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Picked it up for cold outbound. Lat/long landed every pin on the right storefront in Mapbox. Workable, the LinkedIn coverage could be better.
Bought it to seed a CRM import. Connect rate jumped noticeably once we filtered by category. Will buy again.
Bought a sample first. Connect rate jumped noticeably once we filtered by category. Bought it for budget hotel prospecting across India. Workable, the LinkedIn coverage could be better.
Pulled the trigger after reading the row count. Address quality is the strongest column in the file. Bought it as the seed list for a budget hotel outbound push in India. Money well spent.
Field-tested by my team. Cross-checked 50 entries against Google Maps and 47 matched cleanly. Bought it to scope a India territory in the budget hotel segment. Will buy again.
Compared this side-by-side with two competitors. Email coverage is the highest I've seen for India B2B data. Bought it for budget hotel prospecting across India. No complaints from the field reps.
Stress-tested it during a client pitch. Cross-checked 50 entries against Google Maps and 47 matched cleanly. Saved us hours of manual cleanup.
Decent dataset for the price. Hours-of-operation field meant my SDRs called during open windows. Bought it for India's budget hotel segment specifically. Minor cleanup needed but nothing major.
Looking to scope a regional rollout. Bounce rate stayed under 4% on a 1,000-contact email send. Bought it while planning a budget hotel campaign in India. Saved us hours of manual cleanup.
Loaded the file the morning we got it. The phone column was live for 95% of the rows I tested. Bought it for our budget hotel sales team's India pipeline. Renewed for another quarter already.
Saved me a scraping project I'd been dreading. The phone column was live for 95% of the rows I tested. Sales team is happy.
Bought this for a cold outbound push. Hours-of-operation field meant my SDRs called during open windows. Recommended.
Onboarded a junior with this dataset. Loaded into Power BI without a single import warning. Bought it as part of a wider budget hotel expansion into India. Will buy again.
Compared this side-by-side with two competitors. The phone column was live for 95% of the rows I tested. Bought it to scope a India territory in the budget hotel segment. Recommended.
Stress-tested it during a client pitch. Imported into HubSpot in two clicks, every column mapped automatically. Bought it to support a budget hotel rollout in India. Renewed for another quarter already.
Looking to scope a regional rollout. Hours-of-operation field meant my SDRs called during open windows. Bought it for India's budget hotel segment specifically. Will be the default vendor for us now.
Needed addresses field reps could actually drive to. Address quality is the strongest column in the file. Bought it for a India budget hotel market-sizing project. Recommended.
Bought a sample first. Google rating column came included, which we hadn't expected. Renewed for another quarter already.
Last Update:
Aug 18, 2026 05:45 AM
Published:
May 11, 2026 02:28 AM
Rows (Regular):
2,815
Rows (Extended):
5,629
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
