How Route Built $42M ARR Pipeline in 3 Quarters
117 opportunities in month one; $3.5M MRR ($42M ARR) pipeline generated over 3 quarters
E-commerce merchants experiencing package loss, damage, and theft complaints—plus gaps in shipping protection policies
Complete e-commerce merchant universe with shipping policy analysis, complaint signals, and buying readiness indicators
Salesforce views segmented by pain signal strength, automated checkout verification, and campaign sequences
117 opportunities in month one; $3.5M MRR ($42M ARR) pipeline generated over 3 quarters
Data Deliverables
Thousands of e-commerce merchants with decision maker contacts
TAM monitoring for complaint signals + policy gap analysis
- Shipping protection policy status
- Package complaint signal strength
- E-commerce platform used
- Estimated order volume
- Salesforce views by signal strength
- Automated checkout screenshot verification
- Campaign sequences by segment
- Weekly updated target lists
Weekly TAM monitoring + Daily signal processing
- New complaint signals detected
- Policy changes identified
- Competitor churn signals
- Merchant growth indicators
The Challenge
Route sells shipping protection to e-commerce merchants. Their ideal customer is a merchant experiencing package loss, damage, or theft complaints—who doesn’t currently have shipping protection.
The problems:
- No database coverage: E-commerce merchants aren’t well-covered in B2B databases
- Signal blindness: No way to systematically identify merchants with shipping problems
- Policy gaps invisible: Knowing who doesn’t have protection requires checking each merchant
- Rapid market changes: New stores launch, policies change, competitors move
The Data Solution
We built Route’s signal-aware e-commerce universe:
Signal Captured
We monitored the entire e-commerce TAM for two key signals:
- Complaints: Merchants receiving customer complaints about lost, damaged, or stolen packages
- Policy gaps: Merchants without shipping protection (or with competitor solutions showing churn signals)
Data Asset Built
- Complete e-commerce merchant universe with decision makers
- Shipping policy analysis for every merchant
- Package complaint signal strength scoring
- Platform, technology, and volume indicators
Activation Delivered
The activation was sophisticated:
- Automated checkout bot: We built a bot that went through checkout on merchant sites, taking screenshots to verify shipping policy status
- Signal-strength segmentation: Salesforce views organized by complaint intensity and policy gap
- Campaign sequences: Playbooks matched to signal type
- Weekly refreshed lists: Targets updated based on new signals
Freshness Loop
- Daily signal processing for complaints
- Weekly TAM scan for new merchants
- Continuous policy monitoring
- Competitor churn detection
The Outcome
In month one: 117 opportunities.
Over three quarters: $3.5M MRR ($42M ARR) pipeline.
This wasn’t luck—it was systematic signal detection feeding into a precision sales motion. Route knew who had the problem, what the problem was, and when to engage.
Data Deliverables Summary
| Category | What We Delivered |
|---|---|
| Entities | Thousands of merchants + decision makers |
| Coverage | Full e-commerce TAM with signal monitoring |
| Hard Fields | Shipping policy, complaint signals, platform, volume |
| Activation | Checkout bot, SFDC views, campaign sequences |
| Freshness | Daily signals + Weekly TAM refresh |
The Winning Plays
What made Route’s engagement work:
- Complaint-triggered outreach: When a merchant showed complaint signals, they got engaged within days
- Evidence-based messaging: “We noticed your checkout doesn’t include package protection” (with screenshot)
- Timing precision: Engaging when the problem is fresh, not when it’s been solved
- Systematic coverage: Not missing merchants because they weren’t in a database