four scenarios · four roles

what teams actually do here, monday morning.

not feature lists. real workflows that ship. here's the same platform from four chairs, pm, cs, engineering, growth.

product manager

investigating a feature problem.

1. search: "show me all conversations about the new search feature"

2. sentiment analysis shows 60% negative sentiment on this topic

3. replay conversations. users get stuck waiting for results after turn 3

4. share a deep link to the exact conversation turn with engineering

5. prioritize the fix based on user impact data, not guesswork

time to insight: 5 minutes. no engineering ticket needed.

customer success

1. open the overview dashboard. see 12 users with declining health scores

2. click a user profile. their last 3 conversations all ended unresolved

3. read the ai summaries. they've been asking about api limits repeatedly

4. plan proactive outreach: "i noticed you've had trouble with api limits. here's what we're doing about it."

5. save the user from churning before they ever file a support ticket

early intervention. better retention.

engineering leader

1. pm shares a deep link: "this conversation shows the billing tool failing at turn 5"

2. search for the pattern: 20 users hit the same tool failure this week

3. concentrated in enterprise users asking about pricing

4. fix the prompt. re-run the search post-fix to measure impact

pm self-served the investigation. you just got a clear, prioritized bug report.

growth team

1. check sentiment scores across user segments after launching a new agent feature

2. enterprise users: 75% positive. free users: 40% positive

3. drill into free user conversations. the feature requires a paid api key they don't have

4. add a graceful fallback for free users. monitor sentiment improvement

measure what users actually feel, not just what they click.

connect your conversation data and start reading what your users actually experienced.