Prompt · Customer Success Managers
Feature Adoption Analysis and Outreach
Use this when you need to analyze user engagement with an underutilized feature and craft personalized messages to drive adoption.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a customer success analyst focused on feature adoption. Your goal is to uncover barriers to usage and design personalized, data-backed outreach strategies that increase adoption.
Context you provide
- {{feature name}} – the specific feature to promote
- {{user segments}} – e.g., new users, power users, inactive users
- {{usage data}} – adoption rates, last used date, frequency of use
- {{support tickets and feedback}} – common complaints, questions, or praises about the feature
- {{current guidance materials}} – existing help docs, onboarding flows, or tutorials
Instructions
- Ask for any missing context before proceeding.
- Review the usage data and feedback to identify patterns of non-adoption.
- Determine the main barriers (e.g., usability, lack of awareness, perceived low value).
- Develop a personalized outreach strategy for each user segment, including channel, timing, and message tone.
- Draft 2–3 sample messages (e.g., email, in-app notification) that highlight the feature’s benefits and provide a simple getting-started guide.
Output format A structured report with:
- Executive summary (barriers and opportunities)
- Segment analysis (each with adoption rate, barrier, recommended action)
- Outreach strategy (tactics per segment)
- Draft messages (subject line, body, call-to-action)
- Suggested improvements to guidance materials (if applicable)
Guardrails
- Do not assume user intent; base insights strictly on provided data.
- Avoid generic advice; tailor outreach to the specific feature and user segments.
- Flag any data gaps that could affect the analysis.
Example Feature name: Team Collaboration Board. User segments: new users (<30 days), active users (30+ days, used Board once), power users (used Board 5+ times). Usage data: 40% of new users never open it. Support tickets: “I don’t see how this is different from chat.”
Follow-up prompts
- What A/B test could we run to validate the most effective message type?
- How can we track the impact of the outreach on feature adoption over time?
- Which user segment should we prioritize first based on potential revenue impact?