Conversation analysis is too much of a hassle: use ChatGPT, Claude, and Gemini to do customer service QA in one click, then use Midjourney to generate visuals

Customer service chat logs pile up like mountains. If you want to know what users are actually cursing about, what they’re praising, and which step they’re getting stuck on, doing it manually will make you doubt your life. My lazy approach is: break “conversation analysis” into a few small tasks, keep it KISS, delegate the work across ChatGPT, Claude, and Gemini, and finally have Midjourney make the results look presentable.

Split conversations by topic first, so your analysis doesn’t get messier and messier

Don’t just dump everything into a model in one go—you’ll likely end up with a bunch of “sounds reasonable but useless” summaries. Learn the multi-conversation/multi-topic approach: group the logs by themes like orders, refunds, login, and invoices; then do the most basic cleanup—remove sensitive information such as phone numbers, addresses, and order IDs. Don’t gamble on privacy.

ChatGPT is good for standardized labels and KPI definitions

I have ChatGPT output a set of unified fields: intent, emotion, resolved or not, time-consuming points, and recommended actions. Its advantage is that it reliably “hands in homework in the required format,” making it great for QA checklists and dashboard metrics.

Claude is better at reading long conversations and is suited for digging out root causes

When you run into those tricky cases that drag on for 30 back-and-forth turns, Claude reads more smoothly and can clearly explain the user’s real request, triggers, and scripting issues. A side note: sometimes it sounds even more like a supervisor than the supervisor does.

Gemini is good for cross-channel attribution and trends

When you mix web forms, emails, and live chat together, Gemini makes it easy to track “how the same issue evolves across different channels.” It’s handy for VoC trends and high-frequency issue rankings.

Midjourney turns reports into visuals you can show your boss

No one likes reading text-only conclusions. Have Midjourney generate a “customer service QA dashboard-style” poster image or a flowchart background—visually it looks instantly two levels more professional. You can write prompts like this:
Customer service conversation analysis dashboard, including a top high-frequency issues ranking, emotion trends, a donut chart for resolution rate, flat corporate style, blue-gray color scheme, clean whitespace

Pitfalls I’ve hit—don’t repeat them

• Too much noise in the conversation data: typos, slang, fragments—remember to have the model “quote evidence sentences verbatim.”
• Training bias: don’t only look at “average emotion”; look at triggers behind extreme negative reviews.
• Trust issues: always mask sensitive information; if it can be done locally, don’t put it in the cloud.

If you’re currently stuck because account/subscription/region restrictions are making the tools hard to use, or you want to run this workflow more cheaply, you can check out Titikey. I also put some commonly used prompts and a pitfall-avoidance checklist there—copying it directly will be faster.