Marketing teams aren’t struggling to create content. They’re struggling to make it usable.

Think of a common buyer objection your team faces. Now ask whether a rep could find the right asset to address it in 10 seconds while on a live call.

Most teams find the answer is no. Not because the content doesn’t exist, but because it’s not organized around how sellers actually search for things in the moment.

The Sales Content Taxonomy Blueprint walks through a six-category framework built around deal stages, not marketing categories.

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Discover the most comprehensive affiliate marketing study powered by real Instagram affiliate data. This report reveals 15 top insights every e-commerce brand should know, from the rise of social commerce to optimizing content mix, tracking performance, and understanding how always-on creator programs can drive sales. You’ll find practical takeaways on market dynamics, platform strategy, creator collaborations, content formats, partnership models, and performance KPIs. Explore how leading brands shape their influencer content, which industries are setting the pace, and the metrics that truly drive sales. Whether you’re a VP of Marketing, an Influencer Partnerships Manager, or a Brand Owner, this report will help refine your 2026 strategy and turn creator impact into measurable growth.

The post 15 Influencer Marketing Trends to double your Affiliate Sales appeared first on ���������.

A by Katherine L. Christensen and Suzanne B. Shu explores exactly this phenomenon. They call it the heritage discount: the tendency for sellers of sentimental or heritage goods to accept lower prices from buyers who share a meaningful connection to the goods’ past. Surprisingly, this happens even when sellers believe the buyer would have been willing to pay more.

They call it the heritage discount: the tendency for sellers of sentimental or heritage goods to accept lower prices from buyers who share a meaningful connection to the goods’ past. Surprisingly, this happens even when sellers believe the buyer would have been willing to pay more.

How the Heritage Discount Affects Markets

The implications of this research extend far beyond individual sales, shaping outcomes for consumers, marketers, and policymakers alike. Heritage value plays a role in massive industries—from the $58 billion self-storage market and the $43 trillion U.S. housing market to the $200 billion secondhand sector and the $450 billion collectibles market.

For marketers, these insights open the door to designing new products and experiences that help consumers maintain a connection to their heritage, whether through family heirlooms, brand storytelling, or collaborations like 23andMe’s partnership with Airbnb’s heritage travel. Such efforts can create offerings that resonate across generations.

Heritage framing also carries weight in the policy sphere. Conservationists, for example, may increase support for protecting natural resources by highlighting their ties to past generations, reducing the public’s willingness to lease or sell them for short-term gain.

Curious about the bigger picture, we asked the authors to share additional takeaways from their study:

Q: Your research uncovers a surprising “heritage discount,” whereby sellers are willing to accept lower prices from buyers with shared heritage. What emotional or psychological dynamics might explain this? Were there any reactions or patterns that genuinely surprised you during your studies?

Dr. Shu: From a more theory-driven perspective, I’ve done other work on the endowment effect and psychological ownership. What intrigued me about this project and what Kate brought into it was that you usually put more value on it when you own something. That’s the endowment effect.

But with heritage, we were proposing something different: you might be willing to accept a lower price. That’s the opposite of the endowment effect, and that flip was fascinating. I’m always curious when a well-established finding in the literature is robust across many studies but then you discover a specific context where it reverses.

In this case, the heritage discount shows up when you sell to someone who can continue the story and respect that heritage. For instance, if Kate were selling her teacups to a collector who didn’t care about continuing the heritage, she would ask for a higher price. But if the buyer valued the teacup’s heritage and wanted to keep it alive, she’d be willing to accept less.

To me, that’s the most interesting part: the heritage discount only applies when the buyer is someone who will keep the story and the heritage alive.

Q: How might the concept of heritage connection help brands support sustainability goals, such as encouraging product longevity, reducing waste, or fostering intergenerational value?

Dr. Christensen: One of the significant trends we’re seeing right now is the rise of vintage. While our paper primarily focuses on transactions, we define heritage goods as goods linked to the past, whether historically or symbolically.

The idea that the past carries symbolic value can increase how much heritage buyers value a product. This is particularly relevant when people use vintage items, such as fashion inspired by the ’90s or ’70s. By wearing these pieces, people aren’t just dressing themselves—they are bringing a piece of their past into the present and sharing it with others. This act becomes a “gift,” offering a glimpse into a different world.

If sellers believe that the past carries value, they may also be more willing to sell. The past can be defined in many ways: an era, a community’s history, even a nation’s identity. That’s why we see a rise in vintage fashion and, in some cases, a rise in nationalism. Both are ways people try to connect to the past.

