{"id":19340,"date":"2021-10-28T15:08:00","date_gmt":"2021-10-28T22:08:00","guid":{"rendered":"https:\/\/www.ispot.tv\/hub\/?post_type=ispot_case_studies&p=19340"},"modified":"2025-02-26T10:25:06","modified_gmt":"2025-02-26T18:25:06","slug":"understanding-the-true-lift-of-tvdraft","status":"publish","type":"ispot_case_studies","link":"https:\/\/www.ispot.tv\/hub\/resources\/case-studies\/understanding-the-true-lift-of-tvdraft\/","title":{"rendered":"Understanding the True Lift of TV"},"content":{"rendered":"\n

Executive Summary <\/strong><\/p>\n\n\n\n

TripAdvisor needed to understand which TV networks generate the most incremental revenue per advertising dollar. The results were eye-opening. Through an iSpot lift analysis comparing ad-exposed households with similar unexposed ones, TripAdvisor pinpointed networks where viewers converted due to ad exposure. This approach enabled TripAdvisor to optimize its TV spend, targeting audiences with a higher likelihood of incremental conversions, resulting in a stronger return on investment.<\/p>\n\n\n\n

Problem<\/strong><\/p>\n\n\n\n

When TripAdvisor started advertising on television, the travel website faced two obstacles \u2013 it needed to attribute user visits and behavior to TV ads and know where its TV ads were most effective.<\/p>\n\n\n\n

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Solution<\/strong><\/p>\n\n\n\n

To overcome these obstacles, TripAdvisor and iSpot joined forces to estimate the causal impact of TV advertising, separating TV viewers that would have come to the site anyway from those truly impacted by TripAdvisor\u2019s TV ads. Doing this allowed TripAdvisor to understand where its messaging was having the most impact.<\/p>\n<\/div>\n\n\n\n

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Results<\/strong><\/p>\n\n\n\n

TripAdvisor found that many TV networks with seemingly high conversion rates also had high baselines. In other words, people who watch these networks would have converted even if they did not see a TripAdvisor TV ad on the network. TripAdvisor reconfigured its television buys to target networks where TV spots didn\u2019t just correlate with, but actually caused conversions. This allowed them to see a higher ROI on their ad spend and identify untapped audiences.<\/p>\n\n\n\n

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\u201c<\/em><\/strong><\/em><\/strong><\/em><\/strong>Working in close collaboration with iSpot, we were able to develop a statistically defensible baseline. In short, we compare people exposed to our TV ads with nearly identical people who were not exposed. Differences in user behavior after the ad can be attributed to TV.\u201d<\/strong><\/em><\/p>\nTim D\u2019Auria, Head of TV Optimization<\/em>, TripAdvisor<\/cite><\/blockquote>\n\n\n\n

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Deeper Dive<\/strong><\/p>\n\n\n\n

TripAdvisor is the world\u2019s largest travel site with 456 million average monthly unique visitors. One of the company\u2019s core beliefs is, \u201cIf It\u2019s Worth Doing, It\u2019s Worth Measuring.\u201d At TripAdvisor, this belief applies no differently to television advertising which is notoriously hard to measure. The two questions the TripAdvisor team sought to answer were: what is the incremental value of television advertising to the top-line and which specific TV buys yield the most value? The company had tried many techniques to answer these questions \u2014from time-series analysis and paired market testing to econometric modeling but nothing was giving them the deep insight they were seeking. TripAdvisor\u2019s challenge to iSpot was to help them optimize their TV spend to align with the causal effects of television. Which networks have an abundance of viewers who would have converted without ever seeing a TripAdvisor commercial and which networks have viewers who converted because they\u2019d seen a TripAdvisor spot?<\/p>\n\n\n\n

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\u201c<\/em><\/strong><\/em><\/strong><\/em><\/strong>Just knowing that a viewer saw our TV ad and came to our site didn\u2019t cut it. We wanted to know what would have happened had that same viewer not seen our ad. This insight enabled us to assess the incremental value of TV across networks.\u201d<\/strong><\/em><\/p>\nTim D\u2019Auria, Head of TV Optimization<\/em>, TripAdvisor<\/cite><\/blockquote>\n<\/blockquote>\n\n\n\n

iSpot and TripAdvisor data scientists worked together to conduct a lift analysis by identifying and comparing near-identical unexposed households for each TV ad-exposed household. Households were matched based on a large number of features that included metrics like the amount of time a household spent watching TV, a profile of networks consumed by the household, the particular kinds of programming watched, consumption of competitive advertising, and more. iSpot then ran tests to compare the conversion rates for viewers who were exposed to TripAdvisor spots and those who were not. What we discovered was that, for some networks, exposure to TripAdvisor TV commercials had minimal impact on conversion levels\u2014there were similarly high levels of conversion among near-identical households who watch the network but had not seen any TripAdvisor TV commercials. For other networks, the difference was substantial, indicating that exposure to TripAdvisor TV commercials on these networks were causing, not just correlating with, conversions on the site. Thus, it made sense for TripAdvisor to spend more money against the latter group, where the potential for impact was higher.<\/p>\n\n\n\n