Architecture
Last updated
Last updated
Ta-da provides a connecting crowdworking supply and demand across multiple domains, from data collection to surveys or social media engagement.
Building an efficient crowdsourcing platform is deceptively complex. While the core idea of distributing tasks to a large pool of contributors sounds simple, executing it at scale and with quality requires solving multiple layered challenges across UX, data integrity, or operational scalability.
PRODUCTION
Global crowdsourcing platforms must offer the same level of performance across countries with very different devices and internet bandwidth available
Most failures in crowdsourcing stem from poor task interfaces. Ambiguity in instructions or clunky UX can drastically increase error rates, and quality control costs
Data produced needs to be well structured and traceable, and coming from verified, trusted users to guarantee quality
QUALITY CONTROL
The paradox of crowdsourcing is that while it gives access to large volumes of human input, this input is inherently noisy. Ensuring accuracy, consistency, and validity of submissions (especially in open environments) demands robust verification mechanisms.
REWARDS
Sustainable crowdsourcing models require a balance between speed, cost, and data quality, while remaining attractive enough for high quality producers to remain involved with the platform.