This concept plays out in sustainability and the environment, too. Think about how people connect to the human past and are tied to the land (in meaningful ways). For example, I recently learned that my uncle’s family were Adirondack guides who once took Theodore Roosevelt through the Adirondacks. When I return to those mountains, I experience them differently—I feel connected to that history, which increases the value of the place for me.

Q: How can environmental organizations and policymakers leverage your findings that framing natural resources as shared heritage reduces public support for exploitation?

Dr. Christensen: National parks provide one of the easiest examples of an intergenerational tie to the land. For me, that’s also my tie to the Adirondack Mountains. I was just there recently, and I had this powerful feeling that the trees were changing, connecting me back to my grandmother, even though she’s no longer here. That is why the natural landscape holds tremendous value to me.

I think that’s something you see often in regional marketing: how it ties people to the past. You also see it in the national parks. Their retro branding, for instance, emphasizes the idea of connecting to your ancestors. In a way, the parks themselves are marketed as a type of heritage good.

There’s also this initiative where fourth graders get a free national parks pass for a year, and their whole family can enjoy it. That’s positioned almost like a gift parents can give their kids—something that connects to what they did as children while creating new memories for the next generation.

So, the parks are marketed as timeless destinations, where parents, children, and even grandparents can share a sense of continuity and connection across generations

Q: Your research touches on the power of heritage in shaping value, but heritage can also be a sensitive area, especially regarding things like Indigenous crafts, national symbols, or traditional foods. What can marketers learn from your findings about why some communities push back against the commercialization of culturally significant goods?

Dr. Christensen: If you look at almost any nation’s history, there’s usually an original group that owned it, and then there was a loss of ownership. So, when another group comes in, and it’s not the original group, not the Indigenous group in your example, it can feel like a massive loss of heritage connection. If the transaction is viewed as purely about money, then that sense of loss and disutility is very high.

Often, when we see cultural trends that borrow from historically disempowered groups, there’s a sense that the practice isn’t really connected to the past. It’s just being used as a visual signifier. And that disconnect leads to tremendous backlash.

One of the most interesting examples I’ve seen in the work of some wonderful colleagues, focuses on restoring heritage to people who have lost that connection. The forced relocation of many Indigenous communities has had a lasting impact. In their new locations, these communities often lose traditional access to vital resources, such as water needed for growing crops. Unlike those who were not forcibly moved, they may lack the resources or the ability to maintain a connection to their ancestral lands and history.

Rebuilding that connection strengthens the whole ecosystem. It’s not just the consumer. The producer makes the food and knows how to cook it, and then the consumer eats it. When all those layers feel connected to heritage, I hypothesize that the value increases for the end user and everyone along the line. Everyone who opts in wants to maintain that link to the past.

But it also matters who is doing it. Sometimes, groups want to separate from others’ histories because, in a sense, it’s not theirs, and that creates complications. Heritage can become competitive, and tensions around commercialization often emerge.

Q: In today’s digital world, consumers express their identities through social media memories, digital collectibles, and even AI-generated family stories. Do you see a heritage connection evolving in these virtual spaces?

Dr. Christensen: The growing digital world may increase our need to connect to the past. In terms of how it happens technically, social media makes it much faster and easier. Right now, you can create a virtual person or save your mom’s phone messages from the human desire to preserve memories. As people contemplate how to connect with and share their own memories, they find value in these digital artifacts. These things give us value as human beings, and I believe we’re losing some of that, which is why I think there’s a growing need for heritage in the digital world. It’s now easier to create products that resurface those connections. For example, how do we bring back memories from childhood? They’re there, just buried.

Do we want to preserve the ideas of our grandparents? For some, that might feel weird or even like a violation. But for others, it’s a powerful sense of connection to the past, something they’d likely pay more for not just for themselves but to pass on to future generations. I think that at moments when the future becomes present, the past becomes especially valuable. For example, that intergenerational link suddenly comes alive when you have a child. You’re both giving something to the future and wanting to preserve the past.

Q: How might this shift influence how people assign value or feel a sense of ownership over digital goods, and what could this mean for brands trying to build emotional connections online?

Dr. Shu: For some reason, my social media feeds have been filled lately with stories about people doing DNA testing and trying to trace their ancestors. It’s fascinating how technology makes it so easy now. People say, “I have a grandparent I know nothing about, and I don’t know how to trace them,” but DNA testing opens that door and gives them access. They can then do a bit more searching and find previously impossible connections.

That ability to rediscover heritage is powerful. It also opens space for brands to build emotional and heritage connections. Kate had a great example, but it didn’t make it into the paper, of Airbnb offering heritage-based vacations. Imagine someone whose family was originally from Turkey but lived elsewhere for generations. A descendant might say, “I wish I understood my connection to Turkey.” A trip could then be designed to take them back to their ancestral hometown.

