited instead.
- AI Buyer Score: Replays an autonomous shopping agent's decision against your store across 8 dimensions — product discovery, understanding, proof checking and recommendation — and returns a binary verdict rather than a vague score.
- Correction Copilot: Generates the exact Shopify-specific fix for each detected issue, citing the precise URL and the verbatim observed text; nothing is written to the store without approval and every fix is reversible for 30 days.
- Anti-Hallucination Verification: Dozens of correctors cross-check each finding against pre-fetched structured data (schema.org, robots.txt, sitemap.xml, llms.txt), DOM analysis via headless browser and the raw HTML source, discarding uncertain findings instead of publishing them.
- AI Article Generation: Writes the blog posts, FAQs and translations that answer buyer questions your catalog leaves uncovered, built from the store's real product data and published only after you approve them.
- AI Traffic Monitoring: Connects visits sent by AI engines and assistants through to cart and order, so AI-sourced revenue is measurable rather than inferred.
- Sector Benchmarking: Ships checklists and reference benchmarks for 14 verticals — beauty, fashion, supplements, food, electronics, eyewear, pets, baby, sports, jewelry, home, kitchen, sleep and toys — including the regulated-claims angle for beauty and supplements.
- Shopify-Native Depth: Deliberately supports Shopify only, so fixes account for variants, markets, metafields, native themes, ProductGroup schema, Judge.me injection and Shopify Markets redirects.
Best for
- AI Visibility Audit: A merchant discovers which of their product pages ChatGPT and Perplexity cannot read because content is trapped in JavaScript or schema.org is incomplete.
- Competitive Recommendation Recovery: A brand sees which rival store an AI assistant names instead of theirs for a key buying question, and which page earns that citation.
- Structured Data Remediation: An operator fills in missing GTINs, prices, ratings and delivery times in product structured data so AI comparisons have something to work with.
- Content Gap Filling: A merchant turns recurring unanswered buyer questions into approved FAQ and blog content generated from real catalog data.
- AI Revenue Attribution: A marketing team measures how many Shopify orders originate from AI engines and assistants rather than classic search.
- Regulated-Vertical Compliance: A supplements or beauty store checks that on-page claims are backed by verifiable proof before AI assistants repeat them.