Measuring Signal
Can Anyone Hear Me? . . . . How to measure and verify campaign signal to make informed decisions.
Measuring results in the realms of Linear TV and CTV continues to be challenging. And before I hear you audibly sigh, you’re right: this isn’t a new topic. Nonetheless discussions around first-touch, last-touch, and multi-touch attribution remain prevalent, especially in how each model assigns value to interactions. In marketing, these models offer insights into which touchpoints significantly influence conversions, but they fail to provide a comprehensive view of the picture.
Without a true, deterministic, read, we turn to statistical testing to better understand the outcomes of our “experiment.” In other words, we need to transform a “hunch” into a data-driven insight.
There’s no denying that media mix modeling provides a comprehensive view, but it often involves considerable data history, costs and effort. Before investing large amounts of money, marketers can investigate several methods to measure and verify signals, allowing for faster and more accurate optimization.
So how do we verify these signals?
Like any great experiment, we need to test our hypothesis to determine the causal impact of the advertising efforts with a large percentage of confidence.
Geo based experiments such as a match market studies/ incrementality testing can be implemented to assess the effectiveness of TV and CTV advertising. In this scenario, we compare the key performance indicators of a test group with the counterfactual predictions derived from the control group. This research-based method helps to isolate and measure the impact of TV advertising on various outcomes, such as sessions, new-users, orders, revenue and brand awareness.
Specifically relevant to CTV and digital campaigns, conversion lift studies aim to measure the impact of advertising on user behavior by comparing the behavior of exposed and non-exposed groups to quantify the causal effect.
Last but not least, let’s not overlook brand lift studies, which are not limited to linear TV; CTV now provides the capability to measure brand lift as well. With CTV advertising becoming a major investment for many brands, measuring its overall effectiveness poses similar challenges. By collecting data on consumer exposure to a campaign and then administering survey questions in the same environment, we can assess brand awareness, consideration, preference, and intent.
What is the right solution for you?
The solution needs to align with the goals, strategy, and data available for each campaign. What’s clear is that, in the absence of signal accuracy, statistical models can offer a more nuanced understanding of touchpoint effectiveness, facilitating quicker, data-driven optimizations.
So, my fellow marketers, have you figured it out yet? Contact us today!
Nicky de la Salle is the Vice President of Growth at DirectAvenue. With more than 20 years of experience, including a decade at a “Big 6” global agency, in performance marketing and growth strategy, she is a proven senior leader with specializations in omni-channel marketing, eCommerce and digital marketing channels. Nicky has driven the performance marketing vision for Fortune 500, Entrepreneurs and Tech-Disrupters alike both in the US and internationally.
#economicoutlook #advertising #brandlift #goals #strategy #economy #ctv #datahistory #brandawareness #directavenue #tvconsumption #viewershiptrends #advertising #brandresponse #performancemarketing #performanceadvertising #economicenvironment #brandpresence #campaign #precisiontargeting #audienceresponse #lineartv #optimizations #solutions #effectiveness #attribution #campaign #signalanalysis
