When was the last time you paused to gauge the efficacy of your linear TV ad campaign? Some businesses pay for linear TV ads without quantifying the success (or lack thereof) of those forms of outreach. 

Though linear TV ads have been partially supplanted by new opportunities for customer connections through tech innovation, this form of outreach is still highly effective. However, your analysis of ad performance on linear TV is arguably just as important as using the medium as a conduit in the first place. 

Do Your Linear TV Ads Resonate With the Audience?

Take a brief pause to assess the efficacy of your linear TV ads. If your mind jumps to the Nielsen Ratings commonly used to gauge the success of TV ads aired on cable, satellite and traditional TV, you are not alone. However, the Nielsen Ratings are limited to a relatively small sample size that isn’t necessarily reflective of the audience as a whole. Nielsen ads were originally designed for sizable audiences who tuned into a limited amount of TV content. Rewind time back to the 1980s and most homes had merely 20-30 TV channels to pick from.

Times have changed and your strategy should reflect the times to provide accurate insight into the truth about linear TV ad campaign performance. You need and deserve to know how many households are tuned into your linear TV ads. 

Mind the Following Metrics

Linear TV measurement gauges ad campaign success using data as an informative metric. In particular, reach is especially important for understanding linear TV ad campaign performance. Reach is defined as the number of individuals exposed to an ad aired on linear TV. 

Frequency also matters. Frequency is the aggregate number of times that the ad is shown on TV. Reach and frequency are important yet they don’t tell the whole story. What matters most is that your linear TV ads drive traffic and interest in other forms to convert. Conversions are the number of viewers who take the desired action after viewing an ad. 

Engaged viewers are that much more likely to convert so keep tabs on the level of each linear TV ad’s engagement level. Engagement constitutes the amount of time a viewer invests in watching the ad.

Capture Invaluable Audience Insights

Let’s shift our attention to how to best go about tracking the metrics listed above. Tracking viewer data accurately and with regularity empowers you to understand viewer behavior including responses to your ads. The challenge lies in capturing viewer insights for each individual linear TV ad.

One approach is to use data from set-top boxes. Businesses such as Nielsen use such boxes to gauge TV viewership for individual shows, ads and more. Collect and analyze such viewership behavior statistics and you’ll have a better understanding of what the audience is watching, the times when the audience watches and the demographics of the audience itself.

ACR measurement, short for automated content recognition, is a tech tool businesses use to measure audience viewership of specific content aired on linear TV. The analysis of metadata along with related information positions business owners and marketers in the catbird’s seat to better comprehend the behavior of viewers.

There is also the option of forging an alliance with a tech provider. Link up with TV data tech specialists and you’ll have an invaluable opportunity to analyze your linear TV ad viewership data. Moreover, traditional surveys are also worth considering. Web-based behavior tracking combined with data from social media and the aforementioned surveys offers insight into viewer engagement with your linear TV ads.

Optimize Your Linear TV Ads

Now that you’ve collected the data pertaining to your linear TV ads, your challenge is to optimize those ads for additional engagement. Optimizing ads requires the ongoing measurement of engagement levels with current ads. Track the data that is relevant to your ad campaign including but not limited to:

  • Ad ratings
  • Ad viewer demographics
  • The money spent on individual linear TV ads

Such information facilitates the identification of patterns that help you understand the factors that play a role in ad success or failure. This is the data necessary to alter your ad strategy for subsequent campaigns. 

As an example, your ongoing analysis might reveal airing linear TV ads in specific time slots such as primetime on Friday or Saturday nights greatly improves performance. Alter your company’s media buying approach using such data and you’ll succeed in optimizing your ads including their delivery for maximum engagement.


Sumit is a Tech and Gadget freak and loves writing about Android and iOS, his favourite past time is playing video games.

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