Connected TV (CTV) is rapidly growing, with streaming representing over 44% of US TV viewing. However, industry veteran Tal Melenboim warns that fragmentation, fraud, and measurement gaps remain major obstacles to unlocking its full potential. Melenboim suggests that shared identity systems, privacy-safe data clean rooms, and supply path optimization can help overcome these challenges. He also notes that advertisers will focus less on completion rates and more on proof of incremental reach and sales lift.
Connected TV (CTV) is rapidly growing, with streaming representing over 44% of US TV viewing. However, industry veteran Tal Melenboim warns that fragmentation, fraud, and measurement gaps remain major obstacles to unlocking its full potential. Melenboim suggests that shared identity systems, privacy-safe data clean rooms, and supply path optimization can help overcome these challenges. He also notes that advertisers will focus less on completion rates and more on proof of incremental reach and sales lift.
The $30 billion CTV advertising market is growing fast, but most brands are flying blind on measurement [1]. While 70% of US consumers stream content across multiple platforms, marketers are stuck with fragmented data that makes proving CTV’s true impact challenging. The brands that solve measurement first will dominate this massive opportunity [1].
One of the most pressing challenges is platform fragmentation and data silos. CTV spans a wide range of devices, platforms, and content ecosystems, each with different data collection practices and measurement standards. This fragmentation makes it difficult to understand consumers’ interactions across environments and accurately measure reach and frequency [1]. To address this, data collaboration can help break down silos by connecting different data sets across platforms and partners to turn fragmented views into a unified measurement strategy [1].
Another significant challenge is the lack of standardized metrics. CTV platforms define metrics like impressions, completions, and reach differently, making it difficult to compare performance across partners or channels. Cross-media measurement enables connectivity across these data sources for a unified and standardized view of performance [1].
Measuring incremental reach is also a challenge. Many marketers treat linear and CTV as separate channels, adding CTV after the fact to extend reach. This outdated approach doesn’t align with how today’s consumers engage with content across multiple screens. Cross-screen measurement capabilities can help unify data across linear, CTV, and digital to give a holistic view of reach, frequency, and performance [1].
Brand safety and ad fraud are growing concerns as the CTV ecosystem expands. Spoofed inventory, invalid traffic, and limited transparency make it difficult to conduct quality checks. Identity resolution capabilities can help distinguish real engagements from fraudulent activity [1].
Lack of transparency remains a persistent challenge. Many publishers and platforms don’t provide advertisers with full insight into placement, performance, or whether an ad was truly seen. Clean room technology can provide valuable insights into CTV ad delivery, frequency, and audience engagement [1].
Cross-channel attribution is another challenge. Tying CTV impressions to downstream conversions across web, app, and in-store channels is notoriously difficult. Resolving identity across CTV publishers, platforms, and environments can help link ad exposures to real results [1].
Finally, proving CTV’s business impact is hard using traditional measurement frameworks. Data collaboration can connect CTV impressions to real business outcomes like transactions, conversions, and customer acquisition [1].
The future of CTV measurement belongs to those who unify data, respect privacy, and adapt measurement to meet today’s viewers. By overcoming these challenges, advertisers can maximize ROI, unlock incremental reach, and elevate their media strategies.
References:
[1] https://liveramp.com/blog/ctv-measurement-challenges/
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