Ipsos iSay

Survey Respondent in China


About the company

Ipsos iSay is a rewards community dedicated to ensuring your valued opinion makes a difference for societies, governments and brands. There are millions of Ipsos iSay members across more than 50 markets globally. Ipsos iSay is a part of Ipsos, one of the world’s largest market research firms.

Job description

We're hiring a Survey Respondent to provide valuable feedback on new products, advertisements, and various topics, contributing directly to global company and institutional decisions. This role creates significant impact by influencing key business decisions, operating from a fully remote setup with complete flexibility and no set hours. Key Responsibilities: - Complete paid online surveys matched to your profile and interests, influencing product concepts and brand experiences for leading companies worldwide. - Share opinions on consumer trends, product innovations, and healthcare topics, directly shaping future products and policies through thoughtful feedback. - Participate in exclusive research studies and specialized panels through the Ipsos network, contributing to in-depth market understanding and strategic development.

Job benefits

- Earn iSay points for every completed survey, equating to $0.01 per point, with typical surveys paying between $0.45 and $2.00, cash out from $5. - Enjoy a fully remote, flexible, self-paced opportunity with no set hours or minimum commitments, choosing when and how often to participate. - Receive bonus points for referrals and screening out, with reward options including PayPal, Visa prepaid cards, and gift cards from Amazon.

Job requirements

- 0 years experience needed, as no prior experience is required; your honest and thoughtful opinions are the primary qualification. - Access a smartphone, tablet, or computer with an internet connection; utilize the Ipsos iSay mobile app (iOS/Android) for survey completion. - Demonstrate willingness to provide honest, thoughtful answers to survey and screening questions, ensuring high-quality data contribution.