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Research Comparison

Updated

Markdown

Summary

B2B sales intelligence platform providing verified contact data, company insights, and buying signals to help GTM teams and AI agents build pipelines and drive revenue.

Funding

$245M (Series B)

Founded

2016

Team

200-500

lusha.com

Critical Notes

- Praised for seamless Chrome extension, strong North American coverage, frictionless free tier - Phone reveals cost 5 credits vs 1 for email, burning credits quickly - €2M Italian fine (July 2026) for contact data mishandling; US class-action lawsuits - Crowdsourced data via Community Program is a compliance risk

Key Features

- Search database with 515M+ verified contacts and 29M companies - Deep Intelligence layer: predictive scoring, buying committee mapping, lookalike audiences - 26 buying signal types: funding rounds, hiring surges, leadership changes - Browser extension overlaying contact data on LinkedIn, Sales Navigator, company websites - API and MCP integrations for AI assistants like Claude and ChatGPT - Native CRM integrations: Salesforce, HubSpot, Zoho, Monday - Automated enrichment for inbound leads, CSV lists, waterfall workflows

Details

B2B sales intelligence and data platform founded 2016 by Yoni Tserruya and Assaf Eisenstein. HQ Boston, engineering/data in Tel Aviv. $245M raised; $205M Series B (Nov 2021) at $1.5B valuation after $40M Series A. ~$55M revenue, ~514K monthly visits, ~68K LinkedIn followers. Product-led: freemium, no credit card, monthly free credits, Chrome extension, self-serve Starter/Pro/Premium tiers. Sales-led secondary: custom Scale plan with annual agreement; gates full API, Salesforce enrichment, advanced intent, high-volume CSV. Open-source: lusha-oss GitHub with Apache-2.0 MCP server and n8n, Cursor, VS Code Copilot plugins; core data proprietary. Data vendor, not platform: no unified person timeline, no rep workbench, workflows outsourced to Clay/n8n. Commercial market: SMB/startup sweet spot, thin gated enterprise features.

Signalscompared to Common Room

1st Party

  • Salesforce, HubSpot, Pipedrive, Zoho, Dynamics 365 CRM sync; real-time CRM enrichment on lead creation; Salesforce/HubSpot report import; company-level website visitor ID
  • CRM enrichment pipes only, no bi-directional signal ingestion; no product usage/data warehouse, marketing automation, paid ads, chat/support, CS or sales engagement signals; visitor ID not person-level; Salesforce enrichment gated to Scale plan

2nd Party

  • Chrome extension overlay on LinkedIn, Sales Navigator, company websites; open-source MCP server; n8n, Cursor, VS Code Copilot plugins
  • No 2nd-party signal ingestion; no community, open-source activity, social, review, event or commerce sources; MCP only pulls Lusha data out

3rd Party

  • 26 buying signal types (funding, hiring, leadership changes, tech installs, news); Intent 2.0 with predictive scoring, buying-committee mapping, lookalikes; LinkedIn activity intent
  • Single proprietary intent source; no 6sense, Demandbase, Bombora, G2 integrations; advanced intent gated to Scale plan; action on signals often routed via Clay

Custom

  • REST API (Search, Prospecting, Enrichment, Lookalikes, ICP Fit); bulk CSV enrichment; Zapier, Make, Workato, Pipedream; webhooks; native MCP connector
  • Full API and high-volume CSV Scale-plan only; no native Google Sheets; API retrieves Lusha data, not customer signal ingestion; credit-metered calls

1st: Salesforce, HubSpot, Pipedrive, Zoho, Dynamics 365; real-time CRM enrichment; report import; company-level visitor ID. 2nd: Chrome extension on LinkedIn, Sales Navigator, websites; open-source MCP server; n8n, Cursor, Copilot plugins. 3rd: 26 buying signal types; Intent 2.0 with predictive scoring, buying committees, lookalikes; LinkedIn activity intent; routed via Clay. Custom: REST API, bulk CSV, Zapier, Make, Workato, Pipedream, webhooks, MCP connector. Gaps: no product usage, warehouse, community, support/CS signals; single intent source; Scale plan gating.

