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Saved me a scraping project I'd been dreading. Sample matched live data when I spot-checked random rows. Bought it for our obstetrician doctor sales team's India pipeline. Will be the default vendor for us now.
Field-tested by my team. ROAS improved roughly 30% versus the lookalike audience we ran before. Bought it for India's obstetrician doctor segment specifically. Decent value, would tighten one or two fields.
Compared this side-by-side with two competitors. Catchment overlap with our existing CRM was minimal — almost all net-new leads. Bought it to support a obstetrician doctor rollout in India. Sales team is happy.
Looking to scope a regional rollout. Categorisation was granular enough to segment by sub-vertical without regex. Bought it for India's obstetrician doctor segment specifically. Renewed for another quarter already.
Loaded the file the morning we got it. Refresh cadence means the data feels current, not 2-years-old. Bought it to support a obstetrician doctor rollout in India. Will buy again.
Bought a sample first. Dedup pass only flagged 1.2% — cleanest dataset I've worked with. Bought it for our obstetrician doctor sales team's India pipeline. Will buy again.
Bought it to seed a CRM import. Imported into HubSpot in two clicks, every column mapped automatically. Bought it to underpin a India obstetrician doctor campaign. Will buy again.
Honest reaction after a week of use: Hours-of-operation field meant my SDRs called during open windows. Bought it to map obstetrician doctor density across India. Genuinely useful.
Honest reaction after a week of use: Hours and GPS were the missing pieces in my last vendor's file — this has both. Otherwise no complaints.
Live-tested 30 random rows before committing. Connect rate jumped noticeably once we filtered by category. Bought it for India's obstetrician doctor segment specifically. Worth the price.
Onboarded a junior with this dataset. Lat/long landed every pin on the right storefront in Mapbox. Will buy again.
Picked it up for a one-off campaign. Cross-checked 50 entries against Google Maps and 47 matched cleanly. Bought it for a India obstetrician doctor market-sizing project. Sales team is happy.
Picked it up for a one-off campaign. Categorisation was granular enough to segment by sub-vertical without regex. Will buy again.
Needed it for a fast launch. ROAS improved roughly 30% versus the lookalike audience we ran before. Renewed for another quarter already.
Ran the CSV through our deduper first. Website URLs were populated for ~80% of rows, far better than the competition. Bought it to underpin a India obstetrician doctor campaign. Acceptable trade-off at this price.
Pulled the trigger after reading the row count. ROAS improved roughly 30% versus the lookalike audience we ran before. Bought it to scope a India territory in the obstetrician doctor segment. Worth the price.
Fine for the prospecting list. Loaded into Power BI without a single import warning. Bought it to handle obstetrician doctor lead-gen for the India region. Workable, the LinkedIn coverage could be better.
Latitude / longitude was useful for the mapping work. A couple of rows had stale hours, easy to filter out but worth flagging.
Last Update:
Aug 19, 2026 06:04 AM
Published:
May 11, 2026 03:35 AM
Rows (Extended):
310
Category:
Roll-up datasets — broader coverage at a higher tier are highlighted below.
