7thonline
Information Technology And Services, 24 W 40th St Fl 11, New York, 10018, United States, 201-500 Employees
Phone Number: 21********
Who is 7THONLINE
7thonline is a leading data-driven SaaS solution, powered by analytics and ML/AI for Tier 1 retailers that specializes in merchandise planning and demand forecasting for global retailers ...
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- Headquarters: 24 W 40th St Fl 11, New York, New York, 10018, United States
- Date Founded: 1999
- Employees: 201-500
- Revenue: $25 Million to $50 Million
- Active Tech Stack: See technologies
- CEO: Max Ma
Industry: Information Technology and Services
SIC Code: 7371
7thonline Org Chart and Mapping
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Frequently Asked Questions Regarding 7thonline
Answer: 7thonline's headquarters are located at 24 W 40th St Fl 11, New York, 10018, United States
Answer: 7thonline's phone number is 21********
Answer: 7thonline's official website is https://7thonline.com
Answer: 7thonline's revenue is $25 Million to $50 Million
Answer: 7thonline's SIC: 7371
Answer: 7thonline has 201-500 employees
Answer: 7thonline is in Information Technology and Services
Answer: 7thonline contact info: Phone number: 21******** Website: https://7thonline.com
Answer: 7thonline is a leading data-driven SaaS solution, powered by analytics and ML/AI for Tier 1 retailers that specializes in merchandise planning and demand forecasting for global retailers and wholesale brands. Our customers such as Patagonia, Michael Kors, Canada Goose, Calvin Klein, Jimmy Jazz and Tommy Hilfiger are able to drive tangible results including higher inventory turns, decreased markdowns, increased fill rate, and greater margins. Our solution offerings span across all key channels: retail, wholesale and eCommerce. This makes us uniquely positioned to help progressive brands and retailers to meet todays omni-channel challenge, enabling them to make integrated merchandising decisions based on localized demand. Our complete suite of merchandise and assortment management solutions help customers drive profit margins through effective inventory optimization based on granular-level demand insights.
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