Territory Optimizer module
Cluster customers into balanced territories, then drag them between territories — or drag route-stops between days — and the workload, distances and cost-to-serve re-optimize on the spot.
Coverage and whitespace, visit adherence by rep, side-by-side scenario comparison, TSP route planning with printable call cards, and admin-grade geocode validation — all built on your transactions and customer master, with cost-to-serve when you have it.
What's inside
The whole lifecycle in one place: validate and fix the geo, design the territories, drag to fine-tune, compare the alternatives, plan the routes, and hold the field team to the plan. Save a design once and every downstream page uses it.
The data quality behind every map. It flags customers with missing, zero, or out-of-region coordinates, and lets an admin correct a lat/lon through an override that's merged at read time — so a fix flows to every page without ever touching your source data.
Capacity-constrained clustering draws balanced territories — Presell weighted by visit workload, Delivery by volume — with a workload-balance score, average and maximum drive distance, the dominant current rep, and per-territory cost-to-serve. Save any design as a reusable scenario.
Drag a customer into another territory's cluster on the map and it rebalances live: workload variation, distances and cost-to-serve update on every drop. Save writes the change straight back into the scenario, so the routes downstream pick it up.
Diff two saved designs — which customers migrate between territories (matched by maximum overlap), where they move on the map, and how workload balance and cost-to-serve change. See the trade-off before you commit to a redraw.
Builds Mon–Fri × A/B-week visit routes per territory with a nearest-neighbour + 2-opt tour, per-day drive and service time, and constraint checks. Drag a stop to another day and both routes re-optimize instantly. Export a field-ready Rep Call Card PDF — one territory, or a ZIP of them all.
Where your active customers and revenue concentrate versus the pockets of inactive customers that signal prospecting whitespace — grid-binned and ranked by untapped opportunity, so the field team knows where to open doors next.
Recommended visit cadence versus how often customers are actually serviced (a proxy from invoice frequency): a visit-weighted adherence score, a Below-Plan / At-Risk / Healthy / Over-Visited breakdown, a per-rep rollup, and the most under-serviced customers.
What you'll surface
The Territory Optimizer is built around the decisions distributors and CPG manufacturers actually make about who covers whom — not a generic map. Each view is opinionated about the next move, and the design you save carries straight into the routes.
What we need from you
Map your existing spreadsheets to our canonical schema through the ingestion wizard — column names don't need to match ours. Your customer master carries the coordinates; if a few are wrong or missing, Geo Validation lets you fix them in place. Add the cost-to-serve file to turn on per-territory economics.
| Source | Description | Required |
|---|---|---|
| sales | Sales transactions | Required |
| customer_master | Customer master (with latitude / longitude) | Required |
| ctserve | Cost to serve | Optional |
Full schema details on the Data Schema page once you sign in.
Request a demo and we'll walk you through the modules with sample data shaped like yours.
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