See whether an issue is improving after a fix or getting worse.
You need to know whether an issue is getting better or worse. Chattermill tracks a chosen theme over time, so you can see if an action worked or a problem is growing.
This guide walks you through selecting a theme, viewing its trend, marking when you deployed a change, and assessing whether the theme improved afterwards. You finish with evidence of impact to report.
Replace manual feedback review with an evidence-based customer-health summary.
Give management an evidence-based view of complaint drivers without manual compilation.
Show which issues most drive customers to leave so fixes target what matters.
Select the complaint theme to track. Choose the theme you want to monitor.
View its volume and sentiment trend over time. Display the theme's volume and sentiment over time.
Mark when any fix or change was made. Note the date when the fix or change was deployed.
Assess whether the theme improved after the change. Compare the trend before and after the change date.
Report the trend as evidence of impact. Use the trend data to show whether the action worked.
Scenario: [Your team] deployed a fix on [date]. You want to see if complaints declined. 1. Select the [theme name] theme in Chattermill. 2. Set the date range to [period before the fix] through [period after]. 3. Mark [fix deployment date] on the trend. 4. Observe: - Volume before: [X mentions] - Volume after: [Y mentions] - Sentiment before: [score] - Sentiment after: [score] 5. Report: "[Theme] complaints changed after the fix on [date]."
Track the [theme] over time by volume and sentiment, mark when the related change was made, and show whether the theme improved afterwards.
Surface negative sentiment and churn signals tied to specific customers.
Analyse NPS, CSAT, and support conversations together rather than piecemeal.