Technographic datasets identify SaaS adopters, but ignore whether these firms can sustain spend. Financial datasets show solvency, but not technology readiness.
This segment unites both, and adds a conversion wallet estimation per account: turnover × sector ratio × digital signals × solvency filter. Each figure is transparent, benchmarked against peers, and explained with plain-language comments.
Detect SaaS, AI, and cloud tools on company sites.
Overlay solvency and turnover with sector IT spend ratios.
Calibrate spend potential with adoption multipliers and solvency filters.
This segment is activated with a blend of trusted sources and your own inputs
AI reasoning
User Input
Curated APIs
Web intelligence
Turnover, solvency score, and credit percentile per account
Detected SaaS, AI, and cloud stack
Estimated targetable spend and realistic conversion wallet size
Confidence scores for every calculation and benchmark comparisons by sector/country
Plain-language comments to explain spend potential and adoption readiness
Your questions on this segment, answered
Your questions on this segment, answered
Which industries or regions are best covered?
Coverage spans major SaaS-adopting industries and markets. Sector IT ratios and benchmarks ensure estimates remain comparable across geographies.
Isn’t this just another descriptive dataset?
No. Each account has a conversion wallet calibrated with solvency and adoption filters. The result is a realistic spend figure, directly exportable into CRM/BI for activation.
How often are solvency and stack signals refreshed?
Financials are updated as new filings appear; SaaS, AI, and cloud stacks are monitored continuously. Each account record carries a “last verified” timestamp.
How do I actually use these wallet estimates in GTM?
Accounts can be ranked by wallet size and conversion potential. RevOps and sales teams use these signals to prioritize outreach, allocate resources, and size realistic revenue opportunities.
How is this different from a simple technographic or financial dataset?
Tech datasets show adoption but ignore financial strength; financial datasets show solvency but miss digital readiness. Starzdata unites both to highlight the firms that are both tech-forward and budget-ready.
How do I know the spend and wallet estimates are trustworthy?
Each estimate is built from verified turnover, peer benchmarks, and technology adoption signals. Every figure carries a confidence score and a plain-language comment, so you can see both the number and the reasoning.
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