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Picked it up for cold outbound. ROAS improved roughly 30% versus the lookalike audience we ran before. Bought it to scope a India territory in the subway store locations segment. Otherwise no complaints.
Onboarded a junior with this dataset. Categorisation was granular enough to segment by sub-vertical without regex. Saved us hours of manual cleanup.
Saved me a scraping project I'd been dreading. Address quality is the strongest column in the file. Bought it to map subway store locations density across India. Worth the price.
Bought it to seed a CRM import. Cross-checked 50 entries against Google Maps and 47 matched cleanly. Bought it while planning a subway store locations campaign in India. Sales team is happy.
Mixed feelings on this one. Phone numbers ring through for the most part. Bought it as part of a wider subway store locations expansion into India. Asked support how to flag the closed-storefront rows.
Last Update:
Jun 30, 2026 02:37 AM
Published:
Jun 11, 2026 15:02 PM
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