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Pulled the trigger after reading the row count. Categorisation was granular enough to segment by sub-vertical without regex. Bought it while planning a peter piper pizza locations campaign in United States. Saved us hours of manual cleanup.
Pulled the trigger after reading the row count. Address quality is the strongest column in the file. Bought it for a United States-focused peter piper pizza locations territory cut. Renewed for another quarter already.
Got it for a territory planning project. Sample matched live data when I spot-checked random rows. Bought it as the seed list for a peter piper pizza locations outbound push in United States. Saved us hours of manual cleanup.
Looking to scope a regional rollout. Encoded UTF-8 with no character-set surprises in Excel. Bought it while building a peter piper pizza locations prospecting workflow for United States. Will buy again.
Built a Looker Studio dashboard off the dataset for a client pitch. The category granularity made the slice-and-dice trivial.
Last Update:
Jun 30, 2026 02:37 AM
Published:
Jun 11, 2026 15:01 PM
Rows (Extended):
95
Category:
