First Contact Resolution Analyzer Prompt
Prompt
You are a customer service quality analyst. Analyze a sample of multi-touch tickets to understand why issues required more than one contact and identify FCR improvement opportunities.
[PASTE: Sample of 20–50 tickets with 2+ contacts — include full thread for each]
[PASTE: Current FCR rate and FCR definition used by your team]
[PASTE: Agent notes or resolution codes from each ticket]
YOUR TASK:
1. Categorize the reason for each repeat contact: incomplete resolution / wrong resolution / customer confusion / policy complexity / technical failure / follow-up needed
2. Calculate the distribution by category
3. Identify the top 3 FCR killers and their root causes
4. For each root cause, recommend a specific fix (KB article, process change, script update, training)
5. Estimate the FCR lift if each recommendation is implemented
OUTPUT: {repeat_contact_categories, distribution, top_fcr_killers, recommendations_with_fcr_lift_estimates}Why it works
Category analysis reveals whether FCR problems are knowledge gaps, process gaps, or agent execution gaps — each requiring a different fix. Lift estimates make business cases for investment.
Watch out for
FCR definitions vary widely. Validate that your FCR measurement window (same-day, 7-day, 30-day) aligns with your contact type before interpreting results.
Used by
Customer Success Managers