A new Journal of Marketing study finds that ALN is effective—but only under specific conditions. Some businesses experience significant increases in sales, while others see little to no impact. The key factors determining success include the nature of the sales cycle, deal complexity, and whether the customer is new or returning.

We uncover a critical insight: ALN enhances lead interactions and improves the quality of sales conversations, but it does not guarantee higher conversion rates across all industries. ALN works best when used for new leads, short sales cycles, and lower-value deals. However, its benefits decline in high-ticket purchases or industries where buyers conduct extensive independent research.

ALN works best when used for new leads, short sales cycles, and lower-value deals. However, its benefits decline in high-ticket purchases or industries where buyers conduct extensive independent research.

This distinction has major implications for businesses investing in ALN. Many companies measure ALN success using vanity metrics—email opens, click-through rates, and engagement levels—without assessing whether those interactions lead to actual sales. Our findings suggest that firms should rethink how they evaluate automation success and shift their focus to measuring ALN’s impact on meaningful outcomes like sales meetings and conversions.

When ALN Works—and When It Doesn’t

For companies selling relatively simple products or services with shorter sales cycles, ALN can be a powerful tool. By delivering targeted content at the right time, ALN reduces uncertainty for potential buyers and ensures that sales teams engage with more informed prospects. Our research finds that in such cases, ALN can lead to a 23 percentage point increase in conversion rates.

However, for industries with long and complex sales cycles, such as B2B enterprise software or industrial equipment, ALN’s impact is less clear. In these cases, buyers rely on detailed research, peer recommendations, and in-depth consultations rather than automated content. ALN may increase engagement but does not necessarily lead to more closed deals.

Returning customers also respond differently to ALN compared to first-time buyers. Since they already have a relationship with the brand, they are less likely to need automated content to guide their purchase decision. This means companies must differentiate how they nurture new versus existing leads, rather than applying a one-size-fits-all approach.

Are Businesses Measuring the Wrong Metrics?

One of the biggest mistakes we observe is companies focusing too much on engagement metrics rather than true business outcomes. Many firms evaluate ALN success on the basis of email opens, website visits, or social media interactions. Although these indicators suggest interest, they do not necessarily translate into revenue.

Our research suggests that businesses should measure ALN effectiveness by tracking:

• Lead-to-sales meeting conversion rates (Does ALN drive actual conversations between buyers and sales teams?)
• Sales cycle speed (Does ALN shorten the time it takes to close a deal?)
• Revenue impact (Does ALN increase the number of closed deals and overall profitability?)

Shifting to these meaningful metrics will help businesses make informed decisions about ALN’s true value.

How Companies Can Use ALN Strategically

We find that ALN works best as an enhancement—not a replacement—for human sales interactions. Companies that rely too heavily on automation risk alienating high-value prospects who expect personalized, consultative selling. Instead of viewing ALN as a standalone solution, businesses should:

• Segment their leads and tailor ALN for different customer groups (e.g., new vs. returning buyers).
• Use ALN to complement human interactions, rather than replace them, particularly for complex sales.
• Refine ALN strategies over time by tracking real business outcomes rather than engagement metrics.

For marketing leaders, the takeaway is clear: ALN can be a powerful tool, but only if it is applied strategically. Businesses should test its impact before fully committing, ensuring that automation aligns with their sales process rather than relying on industry hype.

Source: Johannes Habel, Nathaniel Hartmann, Phillip Wiseman, Michael Ahearne, and Shashank Vaid, “Sales Pipeline Technology: Automated Lead Nurturing,” Journal of Marketing.

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Our research team explores the nuances of these partnerships and uncovers critical insights for improving their effectiveness. We find that the way brands manage these collaborations—often through excessive control and reliance on short-term metrics—creates imbalances that undermine trust, content quality, and overall outcomes.

The Dynamics of Sponsored Content

Sponsored content operates in a unique space where brands, influencers, and audiences converge. While influencers offer authenticity and audience trust, brands often prioritize reach and sales metrics. This mismatch of goals can lead to friction.

Our study reveals that brands frequently attempt to script influencer content or impose stringent controls on messaging. While this approach aims to ensure alignment with brand objectives, it often devalues the creative expertise that makes influencers effective. This not only damages the influencers’ relationships with their audience but also reduces the perceived authenticity of the partnership.

