Adapty

Adapty is a subscription monetization platform for mobile and web apps. It exposes a batch Analytics Export API and a paginated paywall list through its Server-side API.

Bruin supports Adapty as a source for Ingestr assets, and you can use it to ingest data from Adapty into your data warehouse.

In order to set up an Adapty connection, you need to add a configuration item in the .bruin.yml file and in the asset file. You need the secret api_key from App Settings → General → API keys. Use the secret API key, not a public SDK key.

Follow the steps below to correctly set up Adapty as a data source and run ingestion.

Configuration

Step 1: Add a connection to .bruin.yml file

To connect to Adapty, you need to add a configuration item to the connections section of the .bruin.yml file. This configuration must comply with the following schema:

    connections:
      adapty:
        - name: "my_adapty"
          api_key: "secret_live_..."
          lookback_days: 30
          timezone: "UTC"

• api_key: Required. The app-specific secret API key from Adapty.
• lookback_days: Optional. Number of days loaded when no analytics interval is supplied. Defaults to 30; use 0 to load only today.
• timezone: Optional. IANA timezone used by Adapty to group analytics dates. Defaults to UTC.

Step 2: Create an asset file for data ingestion

To ingest data from Adapty, you need to create an asset configuration file. This file defines the data flow from the source to the destination. Create a YAML file (e.g., adapty_ingestion.yml) inside the assets folder and add the following content:

name: public.adapty
type: ingestr
connection: postgres

parameters:
  source_connection: my_adapty
  source_table: 'analytics?chart_id=revenue'

  destination: postgres

• name: The name of the asset.
• type: Specifies the type of the asset. Set this to ingestr to use the ingestr data pipeline.
• connection: This is the destination connection, which defines where the data should be stored. For example: postgres indicates that the ingested data will be stored in a Postgres database.
• source_connection: The name of the Adapty connection defined in .bruin.yml.
• source_table: The name of the data table in Adapty that you want to ingest. See the tables below.

Step 3: Run asset to ingest data

bruin run assets/adapty_ingestion.yml

As a result of this command, Bruin will ingest data from the given Adapty table into your Postgres database.

Available Source Tables

Table	Required parameters	PK	Inc Strategy	Details
analytics	chart_id	–	delete+insert on date	Revenue, MRR, ARR, ARPU/ARPPU, subscriptions, trials, refunds, billing issues, installs, and related chart metrics.
cohorts	–	–	delete+insert on date	Cohort revenue, subscriber, subscription, ARPU, ARPPU, and ARPAS analytics.
conversion	from_period, to_period	–	delete+insert on date	Conversion between two subscription states. Use from_period=null when there is no starting state.
funnel	–	–	delete+insert on date	Subscription funnel and churn analytics.
ltv	–	–	delete+insert on date	Actual lifetime value for revenue, proceeds, and net revenue.
retention	–	–	delete+insert on date	Subscriber retention analytics.
placements	placement_type	–	replace	Exported paywall or onboarding placement configuration.
paywalls	–	paywall_id	merge (inc key updated_at)	All paginated paywalls, including their state, deletion marker, and nested products.

The six analytics tables are requested one calendar day at a time and receive an ingestr-managed date column. When no interval is supplied, they load the last lookback_days days by default.

The paywall API does not accept an updated_at filter. ingestr scans its paginated list and applies the incremental interval client-side. Adapty returns archived and deleted paywalls with state and is_deleted, allowing merge loads to retain lifecycle changes.

Provider response objects and arrays, such as cohort values and paywall products, remain nested rather than being flattened.

Analytics table parameters

Parameters are URL-style query parameters on the source table. All six analytics tables accept these optional filters:

• compare_date: Exactly two YYYY-MM-DD dates.
• store, country, store_product_id, duration
• attribution_source, attribution_status, attribution_channel, attribution_campaign, attribution_adgroup, attribution_adset, attribution_creative
• offer_category, offer_type, offer_id

List values are comma-separated. Each table also accepts its endpoint-specific parameters:

Table	Optional parameters
analytics	date_type, segmentation
cohorts	period_type, value_type, value_field, accounting_type, renewal_days, prediction_months
conversion	date_type, segmentation
funnel	show_value_as, segmentation
ltv	period_type, segmentation
retention	segmentation, use_trial

Valid chart_id values are: revenue, mrr, arr, arppu, subscriptions_active, subscriptions_new, subscriptions_renewal_cancelled, subscriptions_expired, trials_active, trials_new, trials_renewal_cancelled, trials_expired, grace_period, billing_issue, refund_events, refund_money, non_subscriptions, arpu, and installs.

Examples

Load daily purchase revenue:

parameters:
  source_connection: my_adapty
  source_table: 'analytics?chart_id=revenue'

Load refund totals for selected stores and countries:

parameters:
  source_connection: my_adapty
  source_table: 'analytics?chart_id=refund_money&store=app_store,play_store&country=us,gb'

Load cohort revenue by days:

parameters:
  source_connection: my_adapty
  source_table: 'cohorts?period_type=days&value_field=revenue&accounting_type=net_revenue&renewal_days=0,1,3,7,14,30'

Load paywall placement configuration:

parameters:
  source_connection: my_adapty
  source_table: 'placements?placement_type=paywall'

Load all paywall definitions:

parameters:
  source_connection: my_adapty
  source_table: 'paywalls'