We live in a society where people move around much more than in the past, when several generations might have stayed in the same small town. Today, companies can help people reconnect with their roots and their history. That’s something consumers respond to. They lack that connection and search for it, and brands can help fill that gap.

Source: Katherine L. Christensen and Suzanne B. Shu (2024), “,” Journal of Marketing Research, 61 (3), 571–86. doi:.

References

Absolute Reports (2023), “7.5% Growth in Self Storage Market by 2023−2028: Exploring the Growing Trend Regional Analysis Competitive Scenario,” GlobeNewswire (March 14), .

Credit Suisse (2020), “Collectibles: An Integral Part of Wealth,” research report, Credit Suisse Research Institute and Deloitte (October).

Market Decipher (2023), “Collectibles Market Size, Statistics, Growth Trend Analysis and Forecast Report, 2023-2033,” .

ThredUp (2023), “Resale Report,” (accessed August 9, 2023), .

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However, in a , we find this is not the whole story. Contrary to the popular belief that customer interactions are essentially draining, our study shows that, under certain conditions, these interactions can rejuvenate service employees. Service interactions can generate high levels of emotional energy, similar to the confidence and excitement experienced at a great concert or a thrilling soccer game.

The key question we pose is: Could customer interactions become a source of emotional energy for frontline service staff? And, if so, how?

The Club Med Experience

Our study is based on research conducted in Club Med resorts, a unique service environment where employees and customers frequently participate in high-energy activities together such as singing, dancing, and playing sports or sharing drinks and meals. Club Med offers a rich context for studying the emotional dynamics of service work because the interactions here are not just incidental but embedded into the company’s culture.

At Club Med, we observed that certain rituals, such as the iconic “Crazy Signs” dance performed every evening by staff and guests, serve as powerful sources of emotional energy. During these rituals, the coordinated actions of participants lead to a collective emotional high. The synchronization of movements and emotions not only enhances the experience for customers but also energizes the employees who lead them. In this way, Club Med employees find joy and rejuvenation in interactions that might be stressful in other service contexts.

Our research also highlights the importance of autonomy and status in generating emotional energy. Employees who have more control over their work and who are given opportunities to elevate their status, even temporarily, are more likely to experience positive emotional energy. At Club Med, employees often take on leadership roles during rituals and performances, becoming the focus of attention and, in the process, gaining a temporary boost in status. This elevation is crucial in transforming potentially draining interactions into energizing ones.

Our findings challenge the conventional wisdom that service interactions are inherently depleting. Instead, we argue that under the right conditions—such as opportunities for entrainment, autonomy, and status elevation—customer interactions can be a source of emotional rejuvenation for service employees. This has important implications for service organizations seeking to improve employee well-being and engagement. By fostering environments where positive customer interactions can flourish, organizations can help their employees maintain high levels of emotional energy that can lead to better service outcomes and lower turnover.

Lessons for Chief Marketing Officers

• Create rhythmic entrainment: Consider the famous safety announcements from Southwest Airlines. These humorous announcements foster a lighthearted atmosphere, yet this interaction also becomes a moment of mutual focus for employees and customers. It allows airline crews to move their bodies in a synchronous fashion, and through this synchronization—an example of rhythmic entrainment—converge toward the same lighthearted mood. This is a good example of how it is possible to take an existing service interaction that does not normally generate emotional energy for service employees and turn it into one that increases employees’ emotional energy.

• Increase employee autonomy and status: Cycling brands like Rapha organize outings where customers and employees ride together. These experiences act as a regenerative moment for employees because the power differential associated with serving someone is temporarily removed. Such an environment develops common ground between service employees and customers.

• Create “Breathing Rituals”: Organizations should consider introducing “breathing rituals”: moments that allow employees and customers to interact on a more equal footing. For example, in some cases, Club Med employees and guests form lasting bonds through experiences such as sharing a meal or drinks. These interactions are both pleasurable and also serve as a counterbalance to the more routine, hierarchical aspects of service work.

By recognizing the potential for customer interactions to generate emotional energy, service organizations can create conditions that protect employees from burnout and enhance their overall work experience. This shift in perspective—from seeing customer interactions as a burden to viewing them as an opportunity for emotional renewal—could help address the persistent challenges faced by the industry. By intentionally designing customer interactions with emotional energy in mind, we can transform service work into a more meaningful and joyful experience.

Source: Julien Cayla and Brigitte Auriacombe, “,” Journal of Marketing.