Power Imbalances in Partnerships

We find that these collaborations often favor brands, leaving influencers with little agency. For example:

• Influencers are pressured to prioritize metrics like reach or sales, which can shift their focus away from creating engaging, authentic content.
• In response, some influencers resort to acquiring fake followers or engagement to meet brand expectations, which in turn triggers surveillance and distrust from brands.

This cycle of control and distrust weakens partnerships, ultimately harming both parties’ reputations and outcomes.

The Risks of Short-Term Thinking

Short-term metrics, such as immediate sales or engagement rates, dominate many influencer–brand partnerships. While these metrics are easy to measure, they often miss the broader value that influencers bring—such as long-term brand loyalty, deeper audience engagement, and organic reach.

Brands that focus solely on short-term results risk undermining the authenticity of their campaigns and alienating audiences.

Recommendations for Brands and Influencers

For Brands:

• Respect Creative Independence: Recognize that influencers have their own unique voices and audiences. Avoid over-scripting or pressuring influencers to change their tone, which can jeopardize their authenticity and effectiveness.
• Focus on Long-Term Metrics: Shift away from a narrow focus on reach and sales. Instead, prioritize metrics that reflect long-term impact, such as audience loyalty or sentiment.
• Build Trust: Reduce hierarchical dynamics in partnerships. Collaborate with influencers as equal partners, acknowledging their expertise and audience insights.

For Influencers:

• Professionalize Business Practices: Invest in skills or outsource management tasks to handle the business side of partnerships more effectively, freeing up time for creative work.
• Collaborate with Peers: Engage in collective action to address power imbalances and advocate for fairer terms in partnerships.

The insights from this study extend beyond influencer marketing. We argue that similar challenges arise in other emerging markets involving complex, “epistemic” objects—products or services that are not fully understood by their creators or consumers. Examples include NFTs, the Metaverse, and generative AI. In these contexts, valuation and production often involve ambiguities that lead to imbalanced relationships among stakeholders.

Brands and creators working in these spaces can benefit from more calibrated valuation models and efforts to flatten hierarchies, fostering trust and mutual understanding. Influencer–brand partnerships are here to stay, but their potential remains underutilized. Brands and influencers must move beyond short-term metrics and hierarchical relationships to unlock the true value of these collaborations. By fostering trust, respecting creative independence, and focusing on long-term impact, both parties can create campaigns that resonate deeply with audiences while achieving meaningful results.

Source: Zeynep Arsel, Maria Carolina Zanette, and Carolina da Rocha Melo, “Sponsored Content as an Epistemic Market Object: How Platformization of Brand–Creator Partnerships Disrupts Valuation, Coproduction, and the Relationship Between Market Actors,” Journal of Marketing.

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Fillingness, Taste, and Healthiness

• The Role of Food Attributes in Choices
  
  Our study highlights three key attributes—fillingness, taste, and healthiness—that shape food choices. While all consumers value taste, low-SES individuals place a much greater emphasis on fillingness, often at the expense of healthiness. In contrast, high-SES consumers prioritize healthiness, reflecting their access to more abundant and diverse food options.
  
  
• Perceived Relationships Between Attributes
  
  Low-SES consumers often associate healthy foods with being less filling and less tasty, reinforcing their preference for high-calorie, less nutritious options. These beliefs stem from limited exposure to healthy foods and fewer opportunities to experiment with cooking. High-SES individuals, who face fewer resource constraints, are less likely to hold these negative associations.
  
  
• Fillingness as a Critical Factor
  
  Fillingness, while often overlooked in public health strategies, is crucial for low-SES consumers. For individuals facing food insecurity or limited resources, satiety is a pressing concern. Policies and campaigns that ignore this dimension risk promoting foods that low-SES consumers perceive as unappealing or insufficient.

Implications for Policymakers

Our findings suggest that addressing nutritional inequality requires more than just making healthy foods affordable and accessible. Policymakers should focus on creating and promoting healthy options that are perceived as both filling and tasty.

• Expand the Availability of Filling Healthy Foods: Increase access to options like whole grains, legumes, and lean proteins, which are both nutritious and satiating.
  
  
• Incorporate Fillingness in Subsidies: Subsidize filling healthy foods to make them more affordable and attractive to low-SES consumers.

Public health campaigns should also work to reshape perceptions. By emphasizing the satisfying and flavorful aspects of healthy foods, marketers and policymakers can challenge the belief that “healthy equals unsatisfying or bland.”

Marketing and Industry Applications

From a marketing perspective, our research offers actionable strategies to encourage healthier eating habits:

• Reframe the Narrative: Highlight the filling and tasty qualities of healthy foods through advertising and packaging.
  
