Moloco has launched an AI-powered performance connected TV (CTV) offering built specifically for app marketers. The company says the product brings mobile-grade measurement and optimization to the living room, a combination the CTV segment has so far struggled to deliver.

The core pitch is straightforward. App marketers have spent years tuning install campaigns on mobile, where user-level signals, attribution, and optimization loops let them tie ad spend directly to downstream events like installs, purchases, and retention. TV advertising has historically offered reach and brand impact, but weak accountability. Moloco is betting it can close that gap.

The new product applies Moloco's machine learning stack — the same infrastructure the company built for its performance advertising business — to CTV inventory. According to the company, the system optimizes toward the outcomes app marketers already track on mobile, rather than proxy metrics such as completed views or reach frequency.

Measurement is the second half of the proposition. Moloco says advertisers get mobile-grade measurement on CTV placements, meaning campaign performance can be evaluated against the same action-based KPIs used in app-install campaigns rather than panel-based brand lift studies or gross rating points.

Why it matters

CTV spend keeps growing as viewers shift hours from linear to streaming, but the channel's performance tooling has lagged mobile. App marketers in gaming, e-commerce, and subscription services have been the most aggressive adopters of outcome-based buying, and they have largely kept their budgets on mobile and social where the optimization loop is closed.

If a vendor can genuinely deliver install-level or event-level optimization on CTV inventory, the channel becomes competitive for performance budgets, not just brand budgets. That is the bet Moloco is making — and it is one that rivals including AppLovin, Adjust-connected demand partners, and the streaming platforms' own ad suites are also chasing.

What to watch

The announcement describes the product's positioning and intent; the proof will be in third-party-validated results. Key questions for buyers:

• Attribution mechanics. CTV lacks the deterministic device identifiers that mobile attribution relies on. How Moloco reconstructs the conversion path — probabilistic matching, clean rooms, or direct integrations with measurement partners — will determine whether "mobile-grade" is a technical description or marketing language.
• Inventory quality. Performance outcomes depend on where ads actually serve. Transparency into publisher mix and placement quality will matter to buyers used to mobile-level reporting.
• Scale. Machine learning optimization needs volume to learn. Early campaigns will show whether the system can exit the learning phase fast enough to compete with mature mobile channels.

Who uses it

The target buyer is the app marketer — performance teams at mobile-first companies that already run install and re-engagement campaigns and want incremental reach without giving up outcome-based buying. Moloco's existing customer base in mobile performance advertising is the natural first audience for the offering.

Moloco positions itself as a commerce-media and performance advertising company powered by machine learning, and this launch extends that franchise from mobile and web into the living room. The company has not disclosed pricing, launch customers, or availability timelines in the announcement materials.

For performance teams weighing CTV, the practical takeaway: another vendor now claims closed-loop optimization on streaming inventory. Treat the "AI-powered" label as table stakes, and pressure-test the measurement claims — attribution method, validation partners, and reported incremental lift — before shifting budget.