New research finds brands that leverage a reputation for quality to pay employees less risk eroding profits.

The paper, published in the Journal of Marketing Research and authored by researchers from Duke University, London Business School and Texas A&M University, shows that vertical brand differentiation (being perceived as better) is associated with lower pay, whereas horizontal brand differentiation (being perceived as different) is associated with higher pay.

High-quality brands taking advantage of brand cachet to pay employees less erodes profits due to negative effects on employee productivity and retention. More unique brands which tend to pay more, on the other hand, yield a net positive effect on profits due to positive effects on the same employee behaviors.

“High-end brands, which are known for their quality and heritage of excellence, find it easier to attract employees who want the résumé boost of working for a well-known brand,” said Christine Moorman, Professor of Business Administration at Duke’s Fuqua School of Business. “Experiments undertaken during our study show that Human Resource managers believe, and employees agree that, on average, they will accept lower pay for such benefits.”

“More unique, lesser-known brands don’t have the same résumé cachet,” Moorman said. “Managers believe, and job candidates agree, that they require higher pay to work for these unique brands as such employment does not convey the same résumé power in securing future jobs.”  

Critically, these differential brand-pay relationships have important downstream effects on employee behavior and, consequently, on firms’ profits.

Nader Tavassoli, Professor of Marking at London Business School explained: “Taking advantage of high-quality brand cachet to lower pay represents a false economy because profits are diminished by negative effects on employee productivity and retention. Pay dissatisfaction can lead to people working less hard or leaving, ultimately costing companies money. Managers should, therefore, rely on brand reputation to attract talent, but not leverage it to suppress pay.”

“Higher pay can be motivating as employees exert extra effort, thereby driving up productivity and profits,” added Alina Sorescu, Professor of Marketing at Mays Business School, Texas A&M University.

“As Henry Ford once said, ‘Paying good wages is not charity at all, it is the best kind of business,'” Sorescu said. “This is borne out by our findings, which show that when managers at more unique firms pay more, profits increase.”

Given these dynamics, the researchers recommend that managers should consider brand differentiation in their pay benchmarking:

• Consider your brand in setting pay, as your brand’s perceived quality and uniqueness have opposing pressures on employee pay.
• Leverage your brand’s perceived quality to attract talent but not to pay less, as this results in a net profit loss due to negative effects on employee productivity and retention.
• Take a benign view of paying employees more based on your brand’s perceived uniqueness, as this results in a net profit gain due to positive effects on employee productivity and retention.
• Adjust your competitive pay benchmarking based on relative levels of both vertical and horizontal brand differentiation.
• Have marketing and HR work together to compete effectively in the war for the “right” talent.

“Brands in the Labor Market: How Vertical and Horizontal Brand Differentiation Impact Pay and Profits Through Employee-Brand Matching” by Christine Moorman, Alina Sorescu and Nader T. Tavassoli appeared in the Journal of Marketing Research.

Researchers from Yale University and University of Southern California published a new Journal of Marketing study that synthesizes and evaluates over 50 studies conducted over four decades to determine when mental simulation prompts heighten consumers’ purchases.

The study, forthcoming in the Journal of Marketing, is titled “From Mentally Doing to Actually Doing: A Meta-Analysis of Induced Positive Consumption Simulations” and is authored by Gizem Ceylan, Kristin Diehl, and Wendy Wood.

Enticing people to buy a juicy burger or the new Apple Vision Pro spatial headset computer can involve the same marketing approach: prompting consumers to mentally simulate future purchases or consumption.

Marketers often prompt mental simulations via visuals or via verbal calls to action. For example, restaurants try to entice patrons with mouthwatering photos on their Instagram accounts or menus. The Apple Vision Pro launch video shows people using the new headset computer in a hope that consumers will simulate how they would use the device. A commercial for EasyJet, a leading European airline, asks people to “Imagine Where We Can Take You” along with visuals of flying over clouds and of different holiday locations from beaches to cities.

