scheduling/flighting

  • Article

ARF KC Key Takeaways: Media Planning & Lift Benchmarks

A review of the available research on media planning best practices did not reveal any published benchmarks or empirical generalizations on which specific media planning executions drove lifts in specific brand metrics. In addition, many different studies and research were not always aligned on specific guidelines or recommendations, which may be due to different research methodologies, objectives and executions. A number of studies also noted that there were too many different factors at play to determine the best media planning execution for every or most brands, and they called for custom researching what would best suit the specific brand or campaign. While this report is not prescriptive, it includes general, directional guidance.

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  • Article

Leveraging Large-Scale Granular Single-Source Data for TV Advertising

Rex Du (University of Texas at Austin) introduced a method to estimate the causal impact of linear TV advertising using large-scale, single-source data that links household-level TV viewing and ad exposure to daily purchase behavior. The methodology leveraged viewing data from a smart TV panel of 1.4 million households over four and a half months, matched with first-party CRM purchase data for an online food delivery brand. Linear TV ad exposure is influenced by which shows the brand buys, what each viewer watches, and how networks schedule the ads, leading to targeting and activity biases that can inflate the perceived ad effectiveness. To correct for these biases, the network’s within-show ad placement was treated as a quasi-random process, and an expected exposure metric (the fraction of ads a viewer watched in a targeted show) was introduced as an instrumental variable. Including this bias-correction variable in the response model significantly reduced the overestimation of an ad’s impact, lowering the estimated sales lift per TV ad exposure from 7.5% to 4.6%. Validation over six years confirmed that this one-variable correction approach effectively isolates the causal effect of TV ads. The results demonstrated that baseline purchase propensity and ad responsiveness vary systematically with both the frequency and recency of past purchases.

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Inside the Journal of Advertising Research: What Drives Ad Engagement: From AI and Skippable Ads to Life Transitions

Inside the Journal of Advertising Research: What Drives Ad Engagement: From AI and Skippable Ads to Life Transitions

  • ARF
  • JAR INSIGHTS STUDIOS

On December 11, we highlighted three new articles from the Journal of Advertising Research on how emotion, control, and context shape the evolving dynamics of ad effectiveness in the digital age. Across sessions, speakers emphasized that consumer engagement is shaped not just by creative content, but by emotional responses, timing, predictability, and personal context. The discussion underscored the importance of designing advertising strategies that balance attention capture with trust, comfort, and long-term effectiveness.

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Augmented Reality – Unlock New Technology to Drive Brand Growth

Augmented Reality – Unlock New Technology to Drive Brand Growth

Aarti Bhaskaran – Global Head of Research & Insights, Snap

Kara Louis – Group Research Manager, Snap

Aarti Bhaskaran and Kara Louis of Snap presented their amalgamation of work on augmented reality (AR) with key data and client case studies from the last two years. Showcasing the growth of the AR landscape, Aarti and Kara featured how consumers are gravitating towards AR and the expanding number of opportunities available for advertisers in reaching new audiences and utilizing within the media mix. Case studies include brands using AR try-on technology from Champs Sports and Clearly eyeglasses. Key takeaways:
  • AR usage is widespread and growing, from Boomers to GenZ. By the year 2025 there will be approximately 4.3 billion AR users across all generations.
  • Almost all marketers (91%) think consumers use AR for fun, but 67% of consumers prefer using AR for shopping over fun (53%).
  • Interacting with products that have AR experiences leads to a 94% higher purchase conversion rate, as individuals can better assess them and feel connected with brands. Certain AR applications can substitute physical shopping with different features varying across the customer journey.
  • Interactive and personalized shopping experiences reach Gen Z—92% are interested in using AR for shopping, with over half of Gen Z saying they’d be more likely to pay attention to ads using AR. Gen Zs are also twice as likely to buy items that they have experienced first using AR than those who don’t.
  • AR lenses on Snapchat outperformed all other media formats. Other platforms would need 14-20 ads to generate the same level of attention as Snapchat lenses.
  • AR not only drives short-term impact with higher purchase intent and brand preference, but it also improves brand opinion, influences implicit associations and increases likelihood to purchase and recommend.
  • The creative attributes that include logo and product branding, complexity, messaging and user experience show a significant relationship with AR performance in brand lift.

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