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@dpannasch@Carlosedo I put up this PR as a draft just as a heads up to both of you that I'm working on this, I think it mostly just needs to be cleaned up (I'm going to try to stick to an 80 character line length since the comments can get quite long)
No worries @dpannasch thanks for the review! I just work on this in bursts as needed. I think I addressed everything except the comment about duplicative comments as I was a little confused about that, let me know what you think!
RevenueCat's Paywalls allow you to remotely configure your entire paywall view without any code changes or app updates. Whether you’re building a new app, exploring new paywall concepts, or diving into experimentation; RevenueCat’s Paywalls make it easy to get started.
Paywalls are supported in the following SDK versions:
RevenueCat SDK
Version required for Offering Metadata
purchases-ios
4.26.0 and up
purchases-android
7.1.0 and up
react-native-purchases
7.4.0-beta.2
purchases-flutter
6.3.0-beta.1
❗️
Within the SDKs, Paywalls are available on the following platforms:
iOS 15.0+
visionOS 1.0+
Mac Catalyst 15.0+
watchOS 8.0+
Android 7.0 (API level 24)
Support for more platforms is coming soon: macOS, tvOS, and others!
Android paywalls is currently behind an experimental flag (ExperimentalPreviewRevenueCatUIPurchasesAPI).
It is safe to release app updates with it. We guarantee that paywalls will continue to work and any changes will always be backwards compatible.
They are stable, but migration steps may be required in the future. We'll do our best to minimize any changes you have to make.
Our paywall templates use native code to deliver smooth, intuitive experiences to your customers when you’re ready to deliver them an Offering; and you can use our Dashboard to pick the right template and configuration to meet your needs.
To use RevenueCat Paywalls, simply:
Create a Paywall on the Dashboard for the Offering you intend to serve to your customers
See displaying paywalls for how to display it into your app.
Offerings and Paywalls
You can think of a Paywall as an optional feature of your Offering. An Offering is the collection of Products which are organized into Packages to be displayed to your customers as a single "offer" across platforms. Now, with Paywalls, you can control the actual view that is used to display that "offer" in addition to controlling the products that are offered.
Therefore, you can create a unique Paywall for each of your Offerings, and can create an unlimited number of Offerings & Paywalls for each variation you want to test with Experiments.
Limitations
Platforms (support for more coming)
✅ iOS 15.0 and higher
✅ visionOS 1.0 and higher
✅ Mac Catalyst 15.0 and higher
✅ watchOS 8.0 and higher
✅ Android 7.0 (API level 24)
❌ macOS
❌ tvOS
Android's Google Play developer determined offers
Paywalls in Android will use the default subscription option which, in case you use developer determined offers, will always be available, providing these types of offers always to your users. If you want to avoid this behavior when using paywalls, add the rc-ignore-offer tag to the developer determined offer from your product.
Next Steps
Now that you know how our paywalls work, read about creating paywalls
Once you're ready to see your paywalls in action, you can follow our guides on displaying paywalls
If you need inspiration with some paywall examples, you can try our Paywalls Tester app
Scheduled data exports are available to all users signed up after September '23, the legacy Grow and Pro plans, and Enterprise plans. If you're on a legacy Free or Starter plan and want to access this integration, migrate to our new pricing via your billing settings.
RevenueCat can automatically send data deliveries of all of your apps' transaction data to various cloud storage providers. These are in the form of gzip compressed .csv files delivered daily.
