Skip to Content Skip to Footer
A Tale of Two Channels: How Digital Ads Perform in AI Recommendation vs. User Subscription Channels on Platforms Like Twitter, Google News, and TikTok

A Tale of Two Channels: How Digital Ads Perform in AI Recommendation vs. User Subscription Channels on Platforms Like Twitter, Google News, and TikTok

Beibei Dong, Mengzhou Zhuang, Eric (Er) Fang and Minxue Huang

How do you get news on a daily basis? Do you subscribe to topics you are interested in? Or do you let artificial intelligence (AI) algorithms recommend news to you? Platforms like Google News, Twitter, and TikTok offer two distinct methods of curating organic content: user subscriptions and AI algorithms.

If, for example, you log into Twitter (now known as “X”) and open the “Following” tab, you will encounter posts from the sources to which you are subscribed. But if you open the “For You” tab, you will see content recommended by AI algorithms based on what AI predicts you are interested in viewing.

These different methods of delivering content provide distinct contexts for in-feed ads. However, little is known about how the performance of in-feed ads compares between subscription and AI-recommendation channels.

In a new Journal of Marketing study, we look into in-feed advertising and examine its performance across these two channels. In-feed ads blend into your news feed, matching the format and style of content while clearly indicating their sponsored status. These ads can take various forms, from text-based ads on Apple News to eye-catching images on Instagram and engaging videos on TikTok. In-feed advertising has seen significant growth, with 58.3% of U.S. digital display spending allocated to these ads in 2018.


In-feed ads ideally fit seamlessly into the organic content stream, and their effectiveness is determined by both the ads’ attributes and where they are placed. Our research team examined how each channel affects ad effectiveness and whether the effects also depend on ad attributes. We considered two core digital ad attributes:

  • Ad appeal that describes key content of the ad, which can either be informational (focusing on factual product information) or emotional (emphasizing the product experience through subtle feelings)
  • An ad link that leads to consumer action, which can be direct (e.g., “buy now”) or indirect (e.g., “click for more information”)

Channel Difference and Consumer Engagement

The manner in which content is delivered (through subscription or recommendation) has a big impact on how customers engage with that content. This, in turn, can determine whether they view in-feed ads as intrusive and if they decide to click on the ads and make purchases.

We find that subscription and recommendation channels have two key differences: source credibility and content control. Subscription channels have greater source credibility and more content control because consumers can actively choose their sources, motivating them to exert greater cognitive effort in processing content. In contrast, AI-recommended content may be perceived as less credible, and reliance on algorithms reduces consumers’ motivation to exert cognitive effort, leading to lower engagement.

Ad Intrusiveness and Ad Performance

In the subscription channel, high customer engagement with the organic content makes readers more goal-oriented, and they thus end up perceiving ads as more annoying and interruptive. However, customers who do click on an ad, despite the annoyance, show stronger interest and a higher conversion rate. By contrast, in the recommendation channel, customers are in an exploratory state and thus perceive ads as less intrusive. Consequently, customers are more inclined to click on ads in the recommendation channel.

We use two ad performance metrics for our analysis: click-through rate (CTR), the ratio of clicks to exposures, and the conversion rate (CR), the ratio of purchases to clicks. In the subscription channel, higher ad intrusiveness leads to lower CTRs but higher CRs, while in the recommendation channel, lower ad intrusiveness may generate higher CTRs, but the proportion of genuine interest and subsequent purchases is smaller. Therefore, in addressing which channel has better ad performance, we show that the recommendation channel underperforms the subscription channel in converting sales but excels at eliciting clicks.

Takeaways for CMOs

Our study offers key lessons for Chief Marketing Officers:

  • If the goal is to convert ads to sales, companies should strive for high conversion rates. Conversely, if the goal is to drive traffic and generate interest, companies should strive for high click-through rates.
  • If advertisers’ goal is to maximize click-through rates, the optimal strategy is to release emotional ads with indirect links for both the subscription channel and the recommendation channel. Conversely, if advertisers want to maximize conversion rates, informational ads with indirect links work best for the subscription channel while emotional ads with indirect links are the best for the recommendation channel.
  • For recommendation channels, informational ads with direct links have the largest increase in click-through rates and the largest decrease in conversion rates. By contrast, emotional ads with indirect links have the largest decrease in click-through rates and the largest increase in conversion rates.

Read the Full Study for Complete Details

From: Beibei Dong, Mengzhou Zhuang, Eric (Er) Fang, and Minxue Huang, “Tales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels,” Journal of Marketing.

Go to the Journal of Marketing

Beibei Dong is Associate Professor of Marketing, Lehigh University, USA.  

Mengzhou Zhuang is Assistant Professor of Marketing, University of Hong Kong, Hong Kong.  

Eric (Er) Fang is Professor of Marketing, Iacocca Chair of Business, and Director of Center of Digital Marketing Strategy and Analytics, Lehigh University, USA.

Minxue Huang is Professor of Marketing, Wuhan University, China.