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

# Payback reports

> Understand which acquisition cohorts are actually paying back.

Payback reports are FloKit's primary analysis surface. They connect your acquisition spend to downstream subscription revenue so you can see which campaigns, creatives, countries, and offers are paying back — and which aren't. Unlike platform-reported ROAS, payback reports are grounded in actual subscription revenue from RevenueCat, Adapty, or your warehouse — net of refunds and including renewal revenue.

## What a payback report shows

| Metric                     | Definition                                                     |
| -------------------------- | -------------------------------------------------------------- |
| **Spend**                  | Total acquisition spend for the cohort, by campaign or channel |
| **CAC**                    | Cost per paying subscriber (spend / paying subscribers)        |
| **Trial conversion rate**  | Trials started / attributed installs                           |
| **Renewal rate**           | Renewals / first subscriptions for the cohort                  |
| **Revenue by cohort week** | Cumulative subscription revenue over time                      |
| **Payback window**         | Days until cohort revenue exceeds total acquisition spend      |
| **Projected LTV**          | Estimated lifetime value at 6-month and 12-month horizons      |
| **ROAS at 30/60/90 days**  | Revenue returned per dollar spent at each time window          |

***

## Reading a payback curve

A payback curve plots cumulative cohort revenue against time. The point where the curve crosses your CAC line is your payback day.

**Example:** A campaign spending $10,000 acquires 200 paying subscribers at a $50 CAC. If the average subscriber generates \$55 in revenue over 3 months, the cohort is on a 90-day payback window — breakeven at month three, then profitable.

Now compare that to a second campaign spending $20,000 for 200 subscribers at a $100 CAC — but where the average subscriber generates \$120 over 3 months. That campaign hits payback in 75 days despite twice the spend per user. Higher CAC, faster payback, more total profit.

**The insight:** CAC alone doesn't tell you whether a campaign is worth scaling. The payback window — and the LTV trajectory behind it — is what matters. FloKit surfaces both so you can compare campaigns on a like-for-like basis.

***

## Dimensions

Group any payback report by:

* **Campaign** — top-level campaign.
* **Ad set** — ad group or ad set within a campaign.
* **Creative** — individual creative asset.
* **Channel** — paid social, search, influencer, ASA, etc.
* **Country** — acquisition country.
* **Offer** — trial length, discount, or plan type.
* **Paywall variant** — A/B test variant the user saw at conversion.
* **Cohort week** — the calendar week the cohort was acquired.

Combine dimensions to answer questions like: "Which creatives on Meta in the UK have the strongest 90-day ROAS?"

***

## Filters

* **Date range** — set acquisition cohort start and end dates.
* **Channel** — filter to one or more acquisition channels.
* **Country** — filter to specific markets.
* **Product** — filter by subscription plan (monthly, annual, etc.).
* **Minimum spend threshold** — exclude cohorts below a spend floor to remove statistical noise from small tests.

***

## Payback windows

FloKit calculates payback at five standard windows:

| Window   | Best for                                            |
| -------- | --------------------------------------------------- |
| 30 days  | Monthly subscriptions                               |
| 60 days  | Monthly subscriptions with a free trial             |
| 90 days  | Monthly subscriptions, quarterly cash-flow planning |
| 180 days | Semi-annual plans or high-LTV monthly subscribers   |
| 365 days | Annual subscriptions                                |

Use the window that matches your primary subscription plan length. For annual plans, 90-day ROAS is a leading indicator — 365-day is the definitive figure.

***

## Accessing payback reports

**Dashboard**

Go to **Reports → Payback**. Select your date range, grouping dimension, and payback window. The report updates every 6 hours.

**API**

```bash theme={null}
GET https://api.flokit.ai/v1/reports/payback
```

See [API reference → Reports](/api-reference/reports) for query parameters and response schema.

**CSV export**

From **Reports → Payback**, click **Export** to download the current view as CSV. Export includes all visible rows and columns at the selected grouping and filter settings.

***

## How long before the report populates

| Data source                                | Time to first report             |
| ------------------------------------------ | -------------------------------- |
| RevenueCat or Adapty (live)                | 7–14 days of subscription events |
| RevenueCat or Adapty (historical backfill) | 2–4 hours after connecting       |
| Warehouse (historical cohort table)        | Immediately after sync validates |
| MMP attribution (AppsFlyer / Adjust)       | 2–4 hours after connecting       |

Historical data from RevenueCat, Adapty, or your data warehouse backfills immediately — you don't need to wait weeks to see your first payback curves.

**For large-scale apps:** Payback reports update every 6 hours by default. For apps with more than 1M monthly actives who need real-time report access, contact FloKit.