Trial to Paid Attribution: A Guide to Channel Credit Rules
Trial to paid attribution compares mature trial-start cohorts by a consistent channel-credit rule, with guidance on first-touch versus Airbridge attribution.
Measure trial-to-paid conversion by trial-start cohort and label the channel-credit rule.
- Count paid conversions from each set of trials that started in the same period.
- Compare cohorts after every included trial has had time to convert or expire.
- Use first-touch credit to study acquisition origin, and use Airbridge attribution for the touchpoint Airbridge assigns to the app target event.
- For RevenueCat, separate trial conversions from direct purchases even though both map to Airbridge’s Subscribe event.
Trial to paid attribution works best as a trial-start cohort rate with one channel-credit rule applied consistently. For a lean subscription team, use the channel view that answers the budget question: first touch for the channel that began the acquisition journey, or Airbridge’s event attribution for the eligible touchpoint selected for an app target event and inherited by later subscription events within its attribution window.
Define the trial-to-paid rate by channel
A trial-to-paid conversion rate answers: of the trials that began in a defined period and were credited to a channel under a stated rule, how many later became paid? Set the cohort date to the date the trial starts. Count trial subscriptions in that cohort as the denominator, and count those that convert to a first paid subscription by a fixed outcome deadline as the numerator.
RevenueCat’s Trial Conversion Rate chart cohorts trials by their start date and counts each trial subscription once. It also treats dates with trials still in progress as incomplete, because those trials may still convert. That makes the trial start date the useful anchor for comparing channels, rather than the calendar date when payments happened.
Choose an observation deadline that gives every included trial the same chance to reach a paid decision. In practice, base it on the longest trial duration offered to that cohort, plus a consistent allowance for the paid event to arrive. Include only cohorts whose deadlines have passed. A trial that has not ended yet stays out of a mature-cohort comparison, because it has had less time to convert.
Those two calendar totals can describe different users. In its cohort-metrics guidance, Statsig explains that users with different amounts of follow-up time create mixed-maturity cohorts. Equal observation periods make early and late cohorts more directly comparable, though the completed cohorts include fewer recent users.
For example, assume Channel A brought in 100 trial subscriptions whose full observation deadlines have passed. If 32 of those subscriptions reached their first paid conversion by the deadline, Channel A’s trial-to-paid rate is 32%. Apply the same cohort dates, deadline, numerator definition, and channel-credit rule to Channel B before using the rates to move spend.
When first-touch credit fits
Use first-touch credit when the question is, “Which channel first brought this user into the acquisition journey?” It gives the origin channel credit for the user’s later conversion, so it helps assess discovery and initial acquisition. A team choosing this rule should define the first eligible touch it records, such as the first attributed acquisition interaction, then preserve that source for the trial cohort.
Google Analytics describes the acquisition-origin idea through its First user source / medium dimension. It represents the source or medium that acquired a user in the first session, and its user-level value stays the same as that person returns. Google distinguishes it from session-scoped source values, which can change with later sessions.
First touch is useful when a growth team wants to reward the channel that introduced users, including when another eligible touch occurs later. Because first touch leaves later interactions out, it can give awareness channels more emphasis and leave the role of later nurturing and product trials less visible, as HubSpot explains. Keep that report separate from a report that assigns a later, eligible touchpoint to the outcome, because the two numbers answer different questions.
Connect RevenueCat trial events to Airbridge
RevenueCat sends separate source events for trial starts and trial conversions, but the default Airbridge mapping sends both TRIAL_CONVERTED and INITIAL_PURCHASE to Subscribe. Use the RevenueCat source event and trial-start cohort to identify trial-to-paid outcomes; a total of Subscribe events combines trial conversions, initial purchases, and renewals.
| RevenueCat event | Default Airbridge event | Use in the trial-to-paid calculation |
|---|---|---|
TRIAL_STARTED | Start Trial | Starts the trial cohort and sets its start date. |
TRIAL_CONVERTED | Subscribe | Identifies a trial that converted to paid. |
INITIAL_PURCHASE | Subscribe | Separate source event; keep it distinct from TRIAL_CONVERTED. |
RENEWAL | Subscribe | A later subscription renewal. |
Follow the RevenueCat integration setup in this order:
- Set up the RevenueCat SDK first. The integration requires device IDs collected by Airbridge to be sent to RevenueCat.
- Match the user ID used in the Airbridge SDK to the RevenueCat App User ID. The integration guide recommends sending RevenueCat’s App User ID to Airbridge for events such as sign-up and sign-in, which often happen before a subscription.
- In Airbridge, open Integrations > Third-party Integration > RevenueCat and copy the Airbridge Subdomain and Airbridge Token.
- In RevenueCat, open Integrations > Attribution > Airbridge, enter the subdomain and token, select Use default event names, and add the integration.
