Advertisers Admit Falling Short On Optimizing Converged TV

Despite heavy time commitments to trying to optimize performance of converged TV campaigns, many advertising professionals admit that they’re not fully achieving this objective.

Nearly 90% of 250 senior-level brand and agency executives surveyed in August by Innovid agreed that a unified view of performance across converged campaigns — defined as linear, connected TV and digital — is important, and 91% said that standard KPIs across converged TV advertising are important at some level.




Asked about the top drivers of optimization goals, respondents identified improving relevance of the brand’s audience, finding new audiences, driving more response, finding more effective ways to buy and lowering ad frequency.

More than 60% said that they plan to increase budgets for converged TV ads moderately or significantly (chart above).

And more than half (56%) said they currently spend more than half of their time working to optimize these types of campaigns.

But just 40% rated their optimization practices as “very good,” with the rest saying their efforts are falling short.


One reason: Campaigns are being optimized less frequently than they're measured.

More than two-thirds (68%) are measuring the performance of converged campaigns on at least a weekly basis, and 39% are measuring them either daily or in real time. In comparison, 58% report implementing media optimization efforts on a weekly or more frequent basis.

“Speed in moving insights into action is essential,” notes the Innovid report. “A sharp insight yesterday may be worthless today.”


According to Innovid, another contributor to less than optimal optimization is inefficiencies caused by using separate partners for performance measurement and campaign management/delivery —the current practice of 60% of the advertising professionals surveyed.

Innovid — which is pitching its own platform’s ability to connect converged TV ad measurement with the ability to automatically optimize — says breaking up these functions causes data loss and increases integration needs.

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