Industry Context
The restaurant services industry operates on route-based distribution models where profitability depends heavily on territory density and operational efficiency. Companies serving fragmented local markets face increasing complexity in identifying high-value prospects while managing expensive direct sales forces. Traditional territory planning relies on manual processes and limited data visibility, creating inefficiencies that compound across large sales organizations.
The Challenge
Restaurant Technologies' territory design was inefficient, with limited visibility into smaller locally owned restaurants near large national accounts. Sellers relied on manual prospecting and cold outbound efforts, resulting in high-cost pipeline generation, suboptimal conversion rates, and decreased sales velocity due to longer cycle times and inconsistent targeting.
The Aha! Insight
The breakthrough came from realizing that AI and digital data sources (Yelp, Google, restaurant menus) could systematically identify and target high-potential independent restaurants. This enabled more precise territory coverage and faster, more productive sales cycles.
Jeff Kiesel, CEO of Restaurant Technologies, noted the impact of giving salespeople actionable data:
"We have 120 salespeople, and all of a sudden each of them has an extra day a week to work because we give them the information on where they should go, how to spend their time, and which prospects actually need our services."
SBI's Approach
SBI deployed SBI Wayforge™ Signal to build a custom research agent that continuously scanned Yelp, Google, and restaurant menus to rank local accounts by fryer oil usage potential. Territories were remapped to expand into independent restaurants adjacent to national anchors, and sellers were directed to focus on clusters of high-fried-food restaurants. Account lists were refreshed quarterly to maintain accuracy and adapt to market changes.
Before vs. After
Results
- $25 to 40 million projected incremental bookings uplift
- 11 percent improvement in client-facing time per seller
- 5 percent increase in bookings productivity across a 150+ rep field salesforce
- More predictable and efficient growth with improved margins and better supply chain synchronization
Executive Perspective
"When running a go-to-market organization, AI will be the death of human intuition. Intuition alone can no longer power growth in the age of AI. By partnering with SBI we have embraced AI, and now we will be able to power our growth faster and more effectively."
—Jeff Kiesel, CEO, Restaurant Technologies
Risk of Inaction
Without addressing territory inefficiency and leveraging AI, Restaurant Technologies risked continued high-cost, slow-growth sales cycles, missed local opportunities, declining productivity, and an inability to sustain double-digit growth. Inaction would result in lost market share, lower margins, and reduced enterprise value for future investors.
Industry Implications
This case demonstrates that AI-driven territory design and micro-segmentation are essential for scalable and predictable growth in complex route-based B2B businesses. Human intuition and manual processes are no longer sufficient. Organizations must embrace data enrichment and automation to remain competitive. These lessons apply broadly across industries with fragmented local markets and high operational complexity.
Role-Based Impact
- CEO: AI-driven territory optimization delivers predictable double-digit growth while reducing operational complexity. This strengthens competitive advantage and positions the company for premium valuations in future transactions.
- CFO: The 11 percent improvement in seller productivity and 5 percent increase in bookings directly impact unit economics. Predictability improves cash flow forecasting and supply chain optimization, strengthening working capital management.
- CRO: Enhanced territory design and account targeting reduce customer acquisition costs while accelerating sales velocity. Shifting from manual prospecting to AI-driven insights enables sales teams to focus on high-probability opportunities.
- CMO: Micro-segmentation capabilities enable precise targeting and messaging for different restaurant types. The data-driven approach improves marketing ROI by identifying look-alike prospects based on successful customer profiles.
Call to Action
Territory-based businesses must embrace AI-driven segmentation and targeting to remain competitive. Organizations that continue relying on manual prospecting and intuition-based territory design risk falling behind competitors that use data enrichment and automation to drive predictable growth.