Identitycompared to Common Room

Enrichment

  • 515M contacts, 29M companies; native waterfall; claims 98% email, 86% phone accuracy; pay only for matches; inbound, CSV, CRM enrichment
  • Independent benchmarks 81-84% email accuracy; 5 credits/phone, waterfall 2/email and 8/phone; no AI quality-control layer; crowdsourced data provenance risk

AI Powered

  • MCP server for Claude/ChatGPT resolution and enrichment; LLM dedup and fuzzy matching via connector
  • Nothing native; DIY with own LLM, n8n, prompts; no in-platform AI matching or auto-enrichment

Identity

  • Match hierarchy: LinkedIn URL, email, name+company, name+domain; continuous refresh for job changes, promotions, phone updates; B2B-focused
  • Matches database contacts to CRM records only; no cross-channel person timeline; no merge review queue or manual merge UI

Aggregates public profiles, company sites, directories, community contributions. Match order: LinkedIn URL, email, name+company, name+domain. B2B-focused; continuous refresh on job changes and promotions. Enrichment: native waterfall; claims 98% email, 86% phone accuracy (independent 81-84% email); waterfall lifts US work email coverage to 98%. Credits: 1/email, 5/phone; waterfall 2/email, 8/phone. Bulk CSV, CRM, inbound enrichment. AI: MCP server for Claude/ChatGPT; LLM dedup via connector as canonical truth layer; n8n + Gemini fuzzy matching workflows. All DIY, none native.

Automationcompared to Common Room

Combine

  • Topic-Synergy Intent Scoring merges intent topics into one level
  • No native combining of firmographics, intent, job change, 1st-party in one trigger; relies on Clay or n8n

Score

  • Intent tiers (Very Hot, Hot, Warm); ICP fit scoring vs closed-won; lookalike audiences
  • Limited to Lusha fields; no custom scoring across 1st/2nd-party signals; black-box model

AI Message

  • AI Email Assistant (OpenAI) in Engage; multi-step sequences, personalization tags, variants
  • Context limited to firmographic/contact data; tied to Lusha Engage, not existing SEP

AI Research

  • Official MCP server; pulls company context, growth signals, decision-makers in one prompt; out-of-box prompt library
  • Needs external AI assistant; no in-app agent; limited to Lusha database, no 1st-party context

Workbench: none. Workflow: Lusha Automations and Engage; ICP/job change/intent triggers sync to CRM and enroll in email sequences; complex flows via n8n, Zapier, Activepieces. Alerts: job change (company change, promotion, new title, verified email) and intent; Slack/CSM/CRM routing via integrations. Combine: Topic-Synergy Intent Scoring; full combining requires Clay or n8n. Score: Very Hot/Hot/Warm intent tiers; closed-won based custom scoring. AI Message: OpenAI-powered Email Assistant in Engage with multi-step sequences and variants. AI Research: MCP server for account research in Claude/ChatGPT; out-of-box prompts.

Supportcompared to Common Room

Systems

  • Help Center; AI chatbot with human escalation; email/ticketing; dedicated Account Manager on Scale plan
  • AI-first gating before human; dedicated support only top tier; no phone support

Content

  • Written docs (setup, CRM, billing, extension troubleshooting); Lusha Campus; API and MCP docs; Trust Center (SOC 2 Type II, ISO, GDPR/CCPA); case studies (Zendesk, Google)
  • No video training library; Trust Center driven by regulatory exposure

Community

  • Ideas Board; lusha-oss GitHub; Community Program (opt-in data sharing for perks)
  • No user forum, Slack community, or template library; OSS support deflected to n8n forum; Community Program drives privacy risk

...

Status: Watch

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