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One of the most commonly used SPM practices involves companies publishing the sales performance rankings of their salespeople on key performance metrics. The goal of publishing performance rankings is to provide feedback to all salespeople by disclosing their performance relative to their peers, thereby creating a competitive motive for performance improvement. However, despite widespread use, the effectiveness of these rankings has not been explored.

In a , we examine how the presentation of performance rankings influences critical outcomes, including salesperson quota attainment and employee turnover.

Questions around Performance Rankings

Our research poses four primary questions:

1. Do performance rankings effectively motivate salespeople to improve their performance?
2. Does this effectiveness vary by the type of information published alongside the ranking?
3. What are the conditions under which publishing certain information with performance rankings is more or less effective?
4. What are the long-term implications of performance rankings on salesperson turnover?

Our research team conducted two studies involving over 27,000 salespeople from more than 170 firms across 83 countries. These studies leveraged extensive field data to examine the effects of three distinct information conditions: anonymized performance rankings, identifiable performance rankings, and identifiable rankings with quotas.

Our findings reveal that while performance rankings can positively influence sales outcomes, their effectiveness—and, by extension, the value derived from the performance ranking dashboard—hinges significantly on the type of information disclosed within the dashboards.

While performance rankings can positively influence sales outcomes, their effectiveness—and, by extension, the value derived from the performance ranking dashboard—hinges significantly on the type of information disclosed within the dashboards.

For instance, anonymized rankings effectively motivate salespeople to increase their quota attainment, yet they also lead to higher turnover rates, which can result in substantial indirect costs related to recruitment, training, and loss of organizational knowledge. As a result, the costs associated with implementing and maintaining anonymized ranking systems may not be justified by the outcomes unless turnover can be effectively managed.

In contrast, identifiable performance rankings have the most substantial positive impact across our two studies, significantly enhancing quota attainment and reducing turnover. Our findings indicate that when salespeople know the identities of their peers in the rankings, they are motivated not only to improve their performance but also to maintain a positive social image. This dual motivation of self-improvement and self-presentation drives better performance and lowers turnover rates. However, when quotas are disclosed alongside identities and performance rankings, we fail to see performance enhancing benefits.

Lessons for Chief Marketing Officers

Our study offers valuable lessons for managers and salespeople:

• More information is not always better. Instead, the strategic selection and combination of performance data are crucial for achieving both immediate and enduring positive outcomes.

• Managers should develop and implement identifiable ranking systems, ensuring transparency in how rankings are determined and communicated.

• Managers should avoid including fixed or objective performance metrics (i.e., quotas) in ranking systems to focus on relative performance evaluations, which is essential for the effectiveness of these systems.

Implementing these recommendations can drive essential behavioral changes among sales managers and executive leadership within sales organizations. Sales managers will be able to adopt a more strategic approach to performance ranking disclosures, emphasizing transparency and leveraging the motivational benefits of identifiable rankings, which should lead to improvements in quota attainment and reduced turnover within their teams.

Furthermore, executive leaders can invest in performance ranking dashboards that are tailored to their organization’s unique characteristics, taking into account their sales force’s compensation structure and size. By doing so, they can ensure the investment in performance dashboards will justify the costs by achieving substantial performance gains and minimizing turnover, thereby enhancing the overall effectiveness of the sales force.

Our research highlights the critical role of transparency and information type in performance rankings. By implementing performance rankings and carefully selecting the information disclosed alongside them, they can create a more motivated and loyal sales force. This approach will not only drive better performance outcomes but also contribute to a more sustainable organizational culture.

We urge scholars to build on our research and explore rankings on team goals and how they interact with individual salesperson rankings. Furthermore, it is important to study factors such as familiarity and social interactions between salespeople, office proximity and location, physical versus virtual contact between peers, and the extent of knowledge sharing. Future studies can also expand our understanding of how performance rankings may differ in effectiveness depending on the motivational orientation of salespeople.

Source: Molly Ahearne, Mohsen Pourmasoudi, Yashar Atefi, and Son K. Lam, “,” Journal of Marketing.

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In a , we offer a compelling reason for considering brand strength when designing sales incentives in brand-managed retail (BMR) sales settings.

For context: a BMR setting may be a store-within-a-store (SWAS), such as the cosmetics counters in most major U.S. department stores, or a brand-managed standalone store such as Aveda or Gap. Such BMR settings are typically staffed by the brand rather than the retailer, with the brand also having autonomy over inventory and pricing decisions for its products. Although BMR has been historically more prevalent in Europe and Asia than in the U.S., brands are adding SWAS offerings everywhere to reach new customers and to offer additional touchpoints for customers.