[block:parameters]
{
"data": {
"h-0": "Header",
"h-1": "Description",
"h-2": "Type",
"h-3": "Example value",
"h-4": "Can be null",
"0-0": "rc_original_app_user_id",
"0-1": "Can be used as a unique user identifier to find all of a user's transactions.",
"0-2": "string",
"0-3": "$RCAnonymousID:87c6049c58069238dce29853916d624c",
"0-4": "",
"1-0": "rc_last_seen_app_user_id_alias",
"1-1": "Can be used together with rc_original_app_user_id to match transactions with user identifiers in your systems.",
"1-2": "string",
"1-3": "$RCAnonymousID:87c6049c58069238dce29853916d624c",
"1-4": "",
"2-0": "country",
"2-1": "Store country of a transaction when known, or an IP-based estimate of a subscriber's country when not known.",
"2-2": "string",
"2-3": "GB",
"2-4": "✅",
"3-0": "country_source\",
"3-1": "from_sdk when the store country of a transaction is known, or estimated when country is sourced from an IP-based estimate.",
"3-2": "string",
"3-3": "from_sdk",
"3-4": "✅",
"4-0": "product_identifier",
"4-1": "The product identifier that was purchased.",
"4-2": "string",
"4-3": "rc_subscription_monthly",
"4-4": "",
"5-0": "product_display_name\",
"5-1": "The display name of the product identifier if one has been set",
"5-2": "string",
"5-3": "Monthly $9.99",
"5-4": "✅",
"6-0": "product_duration\",
"6-1": "The standard duration of the product if one is known by RevenueCat. May be null if RevenueCat does not know the authoritative duration. \n \nproduct_duration does not represent the trial or introductory period length of a transaction, it only represents the standard duration of the product that's been subscribed to.",
"6-2": "string",
"6-3": "P1M",
"6-4": "✅",
"7-0": "start_time",
"7-1": "Purchase time of transaction.",
"7-2": "datetime",
"7-3": "2023-01-01 08:27:06",
"7-4": "",
"8-0": "end_time",
"8-1": "Expected expiration time of subscription. Null when is_auto_renewable = false \nFor Google Play, end_time can be before start_time to indicate an invalid transaction (e.g. billing issue).",
"8-2": "datetime",
"8-3": "2023-02-01 08:27:06",
"8-4": "✅",
"9-0": "grace_period_end_time",
"9-1": "Expiration time of a grace period (if applicable) for a subscription. Will remain set while a subscription is in its grace period, or if it exited its grace period without renewing. Null when a subscription is not in a grace period or expiration was not due to a grace period.",
"9-2": "datetime",
"9-3": "2023-02-17 08:27:06",
"9-4": "✅",
"10-0": "effective_end_time",
"10-1": "Single reference point of a subscriber’s expiration and entitlement revocation; inclusive of each store’s logic for cancellations, grace periods, etc.",
"10-2": "datetime",
"10-3": "2023-02-17 08:27:06",
"10-4": "✅",
"11-0": "store",
"11-1": "The source of the transaction. Can be app_store, play_store, stripe, or promotional.",
"11-2": "string",
"11-3": "play_store",
"11-4": "",
"12-0": "is_auto_renewable",
"12-1": "true for auto-renewable subscriptions, false otherwise.",
"12-2": "boolean",
"12-3": "true",
"12-4": "",
"13-0": "is_trial_period",
"13-1": "true if the transaction was a trial.",
"13-2": "boolean",
"13-3": "false",
"13-4": "",
"14-0": "is_in_intro_offer_period",
"14-1": "true if the transaction is in an introductory offer period.",
"14-2": "boolean",
"14-3": "false",
"14-4": "",
"15-0": "is_sandbox",
"15-1": "true for transactions made in a sandbox environment.",
"15-2": "boolean",
"15-3": "false",
"15-4": "",
"16-0": "price_in_usd",
"16-1": "The revenue (converted to USD) generated from the transaction after accounting for full and partial refunds. Can be null if product prices haven't been collected from the user's device. ",
"16-2": "float",
"16-3": "0",
"16-4": "✅",
"17-0": "purchase_price_in_usd\",
"17-1": "The gross revenue (converted to USD) generated from the transaction. Remains set for refunded transactions. Can be null if product prices haven't been collected from the user's device.",
"17-2": "float",
"17-3": "9.99",
"17-4": "✅",
"18-0": "takehome_percentage",
