This session focused on two major themes: 1. A new paper arguing that marketers frequently misuse ROI when making allocation decisions from MMMs and 2. A discussion about how AI is beginning to influence MMM workflows and marketing analytics more broadly.
Content repetition is a foundational principle in advertising, yet marketers frequently face the decision of whether to reinforce a single message or rotate multiple creative variations.
In this webinar, we present causal evidence from a large-scale field experiment examining when repetition strengthens performance and when content variation delivers greater impact. Join us to gain actionable insights on how to optimize ad content decisions to improve engagement, conversion, and overall marketing effectiveness.
How much do your ads really drive results? Measuring true incrementality, the causal impact of ads on conversions, remains one of the toughest challenges in digital marketing. While experiments are a reliable way to establish causal impact, they can come with costs and tradeoffs.
In this webinar, we explore new research on how advertisers and platforms make experimentation decisions—and why some firms choose not to test at all. You’ll gain practical insights on when experimentation pays off, how platform dynamics shape outcomes, and what it means for improving marketing ROI.
Content repetition is a foundational principle in advertising, yet marketers frequently face the decision of whether to reinforce a single message or rotate multiple creative variations.
In this webinar, we present causal evidence from a large-scale field experiment examining when repetition strengthens performance and when content variation delivers greater impact. Join us to gain actionable insights on how to optimize ad content decisions to improve engagement, conversion, and overall marketing effectiveness.
How much do your ads really drive results? Measuring true incrementality, the causal impact of ads on conversions, remains one of the toughest challenges in digital marketing. While experiments are a reliable way to establish causal impact, they can come with costs and tradeoffs.
In this webinar, we explore new research on how advertisers and platforms make experimentation decisions—and why some firms choose not to test at all. You’ll gain practical insights on when experimentation pays off, how platform dynamics shape outcomes, and what it means for improving marketing ROI.
MSI and ARF members discussed how AI, changing buyer behavior, and evolving relationship dynamics are affecting today’s B2B marketing and sales. The conversation highlighted a growing paradox: while AI is accelerating information access and automating parts of the buying process, B2B decisions are becoming more complex, more relationship-driven, and harder for sellers to influence early.
Random controlled trials (RCTs) can assess causal effects of marketing but are expensive and incur opportunity costs by excluding control groups. Predicted Incrementality by Experimentation (PIE) uses samples of RCT-run campaigns to determine which characteristics map to causal outcomes and then applies that mapping to campaigns not run as RCTs.
Predicted Incrementality by Experimentation (PIE) uses samples of RCT-run campaigns to determine which metrics map to causal outcomes and then applies that mapping to campaigns not run as RCTs, resulting in accurate predictions of advertising effects.