Ahrefs Brand Radar vs StoreCited: Which AI Visibility Tool Fits?
Ahrefs Brand Radar and StoreCited solve AI visibility jobs. Brand Radar combines Ahrefs’ search-backed prompt database with configurable prompt tracking and recurring competitive research. StoreCited provides a point-in-time Shopify/DTC storefront readiness scan. Choose Brand Radar for broad visibility intelligence, StoreCited for focused diagnosis, or both with their evidence layers kept separate.
Ahrefs Brand Radar fits teams needing recurring research across a modeled prompt database and tracked questions. StoreCited fits Shopify and DTC operators needing a dated diagnosis of public storefront signals. Their measurements can complement each other, but are not equivalent.
This comparison uses official materials observed on July 13, 2026. Ahrefs database scale, coverage, feature, and outcome statements are identified as dated vendor claims; pricing is dated because packaging changes. Search-backed prompts and configured checks remain samples, not complete private conversations, proprietary model indexes, or causal evidence.
What are Ahrefs Brand Radar and StoreCited designed to do?
Ahrefs Brand Radar is built for recurring visibility research across a large search-backed prompt index and configured prompt checks, while StoreCited is built for a dated Shopify/DTC storefront-readiness assessment. Brand Radar organizes sampled mentions, citations, impressions, share of voice, cited pages, domains, and competitors; StoreCited turns public storefront gaps into a prioritized report.
Ahrefs describes the product on the Brand Radar page and in its usage guide. StoreCited documents its point-in-time evidence standards in research. One researches recurring outputs; the other audits observable storefront inputs.
Which platform fits each buyer?
Choose Brand Radar when a team needs recurring large-scale research, competitor comparison, cited-page discovery, Ahrefs workflows, API access, or custom prompt tracking. Choose StoreCited when a Shopify or DTC operator needs a focused public-signal diagnosis, a free starting scan, and a fixed-price report without adopting an enterprise-scale monitoring subscription.
| Decision factor | Ahrefs Brand Radar | StoreCited | Evidence limit |
|---|---|---|---|
| Primary job | Recurring visibility research | Point-in-time readiness audit | Outputs versus inputs |
| Measurement unit | Modeled database and prompt checks | Scanned storefront signals | Neither is exhaustive |
| Research scope | Brands, products, regions, people | Shopify/DTC storefront | Different questions |
| AI surfaces | Package-dependent coverage | No prompt panel | Verify current platforms |
| Metrics | Mentions, citations, impressions, share | Readiness findings | Metrics are not outcomes |
| Competitive view | Cited pages, domains, competitors | Inferred category peers | Different methods |
| Reporting | Ahrefs reports and API | Downloadable report | Access depends on package |
| Custom depth | 2,500 checks in observed package | Not applicable | Configured sample |
| Price model | Monthly platform access | Free scan; $49 report | Packaging can change |
What does Brand Radar’s prompt database measure?
As observed on July 13, 2026, Ahrefs’ product page displayed more than 403 million total monthly prompts across its search-backed database. Treat that number as a dated vendor scale claim, not a census of private conversations. The page changes frequently, and modeled prompt volume, indexed answers, coverage, and freshness require separate interpretation.
Database breadth can surface patterns across brands, products, regions, people, cited pages, and domains. It cannot disclose every private prompt, personalized answer, or retrieval path. Recheck the live product page before citing its database total, because Ahrefs updates the displayed number frequently.
How does custom prompt tracking complement database research?
Database research and custom prompt tracking answer complementary questions. The database offers breadth for discovery across modeled demand, brands, products, regions, people, citations, pages, and domains; custom prompts add depth for questions you define. Neither approach captures every personalized answer or private user conversation, and neither establishes why visibility changed.
Ahrefs’ custom prompt setup guide describes the configured workflow. Keep prompt wording, platform, region, settings, run date, and changes with every observation. More checks can improve consistency without making the panel exhaustive or causal.
Which AI surfaces, metrics, fan-out queries, and reports are supported?
Ahrefs documents AI Overviews, AI Mode, ChatGPT, Copilot, Gemini, Perplexity, and Grok across current Brand Radar packaging, although product pages may describe six or seven AI surfaces as bundles change. It also documents AI visibility metrics, report creation, fan-out queries on supported surfaces, competitor comparisons, cited assets, and API availability.
Use Ahrefs’ guides for AI visibility metrics, report creation, fan-out queries, and the Brand Radar collection as vendor documentation. Confirm which surfaces expose fan-out data and API fields in your package.
How much does Ahrefs Brand Radar cost?
As observed on July 13, 2026, Ahrefs showed individual AI-platform access around $398 per month and All Platforms at $699 per month, including 2,500 custom-prompt checks monthly. The package also advertised bonus Reddit, TikTok, and YouTube beta access plus broader search and web visibility. StoreCited lists a free scan and $49 report.
Verify the live pricing and package details at checkout. Platform counts, database size, package names, custom-check limits, beta access, and prices can change. Compare required surfaces, API availability, search and web data, seats, and billing terms—not the headline number alone.
How do Brand Radar research and StoreCited readiness differ?
Brand Radar and readiness auditing answer different questions. Brand Radar observes modeled database records and configured outputs over time, while StoreCited inspects public storefront inputs at scan time: crawl access, structured product and Organization data, buyer-question coverage, evidence, policies, usability, and measurement. Neither layer reveals proprietary model indexes, guarantees citation, or proves revenue.
StoreCited does not live-monitor citations, generate publish-ready FAQs or exact schema, access proprietary model indexes, or observe every competitor selection. Google’s AI features guidance, Search Console performance report, and helpful content guidance are Google-specific evidence, not proof of visibility across private AI platforms.
When should you choose Brand Radar, StoreCited, or both?
Choose Brand Radar for large-scale, recurring AI visibility research inside Ahrefs; choose StoreCited for a focused Shopify/DTC storefront diagnosis; use both only when database research, custom prompt samples, and readiness findings support distinct decisions. Preserve dates, platform packages, query definitions, database scope, site evidence, and attribution limits instead of merging everything into one score.
Use this buyer checklist:
- Do we need database breadth, custom-prompt depth, or readiness evidence?
- Which AI surfaces, regions, products, and competitors matter?
- Can we preserve query definitions and comparable history?
- Which package, API fields, and check limits are required?
- Do we need Shopify-specific public-signal remediation?
- Will each dataset change a documented decision?
Compare AI visibility alternatives before buying. If storefront readiness is the unresolved layer, Run the free StoreCited readiness scan. Add Brand Radar only when its database, custom checks, and Ahrefs workflow justify their separate budget and governance.