Strong Tower Consulting has spent more than 18 years helping asset-based motor carriers transform their commercial bidding, pricing, and customer-retention processes. Our engineering playbooks integrate directly with Truckmate, McLeod, TMW, and other leading transportation management systems to deliver automated RFP response engines, multi-lane rate quoting matrices, and predictive customer churn radar.
Whether responding to a 400-lane shipper RFP, dynamically adjusting fuel surcharges on an EDI 204, or identifying early warning signs of volume migration to competitors, the architecture described here has been proven across dry-van, refrigerated, and flatbed operations.
The Commercial Data Foundation
Effective carrier bid response begins with a clean, queryable data foundation. We model historical lane performance using normalized SQL schemas that capture:
- Origin-destination pairs at 5-digit ZIP or 3-digit market level
- Equipment type, average load weight, and accessorial frequency
- Loaded and empty miles, fuel surcharge type (diesel or regional), and detention history
- Driver settlement cost per mile, including per-diem and escrow activity
- EDI 210 invoice acceptance rate and days-to-payment by shipper
These tables feed both real-time quoting engines and the churn radar heuristics. Most carriers we engage already have the raw data inside their TMS; the challenge is surfacing it at the speed of sales.
Automated RFP Rate Matrix Bidding Engine
When a shipper issues an RFP containing dozens or hundreds of lanes, manual quoting becomes a bottleneck. Our architecture uses a carrier-rate-matrix-optimization layer that:
- Imports the RFP lane list via spreadsheet or EDI 204 template
- Matches each lane against 24 months of historical cost and revenue data
- Applies dynamic pricing elasticity models that factor current capacity, fuel prices, and driver availability
- Generates a complete rate matrix with base rates, fuel tables, and accessorial caps
- Exports the bid back in the shipper’s required format while simultaneously loading awarded lanes into the TMS
The engine respects each carrier’s unique cost structure. For example, a refrigerated carrier running dedicated lanes may weight driver detention and layover pay more heavily than a dry-van fleet focused on high-velocity freight.
| Metric | Manual Process | Automated Matrix Engine |
|---|---|---|
| Average RFP response time | 14 days | 2.5 hours |
| Lanes quoted per RFP | 38 | 187 |
| Margin variance on awarded lanes | ±19% | ±4% |
| Win rate on strategic lanes | 31% | 54% |
Customer Volume Churn Radar
Customer churn is rarely sudden. Our churn radar continuously monitors six leading indicators pulled nightly from the TMS and accounting system:
- 30-day rolling tender acceptance rate decline
- Increase in EDI 214 exceptions or carrier-failed status codes
- Drop in average weekly loads versus same period last year
- Rising days-sales-outstanding on EDI 210 invoices
- Driver settlement cost creep on the customer’s primary lanes
- Competitor rate inquiries appearing in load boards for the same lanes
A composite risk score is calculated and displayed in a live dashboard. When the score crosses a configurable threshold, the account manager receives an early-warning alert with recommended retention actions such as targeted rate adjustments or dedicated capacity offers.
Dynamic Pricing Elasticity Models
Static rate matrices quickly become obsolete. The architecture includes a pricing service that recalculates suggested rates based on real-time market conditions, fuel surcharges, and remaining capacity. Integration with ELD and telematics data allows the model to factor actual transit times and on-time performance into the quoted price, giving carriers a defensible basis for premium pricing on high-service lanes.
Independent by design
Strong Tower Consulting, LLC and Exspeedite LLC are separately organized sister companies under common ownership (separate EINs; liability firewall). We never require you to purchase or license software to receive our consulting and architecture services. Our clients implement these designs inside their existing Truckmate, McLeod, or TMW environments or with the open-source components of their choice.
Implementation Roadmap
A typical engagement begins with a technical assessment of your current TMS data model and commercial processes. From there we deliver:
- SQL views and stored procedures for lane profitability
- Automated RFP import and matrix generation routines
- Churn radar heuristics with Power BI or custom web dashboard
- EDI 204/214/210 transaction lifecycle enhancements
- Training for sales, pricing, and operations teams
Carriers typically see measurable improvement in bid win rates and customer retention within the first two quarters.
To discuss how this architecture can be tailored to your specific fleet size, geographic focus, and TMS environment, contact us at 763-244-1373 or complete a no-cost assessment.
Frequently Asked Questions
How do you handle fuel surcharge variability in multi-lane RFP responses?
We maintain separate weekly and monthly fuel tables linked to the Department of Energy regional averages or the specific carrier’s actual fuel purchase locations. The quoting engine automatically applies the correct table based on the shipper’s requested surcharge method and includes escalation language for lanes with high empty-mile exposure.
Can this architecture integrate with both McLeod and Truckmate simultaneously?
Yes. Many carriers operate mixed fleets or have grown through acquisition. Our SQL data-mining layer normalizes cost and revenue data from both platforms into a single analytical repository, allowing unified churn radar and rate matrix logic across disparate TMS instances.
What early warning signs does the churn radar look for beyond tender volume?
In addition to load count, the radar tracks increases in detention and accessorial disputes, lengthening payment cycles on EDI 210s, driver turnover on the account’s lanes, and sudden increases in competitor postings for the same origin-destination pairs. These signals often appear weeks before a shipper formally reduces volume.
Do I need to replace my current CRM to use this system?
No. The churn radar and quoting engine are deliberately TMS-centric. They pull customer and shipment data directly from your transportation management system and accounting integration rather than requiring a separate sales CRM. We can push alerts into Microsoft Teams, email, or your existing CRM if desired.
Published April 2025 by Strong Tower Consulting, LLC. Founded in Minnesota in 2008 by Scott Elliott. In business for more than 18 years.