Learn how a 300-person B2B analytics consultancy used Decisions Lab to transform cold insurance outreach from 0.2% to 4% positive replies without sending more emails.
Success Metrics
- 20× reply rate improvement
- 4% positive reply rate sustained
- Week 2 first qualified conversation
For a 300-person analytics consulting firm targeting enterprise insurance companies across Asia, outbound was a numbers game they couldn't win.
Their SDR team was disciplined, researching prospects manually, A/B testing subject lines, and hiring agencies to optimize cadences. The result: 0.2% reply rate, one response per 500 emails sent. The problem wasn't effort or deliverability, it was visibility into buyer psychology.
The invisible gap in traditional outreach
Before Decisions Lab, their process looked like every other outbound motion. SDRs manually researched prospects on LinkedIn and company websites, applied a templated value prop based on industry and role, then sent and hoped.
What they couldn't see: how each individual buyer would actually process the message, which wording triggered skepticism, what pain points actually mattered to this decision-maker, why objections formed before replies were sent.
Every optimization was retrospective guesswork, and by the time they learned what didn't work, the prospect was gone. They were personalizing company names and pain points, but had no way to predict whether their angle would resonate with how that specific insurance VP makes vendor decisions.
Pre-sending what works with prospect simulation
The firm consolidated around Decisions Lab to solve a problem traditional sales tools don't address: simulating buyer reception before outreach is sent.
Here's how their new process works:
Import prospects directly into Decisions Lab
SDRs bring target lists (~1,000 prospects/month) from their CRM or prospecting database
Simulate psychological triggers for each buyer
Decisions Lab analyzes each prospect's digital footprint to map which messaging angles activate interest vs. skepticism for this individual, what decision patterns drive their vendor evaluation process, and which psychological triggers (FOMO, risk mitigation, competitive pressure, efficiency) actually move them
Generate calibrated outreach
The platform produces personalized emails optimized to each buyer's predicted response patterns, not generic templates
Review simulation insights before sending
SDRs see why the message is structured this way, what the simulation predicts, and the specific reasoning before they hit send
The impact: from blind testing to predictive precision
The results were immediate with their first qualified reply from a tier-1 regional insurer coming in Week 1. They sustained a 4% positive reply rate, 20× their baseline, across enterprise insurance and banking prospects, booking demos with household-name insurers and major Asian banks across the region.
But the operational shift was just as significant. SDRs stopped manually researching psychological triggers they couldn't see, running retrospective A/B tests on messaging that already failed, and chasing cold prospects who were never going to respond. Instead, they engaged buyers pre-disposed to their specific approach.
Why traditional personalization falls short
Traditional personalization focuses on merge fields like name, company, and role. It applies generic value props by industry, runs A/B testing after the send, and optimizes retrospectively based on what already failed.
Decisions Lab simulation identifies the psychological triggers that drive yes/no decisions for each individual buyer. It predicts the strategy that will resonate with this buyer's patterns, validates what works before the send, and calibrates outreach prospectively.
Current tools optimize what you send, but Decisions Lab predicts how buyers will react.
Built for complex B2B motions
This approach works when you're selling into enterprise or regulated markets where credibility determines access, your product requires consultative positioning rather than transactional pitches, you're targeting senior decision-makers who filter aggressively, and your team is done with spray-and-pray and ready for precision.
The shift from guesswork to prediction
The firm didn't change their ICP, hire more SDRs, or increase send volume. They simulated reception before outreach and eliminated the guesswork that kills most enterprise campaigns.