Most organizations rely on standard classifications that were never designed for strategy. NAICS in the US, NACE in Europe, APE/INSEE in France, SIC in the UK — or firmographic codes embedded in CRM and data platforms (from Dun & Bradstreet to off-the-shelf CRM segmentations). These taxonomies are inconsistent across markets, often unreliable, and — most importantly — imposed by external providers.
This leads to wasted time reclassifying accounts, poor fit for commercial strategies, and misaligned targeting. With Starzdata, your own taxonomy becomes the single source of truth: every account in your CRM or market universe is tagged against your definitions, with full explainability and confidence scoring.
Apply your taxonomy to company names, domains, and structured web content.
Score each sector tag with a confidence percentage.
Label the match type (name, domain, or content) for transparency.
Ingest your own taxonomy labels and descriptions (1–50 segments). Each label includes a narrative definition that guides the matching process.
Match companies against publicly available web sources: corporate websites, industry reports, press mentions, structured directories — going far beyond CRM-imposed firmographic tags.
Delivery adapts to your mode: packaged projects in 72h, or near real-time on the platform (minutes to days depending on volume).
This segment is activated with a blend of trusted sources and your own inputs
User Input
Web intelligence
Curated APIs
A dataset where all fields are standardized, scored, and traceable — ready to integrate into CRM, BI, or GTM workflows.
Each company receives:
A primary sector tag aligned to your taxonomy.
A confidence score for the tag.
A rationale explaining the match.
Matching logic based on your submitted labels and descriptions, enriched with signals collected across the web, not just CRM firmographic fields.
Delivered as a structured, enriched dataset — for lists from 100 to millions of accounts.
Your questions on this segment, answered
Your questions on this segment, answered
How do consultants and RevOps teams use custom sector tagging in real projects?
Consultants use it to build peer groups and benchmarks in days instead of weeks. RevOps enrich CRMs with tags aligned to GTM plays. Strategy teams use it for foresight dashboards, market sizing, and entry planning.
Can this segment handle millions of accounts from a CRM and still deliver explainable tagging?
Yes. Starzdata scales from 100 to millions of accounts. In project mode, delivery takes 72h; on the platform, it’s near real-time. Scale never compromises transparency — every account has a tag, score, and rationale.
Why is it difficult to reconcile a client’s custom segmentation with NAICS or SIC codes using standard machine learning?
ML models force-fit accounts into pre-set codes. These codes don’t reflect client GTM strategies, and the mapping is a black box. Starzdata flips this: your taxonomy is the input, and every match is explainable.
How are confidence scores and explanatory rationales attached to each sector tag?
Every tag includes a confidence score and a rationale showing if it came from a name, domain, or content match. This transparency lets RevOps trust GTM targeting and consultants justify benchmarks.
What makes Starzdata’s web-based sector matching different from registry or CRM-based classifications?
Registries and CRM firmographics rely on static codes. Starzdata scans public web signals — corporate websites, reports, press mentions — so tags reflect how companies operate today, not how they were once registered.
How does Starzdata turn a client’s internal taxonomy labels and descriptions into an actionable dataset?
Clients provide 1–50 sector labels with descriptions. These become the reference system. Starzdata applies them at scale to CRM or market universes using company names, domains, and web content. Each company gets a tag, confidence score, and rationale.
Why are standard codes like NAICS, NACE, APE, SIC or CRM firmographic tags unreliable for strategic targeting?
Because they are imposed, inconsistent, and often wrong. CRM firmographics from providers like D&B or ZoomInfo frequently misclassify — e.g., a MedTech SaaS tagged as just “software.” That means wasted spend for RevOps and irrelevant peer groups for consultants.
What are NAICS, NACE, APE or SIC codes, and how are they applied in company databases?
NAICS, SIC and similar codes are registry-driven classifications built for compliance and statistics. They group companies into broad buckets like “software” or “manufacturing.” While useful for regulators, they rarely align with how consultants or SaaS vendors segment markets.
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