DESIGN
Post-Launch Evaluation
Collect and Analyze User Feedback
Post-launch feedback provides insights into user satisfaction, pain points, and potential feature requests.
Why it's Important
Ensures the product evolves based on user needs.
Highlights issues missed during pre-launch testing.
Builds user trust by showing responsiveness.
How to Implement
Set Up Feedback Channels: Use surveys, support tickets, reviews, and forums.
Encourage User Engagement: Prompt users to share feedback within the app or website.
Categorize Responses: Group feedback into usability issues, feature requests, and general comments.
Prioritize Themes: Focus on recurring or high-impact feedback.
Follow Up: Respond to user feedback and communicate changes made.
Available Workshops
Feedback Review Sessions: Organize and prioritize user responses.
Pain Point Mapping: Identify frequent frustrations from feedback.
Feature Request Analysis: Evaluate the feasibility of new feature suggestions.
Sentiment Analysis Workshop: Assess overall user satisfaction trends.
Follow-Up Planning: Plan how to address and communicate fixes or updates.
Deliverables
Categorized user feedback report.
Actionable insights based on feedback.
Updated feature roadmap incorporating high-priority items.
How to Measure
Volume and quality of user feedback collected.
Percentage of actionable insights derived.
User satisfaction ratings after addressing feedback.
Real-World Examples
Slack
Introduced custom statuses and notification preferences based on user feedback.
Netflix
Adjusted playback controls after users requested better rewind and skip options.
Added dark mode following significant user demand.
Get It Right
Make feedback collection seamless and accessible.
Act on high-impact feedback quickly.
Regularly communicate updates based on user input.
Use both quantitative and qualitative feedback.
Create a feedback loop that encourages ongoing engagement.
Don't Make These Mistakes
Ignoring feedback from less vocal user segments.
Collecting feedback without acting on it.
Dismissing feature requests without proper evaluation.
Overloading users with excessive feedback requests.
Failing to acknowledge user contributions.