"18-1": "[DEPRECATED] The estimated percentage of the transaction price that will be paid out to developers after commissions, but before VAT and DST taxes are taken into account. (will be either 0.7 or 0.85) \n \nWe recommend using tax_percentage and commission_percentage to calculate proceeds instead. Learn more here.",
"18-2": "float",
"18-3": "0.7",
"18-4": "",
"19-0": "tax_percentage",
"19-1": "The portion of a transaction’s price that will be deducted by the store for taxes. VAT & Digital Services Taxes may be withheld by stores depending on the store and country. To learn more about how RevenueCat estimates taxes, click here.",
"19-2": "float",
"19-3": "0.1442",
"19-4": "",
"20-0": "commission_percentage",
"20-1": "The portion of a transaction’s price that will be detected by the store for commission. In stores where taxes are deducted before commission, this value will not equal the published commission from a store, because that commission is calculated on the post-tax revenue.",
"20-2": "float",
"20-3": "0.15",
"20-4": "",
"21-0": "store_transaction_id",
"21-1": "orderId or transaction_identifier. Can be used as unique id.",
"21-2": "string",
"21-3": "123456789012345",
"21-4": "",
"22-0": "original_store_transaction_id",
"22-1": "orderId of first purchase or original_transaction_id. Can be used to find all related transactions for a single subscription.",
"22-2": "string",
"22-3": "011223344556677",
"22-4": "",
"23-0": "refunded_at",
"23-1": "When a refund was detected, null if none was detected. Is not set in the case of upgraded transactions for which the App Store issues a partial refund.",
"23-2": "datetime",
"23-3": "2023-02-20 05:47:55",
"23-4": "✅",
"24-0": "unsubscribe_detected_at",
"24-1": "When we detected an unsubscribe (opt-out of auto renew).",
"24-2": "datetime",
"24-3": "2023-02-16 14:17:10",
"24-4": "✅",
"25-0": "billing_issues_detected_at",
"25-1": "When we detected billing issues, null if none was detected.",
"25-2": "datetime",
"25-3": "2023-02-01 08:27:15",
"25-4": "✅",
"26-0": "purchased_currency",
"26-1": "The currency that was used for the transaction.",
"26-2": "string",
"26-3": "GBP",
"26-4": "✅",
"27-0": "price_in_purchased_currency",
"27-1": "The revenue (in the purchased currency) generated from the transaction after accounting for full and partial refunds. Can be null if product prices haven't been collected from the user's device.",
"27-2": "float",
"27-3": "0",
"27-4": "✅",
"28-0": "purchase_price_in_purchased_currency\",
"28-1": "The gross revenue (in the purchased currency) generated from the transaction. Remains set for refunded transactions. Can be null if product prices haven't been collected from the user's device.",
"28-2": "float",
"28-3": "3.99",
"28-4": "✅",
"29-0": "entitlement_identifiers",
"29-1": "An array of entitlements that the transaction unlocked or null if it didn't unlock any entitlements.",
"29-2": "string array",
"29-3": "\"[\"\"membership\"\", \"\"full_access\"\"]\"",
"29-4": "✅",
"30-0": "renewal_number",
"30-1": "Always starts at 1. Trial conversions are counted as renewals. is_trial_conversion is used to signify whether a transaction was a trial conversion.",
"30-2": "integer",
"30-3": "2",
"30-4": "",
"31-0": "is_trial_conversion",
"31-1": "If true, this transaction is a trial conversion.",
"31-2": "boolean",
"31-3": "true",
"31-4": "",
"32-0": "presented_offering",
"32-1": "The offering presented to users.",
"32-2": "string",
"32-3": "Default Offering",
"32-4": "✅",
"33-0": "ownership_type",
"33-1": "Will be PURCHASED when a recorded transaction results from the subscriber’s direct purchase of it, or FAMILY_SHARED when a recorded transaction results from the subscriber having received it through Family Sharing. \n \nNOTE: The FAMILY_SHARED designation is only supported on App Store transactions.",
"33-2": "string",
"33-3": "PURCHASED",
"33-4": "✅",
"34-0": "reserved_subscriber_attributes",
"34-1": "The reserved subscriber attributes set for the subscriber. Keys begin with $.",
"34-2": "string JSON",
