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When consumers feel intimidated by too many features in a product, highlight their user-friendliness

People were more likely to buy a product if they thought it would be both capable and usable.

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Wifi-enabled washing machines. Voice-controlled microwaves. App-enabled TVs, vacuum cleaners, and even window blinds you can control from the comfort of your couch.

Many of the technological features now included in everyday products are useful and accessible. But research has shown that having too many can overwhelm potential buyers, making them less likely to make a purchase.

In new research, Wayne Hoyer, marketing professor and James L. Bayless/William S. Farrish Fund Chair for Free Enterprise at Texas McCombs, digs into the phenomenon of “feature creep” and its impact on consumer sentiment. His findings might help companies strike the right balance as they design new products — or more effectively market ones that are feature-rich.

“Traditionally, marketers and researchers addressing the topic of product complexity have only looked at the number of features,” Hoyer says. He and co-researchers Andreas Fürst and Nina Pecornik, both of the Universität of Erlangen-Nürnberg in Germany, examined not only the number of features but also the relationships among them.

The team looked at two very different dimensions of complexity in a consumer tech product.

  • Heterogeneity: how similar or dissimilar the features are. A highly heterogeneous product would be a smart home system that controls dissimilar features, such as floor heating, the refrigerator and television.
  • Interrelatedness: how functionally connected they are, as with a smart home system that automatically closes the blinds and fires up the audio system when the television gets turned on.

How do each of these dimensions affect consumers’ expectations about how capably a product will perform and how easy it will be to use — and thus, how likely they will be to buy it?

To find out, the researchers asked a total of 1,300 people in four experiments to evaluate and rank two different types of products — smart home systems and smartphones — under various scenarios. They ranked each product on a scale from 1 to 7, with 1 representing the lowest or least favorable response. They also ranked their purchase intentions.

Unsurprisingly, the team found that the participants were more likely to buy a product if they thought it would be both capable and usable. But several factors influenced those judgments:

More useful but less user-friendly. The more features a product had, the more consumers expected it to be capable — but the less they expected it to be easy to use.

More complex, less usable. The less similar and the more interrelated the features were, the harder consumers thought a product would be to operate.

For example, participants in the smart home group ranked rated usability at 3.56 when a system had a lot of features that were not very alike. That ranking improved to 4.13 when the features were very similar. The effect was true for smartphones, as well.

Related features, better performance. When features were highly interrelated, consumers expected a product to be more capable. High levels of heterogeneity, on the other hand, had the opposite effect.

The reason, a separate experiment found, is that they don’t trust that products with highly dissimilar features will perform as promised.

“The number of product features is still very important,” Hoyer says. “Marketers just also need to consider heterogeneity and interrelatedness. Our research clearly shows that these two dimensions are very important in determining product complexity and how that affects the consumer.”

The big takeaway for companies and marketers, he says, is that they can boost sales by emphasizing that a product’s features are interrelated, thereby promoting expectations that it will work well. They should deemphasize dissimilar features, so that consumers don’t think the product will be hard to operate.

As for product developers, they should temper the desire to add as many new features as possible by ensuring that those features have plenty of functional connectivity that adds value for the consumer. Says Hoyer, “It’s not really that tricky.”

How Product Complexity Affects Consumer Adoption of New Products: The Role of Feature Heterogeneity and Interrelatedness” is published in the Journal of the Academy of Marketing Science.

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Nostalgia is an asset in company acquisitions, so use it

Tailor nostalgia interventions to different employee categories. Workers with knowledge critical to a company’s value benefit most from identity-based interventions, while “cultural carriers” can help bridge old and new organizational cultures through relationship-focused strategies.

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When companies are acquired, conventional wisdom suggests that employee nostalgia for their pre-buyout days is a problem to be eliminated so workers can more quickly adapt to the new owners’ ways of doing business.

A study published in the journal Strategic Organization led by UC Riverside School of Business professors Boris Maciejovsky and Jerayr Haleblian suggests this thinking is wrong—especially when the new owners want to retain the most talented, productive, and informed workers.

Nostalgia, they found, serves as a comforting and stabilizing force during takeover periods, when employees feel vulnerable, fear losing their jobs, status, or advancement opportunities, and are thus inclined to send out résumés.

“Rather than viewing nostalgia as living in the past, we demonstrate how it serves as a bridge between employees’ pre-acquisition identity and their post-acquisition reality,” explained Haleblian, the business school’s Anderson Presidential Chair in Business. “This temporal bridging is crucial for maintaining organizational commitment during transitions.”