Our research team explores this dynamic retail context and investigates the sales incentives used in a variety of BMR settings. In our investigation, we uncover a significant variability in the use of individual and group sales incentives by brands in these settings. Some brands opt for individual incentives to motivate salespeople based on performance, others lean toward group incentives, and a portion adopt a combination of both approaches. This diversity in incentive structures prompted us to explore the underlying factors driving incentive choices by brands.

The literature shows that among other factors, brand strength and sales incentives affect the selling effectiveness of retail salespersons, leading us to conjecture that the differences in incentive choices by brands may be tied to the strength of those brands.

The Secret to Designing Incentives

We use a theoretical principal-agent model to investigate how brand strength may influence the relative profitability of different types of incentives. Our model assumes a BMR setting with salespersons serving a mix of consumers, including some who might be repeat buyers ready to purchase and others who are uninformed about the brand’s value proposition and need to be sold by the salesperson.

In designing incentives, a firm would ideally like to offer incentives only for selling to the uninformed consumer because this sale requires salesperson effort. Firms cannot usually observe whether a sale made by an individual salesperson was to an uninformed consumer; instead, firms have better information on whether the group as a whole sold to an uninformed consumer because the group output in this case would be higher than otherwise. Our analysis suggests that this information advantage of group incentives is more potent for weaker brands, resulting in the main finding that weaker brands may be more profitable with group incentives. Conversely, we find that stronger brands would be better off with individual salesperson incentives.

Weaker brands may be more profitable with group incentives. Conversely, we find that stronger brands would be better off with individual salesperson incentives.

An important qualification to our theoretical results: they apply to somewhat established brands and not to very weak brands. For example, Clarins and Estee Lauder are both established cosmetic brands, but Clarins ranks lower than Estee Lauder in many brand equity rankings and may benefit from using group incentives in its BMR operations, while Estee Lauder may benefit less.

Lessons for Marketing Managers

Our findings underscore the efficiency implications of aligning sales incentives with brand strength. We offer the following lessons to help Chief Marketing Officers make better decisions about individual and group incentives.

• Managers of BMR sales operations need to determine whether their brand falls on the weak or strong end of the spectrum. This empirical question is to be answered by data, which could be from brand equity metrics such as the revenue premium or from surveys that measure consumers’ knowledge, attitude, and emotional connection toward the brand. These data can help managers form a judgement about the strength of their brand and determine the best sales incentives.
• A combination of individual and group incentives can sometimes be better than having just one type of incentive, although this is less so for weaker brands, which may find that offering a group incentive alone is best.
• Our study underscores the importance of adopting a holistic approach when devising marketing strategies. For instance, when a brand allocates substantial resources over time to elevate its brand image, it is imperative for managers to evaluate potential adjustments to the compensation structures of their customer-facing BMR employees.

A limitation of our study is that it focuses on BMR settings, so future research could examine the applicability of our results beyond these settings. As seen from our empirical results, data from two different settings are consistent with our theoretical predictions. Yet, while the literature does not offer an alternative explanation for why brand strength may be related to the choice of group versus individual incentives, new alternative explanations for our results may emerge in the future.

Source: Wenshu Zhang, Jia Li, and Subramanian Balachander, “” Journal of Marketing.

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Compared to more traditional marketplaces, long-established signals of quality such as brand name are less relevant in the peer-to-peer space. Instead, sellers in these marketplaces directly tell potential buyers about themselves and the production processes behind their goods and services.

What should these sellers say in their bios and product descriptions? In a , we find that one of the best things they can mention is that they enjoy their work.

We suspect that many people who choose to sell things through peer-to-peer marketplaces enjoy making their products, yet sellers rarely mention this. For example, in the profiles of 30,000 sellers across various peer-to-peer marketplaces, only about 1% of sellers mentioned production enjoyment. Over 15 experiments, we find consistent evidence that buyers are more interested in, are more likely to choose, and are willing to pay more for products or services that the seller enjoys producing.

We find consistent evidence that buyers are more interested in, are more likely to choose, and are willing to pay more for products or services that the seller enjoys producing.

We also explore how production enjoyment influences the sellers’ decision to price products and services. Ironically, sellers are willing to accept a lower price—and do indeed charge less—for the products and services they enjoy producing. Although sellers also generally associate production enjoyment with higher quality, they do not rely on this inference in their pricing decisions.

In a field study, we test two ads on Facebook for a search engine optimization (SEO) specialist, one that mentioned production enjoyment (“I really enjoy SEO”) and one that was otherwise identical but did not contain these words. We find that small business owners were more likely to click on the ad that mentioned production enjoyment. The positive reactions that buyers have to sellers’ signals of production enjoyment occur over a broad range of jobs. Across our studies, we examine over 100 different jobs and, in all cases, signaling enjoyment increases buyers’ willingness to pay.

