Cross\u2011device advertising in CTV turns scattered viewers into a unified, measurable audience, closing the gap between TV\u2011screen exposure and mobile or web conversions. By connecting CTV exposures to actions on other devices, brands can assign true performance value to CTV campaigns and shift spend from impressions to outcomes, where every dollar drives installs, sales or leads.<\/p>\n
CTV ad spend is projected to reach $35 billion in the US by 2026, and globally CTV will account for over 30\u202f% of TV advertising budgets. Yet, most CTV campaigns still run on a CPM model, measuring how many households saw an ad instead of how many actually converted. This leaves a huge gap: brands know their ads ran, but struggle to prove they drove installs, e\u2011commerce orders, or store visits.<\/p>\n
A typical CTV viewer might watch a 30\u2011second ad on a smart TV, then five minutes later search for the product on their phone, and buy it on a laptop hours later. Without cross\u2011device tracking, that sale is rarely attributed to the CTV ad. Instead, brands either overpay for reach they don\u2019t need or slash CTV budgets because they can\u2019t prove performance.<\/p>\n
Households today use multiple devices: a CTV to watch streaming, smartphones for browsing, tablets for in\u2011app use, and desktops for purchase. Each device generates its own click or cookie, making it hard to recognise that a single person used several devices. This fragmentation leads to over\u2011counting unique users and under\u2011counting real conversions.<\/p>\n
Without a device graph, marketers can\u2019t reliably connect a CTV impression to a downstream mobile app install or purchase. They often see \u201cincremental\u201d sales increase but can\u2019t isolate the CTV contribution, so they keep relying on brand\u2011lift surveys or last\u2011touch web analytics, both of which are incomplete for CTV.<\/p>\n
When CTV campaigns are evaluated only on reach and frequency, the risk of wasted spend is high. Brands routinely over\u2011buy broad demographic audiences because they can\u2019t target or retarget precisely, pushing up effective CPMs and diluting performance. For direct\u2011response goals, this can result in ROAS well below target.<\/p>\n
Another major cost is missed retargeting opportunities. If a brand doesn\u2019t know which mobile devices belong to CTV viewers, they can\u2019t run follow\u2011up ads to that same person on mobile or desktop. That means lower conversion rates and higher cost per action, especially for app installs and e\u2011commerce.<\/p>\n
Most CTV platforms still rely on broad demographic or contextual targeting, using age, gender, or content genre to define audiences. They can deliver scale, but not precision, so ads are often shown to people who don\u2019t intend to convert, raising the cost of each meaningful action.<\/p>\n
Legacy multi\u2011touch models (like linear or time\u2011decay) struggle to correctly assign credit to CTV because they treat each device as a separate user. A CTV exposure might be recorded as a first touch, but the mobile or web conversion is credited to search, social, or affiliates, making CTV appear less effective than it actually is.<\/p>\n
Even with basic cross\u2011device graphs, many platforms apply attribution rules that don\u2019t match real\u2011world customer journeys. For example, they might ignore CTV exposures if the downstream conversion happens days later, or they may lack the household\u2011level signals needed to confidently link exposures across devices.<\/p>\n
In traditional CTV, budget is often wasted on these three leaks:<\/p>\n
Over\u2011purchasing reach in the same household, showing multiple ads to the same person across devices without frequency capping.<\/p>\n<\/li>\n
Serving ads to \u201clookalike\u201d audiences who resemble converters but actually don\u2019t convert at the same rate.<\/p>\n<\/li>\n
Running broad awareness campaigns that can\u2019t be tied back to app installs or purchases, so optimisation is based on engagement, not revenue.<\/p>\n<\/li>\n<\/ul>\n
These inefficiencies mean that even high\u2011spend CTV campaigns often deliver mediocre ROAS, and brands hesitate to scale despite the screen\u2019s powerful reach.<\/p>\n
A performance\u2011driven cross\u2011device CTV platform links exposures on CTV to conversions on smartphones, tablets and desktops at the household or user level. It uses a device graph to map which devices likely belong to the same person, then applies attribution models that properly credit CTV for driving actions across devices.<\/p>\n
For example, when a viewer watches a CTV ad for a fintech app, the system can later recognise that the same person (or their household) installed the app on an iPhone or completed a signup on a laptop. That conversion is then attributed back to the CTV campaign, enabling true cost\u2011per\u2011install or cost\u2011per\u2011sale reporting.<\/p>\n
Starti is a connected TV advertising platform built specifically for performance and measurable ROI, not just impressions. It turns CTV screens into profit engines by connecting CTV exposures to outcomes like app installs, sales, and leads, so brands pay only for actions that move the business forward.<\/p>\n
Starti\u2019s approach combines:<\/p>\n
A robust cross\u2011device graph that links CTV, mobile, desktop, and tablet activity at the household level.<\/p>\n<\/li>\n
OmniTrack attribution that ties CTV views to downstream conversions across devices, including in\u2011app events and web purchases.<\/p>\n<\/li>\n
SmartReach\u2122 AI that optimises targeting based on which device combinations are most likely to convert.<\/p>\n<\/li>\n
Dynamic creative optimisation (DCO) that personalises ads based on cross\u2011device signals (e.g., showing a product viewed on mobile in a CTV ad).<\/p>\n<\/li>\n<\/ul>\n
Starti\u2019s performance model aligns incentives with client outcomes; over 70\u202f% of its team\u2019s rewards are tied to client ROAS, so the platform is engineered to deliver accountable, optimised CTV campaigns.<\/p>\n