Multi-agentResearch & Competitive IntelligenceAdvancedFree

Customer Interview Analysis System.

3 agents, 3 deliverables.

Run a multi-agent workflow to produce an execution-ready customer interview analysis system deliverable.

WORKFLOW META

Agents3

Total tokens (avg)~500

Run time9 min

AI toolChatGPT · Claude · Gemini

Variables4

DifficultyAdvanced

CategoryResearch & Competitive Intelligence

SEQUENCE MAP · CLICK TO JUMP

· 01 ·

Interview Transcript Processor

· 02 ·

Pattern Recognition Agent

· 03 ·

Insight Synthesis Agent

USE CASE INPUTS

Set the workflow's inputs once.

These variables feed into every agent prompt below. Fill them once, then copy each agent in order.

Number of customer interviews conducted

freelancers and small business owners

Interview topic

AI prompting for beginners

Current analysis method

Customer Interview Analysis System example context

Key decision to make from insights

Customer Interview Analysis System example context

THE AGENTS

The 3-step sequence.

AGENT · INTERVIEW TRANSCRIPT

Interview Transcript Processor

GOAL OF THIS STEP

Design the interview processing system. Create: (1) Transcript cleaning protocol (how to standardize transcripts for analysis), (2) Segmentation framework (break each interview into: context, problem exploration, solution feedback, buying behavior, quotes), (3) The initial coding scheme (15 codes to tag across transcripts — organized into 4 categories: pain points, gains, jobs, objections), (4) The affinity mapping process (how to move from codes to themes).

EXPECTED OUTPUT

Transcript cleaning protocol + segmentation framework + 15-code coding scheme + affinity mapping process

agent-01-interview-transcript-processor.md

### Input
Interview count, topic, current method

### Task
Design the interview processing system. Create: (1) Transcript cleaning protocol (how to standardize transcripts for analysis), (2) Segmentation framework (break each interview into: context, problem exploration, solution feedback, buying behavior, quotes), (3) The initial coding scheme (15 codes to tag across transcripts — organized into 4 categories: pain points, gains, jobs, objections), (4) The affinity mapping process (how to move from codes to themes).

### Output
Transcript cleaning protocol + segmentation framework + 15-code coding scheme + affinity mapping process

AGENT · PATTERN RECOGNITION

Pattern Recognition Agent

AGENT · INSIGHT SYNTHESIS

Insight Synthesis Agent

HOW TO RUN

Three steps. 9 min.

STEP 01

Fill in the variables at the top. Copy them into a note or your tool's context window — every agent below uses them.

STEP 02

In your AI tool, paste Agent 1 and run it. Copy the output. Paste Agent 2 with the output appended. Repeat in order for all 3 agents.

STEP 03

At the final agent, review and refine. It outputs your finished deliverable, ready to publish or hand off.

WHAT YOU GET

The final output, end-to-end.

Interview Transcript Processor

Transcript cleaning protocol + segmentation framework + 15-code coding scheme + affinity mapping process

Pattern Recognition Agent

5 themes by frequency + emotional intensity + unexpected findings + representative quotes + segment differences

Insight Synthesis Agent

3 actionable insights: statement + implication + confidence + recommended action + validation status each

★ MULTI-AGENT PACK

The Multi-Agent Operator Pack.

100 production-ready workflows like this one. Agent prompts, variable cheat-sheets, and the operator's guide.

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Customer Interview Analysis System.

Set the workflow's inputs once.

The 3-step sequence.

Interview Transcript Processor

Pattern Recognition Agent

Insight Synthesis Agent

Three steps. 9 min.

The final output, end-to-end.

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