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Bought this for a cold outbound push. Connect rate jumped noticeably once we filtered by category. Bought it for a Australia discount retail store market-sizing project. Will reconsider for the next refresh.
Used it for a market-sizing exercise. Loaded into Power BI without a single import warning. Bought it for a Australia-focused discount retail store territory cut. Renewed for another quarter already.
Loaded the file the morning we got it. Lat/long landed every pin on the right storefront in Mapbox. Bought it to underpin a Australia discount retail store campaign. Will be the default vendor for us now.
Compared this side-by-side with two competitors. Imported into HubSpot in two clicks, every column mapped automatically. Bought it to map discount retail store density across Australia. Worth the price.
Onboarded a junior with this dataset. Catchment overlap with our existing CRM was minimal — almost all net-new leads. Bought it for our discount retail store sales team's Australia pipeline. Genuinely useful.
Honest reaction after a week of use: Categorisation was granular enough to segment by sub-vertical without regex. No complaints from the field reps.
Fine for the prospecting list. Categorisation was granular enough to segment by sub-vertical without regex. One column I'd add next refresh: secondary email.
Fine for the prospecting list. Dedup pass only flagged 1.2% — cleanest dataset I've worked with. Bought it to scope a Australia territory in the discount retail store segment. Connect rate could have been higher with cleaner mobile numbers.
Bought a sample first. Lat/long landed every pin on the right storefront in Mapbox. Worth the price.
Field-tested by my team. Encoded UTF-8 with no character-set surprises in Excel. Bought it as the seed list for a discount retail store outbound push in Australia. Otherwise no complaints.
Last Update:
Aug 18, 2026 05:45 AM
Published:
May 11, 2026 01:55 AM
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Roll-up datasets — broader coverage at a higher tier are highlighted below.
