Find the latest and most impactful research on the measurement of marketing ROI and attribution here. All the research listed comes from the ARF or one of its subsidiaries: The Journal of Advertising Research (JAR), the Marketing Science Institute (MSI) or the Coalition for Innovative Media Measurement (CIMM). Feel free to bookmark this page, as it will be updated periodically.

MSI: Is Big Brother (or Little Sister) Watching – And Does it Matter?

Who is really watching that TV ad and how does doing so affect their behavior? Analyzing attention in real-time demonstrates the value of TV ads. Attention studies are especially important now with the rapid growth of streaming video on demand (SVOD) and other alternatives. Their rise has heightened the importance of determining what and where audiences are viewing and how that’s impacting their behavior.  Read the article.

JAR: Modeling Cultural Mindsets with Endorser Origins to Predict Brand Attitudes

An endorser’s native origin can trigger brand reactions in consumers due to their cultural predispositions. New research in this area has revisited ethnocentrism and xenocentrism, not as diametrically opposed mindsets but as ones coexisting in dynamic configurations, with each mindset expressed or suppressed as a result of origin cues from brands and endorsers. The resulting models provide blueprints for predicting favorable attitudes, by aligning targeting and messaging strategies with appropriate mindsets and origin cues.  Read the article.

JAR: What’s the Best Format for “Supers” in DTC TV Ads?

In a study on formatting characteristics in direct-to-consumer, prescription-drug advertising, the adage ”God is in the details” rings loud and true. TV and online video ads use superimposed text to convey additional information about a drug’s risks and benefits. But, researchers asked, how much can details like text size and contrast affect awareness and attitudes?

View article.

MSI: Generalizable and Robust TV Advertising Effects

Studies the effect of advertising on sales by pre-selecting 288 brands in Nielsen Scanner data (RMS) and in Nielsen advertising data (Ad Intel); estimates the causal impact of advertising on sales, adjusting for confounding factors using “baseline” and “border” identification strategies.

Read the working paper.

KaH: Oracle Data Cloud Tackles Audience Quality

In 2018, $57 billion was spent on digital display advertising. That doesn’t mean those resources were used wisely. One crucial issue is the need to focus on audience quality. Failure to do so can lead to consumers being buffeted with messages or confronted with irrelevant ones. As a result, they become frustrated and turned off. This equates to missed opportunities and wasted resources. Read More

JAR: Analyzing the Click Path of Affiliate-Marketing Campaigns

Online service providers increasingly use multiple channels for their advertising. Within that universe, an affiliate—usually a small, private company or individual maintaining a website or blog—informs others about a product or service sold by a partnering company (a merchant). This study found that the merchant’s simultaneous use of search-engine advertising, however, “cannibalizes clicks and sales in the click path.” As a result, “affiliates must use different text links to ensure positive impacts on clicks and sales in their affiliate-marketing campaign.”

Read the JAR article.

JAR: Attribution Modeling in Digital Advertising

How do different sales channels impact the consumer’s journey to purchase behavior? In this article, researchers compare and contrast four different attribution models: last-click, time-decay, uniformly distributed, and position-based. Given that different online channels are involved at different stages of the consumer’s purchase journey, they write, it is important to examine the ability of these models to properly attribute credits to the various channels that have an impact upon the final purchase.

Read the JAR article.

MSI: A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook

Are observational methods using good individual-level data “good enough” for ad measurement? Using data from 15 U.S. ad experiments at Facebook, this study showed that current matching and regression-based methods overestimated effectiveness relative to the randomized controlled trials. In half of studies, the estimated percentage increase in purchase outcomes was off by a factor of three across all methods.

Read the working paper.