Shoe Store Database of South Australia Latest August 2026 Updated

Ran the CSV through our deduper first. Google rating column came included, which we hadn't expected. Money well spent.

Wanted a Australia list with verified phones. Dedup pass only flagged 1.2% — cleanest dataset I've worked with. Bought it to scope a Australia territory in the shoe store segment. Money well spent.

Used it for a market-sizing exercise. Cross-checked 50 entries against Google Maps and 47 matched cleanly. Bought it for our shoe store outreach in Australia. Saved us hours of manual cleanup.

Tried three vendors before this. Connect rate jumped noticeably once we filtered by category. Will reconsider for the next refresh.

Picked it up for a one-off campaign. Bounce rate stayed under 4% on a 1,000-contact email send. Bought it as part of a wider shoe store expansion into Australia. Worth the price.

Needed addresses field reps could actually drive to. The phone column was live for 95% of the rows I tested. Bought it to handle shoe store lead-gen for the Australia region. Will be the default vendor for us now.

Onboarded a junior with this dataset. Website URLs were populated for ~80% of rows, far better than the competition. Saved us hours of manual cleanup.

Onboarded a junior with this dataset. Refresh cadence means the data feels current, not 2-years-old. Bought it to handle shoe store lead-gen for the Australia region. Will buy again.

Honest reaction after a week of use: Imported into HubSpot in two clicks, every column mapped automatically. Bought it to map shoe store density across Australia. Will buy again.

Solid file overall. Categorisation was granular enough to segment by sub-vertical without regex. Minor cleanup needed but nothing major.

Used it for a market-sizing exercise. Sample matched live data when I spot-checked random rows. Bought it while building a shoe store prospecting workflow for Australia. Will be the default vendor for us now.

Compared this side-by-side with two competitors. Email coverage is the highest I've seen for Australia B2B data. Bought it to scope a Australia territory in the shoe store segment. Saved us hours of manual cleanup.

Honest reaction after a week of use: Refresh cadence means the data feels current, not 2-years-old. Bought it to underpin a Australia shoe store campaign. Sales team is happy.

Tried three vendors before this. Cross-checked 50 entries against Google Maps and 47 matched cleanly. Bought it for a Australia shoe store market-sizing project. Renewed for another quarter already.

Pulled the trigger after reading the row count. Address quality is the strongest column in the file. Bought it to support a shoe store rollout in Australia. Recommended.

Pulled the trigger after reading the row count. Email coverage is the highest I've seen for Australia B2B data. Bought it to scope a Australia territory in the shoe store segment. Will be the default vendor for us now.

Got it for a territory planning project. Google rating column came included, which we hadn't expected. Bought it while planning a shoe store campaign in Australia. Worth the price.

Needed addresses field reps could actually drive to. Website URLs were populated for ~80% of rows, far better than the competition. Recommended.

Bought for a one-time project. Connect rate jumped noticeably once we filtered by category. Workable, the LinkedIn coverage could be better.

Ran the CSV through our deduper first. Categorisation was granular enough to segment by sub-vertical without regex. Recommended.

Needed it for a fast launch. Hours and GPS were the missing pieces in my last vendor's file — this has both. Bought it for a Australia-focused shoe store territory cut. Saved us hours of manual cleanup.

Stress-tested it during a client pitch. Address quality is the strongest column in the file. Bought it for Australia's shoe store segment specifically. Will be the default vendor for us now.