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Onboarded a junior with this dataset. Address quality is the strongest column in the file. Genuinely useful.
Wanted a Australia list with verified phones. Email coverage is the highest I've seen for Australia B2B data. Bought it for our hardware retail store sales team's Australia pipeline. Will buy again.
Bought it to seed a CRM import. Lat/long landed every pin on the right storefront in Mapbox. Saved us hours of manual cleanup.
Live-tested 30 random rows before committing. Refresh cadence means the data feels current, not 2-years-old. Bought it to map hardware retail store density across Australia. Will buy again.
Bought a sample first. ROAS improved roughly 30% versus the lookalike audience we ran before. Bought it while building a hardware retail store prospecting workflow for Australia. Workable, the LinkedIn coverage could be better.
Loaded the file the morning we got it. The phone column was live for 95% of the rows I tested. Bought it for a Australia hardware retail store market-sizing project. Recommended.
Ran the CSV through our deduper first. Bounce rate stayed under 4% on a 1,000-contact email send. Bought it for hardware retail store prospecting across Australia. Minor cleanup needed but nothing major.
Needed it for a fast launch. ROAS improved roughly 30% versus the lookalike audience we ran before. Bought it for our hardware retail store outreach in Australia. Couple of small gaps but workable.
Field-tested by my team. Sample matched live data when I spot-checked random rows. Bought it as the seed list for a hardware retail store outbound push in Australia. Connect rate could have been higher with cleaner mobile numbers.
Last Update:
Aug 16, 2026 05:45 AM
Published:
May 11, 2026 01:54 AM
Rows (Extended):
477
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
