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Answers to the most common questions advertisers ask about creative, campaign setup, tracking, and billing on AppLovin.
Yes. AppLovin has worked well for many brand-new brands, even without prior validation elsewhere. A good starting budget is one that would generate a few conversions a day on any platform, social or AppLovin. That gives the campaign enough signal to learn and optimize, regardless of where you're starting from.
Most advertisers and content on AppLovin are consumer-focused, but B2B advertisers do run on the platform, and lead-gen campaigns are supported.
AppLovin Ads supports physical ecommerce products, as well as digital products, subscriptions, and services, across both web and app businesses.
You can launch with a budget as low as $15/day. That said, for the model to learn efficiently, aim for a budget that generates at least 10 purchases a day at your typical CPA, and scale from there as you see results.
Ads appear across a variety of top-rated mobile games, including Candy Crush, Sudoku, Solitaire, and Words With Friends.
AppLovin ads are made up of a full-screen video and an AppLovin Interactive Page (AIP), which can be either a static image or an HTML interactive. For full video, image, and HTML specs, see Ad specs & requirements.
Top-performing assets from other platforms often transfer well, but AppLovin also reaches an incremental audience, so give the model a chance to test creative that didn't necessarily win elsewhere. For best results, upload as many creatives as possible; greater volume and variety give AppLovin's model more to evaluate, so it can select and show the best-performing ad for each impression. UGC-style videos tend to perform well, and captions are recommended since most users watch with sound off.
You can test a variety of Playables and Interactives. The in-platform Gen AI tool can generate several Interactives featuring your top ad copy, such as promos, social proof messaging, or other copy you know resonates with your audience. See the Interactive Pages Library for examples.
Generally, no. A user typically sees several ads before converting, and many of them play a role in that outcome. AppLovin's model optimizes to show the best ad for each impression, so a set that looks underperforming may still be effective top-of-funnel creative, even if a different set is what ultimately drives the conversion.
Most advertisers start with a healthy amount of creative, and the model naturally shifts spend toward the assets that perform best. If your budget is limited, you don't need to overload a campaign with creative, but volume generally isn't a constraint. Many brands run hundreds of videos and images within a single campaign without issue.
You can run both simultaneously if you want to balance total purchases against new-customer growth across different cohorts. For best results with Prospecting (or Discovery), integrate the Shopify app or upload historical purchase data through Events Manager, so the model has a clear signal of who your existing customers are.
Your day target tells AppLovin's model which conversion window to optimize toward. It doesn't restrict which attribution windows you can view in your reporting. For more on how attribution windows work, see Measurement and attribution.
Day 7 campaigns typically take longer to exit the learning phase, since cohorts need time to mature. Strong Day 1–2 performance is a reasonable early signal that a Day 7 campaign is scaling safely.
Start with a single campaign. Consolidating into one campaign gives AppLovin's model more data to learn from and makes more efficient use of your budget, especially early on when spend and creative volume are still low.
If you sell multiple SKUs, group your creative sets by product or category within that single campaign rather than creating separate campaigns for each. As a specific product proves out on AppLovin, you can layer in a dedicated campaign for it.
This doesn't mean multiple campaigns are discouraged; it's a sequencing recommendation. Most brands get more value starting with one well-structured campaign and expanding once they have enough budget and creative volume to support splitting further.
Targeting is primarily handled by AppLovin's model. Your creative gives the model additional signal, which is key to your success across AppLovin's 150 million+ daily active users in the US alone. You can also run campaigns optimized for new-customer acquisition if that's your primary objective. See Audience strategy for more.
Generally, leave all metros and states selected and let AppLovin's optimizer shift spend accordingly. If you don't service a particular metro or state, you can deselect it at the campaign level.
Dynamic Catalog shows users personalized product recommendations after the video and interactive. It's enabled at the campaign level, not inside individual creative sets. Your Product Catalog can be built three ways: an inferred catalog from pixel event data, a CSV feed from a third-party provider, or a custom hosted CSV file. See About Dynamic Catalog for setup steps and requirements for each method.
Advertisers using Dynamic Catalog typically see higher conversion metrics than those that don't, so AppLovin recommends keeping it enabled across all eligible campaigns.
After setup, validate your pixel is firing correctly using AppLovin's Pixel Helper before launching a campaign.
Per AppLovin's promotional terms, eligible new advertisers who spend $5,000 within 60 days of valid registration receive $5,000 in ad credit, issued within 7 days of hitting that spend threshold. This is limited to one offer per eligible advertiser, has no cash value, is non-transferable, and can only be used on the AppLovin platform.
Credit offers can vary by how you signed up. Some advertisers are onboarded through a marketing partner and receive a different credit structure (for example, a flat credit at sign-up rather than a spend-matched credit); eligibility and terms should always be confirmed against your specific account and sign-up path, since AppLovin can change or end promotional offers at any time.
AppLovin doesn't publish fixed budget benchmarks by category. Browse the Interactive Pages Library for examples of what similar brands are running today.
In the meantime, set your starting budget high enough to generate several conversions a day at your typical CPA. This gives AppLovin's model enough signal to learn and start optimizing efficiently. A budget too low restricts the model's ability to learn; a budget in the right range lets it start finding your best customers faster.
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