First Contact Resolution Analyzer

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.

{{sample_of_20_50_tickets_with_2_contacts_}}
{{current_fcr_rate_and_fcr_definition_used}}
{{agent_notes_or_resolution_codes_from_eac}}

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}

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Why this 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.

Risks & review

FCR definitions vary widely. Validate that your FCR measurement window (same-day, 7-day, 30-day) aligns with your contact type before interpreting results.