Kiddopia Grew UA Spend 3.1x with Unity Ads ROAS

Oct 26, 2026|3 Min

Daniel Godley - Unity

Senior Content Marketing Manager

Kiddopia logo of a dog teaching numbers and letters

Kiddopia is a Mumbai-based early learning app that teaches children through interactive play, covering subjects from cooking to math. Its primary audience are parents of children in the US and the LATAM regions.

Kiddopia’s primary user acquisition (UA) and monetization strategy leverages a 7-day free trial that converts to a paid subscription. The app doesn’t offer an ad-supported freemium tier - so acquired users at D7 either subscribe or end the free trial.

While maintaining this model, Kiddopia looked to further increase their scale while hitting their internal targets. The Unity team recommended they run campaigns that optimize for in-app purchase (IAP) ROAS and include longer targeting windows. Adding D28 campaigns would enable Kiddopia to capture users who complete the trial but then return later to subscribe.

By optimizing for IAP ROAS, Kiddopia changed both the value of the users they acquired and how much volume they could buy against their efficiency targets. Ultimately this resulted in a 3.1x increase in monthly spend on iOS and an over 69% increase in D7 ARPU.

3.1x

Monthly iOS spend*

+69%

D7 ARPU**

In their own words

“Switching to ROAS optimization changed the quality of what we were buying, not just the volume. D7 ARPU went up 69% while we tripled monthly spend. The ROAS campaigns let us grow and hold our efficiency targets at the same time.”

Shashwat Rai - Kiddopia

Performance Marketing Lead

The Challenge

Kiddopia was already running D7 campaigns optimizing toward trial starts. That was working for the app, but it optimized toward a signal one step removed from the outcome that they wanted to achieve: driving revenue. A trial start doesn’t guarantee a subscriber, and paying for volume at the top of a 7-day trial doesn’t provide transparency into conversions.

The trial model created a second problem. Kiddopia's subscription begins after the free week ends, and a meaningful share of subscribers convert on days 8 to 10 and beyond. Any optimization or measurement window that closes at D7 may not capture those users.

The Solution

Following the Unity team’s recommendations, Kiddopia rebuilt their campaigns using Unity Vector-powered ROAS models, optimizing for IAP revenue.

They also moved to split their campaigns across two attribution windows. Four D7 IAP ROAS campaigns carried the core scale, while a separate D28 IAP ROAS campaign for the US was purpose-built to bid on the late-converting cohort the 7-day window may miss. The two campaign windows run alongside each other in a layered structure: the D7 campaigns capture the users who convert immediately after the trial ends, while the D28 campaign targets the users who could take longer.

Graph showing Kiddopia's monthly iOS and ARPU trend

Implementation

Kiddopia ran on iOS across five campaigns built on Unity Vector-powered ROAS models. These include four D7 ROAS campaigns and one D28 ROAS campaign, all optimizing directly to IAP revenue events. D7 campaigns are particularly useful for the app, as they align with their 7-day free trial model.

Kiddopia opened at deliberately conservative targets, following the Unity Ads’ team guidance that the model needed a learning period on clean revenue signals before it was worth pushing volume. They launched all four D7 ROAS campaigns and split them by market, so each could find its own efficiency level rather than averaging across regions. All four optimized to the same in-app purchase revenue events. Later they added the US D28 ROAS campaign, targeted to specifically capture subscribers converting after the trial closed.

From there, the app scaled depending on performance. Over the following three months Kiddopia raised ROAS targets in five separate increases - each implemented only after weekly performance held above the existing target. Weekly spend followed with D7 ARPU holding throughout, rather than degrading as volume climbed. On creative, standalone playables remained Kiddopia's number one format by share of spend.

Campaign Structure Breakdown

Campaign Type

D7 ROAS (US)

Role in the Campaign Mix

Core scale driver and largest market

Reasoning

Optimizes to in-app purchase revenue with enough conversion volume for the model to learn quickly

D7 ROAS (Tier 1 English)

Role in the Campaign Mix

Extends US learnings into other English-speaking markets

Reasoning

Same optimization logic against a comparable audience, broadening reach without diluting targets

D7 ROAS (LATAM)

Role in the Campaign Mix

Regional scale

Reasoning

Separate targets let the region reach its own targets rather than a blended one

D7 ROAS (Brazil)

Role in the Campaign Mix

Regional scale, run separately from broader LATAM

Reasoning

Brazil market differs enough from the rest of LATAM to warrant localized optimization

D28 ROAS (US)

Role in the Campaign Mix

Captures late-converting subscribers on days 8 to 10 and beyond

Reasoning

A 7-day window doesn’t value a subscriber whose trial has not ended yet; the 28-day window can

The data foundation behind the result

Unity Ads and Unity Vector work best with clean revenue signals, and Kiddopia built that first. They followed Unity's MMP data enablement requirements for Vector and began passing IAP revenue events back. With that incoming data, Vector was able to better predict subscriber value and bid toward it.

The D28 campaign is the clearest illustration of the result: valuing a user who will convert past D7 by modeling behavior far beyond the install. The result is a subscription-based advertiser running the same revenue-optimized approach Unity Ads is known for in ad and IAP monetized games and using it to drive increased revenue.

Grow your game with Unity Ads

*Source: Internal Unity Data, based on Kiddopia campaigns. Monthly spend measured based on a data comparison of 1 January 2026 to 31 July 2026

**Source: Internal Unity Data, based on Kiddopia campaigns. D7 ARPU measured based on a data comparison of 1 January 2026 to 4 August 2026