Smart TVs are in 1.1 billion households as of 2025, and Roku reports that 82% of its users stream content daily. That number is why founders building media, fitness, education, and entertainment apps keep asking whether phone-only is leaving audience on the table.
The honest answer: sometimes yes, often no. The device decision depends on where your users actually watch, how your interface behaves without a touchscreen, and how much extra budget each platform adds to your build. Those three questions have concrete answers.
Which non-phone devices have big enough audiences?
Not every device category deserves a build. The question is whether the audience is large enough and engaged enough to justify the cost before you have found product-market fit.
Smart TVs are the clearest case. Nielsen's 2025 report found that streaming on connected TVs now accounts for 38% of total TV viewing time in the US, up from 28% in 2022. The platforms with the largest install bases are Roku (80+ million active accounts), Amazon Fire TV (50+ million), Samsung Tizen, LG webOS, and Apple TV. Together they cover the overwhelming majority of smart TV households in North America and Europe.
Tablets come second. There are roughly 700 million active tablets worldwide (IDC, 2024), and they skew toward use cases with rich visual content: reading, video, education, and recipe apps. If your content is visually dense or if users typically spend 20+ minutes per session, tablet layouts earn their keep.
Wearables, primarily Apple Watch and Wear OS devices, have about 200 million active units globally (Counterpoint Research, 2024). They matter for health, fitness, and notification-driven apps. They are near-useless for content-heavy experiences because the screen is the size of a large postage stamp.
Desktops and laptops are worth considering only if your product is a SaaS tool, a creator-focused platform, or something that requires extended keyboard input. A responsive web app covers most of these cases without a separate build.
| Device Category | Active Audience | Best-Fit App Types | Skip If |
|---|---|---|---|
| Smart TV | 1.1B households | Media, fitness, education, games | Your content is text-heavy or requires frequent input |
| Tablet | 700M devices | Visual content, reading, long sessions | Your core experience works fine on a phone |
| Wearable | 200M devices | Health, fitness, notifications | Your app needs more than 3–4 UI elements at once |
| Desktop (web) | Already covered by a responsive web app | SaaS, creator tools, keyboard-heavy workflows | Your app is phone-native and sessions are short |
The rule of thumb: build for a new device category only if at least 20% of your target users are likely to use your product there. Otherwise, the maintenance cost of that device eats roadmap time that would have been better spent on core features.
How does a smart TV app interface differ from a mobile app?
This is where founders consistently underestimate the work involved. A smart TV is not a phone plugged into a big screen. The interface model is fundamentally different, and designing for it requires rethinking how users navigate your product.
On a phone, users tap exactly where they want to go. On a smart TV, they press directional buttons on a remote. That distinction reshapes everything about your UI. Every interactive element needs to be reachable by moving left, right, up, or down from wherever the user's focus currently sits. If a user has to make seven button presses to reach the search icon, you have already lost them.
Font sizes are the second major difference. The average user sits 8–10 feet from their TV. Text that reads comfortably at 16px on a phone screen is illegible at that distance. Smart TV guidelines from both Roku and Amazon recommend a minimum of 24px for body text and 36px for navigation labels.
Loading patterns matter more on TV than on mobile. A phone user who waits two seconds for a page to load has seen that before. A TV user expects the experience to feel like a broadcast: instant, no spinners, no perceived loading state. Content must preload before it appears on screen, which requires the app to anticipate what the user is likely to navigate to next.
There is also no equivalent of the keyboard for text input. Typing on a smart TV means navigating an on-screen keyboard one letter at a time with a directional remote. Every field that requires text input on a smart TV is a UX problem to solve. Good TV apps minimize typing to near zero: log in once, browse by category, use voice search when supported.
These differences mean a smart TV version of your app is not a reskin. It is a new interface model built on the same data layer. Expect 35–50% additional design work beyond what your mobile screens required.
What development cost does each additional device category add?
The short version: each device category adds 25–40% to your total build cost, depending on how different the interface model is from your primary platform.