- Choose one source for subscription events. When RevenueCat sends those events to Airbridge, prevent the Airbridge SDK from collecting the same subscription events again.
When Airbridge cannot find a matching RevenueCat user ID, it generates a random ID, which may make the reported number of users for subscription events higher than the actual figure. Use the default mapping for the names above, and keep the source event distinction available when identifying trial conversions.
Which channel Airbridge assigns to a later trial or payment
Airbridge assigns a channel to an app target event using the eligible touchpoints before that event. Its attribution model documentation names three app target events: app install, deeplink open, and deeplink pageview. A lookback window determines how far before a target event Airbridge considers touchpoints. It ranks eligible touchpoints by priority, then selects the closest touchpoint among those ranked.
Purchases, sign-ups, and product detail views within the attribution window can be subsequent events rather than new target events. When it occurs within the attribution window after a target event, Airbridge assigns it to the touchpoint credited to that target event. The paid event’s channel therefore identifies the touchpoint that won for the app install or deeplink target event, which may differ from the user’s first channel and from the touchpoint closest in time to payment.
The two windows cover different parts of the journey. The lookback window searches backward from the target event for eligible touchpoints. The attribution window carries the target event’s winning touchpoint forward to later events.
Airbridge also gives deeplink open and deeplink pageview windows higher priority than an app-install window when the deeplink event occurs within the install window. In a journey with an install and a later app-opening touch, this priority rule can affect which target-event touchpoint wins. The model uses ranked eligibility and timing together, rather than simply assigning every event to the earliest interaction.
Choose the channel view for the budget decision
Select the view that matches the decision you need to make, and write its rule beside every channel rate. For a team deciding whether prospecting channels bring in trial users, acquisition-origin credit is useful. For a team comparing channel performance under Airbridge’s touchpoint rules, use Airbridge-attributed outcomes within the configured attribution window.
| Budget question | Channel credit to use | What the rate tells you |
|---|---|---|
| Which channel first introduced the user who began a trial? | First-touch or first-user acquisition source, fixed at cohort entry. | The share of that channel’s mature trial cohort that became paid, credited to the original source. |
| Which eligible touchpoint received app-event credit? | Airbridge’s winning touchpoint for the target event, inherited by subsequent events within its attribution window. | The share of trial starts associated with that credited touchpoint that later converted during the defined cohort period. |
| Did acquisition origin and later event credit point to different channels? | Keep both labeled views side by side. | Whether a channel starts the journey often, receives later event credit, or both. |
Make the channel rule consistent across each cohort calculation. If you group trial starts by first acquisition source but group paid conversions by a later touchpoint, the numerator and denominator describe different assignments. Show both measures when both questions matter, and use the one matched to your spend decision as the primary rate.
Validate the channel rates before moving spend
Run these checks on a small set of mature trial cohorts before treating a channel difference as a budget signal:
- Confirm the cohort start. A RevenueCat
TRIAL_STARTEDevent should map to AirbridgeStart Trial. Use the trial’s start date to assign its cohort period. - Separate trial conversion from other Subscribe events. RevenueCat maps
TRIAL_CONVERTED,INITIAL_PURCHASE, andRENEWALtoSubscribe. Count the trial-conversion source event for this metric, and keep direct purchases and renewals in their own measures. - Check identity and device IDs. For a test subscriber, trace the same RevenueCat App User ID in both systems and verify that device IDs are sent from Airbridge to RevenueCat. Then verify that the trial start and later conversion join to the same user or subscription record in your reporting source.
- Remove duplicate paths. If RevenueCat imports the subscription events, make sure the Airbridge SDK does not send those same events again.
- Wait for comparable follow-up. Include cohorts only after the chosen trial-conversion deadline has passed. Keep the cohort observation deadline separate from Airbridge’s attribution window, which determines how long later events inherit target-event credit.
- Write down the credit scope. Record whether the channel column means first acquisition source or Airbridge’s winning target-event touchpoint. Apply the same definition to the trial cohort and the paid outcome.
A useful weekly view has one row per trial-start period and channel, with mature trial starts, first paid conversions, conversion rate, the chosen credit rule, and the cohort deadline. If the rate changes after you correct duplicate events or identity joins, use the corrected figure for the budget call. If a conversion falls outside the configured Airbridge attribution window, keep its cohort outcome distinct from an event that has inherited in-window channel credit.
A practical rule for channel decisions
For a small team, calculate trial-to-paid conversion from trial-start cohorts and use mature cohorts for channel comparisons. Choose first-touch credit when you want the origin channel, and choose Airbridge attribution when you want the touchpoint selected for an app target event and carried to in-window subscription events. Keep source event type, cohort deadline, and channel-credit rule visible beside each rate so a change in one measurement rule does not look like a change in campaign performance.
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