> ## 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.

# What FloKit does

> How FloKit connects acquisition, subscription, and revenue data for consumer app growth teams.

FloKit is a growth intelligence layer for consumer subscription apps. It sits between your ad platforms, MMP, subscription stack, and data warehouse — reading acquisition spend, attribution, subscription outcomes, and revenue, then surfacing payback reports and recommended actions for your team to review and approve.

## The core problem

Growth teams optimize for installs or ROAS, but installs don't pay back. A campaign that drives cheap installs with high churn is worse than a smaller, more expensive cohort that renews for 12 months. Most growth teams don't have a clean line connecting what they spent on a campaign to what that campaign actually retained — because the data lives in four different systems and no one has joined it.

FloKit connects spend to retained revenue so teams can see the difference. Not install volume. Not day-7 ROAS on trial starts. Actual retained subscription revenue from a known attribution source, tracked through renewals and cancellations, mapped back to the campaign and creative that drove the install.

## How it works

<Steps>
  <Step title="Connect data sources">
    FloKit reads from your existing stack. No app release required to start. Connect RevenueCat, Adapty, AppsFlyer, Adjust, Stripe, App Store Connect, Google Play, or a data warehouse. FloKit pulls subscription state, install attribution, spend data, and revenue — and keeps it current.
  </Step>

  <Step title="FloKit joins the data">
    FloKit links four identity layers into a single cohort record: the attributed install (from your MMP), the app user (from your subscription platform), the subscription customer (from RevenueCat, Adapty, or Stripe), and any server-side events you send. The result is a joined record that connects a specific ad spend → install → trial → subscription → renewal chain.
  </Step>

  <Step title="Payback analysis">
    With joined cohort data, FloKit calculates:

    * **CAC** — actual acquisition cost by campaign, ad set, creative, country, and offer
    * **ROAS** — at 7, 14, 30, 60, and 90-day windows
    * **Trial conversion rate** — by paywall variant and offer
    * **Renewal rates** — by subscription duration and cohort
    * **Payback window** — when a cohort's cumulative revenue exceeds its acquisition cost
    * **Projected LTV** — at 6 and 12 months, based on observed renewal behavior

    Every metric is sliceable by campaign, creative, country, offer, and paywall variant.
  </Step>

  <Step title="Recommendations">
    FloKit surfaces recommended actions in an approval-gated queue: budget moves, creative pauses, audience shifts, offer tests, and paywall experiments. Each recommendation includes the signal that triggered it, the expected payback impact, and a rollback path. Write access to ad platforms is off by default — your team reviews and approves before anything executes.
  </Step>
</Steps>

## What FloKit is not

**Not an MMP.** FloKit does not replace AppsFlyer, Adjust, or any attribution provider. It reads from them.

**Not a subscription SDK.** FloKit does not replace RevenueCat, Adapty, or Stripe. It reads from them.

**Not an ad platform.** FloKit does not serve ads or manage campaigns directly. It reads spend data from Meta, Google, TikTok, and Apple Search Ads, and surfaces recommendations for your team to act on.

FloKit is the payback intelligence layer on top of your existing stack. It adds the join between systems that your team currently does manually — or doesn't do at all.

## Who uses FloKit

Growth teams and data leads at consumer subscription apps with $10k–$1M+/month in paid acquisition. Typical use cases:

* **Growth engineers and managers** who need to know which campaigns are actually paying back before approving next month's budget
* **Data leads** who want a cleaner payback model than the one in their warehouse spreadsheet
* **CTOs and product leaders** at subscription apps who want to scale paid acquisition without guessing at LTV

Available during private beta — contact FloKit for access.