Enjoyment vs. Quality

We find that this positive impact occurs because buyers interpret production enjoyment as a signal of a high-quality product or service. After all, someone who really enjoys making jewelry or loves painting probably spends more time and focus on it than others. When buyers learn of this enjoyment, they then presume the product/service is of high quality and are therefore more likely to buy it.

Notably, signaling production enjoyment works best when the production process requires a lot of skill. Automation has made many production processes much easier. In situations where buyers assume the production process is largely automated (or assume the offering does not require much skill overall), production enjoyment does not impact buyers nearly as much.

But even in high-skill contexts, why do sellers charge less for products and services they enjoy producing? Like buyers, sellers also associate production enjoyment with high quality products and services, which should increase prices. We think sellers instead charge lower prices because the joy that they experience during the production process already compensates them for their work. In any case, it seems that production enjoyment carries signals for sellers that lead to different pricing decisions.

Taken together, these findings are somewhat contradictory: sellers charge less money for products and services they enjoy producing, even though buyers are willing to pay more for them.

Lessons for Sellers

• When sellers mention production enjoyment in their profiles and marketing, buyers are more interested in their products and services.
  
• By comparing production enjoyment to a variety of other established cues of product quality (e.g., production effort) and identifying several moderators that determine the impact of this signal (e.g., required skill), we give sellers a useful framework for when and how to signal production enjoyment.
  
• Sellers should reconsider their willingness to charge for different products/services. This knowledge can also benefit buyers, who can recognize production enjoyment as a signal of a potential discount, because sellers charge less when they enjoy the production process.
  
  Overall, if you enjoy the work you do, make sure you tell people! They will think you do better work and should be willing to pay you more for it.

Source: Anna Paley, Robert W. Smith, Jacob D. Teeny, and Daniel M. Zane, “,” Journal of Marketing.

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As the importance of data in decision making continues to grow, predictive sales analytics have gained immense popularity in business. Companies are currently using predictive analytics for numerous functions such as predicting conversion likelihood to prioritize clients and improving consumer retention by predicting consumer churn. However, salespeople may be averse to using predictive analytics, as they may mistrust technology or lack the knowledge to use it. Still, it is unclear under what circumstances predictive analytics can be effective.

In a , researchers Johannes Habel, Sascha Alavi, and Nicolas Heinitz address this challenge by focusing on customer churn prediction in a business-to-business context. Their extensive study, which analyzed 9.7 million transactions, revealed that the success of predictive analytics tools hinges significantly on the characteristics of both customers (like churn probability and previous revenue) and salespeople (such as their perceptions of technology and abilities to use it).

The research further demonstrates that the effectiveness of these tools is enhanced when users have realistic expectations about the algorithm’s accuracy, though this was found to be effective only in specific circumstances. These findings, derived from a meticulously conducted field experiment conducted by collaborating with 12 companies for more than two years and reinforced by two follow-up experiments, provide critical insights into the nuanced interplay between predictive models and their real-world application in sales. 

For practitioners, policymakers, consumers, and other stakeholders, the key takeaways from this research are:

1. The success of predictive analytics in sales, specifically for customer churn prediction, is highly dependent on both customer characteristics (like churn probability and prior revenue) and salesperson traits (such as technology perceptions and abilities).
2. Implementing strategies like fostering realistic expectations about the algorithm’s accuracy can improve the effectiveness of predictive analytics tools, but this is highly situational.
3. This study underscores the importance of understanding the nuances of predictive models in sales, encouraging a more informed and strategic application of these tools in various business contexts. These insights are crucial for managers looking to optimize their use of analytics in decision-making processes and for stakeholders interested in the practical implications of predictive analytics in the business sector.

We had a chance to contact the authors to learn more about their study and gain additional insights.

Q: What inspired you to delve into the topic of predictive analytics in sales, particularly in the context of customer churn?

A: The origin of this research project arose from two observations of our team in machine learning and firm practice. Regarding machine learning, we noted that the capabilities and access to machine learning models through the statistics software R vastly improved at that time. At the same time, firms grew increasingly excited about the potential of using such ML for their analytics in sales. In the workshop, we decided to cooperate with a B2B firm to explore the opportunities, potentials, and dangers of using predictive sales analytics. We discussed various use cases with the management of the company for predictive analytics applications in their sales force. Since customer churn often constitutes a key issue in B2B industries, we decided to focus on a predictive tool that could assist the sales force in this respect.

Q: Could you discuss the significance of your research in the broader context of business and technology? How does understanding customer churn through predictive analytics impact the field at large?

