Zapier + ChatGPT workflow for weekly support reports

Recommendation (one-line)
Use Zapier to pull and pre-aggregate Zendesk tickets into a weekly payload, then call ChatGPT to generate a concise executive summary, top-issue list, trends, and recommended actions.

Why this works
Zapier covers the integrations and scheduling reliably, and ChatGPT converts raw or pre-aggregated data into readable executive reports. This keeps the heavy lifting (aggregation, de-dup, simple metrics) in Zapier/Sheets and the narrative work in ChatGPT.

Decision criteria (pick based on your constraints)
- Budget: If you have Zapier paid plan + API access cost for ChatGPT, proceed. If budget is tight, use Google Sheets batch exports and run a cheaper script weekly.
- Skill level: Low/no-code teams—Zapier + ChatGPT is ideal. If you have dev resources, consider a small script (Python) for more control.
- Team size & cadence: Weekly summaries for small teams are fine with a single Zap. Larger teams or multiple queues may need a pipeline that pre-aggregates per queue before sending to ChatGPT.
- Output quality: For crisp, actionable executive text, invest time in prompt design and providing structured inputs (counts, sample excerpts).

Practical checklist (step-by-step)
1) Choose fields to surface: ticket_id, created_at, subject, tags, assignee, SLA breaches, first_response_time, resolution_time, satisfaction_score, transcript excerpt (if useful).
2) Build Zapier trigger: Zendesk “New Ticket” or “Updated Ticket” — filter to only tickets in the week window, or push all new tickets to a Google Sheet or Zapier Storage.
3) Aggregate weekly: use Storage by Zapier or Google Sheets to count by tag/subject/assignee, compute averages (FRT, resolution), and identify top subjects by count. Pre-aggregate rather than sending full text to save tokens.
4) Prepare ChatGPT input: create a compact JSON/CSV summary with top N buckets (issue, count, % change vs prior week), 3–5 sample ticket excerpts per top issue, and key metrics.
5) Prompt template (example):
System: “You are an executive-level support analyst. Convert the data into a 5-bullet executive summary, top 5 issues (count, % change, concise root cause), recommended actions with owner and priority, and 1-week trend chart description.”
User: “Here is the weekly summary JSON: { … } Generate: 1) 3-sentence summary, 2) top 5 issues with supporting excerpt, 3) three recommended actions.”
6) Call ChatGPT in Zapier: use the ChatGPT action (or OpenAI action) with that prompt and payload. Limit each request to a size that fits token limits—if >3k tokens, split by buckets and stitch outputs.
7) Send output to stakeholders: Email, Slack channel, Confluence page, or Zendesk macro. Also store the report in a weekly folder for historical comparison.

Best-for / Avoid-if
- Best-for: teams that need human-readable executive summaries weekly without building backend analytics; small to mid-sized support teams.
- Avoid-if: you need strict reproducible analytics, advanced statistical analysis, or PII-sensitive transcripts (then anonymize or process on-prem).

Notes and tips
- Reduce token usage: pre-aggregate counts and only send 1–3 short excerpts per issue. Avoid sending full transcripts unless needed.
- Quality: iterate the prompt for the tone/length stakeholders want; save a prompt template in Zapier.
- Scale: if you have many queues, aggregate per queue in Sheets and make separate ChatGPT calls.

If you want, I can draft the exact Zap steps + a ready-to-copy prompt tailored to your ticket fields and output length.

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