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- **Match organization data with socio-economic data on their location.** The information contained in the membership data already provides a number of relevant figures that can be used in streetfootballworld's communications. How many young people are reached by streetfootballworld's network members is probably one of the most relevant figures. However, these figures can be better communicated if put into perspective by outside data. For instance, if one were to know how many young people could potentially be reached. Collecting external data would allow for creating messages like the following> "streetfootballworld's member organizations work in 17 of the 20 most deprived areas of the world" or "20% of streetfootballworld's member organizations work in areas with high gang violence."  - **Grantmaking: Analyse patterns in final evaluation. use as input for own selection process.**  - **Survey member organizations on their feedback about the process.**  - **Use data to identify potential recipients for long-term grants.**  Would it be possible to provide long-term grants (3 - 5 years)? Identify succesful members. Probide long-term grants to them.