A: In the broader context of business and technology, our study points to a key tension: AI-based technologies exhibit tremendous potential to improve productivity and diverse other outcomes. But these are only promises of potential, which are not automatically and easily realized. Rather, all too often, implementations of such new technologies fail and may even backfire. Our study underlines the enormous nuances and contingencies that need to be considered when implementing such new AI-based tools. Such implementations never constitute low-effort quick fixes but major change management projects that require massive attention, effort and resources of management to succeed. Findings of our study contribute to marketing research by underlining the fundamental role of contingent effects of such technology implementations and uncovering the most important categories of contingencies.

Q: Are there potential extensions of your work that you find particularly exciting? How could other researchers build on your findings to explore new dimensions in predictive analytics or customer behavior?

A: Our study uncovered that salespeople deal very differently and develop different strategies in response to the implementation of predictive sales analytics tools. At the same time, the firm communication strategy to foster effective tool use did not unconditionally provide the wished for results. Consequently, an intriguing endeavor for future research, as we see it, is to develop a taxonomy of AI implementation strategies in sales and examine the differential impacts of different strategies to foster adoption.

Q: What were the biggest challenges and the most significant lessons you learned from doing a large-scale field study collaborating with multiple companies?

A: The first—and most important—lesson, in our view, is to first identify the right company, that is, the right and suitable cooperation partner. This lesson may sound trivial, but its significance cannot be overemphasized. This is because many companies initially intend to cooperate and join a research project on such an important and promising topic. Yet, after the initial enthusiasm, we noted that many companies realize the high effort and necessary resources which establish barriers. Moreover, sometimes companies are not suitable for compelling field study due to various issues such as lack of data, insufficient commitment or resistance by employees, or organization structural aspects. Therefore, it is important first to ensure the firm partner is eligible and committed. Otherwise, one may face enormous losses of time and energy.

Q: Do you think that predictive analytics also have negative effects in the long term? If so, how could managers mitigate this?

A: Yes, predictive analytics might exhibit negative long-term effects for companies and their employees. Such harmful effects may occur, for instance, if the new technology is initially implemented in an ineffective way such that employees’ fears and aversion had not been properly addressed and resolved. Then, such an implementation might cause disruption in teams, harming interpersonal trust and triggering negative long term social dynamics in the organization. The seed for positive long-term use and development of predictive analytics needs to be set with the initial implementation and introduction. Managers need to:

1. accompany the implementation with a deliberate change management project,
2. select an appropriate tool which indeed provides value and usability to the employees,
3. give them freedom and time to learn and experiment with the tool, and
4. make sure that the tool is employed in the right customer and market situations.

Q: Beyond asking people to have realistic expectations toward predictive analytics tools, what other strategies could be used to trigger people’s trust in predictive analytics even when they can fail sometimes?

A: Employees’ fears and anxieties when asked to work with the new predictive analytics tools often arise from deep-seated uncertainties regarding the potential consequences of the tools. For instance, they might feel uncertain about how to effectively work with the tools, perceive them as an intrusion into their work practices, fear being outperformed by more tech-savvy peers, or, most prominently, might dread being replaced by effective AI tools. Manager strategies to foster trust in predictive analytics must tackle and resolve those fears and uncertainties. A major prerequisite for such strategies to be effective is that a healthy relationship exists between the manager and their employees. For that, managers need to consistently demonstrate to employees that the purpose of the tool is to assist them and help them, and not replace them or monitor them.

Managers need to consistently demonstrate to employees that the purpose of the tool is to assist them and help them, and not replace them or monitor them.

Ideally, managers succeed in establishing a trust-based company culture that prioritizes employee well-being. In such a culture, fears of AI should be less pronounced, and employees should be more open to effectively leverage the opportunities provided by the new technology.

Read the full article:

Johannes Habel, Sascha Alavi, and Nicolas Heinitz, “,” Journal of Marketing Research. doi:.

Go to the Journal of Marketing Research

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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 , 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.

From: Beibei Dong, Mengzhou Zhuang, Eric (Er) Fang, and Minxue Huang, “,” Journal of Marketing.

Go to the Journal of Marketing

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Imagine you’re walking into a tech store to purchase a new phone. As you’re browsing through the phones, a salesperson approaches you asking if you need any help. You’re not sure what accessories you need, but the salesperson suggests a phone case and screen protector. The salesperson explains how the accessories are specifically designed to complement the features of the phone, keeping it safe from scratches and drops. They also mention how these accessories can save you money in the long run by preventing costly repairs. Feeling more confident in your decision, you agree to purchase not only the phone but also the phone case and screen protector. As you leave the store, you feel satisfied with your choice of products.