"34-3": "\"{\"\"$ip\"\": {\"\"value\"\": \"\"203.78.120.117\"\", \"\"updated_at_ms\"\": 1672549200}, \"\"$gpsAdId\"\": {\"\"value\"\": \"\"80480bdc-06e0-11ee-be56-0242ac120002\"\", \"\"updated_at_ms\"\": 1672549200}, \"\"$androidId\"\": {\"\"value\"\": \"\"12345a9876b4c123\"\", \"\"updated_at_ms\"\": 1673097132390}}\"",
"34-4": "✅",
"35-0": "custom_subscriber_attributes",
"35-1": "The custom attributes set for the subscriber.",
"35-2": "string JSON",
"35-3": "\"{\"\"feature_setting\"\": {\"\"value\"\": \"\"1\"\", \"\"updated_at_ms\"\": 1672549200}, \"\"survey_response\"\": {\"\"value\"\": \"\"2\"\", \"\"updated_at_ms\"\": 1599112814785}}\"",
"35-4": "✅",
"36-0": "platform",
"36-1": "Last seen platform of the subscriber.",
"36-2": "string",
"36-3": "android",
"36-4": "✅",
"37-0": "experiment_id\",
"37-1": "The unique ID of the Experiment that the subscriber is or was enrolled in. Will be null if the subscriber has not been enrolled in an experiment. \n \nLearn more about Experiments here.",
"37-2": "string",
"37-3": "prexp3a8a234abc",
"37-4": "✅",
"38-0": "experiment_variant\",
"38-1": "The value of the Experiment variant that the subscriber is or was enrolled in. a represents the Control, and b represents the Treatment. Will be null if the subscriber has not been enrolled in an experiment. \n \nLearn more about Experiments here.",
"38-2": "string",
"38-3": "a",
"38-4": "✅",
"39-0": "updated_at\",
"39-1": "The last time an attribute of the transaction was modified.",
"39-2": "datetime",
"39-3": "2023-02-20 05:47:55",
"39-4": ""
},
"cols": 5,
"rows": 40,
"align": [
"left",
"left",
"left",
"left",
"left"
]
}
[/block]
*Available only on our most recent export version
📘 Re-enable integration to update to latest version
If your exports don't contain all of the columns above, you may be on an older export version. To update to the latest version just delete, and re-add the integration from the RevenueCat dashboard.
A note on transaction data
All transaction data is based on the store receipts that RevenueCat has received. Receipts often have inconsistencies and quirks which may need to be considered. For example:
The expiration date of a purchase can be before the purchase date. This is Google's way of invalidating a transaction, for example when Google is unable to bill a user some time after a subscription renews. This doesn’t occur on iOS.
If you migrated to RevenueCat, Google subscriptions that were expired for more then 60 days before being migrated will not have transaction histories in export files.
Apple and Google do not provide the transaction price directly, so we must rely on historical data for the products that we have. This isn’t 100% accurate in cases where the prices were changed or receipts were imported.
Renewal numbers start at 1, even for trials. Trial conversions increase the renewal number.
Data is pulled from a snapshot of the current receipt state, this means that the same transaction can be different from one delivery to another if something changed, e.g.refunds, and billing issues. You should recompute metrics for past time periods periodically to take these changes into account.
We try to normalize or at least annotate these quirks as much as possible, but by and large we consider receipts as the sources of truth, so any inconsistencies in the transaction data can always be traced back to the receipt
Sample queries for RevenueCat measures
You can use the following sample queries (written in Postgresql) as starting points for reproducing common RevenueCat measures.
-- Active Trials as of your [targeted_date]SELECTCOUNT(*)
FROM
[revenuecat_data_table]
WHEREdate(effective_end_time) > [targeted_date]
ANDdate(start_time) <= [targeted_date]
AND is_trial_period ='true'AND (effective_end_time IS NULLOR DATE_DIFF('s', start_time, effective_end_time)::float >0)
AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'-- The RevenueCat Active Trials chart excludes-- promotional transactions and transactions resulting from family sharing-- since they do not reflect auto-renewing future payments.