Tablets are the cheapest expansion. A phone app built on a modern cross-platform framework can typically support tablets by adjusting layouts, adding a sidebar, and scaling up font sizes and tap targets. A $8,000 phone MVP expands to tablet support for roughly $2,000–$3,000 extra, bringing the total to about $10,000–$11,000. Western agencies quote $35,000–$45,000 for the same scope.
Smart TVs cost more because the interface model is genuinely different. Directional navigation, preloading logic, voice search integration, and the remote-first interaction model all require bespoke work. A $8,000 phone MVP adds $6,000–$8,000 to include a smart TV version, for a total of $14,000–$16,000. Traditional agencies charge $50,000–$60,000 for the same result.
Wearables are cheap to add when the feature set is limited to notifications and simple health metrics, and expensive when the app needs to run independently on the watch. A companion wearable feature adds $3,000–$5,000 to a phone app. A standalone wearable app built from scratch runs $12,000–$18,000.
| Expansion | AI-Native Team (added cost) | Total from $8K Phone MVP | Western Agency Total | Legacy Tax |
|---|---|---|---|---|
| Add tablet support | +$2,000–$3,000 | $10,000–$11,000 | $35,000–$45,000 | ~3.5x |
| Add smart TV support | +$6,000–$8,000 | $14,000–$16,000 | $50,000–$60,000 | ~3.5x |
| Add wearable (companion) | +$3,000–$5,000 | $11,000–$13,000 | $40,000–$50,000 | ~3.5x |
| Full multi-device (phone + tablet + TV) | +$8,000–$11,000 | $16,000–$19,000 | $65,000–$80,000 | ~4x |
One factor that inflates costs significantly: building separate native apps for each device rather than using a shared codebase. A team that builds your phone app in React Native or Flutter can share 60–70% of that code across platforms, reducing the per-device cost. A team that writes separate Swift for iOS, Kotlin for Android, and proprietary code for each TV platform is rebuilding from scratch every time. Ask your agency directly how much code is shared across platforms. The answer tells you whether you are paying for work or redundancy.
How do AI-powered content delivery platforms simplify multi-device rollout?
For media, education, fitness, and entertainment apps, there is a category of tooling that changes this calculation: AI-powered content delivery platforms.
These are services that sit between your content and your users, automatically adapting what gets displayed to match the device, screen size, connection speed, and user behavior. Think of it as a smart intermediary: you publish content once, and the platform handles how it renders on a phone, a tablet, a TV, and a wearable, without requiring separate builds for each.
The business outcome matters here. A content creator who uploads a 30-minute workout video does not want to think about whether it preloads correctly on a Roku or displays at the right quality on a 4K TV. An AI content delivery layer handles that automatically. The same applies to article layouts, course materials, and interactive lessons.
For developers, the impact is concrete. A 2024 Gartner survey found that teams using AI-assisted content adaptation reduced their multi-platform QA time by 42%. When the platform handles device-specific rendering automatically, the manual testing surface shrinks from testing on six device configurations to testing on two.
Timespade builds these delivery layers as part of multi-device projects. The approach: a single content model in the database, an AI adaptation layer that determines presentation per device, and a shared application shell that renders it. The result is one codebase where device-specific behavior is configuration, not custom development.
This architecture makes expanding to a new device much cheaper after the initial build. Once the adaptation layer is in place, adding a new device platform typically costs 30–40% less than the first expansion because the content model and delivery logic already exist. A team that builds its TV app as a separate standalone product pays full price for every platform it adds. A team that builds with a shared content layer pays a decreasing marginal cost per device.
Not every app needs this. A booking tool, a project management app, or a SaaS dashboard does not have content in the sense that a media platform does. For those products, device-specific layouts built into the app itself are the right approach. But if your app is primarily about consuming content, whether that is video, courses, workouts, or articles, an AI delivery layer is almost always worth building at the start rather than bolting on later.
The practical takeaway: if your roadmap includes more than two device categories, start the conversation about a shared content architecture before the first line of code is written. Retrofitting a standalone app into a multi-device platform midway through development costs more than building it right from the start, and the rework disrupts the features you have already shipped.
