Case Study
How an AI SDR increased reply rates and revenue 4x after integrating with Crustdata
Company
AI SDR company
use case
Improving AI SDR data quality
company overview
This company is building an AI SDR serving SMBs and mid-market teams. The agent discovers prospects, enriches them, crafts personalized messages, and enrolls them in multi-step outbound sequences without human intervention. They process thousands of outbound sequences daily across their customer base.
Before partnering with Crustdata, the company's AI agent was sending outreach at scale on top of data infrastructure that couldn't meet the demands of an AI agent, which turned their core product advantage into a liability.
Out-of-Date Data Ruined Their Customers' Sender Reputation
Their existing enrichment provider refreshed quarterly, with profiles lagging 30-60 days behind reality
A message referencing someone's old title or a company they left months ago triggers spam complaints, and at scale those complaints compound against the customer's sending domain until even legitimate emails stop landing in inboxes
The product's core advantage (automation at scale) was becoming the reason customers churned
Inability to run signal based prospecting workflows
Even with accurate contacts, outreach was generic: the right person reached at a random time with no relevant hook
The agent had no visibility into real-time behavioral signals that indicate a prospect is actually receptive
Without signals, the AI agent was guessing on timing which lowered response rates and booking rates when compared with their competitors
Fragile Data Infrastructure for an Always-On Product
Multiple enrichment providers were sued and shut down, forcing a pipeline rebuild
Credits were not returned on failed API calls, making it impossible to meter downstream usage or build margin into pricing
No reliable customer support to reach out to when APIs broke down or when the team had trouble integrating data into their workflows
Crustdata provided the data infrastructure layer for their AI agent: real-time enrichment, behavioral signals, trigger-based automation in a single API along with responsive customer support with direct access to our engineers.
Real-Time Data Enrichment
Every API request triggers live data collection rather than pulling from a pre-built cache in a database
Customers' sending domains stopped accumulating spam complaints as outreach began referencing the right person, at the right company, in the right role
Signal Layer Built Into the Same API
Keyword-based content monitoring surfaced prospects engaging with relevant topics in real time
Watcher API triggers sequences automatically on job changes, hiring signals, and funding rounds
The agentic workflow based on live signals was now possible: detect trigger, enrich data in real time, generate a message referencing that specific trigger, enroll in sequence
Infrastructure Built for The Needs of Agentic Workflows
Rate limits designed for the high, constant needs of agentic throughput
A single API replaced 2-3 vendors, giving the team all the data they need in one API access without managing multiple provider relationships and mapping different datasets
Outreach Quality Increased
Customer reply rates increased from around 2% to 8-12% on signal-triggered sequences
Bounce rates dropped below 1.5% from a prior 6-8% range, keeping customer domains safely below the 2% threshold
Spam complaint rate fell under 0.05%, well below the 0.1% threshold
Revenue growth and reduced churn
The team saw five contract renewals and expansions over nine months, with total ARR growing 4x since partnering with Crustdata
They were able to retain customers that were close to churning in just 2 weeks of integrating Crustdata's data into their workflow
Eliminated Multi-Vendor Dependence
A single API replaced the 3 enrichment vendors the firm had been managing, with engineering resources freed up from data pipeline maintenance and redirected to product development