We propose a basic framework we call precision crowdsourcing – a systematic way of approaching the process of turning an information consumer into a long-term contributor through a series of requests, feedback, and interaction. The framework identifies five key decisions related to precision crowdsourcing:
- Who we ask. the selection of users that we are requesting from, considering users’ history of interactions with the system.
- What we ask for. the task type and contents, considering properties such as task effort, complexity, and relationship to the user’s current context and history. Do we ask for immediate effort or a commitment for later effort?
- When we ask. how does the request relate in time to the user’s activity, including any user interaction with the content related to the task? Do we interrupt, ask later, or even ask at a time triggered by other actions.
- How we ask. what is the rhetoric of the request? Do we frame contribution as self-benefiting? As a way to help others? As an obligation of membership?
- What feedback follows. Do we thank the users? How and when? Do we reference the impact of the contribution on others? Achievement of contribution milestones? Do we link past contributions to future requests?