# Segment players and predict churn with OpenAI: n8n workflow

> Started by another system calling it, and works across in-memory vectors and n8n data table.

Source: https://millionrounds.com/workflow/segment-players-and-predict-churn-with-openai (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [AI assistants](https://millionrounds.com/workflows?category=AI+assistants#library)

# Segment players and predict churn with OpenAI

Started by another system calling it, and works across in-memory vectors and n8n data table. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 23 steps: large, and worth reading before you trust it with anything live.

Large Calls a model: OpenAI Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fsegment-players-and-predict-churn-with-openai)

**23 steps** Large: read it before trusting it with anything live

**0** Branches: places the flow splits

**0** Loops or waits

**2** Services it connects to

## The flow

Starts it 2 Model 19 Logic 1 Service 1

The steps in the order they run, from what starts it.

- 1 **Gameplay Logs Webhook** Webhook *Starts it*
- 2 **Segmentation Model** Lm Chat Open Ai *Model*
- 3 **Segmentation Output Parser** Output Parser Structured *Model*
- 4 **Player Behavior Embeddings** Embeddings Open Ai *Model*
- 5 **Metrics Calculator** Tool Calculator *Model*
- 6 **Statistical Analysis Tool** Tool Code *Model*
- 7 **Prediction Model** Lm Chat Open Ai *Model*
- 8 **Prediction Output Parser** Output Parser Structured *Model*
- 9 **Reward Simulation Model** Lm Chat Open Ai *Model*
- 10 **Reward Simulation Output Parser** Output Parser Structured *Model*
- 11 **Pricing Simulation Model** Lm Chat Open Ai *Model*
- 12 **Pricing Simulation Output Parser** Output Parser Structured *Model*
- 13 **Testing Roadmap Model** Lm Chat Open Ai *Model*
- 14 **Testing Roadmap Output Parser** Output Parser Structured *Model*
- 15 **Player Segmentation Agent** Agent *Model*
- 16 **Player Behavior Vector Store** Vector Store In Memory *Model*
- 17 **Behavioral Prediction Agent** Agent Tool *Model*
- 18 **Reward Redesign Simulation Agent** Agent Tool *Model*
- 19 **Pricing Adjustment Simulation Agent** Agent Tool *Model*
- 20 **A/B Testing Roadmap Agent** Agent Tool *Model*
- 21 **Prepare Analytics Results** Set *Logic*
- 22 **Store Analytics Results** Data Table *Service*
- 23 **Return Analysis Results** Respond To Webhook *Starts it*

## How it's built

- **Starts on:** Another system calling it
- **Steps:** 23
- **Size:** Large: read it before trusting it with anything live
- **Connects to:** in-memory vectors, n8n data table
- **Model:** OpenAI
- **Retrieval:** Answers are drawn from documents you supply, not from the model alone

## Questions

What does it need to run?

An n8n account, plus your own in-memory vectors account, and a key for OpenAI. You connect your own accounts after importing it; none are included.

What starts it?

It starts on another system calling it.

Does it use AI?

Yes. It calls OpenAI. Its answers draw on documents you give it, not on the model alone. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Take your time. At 23 steps it is large: read it before trusting it with anything live.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 23 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fsegment-players-and-predict-churn-with-openai)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Connects to

Each opens the other workflows that use it.

[in-memory vectors](https://millionrounds.com/workflows?service=in-memory+vectors#library)[n8n data table](https://millionrounds.com/workflows?service=n8n+data+table#library)

## Workflows like it

Also ai assistants, with the same services where possible, closest in size first.

- [**Analyze and modernize university curricula with OpenAI** 24 steps · calls a model · in-memory vectors, n8n data table](https://millionrounds.com/workflow/analyze-and-modernize-university-curricula-with-openai)
- [**Draft dental denial appeal packets from Gmail EOBs with OpenAI** 22 steps · calls a model · Gmail, Google Drive](https://millionrounds.com/workflow/draft-dental-denial-appeal-packets-from-gmail-eobs-with-open)
- [**Trip concierge with OpenRouter** 22 steps · calls a model · Email, n8n data table](https://millionrounds.com/workflow/trip-concierge-with-openrouter)
- [**Detect multi-modal plagiarism with OpenAI and Whisper** 25 steps · calls a model · in-memory vectors](https://millionrounds.com/workflow/detect-multi-modal-plagiarism-with-openai-and-whisper)
- [**Route IAM events with OpenAI and Slack** 21 steps · calls a model · Gmail, n8n data table](https://millionrounds.com/workflow/route-iam-events-with-openai-and-slack)
- [**Smart message batching AI-powered Facebook Messenger chatbot use** 25 steps · calls a model · n8n data table](https://millionrounds.com/workflow/smart-message-batching-ai-powered-facebook-messenger-chatbot)