Cancer Treatment Centers of America® (CTCA) is a national, comprehensive cancer care network with three hospitals across the United States. It’s founded on the idea of personalized cancer care, where every patient gets a unique combination of treatments tailored to their needs.

CTCA has historically used an audience-based buying strategy in linear TV to spread awareness of their groundbreaking cancer treatment centers and innovative treatment technology. However, they struggled to quantify the effectiveness of these campaigns and attribute patient acquisition to the channel. Linear TV has always been a critical way to reach patients and gain awareness, but CTCA wanted to prove its effectiveness and optimize campaigns to improve marketing efficiency. Causal impacts and lift analyses only gave directional performance for how the media performed across different designated marketing areas (DMA). CTCA wanted attribution for every single TV spot, which would power campaign optimization at the spot level to improve the effectiveness and efficiency of linear TV’s patient acquisition strategy.

Merkle leveraged TV post-logs as well as Google Analytics 360 (GA360) and call center data to train a machine learning model for each DMA where CTCA was airing broadcast or cable. For each session and call, the model produced an estimated likelihood that the event was driven by TV, based on the proximity of the event to spot airing time, historical volume of events for that specific time of day, DMA, and audience size. Utilizing Merkle’s Merkury identity resolution solutions, the event logs were connected with CTCA’s first-party data, providing an integrated view of the patient journey across offline and online touchpoints. This unified view led to an overall estimate of the contribution of TV to the journey and the lead’s progression throughout the funnel.