For major investments like TV advertising campaigns, marketers need to know what works. Brands spend nearly $100 billion on TV and CTV advertising each year, in the US alone. But for decades, these high-stakes buys have struggled to deliver transparent performance, relying instead on broad audience rating numbers and delayed survey results to estimate success.
Finally, those blind spots are fading. With the rise of Convergent TV (CTV) TV ads are becoming more and more precise and actionable. Still, marketers need the right technology and metrics to measure ad impact, with a greater focus on TV outcomes. Let’s break this down further.
Television has always been the biggest megaphone for advertisers. TV has a proven “halo effect,” generating not only awareness and legitimacy but stronger digital media performance. However, this impact has typically been measured only in audience reach metrics offered by standard-bearers like Nielsen.
Digital TV content offers more trackability, but is also highly fragmented across countless consumer offerings with new streaming players popping up each month. At the same time, marketing budgets are shrinking, and pressure is mounting to maximize every ad dollar.
Some of the top challenges to TV measurement include:
To fully understand the impact of your TV advertising, it’s crucial to track a range of metrics that capture both short- and long-term business outcomes. Here are a few to consider:
Traditional reach metrics are most closely associated with TV ad campaigns. This includes Gross Ratings Points (GRPs), which measure the cumulative impact of an ad, multiplying the audience size by the ad frequency within a set time window. Completion rates for TV ads and the number of social media mentions also offer initial measures of engagement.
More valuable than reach is intentional action taken by your target audience. Marketers can look to brand searches or their own website traffic to measure the uptick in search engagement that follows a given TV ad airing. Evaluate concurrent search volume for brand terms, featured products, or app downloads.
The holy grail of any TV ad is to drive new purchases. Attribution models attempt to tie incremental sales, or related changes to average order value, to specific TV ad spots. However, these models are complex and need regular maintenance with an ever-changing customer journey.
By matching incremental sales with specific TV ads, brands can confidently calculate the return on advertising spend (ROAS) for any given campaign. By comparing cost per acquisition (CPA) attributed to TV versus other marketing channels (such as social or email), advertisers can identify where to focus their marketing investments. However, the process of attributing sales to individual ads or campaigns can be costly and time-consuming — often yielding useful data long after it’s time to plan your next campaign.
It can take weeks or even months after a TV ad has aired for audience panels and surveys to record measurable lifts in brand recall, consideration, affinity, and purchase intent. Longer still are changes in market share, or customer acquisition and retention. Keep tabs on this data to prove ROI and optimize spend allocation.
Marketers will often need to use and compare multiple TV measurement models to address their specific business priorities. No matter which approach you take, smart advertisers are focusing on TV outcomes to maximize the impact of their limited budgets.
Advanced attribution models use statistical techniques and machine learning to correlate TV ad exposures with subsequent consumer actions. This gives you intel into the actions a consumer takes shortly after viewing your TV ad — getting you the most clear picture into the mid-funnel customer journey. These models typically incorporate:
Set-top boxes provide a wealth of viewership data at a household level. By partnering with cable or satellite providers, marketers can access anonymized STB data to:
ACR technology embedded in smart TVs can identify what content is being watched in real time, using advanced audio and video fingerprinting to:
MMM is a statistical approach that analyzes the impact of various marketing activities, including TV advertising, on sales and other key metrics. While not TV-specific, MMM can help quantify the overall contribution of TV ads to business outcomes. MMM can be expensive and complex, requiring agencies or teams with analytical knowledge and often large sets of historical data.
Brand lift studies measure the impact of TV advertising on brand metrics such as awareness, consideration, and purchase intent. Although helpful, often these surveys only provide directional guidance with limited information about awareness of a brand and not ad effectiveness. These studies typically involve:
While every TV ad measurement solution has its strengths and limitations, there are several key dimensions every marketer must consider:
Advanced attribution models offer the most accurate view of TV effectiveness, especially when focused on TV outcomes. Set-top box and ACR data provide more precise exposure data than traditional ratings, while MMM can gauge the overall impact of investments. Ideally, your measurement solution should be able to indicate which ads actually lift engagement.
STB and ACR data offer the most granular insights, often down to the household and individual level. Attribution models also provide detailed results, but this depends on audience data partners and identity resolution to track viewers across channels.
ACR and real-time attribution models, like EDO’s Media Monitoring solutions, can provide near-immediate results for TV ad airings. Controlled experiments and brand lift studies often take longer to execute, while MMM models require days (or weeks) for turnaround and a significant historical data period.
Turnkey TV measurement partners can provide instant access to ad performance insights by screen, category, creative, and more. Custom attribution models need more time and are cost-prohibitive for smaller brands.
Real-time attribution models and ACR data provide actionable insights around ad delivery and policy violations, allowing advertisers to optimize on the fly. Experiments or surveys can inform strategic decisions but are less useful for day-to-day optimization. MMM results guide budget allocation but may lack tactical insights.
Whether you’re just getting started with TV advertising, or looking to improve and scale your existing program, there are some rules of thumb that can drive success:
By embracing the best practices for effective tv ad measurement outlined in this article, you're not just tracking numbers – you're unlocking insights that revolutionize your advertising strategy and drive faster business growth. These tools transform your TV marketing campaigns from blind investments into hyper-targeted growth drivers.
Remember, effective measurement is not just about proving ROI — it's about continuously improving your campaigns to meet and exceed your evolving business priorities.
To learn how EDO can help optimize your TV advertising measurement and win share from the competition, schedule a meeting with us today.