Program Analytics: Measuring What Matters
What You Don’t Measure, You Can’t Scale
Every MGA and wholesaler wants faster quoting, better bind ratios, and stronger carrier relationships — but most can’t prove it with data.
They run reports from multiple systems, chase spreadsheets, and spend hours aligning numbers that never quite match.
RQB changes that.
It captures every data point from submission to bind automatically, then turns it into dashboards that track performance in real time.
No exports. No manual reconciliation. Just visibility.
Why Analytics Must Be Embedded in the Platform
Separate analytics tools create lag and blind spots.
By the time data is exported, filtered, and charted, the opportunity to act has passed.
RQB’s analytics engine runs inside the same workflow that underwriters and producers use daily.
That means every quote, approval, and bind feeds metrics instantly — without waiting for an end-of-week report.
Embedded analytics deliver immediate answers:
- Which carriers respond fastest?
- Which programs convert best?
- Where do submissions stall?
- How long does each approval step take?
Those insights make performance improvement part of the daily workflow, not a quarterly meeting.
The Core Metrics That Define Program Health
RQB tracks performance across every stage of the quoting lifecycle.
1. Submission Metrics
- Total submissions received
- Average time from intake to first quote
- Validation errors or missing data rate
- Ready-to-quote ratio per program
Linked with Submission Intake Automation, this data reveals where intake processes improve or break.
2. Quoting Metrics
- Quotes issued per carrier and per user
- Average quote turnaround time
- Multi-line quote completion rate
- Referral or exception ratio
Tied to Real-Time Rating, these indicators measure the impact of automation on quoting efficiency.
3. Bind Metrics
- Quote-to-bind conversion by program and carrier
- Average bind time
- Bind errors or rework volume
- Carrier acknowledgment turnaround
Integrates directly with Bind Automation: From Quote to Policy Packet Instantly.
4. Carrier and Producer Analytics
- Carrier response speed and SLA adherence
- Producer submission quality and hit ratios
- Average revenue per producer
- Renewal retention by partner
These cross-role insights connect operational performance to business growth.
Visual Dashboards and Real-Time Alerts
RQB dashboards aren’t static. They refresh continuously and are tailored to each role.
Underwriters see open queues, cycle times, and referral reasons.
Managers view program-level hit ratios, SLA compliance, and throughput.
Executives monitor revenue impact and carrier mix in a single snapshot.
Alerts notify teams automatically when SLAs breach or metrics trend down.
No waiting for a report to realize performance slipped.
Drilling Down to Root Cause
Every metric in RQB is clickable.
If quote turnaround time rises, managers can drill down to:
- The specific carrier or user causing delay
- The submission types or states with slower processing
- The stage (intake, rating, bind) creating the bottleneck
This level of transparency turns analytics into an operational tool, not just a dashboard.
Program Comparisons and Benchmarking
For MGAs running multiple programs, RQB compares them automatically.
You can benchmark performance across lines, carriers, or teams:
- Which state has the best quote-to-bind ratio?
- Which program closes fastest?
- Which carriers deliver the most accurate rates?
Over time, RQB builds your own performance baseline — a measurable standard that guides future launches.
For examples of how configuration affects performance, see Speed to Launch: How MGAs Go Live in 30–60 Days.
Data Integrity and Audit Readiness
All metrics derive from live workflow events, not manual entries.
Every number is backed by evidence — timestamped records, approvals, and documents.
That audit trail ensures compliance with delegated authority and carrier SLAs.
If a carrier questions a bind or turnaround metric, you can show the exact timeline — submission to issuance — with supporting evidence.
Predictive Insights with GPT-Driven Intelligence
RQB’s analytics use machine learning and GPT-assisted interpretation to highlight trends automatically.
Instead of just reporting that bind ratios dropped, it explains why — maybe due to slower carrier responses or incomplete submissions.
This turns raw data into recommended actions.
Analytics becomes decision support, not just measurement.
Implementation Roadmap
| Step | Duration | Deliverable |
|---|---|---|
| Metric definition | 1 week | Custom KPIs per program |
| Dashboard setup | 1 week | Live operational view |
| User training | 1 week | Role-based analytics access |
| Automation tuning | 1 week | Alerts, trend triggers |
In less than a month, you move from fragmented reports to continuous visibility.
Business Impact
MGAs and wholesalers using RQB analytics report:
- 30 % faster response times due to SLA tracking
- 20 % higher conversion through proactive alerts
- 100 % audit traceability for carrier reporting
- Improved underwriting profitability through data-driven rule tuning
Data stops being retrospective — it becomes the core of daily execution.
Get Started
Analytics isn’t just about measuring performance — it’s about proving value to carriers, producers, and investors.
With RQB, you know exactly how every quote, approval, and bind contributes to your growth.
Request a Demo or Start a Pilot to see real-time analytics that drive results, not just reports.
FAQ
What systems can feed into RQB analytics?
All RQB modules — intake, rating, bind, and API connectivity — feed analytics natively.
Can we create custom KPIs?
Yes. KPIs and alerts can be defined per program, carrier, or user.
Does analytics work for manual carriers too?
Yes. Manual and API-based workflows both record metrics.
Can analytics be exported?
Dashboards can export to PDF, Excel, or live API feeds for BI tools.
Are insights predictive or descriptive?
Both. RQB identifies trends and suggests actions using GPT-enhanced analysis.