Drawing from psychology research in emotion regulation, social identity, narrative identity, and attachment theories, the study shows nostalgia isn’t mere sentimentality—it’s a powerful tool that helps preserve identity and meaning during disruptive times, said Maciejovsky, an associate professor of management.

“We challenge the prevailing view that nostalgic emotions are maladaptive responses to change,” Maciejovsky said. “Our research shows that nostalgia can transform negative reactions into positive outcomes, thereby mitigating the talent loss that often jeopardizes acquisition success.”

For employees, nostalgia is often triggered by the upheaval of a corporate acquisition that replaces familiar leadership with unfamiliar faces. By understanding these emotions, the authors argue, managers can see that longing for the past is not resistance but a desire to preserve meaning and identity.

The implications are significant in today’s business climate, where acquisitions of startup companies to gain talent and innovations are commonplace—especially in the tech sector, where the strategy is called “acqui-hiring.” Yet retention is poor: in the U.S., 47% of key employees leave within the first year of an acquisition, and 75% within three years, creating a human capital gap that can reduce company value by 10–15%, according to Mentorloop.com.

The study provides practical guidance for managers, outlining two main approaches to support employees during acquisitions. The first involves identity-preserving interventions, such as maintaining familiar company symbols like names, logos, workspaces, and practices. It also includes honoring historical narratives that connect current practices to valued traditions, while ensuring that the missions of the acquiring and acquired companies remain carefully aligned. 

The second approach centers on relationship-focused interventions, which emphasize building strong connections among employees through team-building activities, heritage celebrations, and shared experiences that foster a sense of social connection.

“Companies like American Airlines have successfully used heritage celebrations, featuring paint schemes from acquired airlines like TWA, to honor predecessor companies while facilitating integration,” Maciejovsky said. “These aren’t just feel-good gestures—they’re strategic interventions that tap into nostalgia’s regulatory benefits.”

The study emphasizes tailoring nostalgia interventions to different employee categories. Workers with knowledge critical to a company’s value benefit most from identity-based interventions, while “cultural carriers” can help bridge old and new organizational cultures through relationship-focused strategies.

The study, titled How Nostalgia Facilitates Post-Acquisition Target Employee Retention: An Agenda for Future Research, was co-authored with Tim Wildschut and Constantine Sedikides of the University of Southampton, UK.

The authors call for future research to test the limits of nostalgia in organizational change,  how buyouts differently affect the acquirer and target employees, and how nostalgia impacts other life changes.

“Transparency about change is important, but so is understanding how emotions like nostalgia can be strategically managed,” Maciejovsky said. “Like any powerful tool, nostalgia can have unintended consequences if we don’t use it wisely—but when applied thoughtfully, it can transform acquisition challenges into retention advantages.”

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Labels are everything: New study reveals role of popularity in news articles

The way that news organizations label articles could directly influence how much attention they receive and ultimately impact their revenue.

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News readers often click on articles not based on topic but rather the behavior of their fellow audience members, according to new research from the University of Georgia.

And the way that news organizations label those articles could directly influence how much attention they receive and ultimately impact their revenue.

When you go to a news organization’s homepage, they typically label articles that readers are engaging with the most. The researchers focused on two common labels: “most shared” and “most read.”

“These types of labels are not going anywhere. Popularity even in news labels is a psychological phenomenon,” said Tari Dagago-Jack, lead author of the study and an assistant professor of marketing in the UGA Terry College of Business. “Popularity labels on news outlets are taking advantage of the idea that we follow the lead of others and that our decision-making is influenced by what other people are doing.”

Article section labels influence click rate

At first glance, you may assume that these labels, “most shared” and “most read,” mean the same thing: A lot of people checked out the article. But there’s a clear difference that consumers pick up on.

“If something is most shared, we might assume that means many people had to read it and then deem it interesting enough or important enough to pass it on,” Dagogo-Jack said. “But then there’s this other reality where we know a lot of things that are widely shared are often extremely frivolous like cat videos or funny memes.”

In nine surveys and experiments involving hundreds of people, the study found respondents interpreted “most read” stories as being more informative. “Most shared” articles were viewed as less serious and more entertainment based.

“The primary goal for reading news is to gain information, and the label ‘most read’ is a stronger signal of an article’s information value.” —Tari Dagago-Jack, Terry College

“We as readers have two primary motives: to be informed or to be entertained — that is, for a welcome diversion,” said Dagogo-Jack. “At a baseline level, we were finding that people were choosing ‘most read’ at a way higher rate than ‘most shared.’ The primary goal for reading news is to gain information, and the label ‘most read’ is a stronger signal of an article’s information value.”

