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Sales territory planning with geographic + firmographic scraping

Use cases·1 min read·Updated 2026-05-13·3 sections

You're hiring 5 sales reps and need to give each a balanced territory. Naive splits (by alphabet, by state) waste capacity. Density-based splits using actual account counts per region produce 30-50% better quota attainment.

01

Step 1: map your TAM

For each target metro or region, run Kavex Maps + LinkedIn Companies with your ICP filters. Count accounts per region.

Rate
2 credits / lead
Google Maps
1 credit
$0.001
credits never expire
Per 1,000
$2.00
2,000 credits
RUN SIZECREDITSCOST
30 leads60$0.06
100 leads200$0.20
500 leads1,000$1.00
1,000 leads2,000$2.00
2 credits a lead · 1 credit = $0.001 · a run that finds fewer pays less
02

Step 2: weight by ARPU

Not every account is equal. Multiply count by expected ARPU per region (LinkedIn company size as proxy).

03

Step 3: split to balance

Allocate reps so each gets roughly equal weighted-account count, not equal headcount.

Written after running it
Last run
plumbers · London · Google Maps
Rows
30
Time
23s
Cost
€0.06
30 rows × 2 credits = 60 credits · 1 credit = $0.001

Every number on this page comes from that run, not from a price list.

Point it at something. See what comes back.Your first 500 Google Maps leads are on the house. No card needed.
Start scraping free