-- Active Subscriptions as of your [targeted_date]SELECTCOUNT(*)
FROM
[revenuecat_data_table]
WHEREdate(effective_end_time) > [targeted_date]
ANDdate(start_time) <= [targeted_date]
AND is_trial_period ='false'AND (effective_end_time IS NULLOR DATE_DIFF('s', start_time, effective_end_time)::float >0)
AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'-- The RevenueCat Active Subscriptions chart excludes trials,-- promotional transactions, and transactions resulting from family sharing-- since they do not reflect auto-renewing future payments.
-- Revenue generated on [targeted_date]SELECTSUM(purchase_price_in_usd) as total_revenue,
SUM(price_in_usd) as total_revenue_net_of_refunds,
SUM(price_in_usd * (1- tax_percentage - commission_percentage)) as proceeds
FROM
[revenuecat_data_table]
WHEREdate(start_time) = [targeted_date]
AND is_trial_period ='false'AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'-- Transactions which have been refunded can be identified through the refunded_at field.
/*This query generates a table that mirrors the Subscriber Retention chart. Ituses three intermediate tables: 1. subs - a table grouped by first subscription purchase date 2. retention - a table that counts the number of active subscriptions in each date cohort 3. pending_retention - a table that counts the number of subscriptions that are expected to renewThe three tables are combined in full_table to show a table that looks likethis:+-------------------------+---------------+-------------+---------+| date | period_number | period_name | actives |+-------------------------+---------------+-------------+---------+| 2023-01-01 00:00:00.000 | 1 | Month 1 | 500 |+-------------------------+---------------+-------------+---------+| 2023-01-01 00:00:00.000 | 2 | Month 2 | 600 |+-------------------------+---------------+-------------+---------+| 2023-01-01 00:00:00.000 | 3 | Month 3 | 550 |+-------------------------+---------------+-------------+---------+| 2023-02-01 00:00:00.000 | 1 | Month 1 | 400 |+-------------------------+---------------+-------------+---------+| 2023-02-01 00:00:00.000 | 2 | Month 2 | 300 |+-------------------------+---------------+-------------+---------+In the query you will see place holders that look like this: start_time >= /* desired date range */
Fill in each placeholder by following the instructions in each one.
*/
WITH
-- subs is an intermediate table that maps subscribers to their earliest -- subscription start date. The first subscription start date will be used to -- group billing cycles by cohort.
subs AS (
SELECT-- app user ID will be used to group billing cycles by userrc.app_user_idAS id,
-- first purchase date will be used to group billing cycles by cohort.DATE(MIN(start_time)) AS first_start_time
FROM [revenuecat_data_table] rc
WHERE start_time >=/* desired date range */-- count subscriptions onlyAND end_time IS NOT NULL-- remove any sandbox transactionsAND is_sandbox <>'true'-- remove any trial billing cyclesAND is_trial_period ='false'-- remove any intro offer billing cyclesAND is_in_intro_offer_period ='false'-- remove any subscriptions that were acquired through Family SharingAND ownership_type !='FAMILY_SHARED'AND product_identifier =/* targeted product(s) */GROUP BYrc.app_user_id
),
-- retention is an intermediate table that counts the number of active-- subscriptions in each cohort and billing cycle.
retention AS (
SELECT-- cohorting subscriptions by their first start datessubs.first_start_time,
-- Each period number represents the number of billing cycles the-- subscriber was active for. Be sure to divide the date difference by the-- number of days for the product duration being analyzed (e.g. 30 for-- monthly, 365 for yearly, etc).