That means if editors want certain articles to get more attention, they should tailor the label to the readers’ goals.

Knowing your audience, content is key for engagement

The same went for articles advertised on social media. Posts from faux news organizations that had captions describing a more educational article as “most shared” received fewer clicks.

This wasn’t the case, however, for news stories that were less serious and newsworthy. In that case, the “most shared” label worked as well as the “most read” label.

It’s a key message for reporters, editors and web developers: Know your audience and your content.

“People should ask themselves: Why am I even clicking on this thing? Is it just because everyone else read it?” —Tari Dagago-Jack

“For pop culture, sports or music — more entertainment — in those sections you should highlight what is ‘most shared,’” Dagogo-Jack said. “But for world news, politics and science sections, you should be using things like ‘most read’ or ‘most viewed.’”

Dagogo-Jack also recommends putting thought into labels. Ambiguous choices like “trending” or “most popular” may stump readers altogether, as there are so many things this could mean.

“Providing these lists helps us get over information overload or choice paralysis,” he said. “It’s a crutch and makes the decision process easier, but I often wonder: At what cost?

“You’re clicking on something that a lot of people like and social proof is valuable, but it may not necessarily provide what you are looking for, and you just gave up on the search. People should ask themselves: Why am I even clicking on this thing? Is it just because everyone else read it?”

This study was published in the Journal of Consumer Research and was co-authored by New York University assistant professor Jared Watson.

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Dynamic pricing can optimize profits but alienate customers

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If you’ve ever seen a steep increase in the fare for an Uber to the airport on a Friday, or you’ve checked an item’s cost on Amazon, only to see it has changed hours later, you might have experienced algorithmic pricing.

That’s the practice of using algorithms to automatically adjust the price of goods or services based on factors such as demand, competitor pricing, inventory levels, or data about the customer.

While such pricing practices can squeeze out extra profit, they can also carry a marketing risk if not carefully implemented, according to Gizem Yalcin Williams, assistant professor of marketing at Texas McCombs. In 2012, Uber was widely criticized for raising ride prices during Hurricane Sandy. More recently, customers have expressed outrage over concert ticket surge pricing.

In a paper, co-written with an interdisciplinary group of 12 other researchers, Williams examines algorithmic pricing and the challenges companies can face when integrating it with their other objectives. The researchers offer some preliminary dos and don’ts for aligning pricing with marketing strategy, regulations, and avoiding customer backlash.

One potential factor in customer backlash, Williams says, is driven by feelings of unfairness.

“Let’s say that I just got myself something from Amazon, for my dorm, and then a couple of days later, I saw that the price changed,” she says. “I now feel like I overpaid for it, regardless of how good the product is.”

By the same token, seeing a price increase later might trigger elation, she says. “If I feel like I bought it at a lower price, I feel like I was smart.”

When Prices Get Personal

If pricing sometimes feels a bit more personal when algorithms are involved, Williams says, that’s because it is.

In addition to taking supply or production costs into account, companies increasingly use customer-level data to make pricing decisions, often with the help of artificial intelligence.

The exact data that go into the algorithm might not be always known, Williams says. “But what if the price I receive is different than others because of my own data, such as my shopping history, demographics, or location? Shoppers might react to the same price differently, depending on which data they think affected the price set by the company’s algorithm.”

Besides eroding customer loyalty, companies can face regulatory or legal attention when dynamic or surge pricing goes awry. Last year, the grocery chain Kroger was scrutinized by members of Congress over its plans to introduce algorithmic pricing at its stores.

Practical advice on pricing

As part of its research, Williams’ team surveyed pricing managers and conducted in-depth interviews with five strategic-pricing experts. They offered several pieces of advice.

  • Companies should be aware of how accepting their customers are — or are not — of dynamic pricing to avoid potential reputational damages.
  • Opening the “black box” and increasing transparency about how algorithms work can help managers and employees adopt and oversee them effectively.
  • Companies need guardrails to make sure they can effectively and carefully navigate the competitive and regulatory environment.

For Williams, one takeaway, she notes, is clear: Many companies slap the AI label on their operations, to cut costs or boost efficiency, without comprehensive planning for its design, integration, and monitoring.

 “Managers need to be deliberate about when, where, and whether to integrate AI into their operations,” she says. “And even when decisions are automated, it’s critical to have mechanisms that keep humans in the loop.”

Algorithmic Pricing: Implications for Marketing Strategy and Regulation” is published in International Journal of Research in Marketing.

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