As a young company, TV advertising was a high priority for GoodRx in order to reach healthcare consumers. Kicking off its TV-marketing program, the company worked with an independent media buyer that had its own analytics platform.
Several months into its campaign, GoodRx realized that the basic lift measurements provided were not granular enough to make decisions around where and when to spend on TV. Each time GoodRx wanted to see data in a different dimension or look back at additional attributes, a full rerun of the analytics was required. Additionally, the team at GoodRx was not confident in the media buyer’s custom-designed analytics since there was no way to verify the information.
After learning about TVSquared, Scott Marlette, the co-founder of GoodRx, contacted the company to learn more about its ADvantage platform. TVSquared’s state-of-the-art analytics platform provides same-day insights the who, what, when and where on TV-ad campaigns, helping users better target customers and increase sales.
According to Marlette, he knew TVSquared was a fit as soon as he sat through a demo of ADvantage.
Today, GoodRx regularly uses TVSquared to optimize network, daypart and creative mix strategies for TV advertising. And, above all else, it has gained the confidence in the analytics presented by its media buyer by cross-referencing the data with TVSquared.
Recently, GoodRx was able to pull its aggregate network performance over the entire first part of the year to use as a guide in other offline channels. Before working with TVSquared, this would have required a team member to go back and run through all of the previous data to get the full average. With TVSquared, it took only a few minutes.
The newfound confidence in TV-attribution analytics led to the decision to double GoodRx’s marketing spend over time.
I saw how simple the analytics were presented and how easily I could drill down to different segments of our spend. In particular, the ability to drive down into an individual airing allowed for us to validate the lift data.