CAST(ROUND(DATEDIFF(day, subs.first_start_time, start_time) / CAST(30ASNUMERIC)) ASINTEGER) AS period_number,
-- count the number of active subscriptions in each cohort and billing-- cyclecount(1) AS actives
FROM rc
INNER JOIN subs ONsubs.id=rc.app_user_idWHERE start_time >=/* desired date range */-- count subscriptions onlyAND end_time IS NOT NULL-- remove any sandbox transactionsAND is_sandbox <>'true'-- remove any trial billing cyclesAND is_trial_period ='false'-- remove any intro offer billing cyclesAND is_in_intro_offer_period ='false'-- remove any subscriptions that were acquired through Family SharingAND ownership_type !='FAMILY_SHARED'AND product_identifier =/* targeted product(s) */GROUP BY1, 2
),
-- pending_retention is an intermediate table that counts subscriptions that-- are set to automatically renew in the future, and can therefore be thought-- of possible future retention.
pending_retention AS (
SELECTsubs.first_start_time,
-- This billing cycle calculation is similar to the one made in the-- retention table, with the only difference being it calculates the next-- billing cycle in the future.
CAST(ROUND(DATEDIFF(day, subs.first_start_time, start_time) / CAST(30ASNUMERIC)) ASINTEGER) +1AS period_number,
count(1) AS actives
FROM [revenuecat_data_table] rc
INNER JOIN subs ONsubs.id=rc.app_user_idWHERE-- count only subscriptions that are expected to renew
is_auto_renewing ='true'-- count only the latest billing cycle of a subscriptionAND DATEADD(month, 1, start_time) > GETDATE()
AND start_time >=/* desired date range */AND end_time IS NOT NULLAND is_sandbox <>'true'AND is_trial_period ='false'AND is_in_intro_offer_period ='false'AND ownership_type !='FAMILY_SHARED'AND product_identifier =/* targeted product(s) */GROUP BY1, 2
),
-- full_table combines retention and pending_retention into the final-- subscriber retention table. If you're not interested in pending-- subscriptions, you can remove pending_retention from this below query. For-- example:-- COALESCE(retention.first_start_time, pending_retention.first_start_time) AS first_start_time,-- should be changed into:-- retention.first_start_time AS first_start_time,-- if pending retention is not needed.
full_table AS (
SELECT
COALESCE(retention.first_start_time, pending_retention.first_start_time) AS first_start_time,
COALESCE(retention.period_number, pending_retention.period_number) AS period_number,
COALESCE(retention.actives, 0) + COALESCE(pending_retention.actives, 0) AS actives
FROM retention
FULL OUTER JOIN pending_retention ONpending_retention.first_start_time=retention.first_start_timeANDpending_retention.period_number=retention.period_number
)
-- the final subscription retention tableSELECT
first_start_time asdate,
period_number,
CONCAT('Month ', period_number) AS period_name,
actives
FROM full_table
ORDER BYdate, period_number
Sample queries for customized measures
Scheduled Data Exports are a powerful way to add your own customizations on top of the core measures provided by RevenueCat. Check out the following sample queries (written in Postgresql) for some ideas.
-- How many Active Subscriptions do I have with a given custom attribute value?SELECTCOUNT(*)
FROM
[revenuecat_data_table] rc
WHEREdate(effective_end_time) > [targeted_date]
ANDdate(start_time) <= [targeted_date]
AND is_trial_period ='false'AND (effective_end_time IS NULLOR DATE_DIFF('s', start_time, effective_end_time)::float >0)
AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'AND json_extract_path_text(custom_subscriber_attributes, '[custom_attribute_key].value') = [custom_attribute_value]
-- What is my weekly revenue, where Monday is set as the start day of the week?SELECT
date_trunc('week', start_time) as week,
SUM(price_in_usd) as total_revenue
FROM
[revenuecat_data_table]
WHEREdate(start_time) BETWEEN [targeted_period_start_date] AND [targeted_period_end_date]
AND is_trial_period ='false'AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'GROUP BY week
-- What is my Realized LTV of each monthly subscription cohort, segmented by whether they were offered a trial?