The question is: How effective are these mental simulations? Mental simulation has been shown to improve action readiness and is thus used in advertisements and other communications to facilitate purchase and consumption. “However,” note the researchers, “although some studies have noted positive influences on behavioral intentions and behavior, others have found minimal or even negative effects. It is difficult to interpret these findings given how the modality of simulation, frequency of induction, type of consumption experience, and target populations vary widely in research and practice.”

Behavioral Impact

This new Journal of Marketing study synthesizes and evaluates over 50 studies conducted over four decades (from 1980 to 2020) to analyze when mental simulation prompts heighten consumers’ purchases. It produces several important findings for the industry:

1. Mental simulation increases behavioral responses; however, the average effect is small, suggesting that, while mental simulation works in general, marketers must identify ways to strengthen its impact.
2. The study identifies more powerful mental simulation prompts—such as dynamic visuals with augmented reality (AR) or 360-degree videos, along with verbal instructions to go along with visuals—and guides marketers how to use such interactive media.
3. The frequency and spacing of the mental simulation determines its effect on consumer behavior and we offer guidance to managers for effective ad planning and delivery. For example, when marketers place the same message across different platforms, consumers may be exposed to the same content over and over again within a single episode of mental simulation. In addition to repetition being annoying in general, mass repetition is not just ineffective but it also reduces consumption, likely due to habituation.
4. Simulation has limited impact on behavior in online samples in which participants may not be sufficiently motivated to engage in mental simulation.

“While mental simulation inductions are a common approach found across many industries and product categories, our systematic, large-scale analysis suggests that marketers should carefully consider the right approach, context, and frequency of prompting mental simulations,” the researchers say.

Real-World Implications

This study offers the following lessons for Chief Marketing Officers:

• Using more interactive and engaging simulation prompts, such as 360-degree videos and AR tools, are especially effective in increasing behaviors. Investing in such technologies and approaches could be particularly important for companies that rely on consumers simulating a future experience or outcome.
• Some existing technologies and channels—such as animated graphics and email marketing—can be leveraged for simulation-based communications. Luxury brands already employ unboxing videos on TikTok and Instagram to stimulate viewers’ imagination and influence their future purchases.
• Marketers must consider combining visual and verbal prompts. For instance, in the case of online reviews, consumers find it easier to process the review when the photo and text convey similar aspects of one’s experience, which, in turn, increases the review’s perceived helpfulness.
• For marketers employing mental simulation in their campaigns, controlling, especially limiting, daily exposure is particularly important. For instance, Hulu has taken steps to ensure its viewers can encounter the same commercial only twice per hour, four times per day, or 25 times per week. Platforms such as Facebook and Instagram now allow marketers to place limits on daily or weekly exposure, which we recommend should be set even lower than those employed by Hulu.
• The online studies yielded nonsignificant results as opposed to in-person studies, which produced significant effects. Mental simulation prompts were ineffective for online respondents, possibly because they were not sufficiently involved or engaged in the simulation process. This finding may be particularly alarming for managers because a large chunk of advertising spending is on TV and digital channels that may be consumed during distracting activities and can lead to active disengagement from ads. As a workaround, ads that include mental simulation may better fit into channels in which consumers initiate the marketing activity, such as search ads that ensure greater consumer attention and engagement based on declared interests.

Researchers from Lehigh University, University of Hong Kong, and Wuhan University published a new Journal of Marketing article that examines in-feed advertising’s performance across subscription versus AI recommended news feeds.

The study, forthcoming in the Journal of Marketing, is titled “Tales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels” and is authored by Beibei Dong, Mengzhou Zhuang, Eric (Er) Fang, and Minxue Huang.

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

The authors explain that “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. We examine how the channel affects ad effectiveness and whether the effects also depend on ad attributes.”

They consider 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,” the researchers claim.

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.

The study uses two ad performance metrics for 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. “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,” says the research team.

Takeaways for CMOs

The 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.