How did the salesperson convince you to buy not just the phone but also the additional items? A recent  by Jennifer K. D’Angelo and Francesca Valsesia provides an answer. When an individual, such as a salesperson, stylist, waiter, designer, shop assistant, or influencer, suggests combining two products for purchase or use, they are perceived as an expert in the product category. As a result of this higher level of credibility, consumers are more likely to follow such individuals’ recommendations and make a purchase. This effect holds true regardless of whether the combination is encouraged or discouraged, whether the customer requires the advice, or whether it applies to other products in the category. Furthermore, the more explicit the combinatory recommendation, the stronger the effect.

When an individual, such as a salesperson, stylist, waiter, designer, shop assistant, or influencer, suggests combining two products for purchase or use, consumers perceive them as an expert in the product category and are more likely to follow their recommendations and make a purchase.

We had the opportunity to contact the authors, who kindly provided interesting insights into this article. Read on to discover more details about this fascinating research.

Q: Providing combinatory recommendations is a novel cue that consumption advisers can use to signal expertise. What sparked off the initial research idea of combinatory recommendations as being more impactful?

A: Anecdotally, when browsing images of clothing outfits and interior design, we noticed ourselves thinking, “I would never have thought to put those pieces together, but it totally works.” Those observations sparked the idea that people who have the ability to curate such outfits and designs might possess a novel kind of expertise that the lay consumer doesn’t have.

Jennifer has some ongoing work in the customization domain that finds consumers tend to limit their number of choices (e.g., food ingredients) when these choices are to be combined (e.g., mixed together in a dish). Consumers limit themselves less when making choices that are intended to be consumed individually. This led us to suspect that many consumers have difficulty combining things together. The know-how to combine things requires some higher level of expertise. We later discovered through our research that “higher level of expertise” was greater depth of knowledge.

Q: The real-world persuasive value of combinatory recommendations was tested with a field study (Study 6). Did you face any related challenges? How would you advise scholars or practitioners who are thinking of adopting a similar research approach?

A: The biggest challenge was finding a company that offered a suitable context to operationalize both our combinatory and control conditions. We think that smaller, startup stage companies may be more amenable to experimentation, giving researchers more leeway to better operationalize their constructs in a field study. Many business schools host startup venture competitions. One idea would be to attend these competitions to forge partnerships with these companies for future field experiments. On another note, we think it’s important to read up on Facebook Ad Manager’s latest best practices regarding target market specifications, campaign length, ad formats, etc. as the platform’s guidelines are ever-changing.

Q: Can you elaborate on the potential extensions of your research findings? In particular, what would be the effect of recommending more than two products for joint consumption?

A: This is a great question and one that we have thought about ourselves. Based on our theorizing, a person who can recommend many compatible products exhibits a greater ability to process interactions among products, which might signal even greater expertise than only recommending two products for joint consumption. We find initial support for this prediction from Smart Closet, an online platform where users post clothing pieces that one could wear together: the greater the number of clothing pieces in the post, the more likes the post received. It is nonetheless possible that this effect has an upper boundary: consumers might have a hard time believing an advisor who recommends 20, 50, or 100 products for joint consumption. What this upper boundary is exactly might depend on the product category.    

Q: What do you think would happen if the recommendations are created by artificial intelligence or algorithms instead of human advisors?

A: Prior research has demonstrated consumers’ resistance to adopting AI recommendations (e.g., algorithm aversion; see ). This resistance might translate into consumers having a hard time believing a combinatory recommendation made by nonhuman advisors. This is, of course, if consumers are aware that the recommendation came from artificial intelligence or an algorithm.

Q: What do you think are the key takeaway points of this research that could be of particular interest to practitioners?

A: On the one hand, retailers should consider using personalized communication, such as direct mail, to provide combinatory recommendations. In this vein, fashion retailers like Mango and StitchFix have recently started sending follow-up emails that contain suggestions of clothing pieces to wear with items consumers already own. On the other hand, retailers could also prompt combinatory recommendations when asking consumers to review their products, as well as asking them to post photos of their outfits. Finally, the influencer marketing industry is set to grow to approximately $21.1 billion in 2023. Marketers should encourage influencers they collaborate with to use combinatory recommendations and consider the use of combinatory recommendations as a selection criterion when evaluating influencers with which to collaborate.

Read the full article:

Jennifer K. D’Angelo and Francesca Valsesia (2023), “,” Journal of Marketing Research, 60 (1), 155–69. doi:

References:

Berkeley J. Dietvorst, Joseph P. Simmons, and Cade Massey (2015), “Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err,” Journal of Experimental Psychology: General, 144 (1), 114–26. doi:.

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