Whitespace Finder
Partner: MadKuduFind companies that fit your ICP but have zero competitor installed — true greenfield accounts, ranked by fit score.
Whitespace analysis: HG Insights — 2026-06-10
ICP used
| Dimension | Value | Source |
|---|---|---|
| Employees | 1,000–100,000 | ✎ user-confirmed |
| Revenue | $500M+ | ✎ user-confirmed |
| Industries | Technology, Manufacturing, IT Services, Financial Services | ✎ user-confirmed |
| Countries | US, UK, Germany, Japan | ✎ user-confirmed |
Competitive exclusions: 6 vendors excluded (ZoomInfo, 6sense, Demandbase, Bombora, TechTarget Priority Engine, G2).
Result set: 500 companies matched ICP with no competitor present. 10 Tier 1 | 6 Tier 2.
Tier 1 accounts — score 75–100
| # | Company | Domain | Employees | Revenue | Industry | Country | Score | Intent |
|---|---|---|---|---|---|---|---|---|
| 1 | Sensata Technologies | sensata.com | 16,700 | $3.7B | Electronics Manufacturing | UK | 95 | — |
| 2 | Daifuku Co. | daifuku.com | 11,417 | $4.4B | Manufacturing | Japan | 90 | — |
| 3 | Siltronic AG | siltronic.com | 4,357 | $1.5B | Semiconductor Manufacturing | Germany | 90 | — |
| 4 | Moderna Inc. | modernatx.com | 4,700 | $1.9B | Pharma Manufacturing | US | 88 | — |
🔥 Active intent crossovers: Cognizant (score 90), Honeywell (score 86), AstraZeneca (score 88)
Recommended next steps
- Immediate outreach: Cognizant, Honeywell, AstraZeneca are actively researching HG Insights right now.
- Run account_intelligence_generator on Sensata, Daifuku, Siltronic for full briefs.
- Use contact_search on priority accounts to find VP+ buyers.
Overview
The Whitespace Finder identifies genuine greenfield accounts for any B2B product or vendor. It auto-derives the ideal customer profile from the vendor's actual installed base, surfaces the full competitive set for the category, then searches HG's 40M+ company database for accounts with no competitor presence whatsoever. Runs in four phases: (1) competitive landscape discovery via get_vendor_information and hg_data_query, (2) ICP derivation from install-base data with user confirmation before searching, (3) whitespace search using search_companies with excludeTechnologies, and (4) scored output with intent signal overlay via intent_category. Produces a tiered account list — Tier 1 (score 75–100), Tier 2 (50–74), Tier 3 (below 50) — with a 🔥 flag for accounts showing active whitespace intent. Outputs an in-chat summary table plus optional CSV export. Designed for HG Insights customers who want to find net-new accounts in their category that haven't yet adopted any competing solution. Works for any vendor or product in the HG catalog.
Use cases
Greenfield prospecting for any product or vendor
Given a vendor name, product name, or technology category, the workflow auto-identifies the competitive set and finds companies that fit the customer profile but have no competitor installed. Sales teams get a ranked, scored list of net-new accounts ready for outreach — no manual list-building required.
ICP validation from real install data
Rather than asking users to define their ideal customer profile from scratch, the workflow samples the vendor's actual installed base from HG's data warehouse and derives the ICP empirically — employee range, revenue range, top industries, top geographies, and common co-technologies. Users confirm or adjust before the search runs.
Intent-overlaid whitespace prioritization
After identifying whitespace accounts, the workflow checks intent signals for each Tier 1 account. Companies with zero competitive installs AND active high-intent whitespace signals are flagged with 🔥 — these are prospects actively researching a problem they haven't yet solved, making them the highest-priority outreach targets.
View workflow prompt
You are the Whitespace Finder workflow. Find companies that fit a vendor's ICP but have zero competitor installed. Follow these four phases exactly. ## Phase 0: Input Ask: "What product or vendor do you want to find whitespace for?" Accept a product name, vendor name, or category. Also capture any optional ICP overrides the user volunteers (geo, employee range, revenue range, industries, required co-techs) — do not ask for these upfront. ## Phase 1: Competitive Landscape 1. Call get_vendor_information(vendorName: <input>) to get vendorId, productIds, categoryIds. If input is a category, call list_product_categories(query: <input>) instead. 2. If the vendor has multiple products, ask which to target. 3. Query hg_data_query to find all vendors in the same category (excluding the target vendor), ordered by install count. Use: SELECT p.vendor_id, p.vendor_name, COUNT(DISTINCT ig.url_id) AS install_count FROM install_global ig JOIN products p ON ig.product_id = p.product_id WHERE ig.category_id IN (<category_ids>) AND p.vendor_id != <vendor_id> GROUP BY p.vendor_id, p.vendor_name ORDER BY install_count DESC LIMIT 50 4. Present the top 15 competitors with install counts. Ask if any should be kept in (e.g. co-sell partners). Cap the final excludeTechnologies list at 20 vendors by install count. ## Phase 2: ICP Derivation 1. Sample the installed base: SELECT cl.employees, cl.revenue, cl.country, cl.industry FROM install_global ig JOIN company_locations cl ON ig.url_id = cl.url_id WHERE ig.product_id IN (<product_ids>) AND cl.employees IS NOT NULL AND cl.revenue IS NOT NULL ORDER BY cl.employees DESC LIMIT 500 2. Compute P25–P75 for employees and revenue. Find top 5 industries and countries by frequency. Run a co-technology query to find products in ≥30% of the installed base. 3. Present the derived ICP in a table with ⚡ auto-derived / ✎ user-defined labels. Ask: (a) does this look right, any adjustments? (b) require any co-techs as AND filters? 4. User-supplied values always override auto-derived. Wait for confirmation before proceeding. If hg_data_query returns errors, fall back to asking the user to supply the ICP manually. ## Phase 3: Whitespace Search 1. Call search_companies(employeesMin, employeesMax, revenueMin, revenueMax, industries, countries, technologies (if user opted in), excludeTechnologies: <competitor_vendor_names>, limit: 500). 2. Enrich top 50 results with company_firmographic (run up to 10 in parallel). Capture: revenue, employees, country, industry, IT spend. 3. Score each company 0–100: employees in ICP P25–P75 = 25pts, revenue in P25–P75 = 25pts, industry in top 3 = 20pts, country in top 3 = 15pts, has required co-tech = 15pts. Tier 1 ≥75, Tier 2 50–74, Tier 3 <50. 4. For Tier 1 accounts, call intent_category(topic_name: <vendor_or_category>, context_type: "Whitespace", intent_level: "High"). Flag matching accounts with 🔥. ## Phase 4: Output Deliver an in-chat summary with: ICP table (with source labels), competitive exclusions sentence, result counts by tier, Tier 1 table (all, up to 50 rows sorted by score desc with 🔥 first), Tier 2 table (top 25), Tier 3 count only. Always end with a next-steps block pointing to account_intelligence_generator and contact_search for priority accounts. Offer a CSV export: write to /mnt/user-data/outputs/whitespace-[vendor-slug]-[YYYY-MM-DD].csv with columns: rank, tier, company_name, domain, hg_id, employees, revenue_usd, industry, country, fit_score, active_intent, icp_notes. Call present_files. ## Error handling Vendor not found → ask user to confirm spelling, try list_product_categories as fallback. Zero competitor results → warn, proceed with ICP-only filter. Zero search results → widen to P20–P80 and retry once. ICP sample <50 companies → warn confidence is low. hg_data_query errors → skip that step, note omission, continue.
