> ## 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.

# What Allyy can predict

> The catalogue of models, grouped by the fundraising question they answer

Every Allyy model answers one question about a supporter. They split two ways:

* **By outcome** — a model either estimates a **probability** (classification, e.g. *will they respond?*) or an **amount** (regression, e.g. *how much will they give?*).
* **By scope** — a model is either about a **specific action** ("if we mail this person now, what happens?") or about a **supporter's trajectory** ("what will this person do over the coming year?").

> [!NOTE]
>
> The models are independent — use one on its own or combine several. Which ones fit your programme is something we'll scope with you.

## Two ways to slice the catalogue

Every model sits in one cell of this grid — outcome down the side, scope across the top. That's usually enough to find the one you need.

| | **Specific action** — a mailing or call | **Supporter trajectory** — over time |
| - | - | - |
| **Probability** — *how likely?* | DM propensity · TM reachability · TM conversion | Active donor · Middle donor · Reactivating donor · Subscription acquisition · Subscription churn |
| **Amount** — *how much?* | DM expected amount | Lifetime value *(roadmap)* |

## Where each model fits the supporter journey

As a supporter moves through their relationship with you, a different model supports the next decision.

| Stage | What's happening | Model that helps |
| - | - | - |
| Prospect / one-off donor | first or occasional gifts | DM propensity, TM reachability, TM conversion — target the ask |
| One-off → regular giver | converting to a recurring gift | Subscription acquisition |
| Growing supporter | value rising | Middle donor |
| Active supporter | giving steadily | Active donor — will they give again? |
| Regular giver at risk | may cancel their mandate | Subscription churn |
| Lapsed | stopped giving | Reactivating donor — win them back |

## Targeting a campaign — who to contact

> [card] [DM propensity](https://docs.allyy.io/models/dm-propensity.md)
>
> Will this supporter respond to a mailing? Use it to rank a mailing list and cut volume without losing income.

> [card] [TM reachability](https://docs.allyy.io/models/tm-reachability.md)
>
> Will we actually reach this person by phone? Prioritise dialling lists.

> [card] [TM conversion](https://docs.allyy.io/models/tm-conversion.md)
>
> Given we reach them, will they accept the offer? Focus calls on likely converters.

> [card] Email engagement
>
> Will this supporter open or click? Prioritise digital sends.

## How much to ask — the value of an action

> [card] [Expected amount](https://docs.allyy.io/models/dm-expected-amount.md)
>
> How much is this supporter likely to give in response to this action? Combine with propensity to target on **expected revenue**, not just likelihood.

> [card] Ask amount
>
> What set of suggested amounts (the "ask string", e.g. €20 / €50 / €100) maximises yield for this supporter?

## Keeping supporters — retention & risk

> [card] [Subscription churn](https://docs.allyy.io/models/subscription-churn.md)
>
> Will a regular giver cancel their direct debit in the coming months? Drives save / win-back programmes.

> [card] [Active donor](https://docs.allyy.io/models/active-donor.md)
>
> Will a currently active supporter give again in the next 12 months?

> [card] [Middle donor](https://docs.allyy.io/models/middle-donor.md)
>
> Retention focused on the valuable "middle" segment — where small movements move a lot of income.

> [card] [Reactivating donor](https://docs.allyy.io/models/reactivating-donor.md)
>
> Will a lapsed donor come back if we ask? Prioritise win-back appeals by likelihood to respond.

> [card] [Subscription acquisition](https://docs.allyy.io/models/subscription-acquisition.md)
>
> Will a one-off donor convert to a recurring gift? Find your best regular-giving prospects.

## Long-term value

> [card] Lifetime value (LTV)
>
> What is this supporter worth over a multi-year horizon? Drives stewardship investment.

> [card] Donation frequency
>
> How many gifts will this supporter make in the next year?

## Timing — when something will happen

> [card] Time to next gift
>
> How long until this supporter is likely to give again?

> [card] Time to churn
>
> When is a supporter likely to stop giving?

## How models combine

The models are designed to work together — combined, they describe a supporter more completely than any one alone:

* **Propensity × expected amount** — rank a mailing or call list on expected revenue (likelihood × value), not likelihood alone.
* **Subscription churn × lifetime value** — retention effort weighed against the recurring income at stake.
* **Active donor and reactivating donor** — the same supporter, before and after they lapse.

See [Create & train a model](https://docs.allyy.io/processes/model.md) to set one up.


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