Industry workflows
Google Maps scraper for B2B sales
Sales teams lose more time to list building and territory arguments than to selling. A defined, deduplicated list split cleanly by geography removes both problems, and the qualifying fields mean a rep opens with something specific rather than reading a name off a spreadsheet.
What you get
- Deduplication so two reps never call the same business
- Geographic fields for clean territory splits
- Website, rating and review signals attached to every row
- Filters applied before extraction, so lists arrive qualified
- Consistent columns for repeatable CRM imports
- Re-runnable searches for quarterly territory refreshes
Territory splits that do not cause arguments
Splitting a list alphabetically or by row count creates disputes, because the patches are not comparable. Splitting geographically, by ZIP, postcode district or suburb, gives each rep a coherent patch they can learn and visit. The address field carries what you need for that split, and the deduplication means no business sits in two territories at once.
Give every row a reason to call
A name and number produces a generic opener and a generic result. The same row also carries category, rating, review count and website status. A rep who opens with a reference to the prospect actual situation gets a different reception from one reading off a list. This is the cheapest available improvement to connect and conversion rates, and it needs no new tooling.
Qualify before the list reaches the rep
Reps should not be deciding whether a row is worth working. Encode the ICP as filters: categories in scope, rating bands, review thresholds, website status. The list that reaches them is then already in scope, and the time they spend is spent on conversations. It also makes rep performance comparable, because they are all working the same quality of input.
Importing into the CRM without creating duplicates
The export deduplicates within itself, but it does not know what is already in your CRM. Dedupe on import against existing accounts, ideally on phone or website domain rather than business name, since names vary in formatting. Run a small batch first and check how records landed before pushing a full territory into a live pipeline.
Refresh territories quarterly
Local business data decays fast enough to matter within a quarter. Businesses close, numbers change, websites appear. Re-running the territory searches quarterly and diffing against the CRM surfaces new businesses in the patch, which are usually the most receptive prospects in it, and flags the dead rows before a rep wastes a week on them.
Frequently asked questions
What is the cleanest way to split territories?
Geographically, by ZIP, postcode district or suburb. Alphabetical or row-count splits create patches reps cannot learn and arguments about fairness.
Will two reps end up calling the same business?
Not from within one export, which deduplicates on place identity. Dedupe against your CRM on import to catch overlaps with existing accounts.
What should reps be given beyond a phone number?
Category, rating, review count and website status. Those turn a generic opener into a specific one and are the cheapest improvement available to connect rates.
Should reps qualify rows themselves?
No. Encode the ICP as filters before extraction so the list arrives in scope and rep performance is comparable across the same input quality.
How often should territories be refreshed?
Quarterly. New businesses in a patch are often the most receptive prospects, and refreshing clears dead rows before reps work them.