> ## Documentation Index
> Fetch the complete documentation index at: https://docs.allyy.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> From a fresh account to your first prediction

This walkthrough takes you through the full loop once. Each step links to a detailed guide if you need more.

> [!NOTE]
>
> You'll need an Allyy account (follow the invitation email) and access to a data source — your CRM, a warehouse like BigQuery, or even a CSV export.

**1. Create a dataset**

A dataset is the container for everything that follows. Create one for the body of work you have in mind (e.g. "Direct mail appeals").

**2. Connect a data source**

Inside the dataset, add a data source and enter its credentials. Preview the data to confirm it loaded correctly.

→ [Connect a data source](https://docs.allyy.io/processes/data.md)

**3. Map your data**

Map your columns onto the Allyy data model — Contacts, Responses, Offers, Subscriptions. This is what lets Allyy understand gifts, campaigns and supporters generically.

→ [Data mapping](https://docs.allyy.io/processes/data_mapping.md) · [The Allyy data model](https://docs.allyy.io/data/data-model.md)

**4. Train a model**

Create a model, choose the question you want to answer (e.g. **DM propensity** — who is likely to respond to a mailing), and start training. Allyy builds the features and trains on your history.

→ [Create & train a model](https://docs.allyy.io/processes/model.md) · [What Allyy can predict](https://docs.allyy.io/models/what-allyy-can-predict.md)

**5. Generate predictions**

Point the trained model at the population you want to score. Allyy produces a score for each supporter.

→ [Generating predictions](https://docs.allyy.io/predictions/generating-predictions.md)

**6. Make a decision and export it**

Turn the scores into an optimised, ranked contact list, then export it to your campaign tools.

→ [From predictions to decisions](https://docs.allyy.io/predictions/decisions.md) · [Exporting decisions](https://docs.allyy.io/predictions/exporting.md)

**7. Measure the result**

After the campaign runs, use the model-evaluation dashboards to compare predicted vs actual, and the analytics dashboards to see the effect on your supporter base.

→ [Model evaluation](https://docs.allyy.io/dashboards-evaluation/index) · [Analytics dashboards](https://docs.allyy.io/analytics/overview.md)

## What next?

> [card] [Understand your file first](https://docs.allyy.io/analytics/overview.md)
>
> No model needed — the analytics dashboards describe your supporter base as it is today.

> [card] [Automate the loop](https://docs.allyy.io/automation/workflows.md)
>
> Once it works manually, schedule it with a workflow so it runs on its own.


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