Retail Intelligence for Financial, Location & Grocery Data
RetailStat (retailstat.com) earns a Brand Analyzer score of 67 out of 100, placing it in the Developing tier among SaaS brands, Finance brands, Real Estate brands. Among 12358 SaaS brands analyzed, RetailStat ranks in the 36th percentile (category average 69, leader 97). The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark. Dimension scores: Name Quality 88/100, Digital Presence 76/100, Visual Identity 90/100, Messaging Clarity 95/100, Trust Foundation 72/100, AI Discoverability 48/100, Brand Authority 22/100.
RetailStat (retailstat.com) is a SaaS-based retail intelligence platform serving lenders, retailers, real estate teams, investors, and CPG brands. It combines proprietary data, market visibility, and expert insights to support credit risk assessment, location strategy, and grocery performance analysis. Positioned as a comprehensive retail database, RetailStat enables users to evaluate financial risk, identify market opportunities, and make informed decisions across North American retail and retail real estate industries.
| Brand Name | RetailStat |
|---|---|
| Domain | retailstat.com |
| Industry | SaaS, Finance |
| Main Competitors | Placer.ai, CoStar (64/100), Esri, Buxton, Datassential (74/100), SiteZeus |
Moz Domain Authority 55/100 vs category average 28 / leader 99 - a strong backlink profile, so AI systems frequently encounter mentions of the brand.
Ranked #1,455,858 on the Tranco list of most-visited sites - modest traffic makes the brand easy for AI models to overlook.
No Wikipedia presence was found - a major gap, since Wikipedia is among the most heavily weighted sources in AI training data.
The homepage meta description reads "RetailStat is a retail intelligence platform for financial risk, location strategy, and grocery performance, with data and insights for credit, site selection, and market analysis." (Meta description: 25 words (ideal length). No OG description (falling back to meta)) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: No structured data or Open Graph tags detected. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: robots.txt present, no AI bot restrictions - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Social footprint: verified profiles on LinkedIn, Instagram, YouTube; no detected presence on X (Twitter), Facebook, GitHub - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
RetailStat scores 22/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
RetailStat has a weak AI-visibility profile at 22/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (55/100) and its weakest is visibility (0/100). It benefits from a global traffic rank of #1,455,858 (Tranco), a Moz Domain Authority of 55/100 and open access for AI crawlers (GPTBot, ClaudeBot, etc.). The main gaps holding it back: no clear Wikipedia entity to anchor it in LLM training data, no strong Wikidata entry and thin schema.org structured data.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
RetailStat's main competitors include Placer.ai, CoStar (64/100), Esri, Buxton, Datassential (74/100). These companies compete in the SaaS space for similar customers, offering comparable products or services.
Sources: RetailStat official site
RetailStat and Datassential are competitors in SaaS. Brand Analyzer scores RetailStat at 67/100 and Datassential at 74/100. They target overlapping audiences; the right choice depends on your specific needs and priorities.
Sources: RetailStat official site
Popular alternatives to RetailStat include Placer.ai, CoStar (64/100), Esri, Buxton, Datassential (74/100). Each is an established option in the SaaS space; the best fit depends on your specific needs, budget, and required features.
Sources: RetailStat official site
RetailStat offers a retail intelligence platform that covers three core areas. First, financial risk monitoring tools designed for lenders and investors to evaluate credit risk in the retail sector. Second, location strategy and site selection capabilities for retailers and real estate teams. Third, grocery performance analysis and market intelligence for CPG brands and investors. The platform combines proprietary data, market visibility, and expert insights in a single SaaS environment.
Sources: RetailStat official site
RetailStat is a SaaS-based retail intelligence platform available at retailstat.com. It is described as the industry's most comprehensive retail database and intelligence platform, built specifically for teams driving retail performance and growth. It operates across three primary functional areas: financial risk monitoring, location strategy, and grocery performance analysis, serving the North American retail and retail real estate industries.
Sources: RetailStat official site
RetailStat has low AI-search visibility, scoring 22/100 on Brand Analyzer's AI visibility composite (visibility 0, trust 26, recommendation 55). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
Sources: RetailStat official site
RetailStat provides retail data and expert insights through a single comprehensive platform. It enables lenders to evaluate credit risk, helps real estate and retail teams with site selection and location strategy, and supports CPG brands and investors with grocery performance and market analysis. By combining proprietary data, market visibility, and expert insight, RetailStat allows its users to identify opportunities, assess risk, and make faster, more confident decisions.
Sources: RetailStat official site
RetailStat's platform is used by lenders, retailers, real estate teams, investors, and CPG (consumer packaged goods) brands. These users operate within the North American retail and retail real estate industries. Lenders use it for credit risk evaluation, retail and real estate teams use it for site selection and location strategy, and CPG brands and investors use it for grocery performance monitoring and market analysis.
Sources: RetailStat official site
RetailStat scores 55/100 on Brand Analyzer's AI recommendation signal, indicating it is reasonably likely to be surfaced when AI assistants like ChatGPT suggest SaaS options. Recommendation depends on crawlability, structured data, and category authority.
Sources: RetailStat official site
RetailStat can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
Sources: RetailStat official site
RetailStat is known for being a comprehensive retail intelligence platform that consolidates proprietary data, market visibility, and expert insights into one solution. It is particularly noted for its focus on three specialized areas: credit risk assessment for lenders, location strategy and site selection for real estate teams and retailers, and grocery performance analysis for CPG brands and investors in the North American retail market.
Sources: RetailStat official site
Ranked closest to RetailStat: ResNav Solutions (67/100), Resolv (67/100), Rethinkit (67/100), Risk Cognizance (67/100).
A step up - brands to learn from: ZyG (71/100), Zuant (71/100).
Category leader: Accenture (97/100).