WITH
(SELECTMIN(start_time) as subscription_start_time,
original_store_transaction_id,
MAX(is_trial_period) as had_a_trial,
SUM(price_in_usd) as realized_ltv
FROM
[revenuecat_data_table]
WHEREdate(start_time) > [targeted_period_start_date]
AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'GROUP BY original_store_transaction_id) as subscriptions
SELECT
to_char(first_start_time, 'YYYY-MM') as subscription_start_month,
had_a_trial,
COUNT() as subscriptions,
SUM(realized_ltv) as realized_ltv,
SUM(realized_ltv) /COUNT() as realized_ltv_per_subscription
FROM
subscriptions
-- What portion of my Active Trials are in a grace period?SELECT
CASE
WHEN grace_period_end_time IS NOT NULL THEN 'in_grace_period'
ELSE 'in_trial_period'
end_as period_type,
COUNT(*) as active_trials
FROM
[revenuecat_data_table]
WHEREdate(effective_end_time) > [targeted_date]
ANDdate(start_time) <= [targeted_date]
AND is_trial_period ='true'AND (effective_end_time IS NULLOR DATE_DIFF('s', start_time, effective_end_time)::float >0)
AND ownership_type !='FAMILY_SHARED'AND store !='promotional'AND is_sandbox !='true'GROUP BY period_type
-- What is my Realized LTV per Paying Customer cohorted by First Purchase Date?
WITH filtered_transactions AS
(SELECT*FROM [revenuecat_data_table] rc
WHERE is_trial_period ='false'AND was_refunded ='false'AND ownership_type ='PURCHASED'AND is_sandbox !='true'AND store !='promotional'AND price >0),
first_purchase_dates AS
(SELECT
rc_original_app_user_id,
MIN(start_time) as first_purchase_date
FROM filtered_transactions ft
GROUP BY1)
SELECTDATE(fpd.first_purchase_date) AS first_purchase_date,
COUNT(DISTINCT rc_original_app_user_id) AS paying_customers,
SUM(CASE WHEN DATEADD(day, 7, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)::DECIMAL(18,2) AS total_ltv_7_days,
SUM(CASE WHEN DATEADD(day, 30, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)::DECIMAL(18,2) AS total_ltv_30_days,
SUM(CASE WHEN DATEADD(month, 6, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)::DECIMAL(18,2) AS total_ltv_6_months,
SUM(CASE WHEN DATEADD(month, 12, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)::DECIMAL(18,2) AS total_ltv_12_months,
SUM(CASE WHEN DATEADD(month, 24, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)::DECIMAL(18,2) AS total_ltv_24_months,
SUM(price_in_usd)::DECIMAL(18,2) AS total_ltv_unbounded,
(SUM(CASE WHEN DATEADD(day, 7, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)/COUNT(DISTINCT rc_original_app_user_id))::DECIMAL(18,2) AS avg_ltv_7_days,
(SUM(CASE WHEN DATEADD(day, 30, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)/COUNT(DISTINCT rc_original_app_user_id))::DECIMAL(18,2) AS avg_ltv_30_days,
(SUM(CASE WHEN DATEADD(month, 6, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)/COUNT(DISTINCT rc_original_app_user_id))::DECIMAL(18,2) AS avg_ltv_6_months,
(SUM(CASE WHEN DATEADD(month, 12, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)/COUNT(DISTINCT rc_original_app_user_id))::DECIMAL(18,2) AS avg_ltv_12_months,
(SUM(CASE WHEN DATEADD(month, 23, first_purchase_date) > start_time THEN price_in_usd ELSE 0 END)/COUNT(DISTINCT rc_original_app_user_id))::DECIMAL(18,2) AS avg_ltv_24_months,
(SUM(price_in_usd)/COUNT(DISTINCT rc_original_app_user_id))::DECIMAL(18,2) AS avg_ltv_unbounded
FROM filtered_transactions ft
LEFT JOIN first_purchase_dates fpd
ONfpd.rc_original_app_user_id=ft.rc_original_app_user_idGROUP BY1
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Motivation / Description
people ask us about the subscriber retention chart all the time, including how to implement it using our etl exports
Changes introduced
New code block for the subscriber retention query
Jira ticket (if any)
Additional comments
cc @dpannasch @Carlosedo