COLLECT

Feedback Labs Members' Community Learning Site

Step 2: Collect

The Collect stage is where an AI- and tech-enabled feedback loop moves from planning to action: this is when you actually ask for and receive feedback.

In multilingual and low-participation contexts, good design means meeting people where they are—using simple, well-timed surveys and reminders or even low-tech options when digital tools aren’t accessible.

Effective collection focuses on asking only what you truly need, mixing simple formats with open-ended prompts, and sending clear, language-appropriate reminders or alternative participation options. Throughout, it’s essential to be transparent about automated analysis and data privacy so communities understand how their data will be used and can trust the process.

Typical Challenges Organizations Face

Here is a common challenge that we have found organizations experience in the Collect stage of their feedback loop:

Accessibility

Low participation in multilingual and low-participation communities

Tech Tools & Use Cases

Here are two common strategies that we have found organizations use in the Collect stage of their feedback loop:

Survey tools:

- Tech - Google Forms, Survey Monkey, Typeform
- SMS - WhatsApp, Signal

Use Cases

Send automated reminders to complete the collection method (e.g., survey, sign-up for focus groups, meeting details)

AI Tools & Use Cases

Here are two common strategies that we have found organizations use AI in the Collect stage of their feedback loop:

Platforms

Use Cases

Promotion/reminder frequency and language suggestions
Brainstorm alternative ways to collect if tech is not accessible

Ethical Considerations

Transparency

Include a note in the survey explaining automated analysis and data privacy

Check out more ethical considerations and guidelines in our AI and Tech Resource Guide.

Page updated

Report abuse