Case Study
How a Commercial Real Estate Firm Used Crustdata to find leads
Company
CRE Firm
use case
Lead Generation
company overview
This firm is one of the largest private commercial real estate brokerage firms in the United States. With approximately 1,000 employees and ~$10B in annual asset transactions, they operate across every major US metro. Their technology team built an in-house AI-native CRM. They score every data vendor on freshness and record quality, and actively rotate vendors in and out.
The firm's core business depends on being the first broker to reach a property owner or tenant before competitors do. But their entire prospecting workflow was reactive - waiting for inbound inquiries or working off the same property lists every other brokerage had access to. By the time a company was actively looking for space, five brokers had already reached out to them.
Reactive Deal Sourcing: Always Late to the Conversation
Brokers relied on inbound leads, cold calling off county assessor records, and manual LinkedIn research to find prospects
None of these methods gave them any way to identify companies that would need space six to twelve months out
They were always responding to demand that already existed, not anticipating it
No Growth Signals in Traditional CRE Data
The firm's existing data stack (county assessor records, parcel data, property-level databases) could tell them who owned what, but not who was growing
The signals that predict when a company will need more office space, things like hiring velocity, funding rounds, and headcount expansion, lived in a completely different data universe that no traditional CRE data provider covered
There was no way to connect company growth intelligence to real estate intent
Existing Vendors Couldn't Support Proactive Prospecting at Scale
The firm evaluated multiple data providers including LexisNexis, TruePeopleSearch, LiveRamp's identity graph, and direct web scraping; none of them worked
Some had no API at all; others imposed hard rate limits that forced manual "chunk and check" workflows: upload a batch, wait, download results, repeat
For a team that had built an API-first CRM designed to ingest data programmatically, all existing data providers were a poor fit
Crustdata gave them the company intelligence layer their CRE data stack was missing: growth signals that predict real estate demand before a lease inquiry ever comes in.
Identify Growing Companies Before They Need Space
The firm now filters Crustdata's database of 60M+ companies by headcount growth, geography, and funding stage to spot expansion before it happens
Headcount growth tends to predict office demand six to twelve months ahead of traditional CRE signals. The firm uses this to build proactive outreach lists in any target metro, filtered by the growth patterns that indicate imminent space needs
Real-Time Alerts on Expansion Triggers
The firm set up automated alerts through Crustdata's Watcher API to get same-day notifications when target companies hit expansion triggers in their submarkets
When a portfolio company closes a Series A in Austin or a mid-market tenant crosses a headcount threshold in Boston, the signal comes in as a webhook notification and lands directly in the CRM
Brokers see the alerts the same day, well before a lease inquiry would ever surface through traditional channels
High Rate Limit APIs Built for an API-First CRM
At 100,000 requests per minute supported on in-database queries, the firm can enrich contacts, search for decision-makers, and feed structured JSON directly into their database
Proactive Deal Sourcing
40+ net-new conversations sourced in the first quarter with companies that hadn't yet engaged any broker. These are deals that were previously invisible through traditional inbound or cold call workflows
Growth-signal-driven outreach converted to signed listings at 3x the rate of standard cold outreach
Brokers reaching prospects before competitors shifted the firm from reactive to first-mover in target submarkets
Prospecting Shifted from Manual to Programmatic
What used to require hours of manual LinkedIn research and county-by-county assessor lookups now runs as an automated pipeline inside the CRM
High-growth companies in target metros surface daily, and brokers can focus on outreach rather than research
A New Data Layer for CRE
250+ datapoints per company with 80% email fill rate on enriched contacts - up from zero company-level growth intelligence in their stack
Headcount trends, funding events, and hiring velocity now monitored across every target submarket daily alongside traditional property and parcel data