How can you use community outreach experiments to test and learn from different approaches?

1 Why experiment?

Community outreach experiments are useful for several reasons. First, they help you avoid wasting time and money on ineffective or inefficient outreach activities. By testing your assumptions and hypotheses before scaling up, you can learn what works and what doesn't, and make data-driven decisions. Second, they help you adapt to changing circumstances and feedback. By running multiple experiments with different variables, you can compare and contrast the results, and adjust your outreach plan accordingly. Third, they help you innovate and improve your outreach performance. By trying out new ideas and measuring their impact, you can discover new ways of reaching and engaging your audience, and increase your outreach effectiveness.

2 How to design experiments?

The first step in designing community outreach experiments is to define your goal and research question. What are you trying to achieve with your outreach? What do you want to learn from your experiment? For example, your goal could be to increase awareness, engagement, or conversions, and your research question could be related to your outreach channel, method, message, or audience. Next, you need to formulate your hypothesis and prediction. Based on your research question, what do you expect to happen in your experiment? For example, your hypothesis could be that using a certain outreach channel, method, or message will lead to a higher or lower outcome than another option, and your prediction could be the specific difference or change you anticipate. Finally, you need to decide on your experiment design and metrics. How will you set up and run your experiment? How will you measure and compare the results? For example, your experiment design could be a randomized controlled trial, a split test, or a before-and-after comparison, and your metrics could be quantitative or qualitative indicators of your outcome.

3 How to run experiments?

The second step in running community outreach experiments is to prepare and execute your experiment. Depending on your experiment design, you may need to do some or all of the following tasks: select and segment your sample, create and distribute your outreach materials, collect and store your data, and monitor and troubleshoot your experiment. You should also follow some best practices to ensure the validity and reliability of your experiment, such as: use a clear and consistent protocol, control for confounding factors, minimize bias and error, and document your process and results.

4 How to evaluate experiments?

The third step in evaluating community outreach experiments is to analyze and interpret your data. Depending on your metrics, you may need to do some or all of the following tasks: clean and organize your data, calculate and compare your statistics, visualize and summarize your data, and draw conclusions and recommendations. You should also follow some best practices to ensure the accuracy and usefulness of your analysis, such as: use appropriate and robust methods, check for assumptions and limitations, validate and verify your findings, and communicate your results clearly and effectively.

5 How to learn from experiments?

The fourth and final step in learning from community outreach experiments is to apply and share your learnings. Based on your conclusions and recommendations, you should do some or all of the following tasks: implement and scale your successful experiments, iterate and improve your unsuccessful experiments, test new hypotheses and predictions, and disseminate and discuss your learnings. You should also follow some best practices to ensure the impact and sustainability of your learnings, such as: align your learnings with your goals and strategy, monitor and measure your outcomes and impacts, seek and incorporate feedback and input, and foster a culture of learning and experimentation.

6 Examples of experiments

Illustrating how community outreach experiments work in practice, different organizations and sectors have conducted various experiments. For instance, a nonprofit organization tested email subject lines and content to boost open rates and donations for their fundraising campaign. Additionally, a health care provider trialed text messages and reminders to improve appointment attendance and medication adherence for their patients. Moreover, a social enterprise examined different online platforms and formats to heighten engagement and retention for their online courses. Lastly, a local government experimented with flyers and incentives to raise recycling and composting rates for their residents.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?