A playable ad is working when it brings in installs at an IPM and CPI at least as good as your current best creative on the same network, and those players retain and pay back on your D7 target. Engagement inside the ad tells you why it wins or loses; D7 retention and early ROAS tell you whether to keep paying for it.
Everything else is a supporting signal. The rest of this page is the method: which numbers to read, in what order, against which baseline, and how much data you need before you decide.
Which metrics tell you a playable ad is working?
Read them in this order. The order matters, because a playable can look great on one layer and fail on the next.
| Metric | How to calculate it | What it tells you | Use it to |
|---|---|---|---|
| IPM (installs per mille) | Installs ÷ impressions × 1,000 | How well the playable turns attention into installs. The network's algorithm reacts to this most. | Decide if it can win delivery |
| CTR | Clicks ÷ impressions | How often players tap through. On playables, many clicks happen after play, at the end card. | Diagnose the CTA and end card |
| CVR (click to install) | Installs ÷ clicks | Whether the store page delivers on what the ad promised. | Spot misleading hooks |
| CPI | Spend ÷ installs | What a user costs you. Moves with bids and auction pressure, not only with the creative. | Check efficiency against target |
| Engagement rate | First interaction ÷ playable displayed | Whether the hook gets a first tap. | Fix the opening seconds |
| Completion rate | Players reaching the end state ÷ players who started | Whether the challenge length and difficulty fit. | Fix difficulty and fail state |
| D1 and D7 retention | Players active on day one or day seven ÷ installs (from your MMP) | Whether the playable attracted players who like the real game. | Catch hooks that mislead |
| Early ROAS (D0, D3 or D7) | Cohort revenue ÷ cohort spend | Whether the players pay back on your model. | Decide what stays live and scales |
Engagement and completion live inside the ad. You only get them if the playable fires events and the network reports them. AppLovin documents a fixed set of in-playable events for this. The full event list and what each network allows is on our page on what to track inside a playable ad.
Why isn't IPM enough on its own?
Because the network loves what converts, and your business loves what pays back. Those are often different playables.
UA consultant Matej Lancaric reviewed about 360 creatives that ran for 30 days for one game across four networks, in an analysis published in August 2026. His read: "IPM tells you what the algorithm loves. ROI tells you what your business loves." On Meta, a set with lower IPM returned more than a set with higher IPM.
A playable is a strong candidate for this trap. A satisfying puzzle with a fail state can pull a lot of curious installs from people who never open the game again. That shows up as high IPM, low CPI and weak D7. If the playable shows gameplay the real game does not have, the gap gets wider. We cover that risk in playable vs video vs end card.
What should you compare a playable against?
Three baselines, in order of how much you should trust them.
| Baseline | Why it works | Watch out for |
|---|---|---|
| 1. Your current best creative on the same network, geo and week (the control) | Same audience, same auction, same attribution rules. The only clean comparison. | A long-running control has history; the new playable starts cold. Give it the same sample before you judge. |
| 2. Your video baseline on that network | Tells you if the playable earns its higher production cost. | Playables often win IPM and lose D7, or the reverse. Compare both layers. |
| 3. Published genre or market benchmarks | Useful sanity check when you have no history. | Benchmarks mix very different games. Never use them to make the final call. |
Never compare across networks. AppLovin, Meta, Google and Unity define impressions, engagements and click attribution differently, and self-attributing networks often leave creative-level revenue unassigned. A playable's IPM on AppLovin and a video's IPM on Meta are different numbers that happen to share a name.
When you do need a published reference, use ones with a clear method:
More sourced numbers, each with its method and year, are on our playable ad statistics page.
One read in. One focused change out. Genie Playable builds the next version from the last one, so if the read says "fix the fail state," the fail state is the only thing that changes. No developer in the loop.
Try GenieHow long should you wait before judging a playable?
Long enough to reach a sample you chose before launch, and long enough for the D7 cohort to mature. Not a number of days you picked because the dashboard looked bad on day two.
The networks say the same thing in their own words:
A method that works on any network
Teams we talk to most often go wrong at step five. A playable gets a slow start because the network is still exploring, someone pauses it on day three, and the test never produces an answer. If you cannot afford the sample, test fewer variants, not shorter. Our page on how many playables to test covers the budget math.
When should you cut, iterate or scale a playable?
Once you have the sample, the call is usually clear. Put the delivery read and the quality read side by side.
| Delivery (IPM, CPI) vs control | Quality (D7 retention, early ROAS) vs target | Call | What to do next |
|---|---|---|---|
| Better | At or above | Scale | Move budget, then start the next variant before fatigue sets in |
| Better | Below | Iterate | The hook pulls the wrong players. Make the playable show the real game more honestly |
| Worse | At or above | Iterate | Right players, weak conversion. Work on the first three seconds, CTA and end card |
| Worse | Below | Cut | Keep the learnings, drop the concept |
| Not enough data | Not enough data | Keep running or stop the test | Do not make a call. Extend, or accept the test was too small |
Use in-ad data to choose what to iterate
Once a playable lands in an "iterate" row, the in-playable funnel tells you where to work:
Change one of these at a time. Our guide to iterating a winning playable goes deeper on what to vary.
What makes playable results hard to read?
Same playable, every network. Genie Playable exports optimized builds for Meta, AppLovin, Unity Ads, Liftoff, Google Ads, TikTok Ads, Pangle and Mintegral (Moloco coming soon), so the version you compare on each network is the same creative.
Book a demoWhere does Genie Playable fit?
Genie Playable is where you make and remake the playables you are measuring. It builds a playable from your APK or HTML build plus the assets in Genie, from a format that is already working, or from scratch from a brief with Genie Agent. You iterate from the last version, without a developer. That matters for measurement: when a read says "change the end card," you change the end card and nothing else, and the next test is clean.
What Genie Playable is not: it is not an MMP or an analytics dashboard, and it does not decide for you whether a playable is working. Your network reporting and your MMP do that. We do not publish performance lift numbers for Genie Playable.
It is a good fit if you want more playable variants per month without adding developer time. It is not the right fit if you already have an in-house playable team shipping at the pace you need, or if you run mainly on a network we do not export to yet.
Pricing has two tracks. Self-serve starts at $490 a month, or $249 a month for startups, and sign-up is free, with enough tokens to create your first two playables before you pay. Larger companies usually take the custom plan: a full one-month pilot where the Genie team onboards you and helps you build the playables you want.
Make the next version count. Measurement tells you what to change. Genie Playable makes the change, from your game, without a developer.
Try GenieFAQ
Sources
- 01AppLovin, Playable analytics integration
- 02Google Ads Help, Monitor your App asset experiment
- 03Google Ads Help, Make better creative assets for App campaigns
- 04Unity Grow, Creative Testing configure
- 05Unity Grow, Creative Testing analyze
- 06TikTok Ads Help, How to create Playable ads on TikTok Ads Manager
- 07Liftoff, 2025 Mobile Ad Creative Index press release (vendor data)
- 08GameAnalytics, 2026 Mobile and PC Gaming Benchmarks (vendor data)
- 09AppsFlyer, Creative optimization data report, May 2024 (vendor data)
- 10Matej Lancaric, How to find a winning creative, August 2026
- 11RocketShip HQ, How to test ad creatives on AppLovin, 2026