  
• Product Development: Design healthy food options that cater to low-SES preferences for satiety and flavor.
  
  
• Retail Strategies: Promote healthy, filling meals in stores, particularly in low-income neighborhoods, to align with consumer priorities.

These approaches borrow from the tactics used to market unhealthy foods but reapply them to encourage better choices.

Nutritional inequality is a complex issue that cannot be solved by supply-side solutions alone. Our research shows that consumer preferences and perceptions—particularly regarding fillingness and taste—play a critical role in shaping dietary habits. Addressing these psychological and cultural factors is essential for making healthy foods more appealing and accessible to low-SES populations.

For policymakers, marketers, and public health advocates, the path forward lies in promoting the fillingness and flavor of healthy foods, ensuring that they meet the needs and expectations of disadvantaged communities.

Source: Bernardo Andretti, Yan Vieites, Larissa Elmor, and Eduardo B. Andrade, “How Socioeconomic Status Shapes Food Preferences and Perceptions,” Journal of Marketing.

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We discover that a startup’s ability to combine costly signals (tangible achievements like financial capital, intellectual property, and team credentials) with costless signals (verbal cues like passion and concreteness) can significantly influence funding outcomes. However, the effectiveness of these signals isn’t straightforward—more isn’t always better.

Costly Signals: The Power of Tangible Achievements

Costly signals—substantial markers of a startup’s credibility—include:

• Financial Capital: Investments already made in the business.
• Human Capital: The founders’ education and experience.
• Social Capital: Business and institutional connections.
• Intellectual Capital: Patents and intellectual property.

These signals create confidence among investors by showcasing real progress and potential. However, our study found an “inverted U-shape” effect: while a moderate level of costly signals increases funding likelihood, excessive emphasis on these achievements can deter investors. Why? Too many costly signals might suggest overvaluation, leaving little room for investors to add value or signaling rigidity in the startup’s approach.

Costless Signals: The Subtle Art of Communication

Costless signals—intangible, verbal elements—also play a critical role in pitches:

• Passion: Expressing enthusiasm and emotional intensity.
• Concreteness: Using specific, detailed language.

While passion can enhance investor perception when paired with strong costly signals, it can backfire if used excessively, particularly by startups lacking substantial achievements. In such cases, passion might appear as “cheap talk,” undermining credibility.

Concreteness, on the other hand, provides clarity and specificity, which are crucial for startups with fewer tangible assets. However, overly concrete communication from startups with strong credentials can seem rigid, signaling a lack of strategic flexibility or long-term vision.

Key Insights for Startups

Our findings reveal that costly and costless signals don’t operate in isolation but interact in complex ways:

• Startups with fewer costly signals should focus on moderate concreteness to provide clear, detailed information about goals and achievements. Passion should be used sparingly to avoid seeming compensatory.
• Startups with strong costly signals should confidently showcase passion because it signals commitment and enthusiasm. However, they should avoid being overly concrete, which might make their approach seem inflexible or uninspired.

Lessons for Investors

For investors, decoding these signals is critical to identifying high-potential ventures:

• Look beyond flashy pitches that rely heavily on passion without backing it up with tangible credentials.
• Recognize that concreteness can enhance trust in startups with fewer achievements but may indicate a lack of strategic foresight when combined with strong costly signals.

Practical Applications for Stakeholders

This research underscores the importance of balance in business-to-investor (B2I) marketing. Startups must carefully craft their pitches, combining tangible achievements with just the right level of enthusiasm and detail. Policymakers and VC firms can also leverage these findings to design tools and frameworks that help entrepreneurs refine their pitches, ensuring a healthier startup ecosystem.

The art of the pitch lies in balance. Startups that combine credibility with clarity while avoiding overcompensation are better positioned to win investor trust. Similarly, investors who assess both tangible and intangible signals holistically can uncover promising ventures.

Source: Greg Nyilasy, Shangwen Yi, Stephen Ludwig, and Darren W. Dahl, “Business-to-Investor (B2I) Marketing: The Interplay of Costly and Costless Signals,” Journal of Marketing.

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In a new Journal of Marketing study, we find that a higher level of air pollution is associated with greater spending. A quantitative analysis of credit card usage data and experimental evidence further reveals that this correlation is pronounced in hedonic (pleasure-seeking) categories, as products and services in these categories tend to lift the mood of consumers.

Benefits for Retailers

There are several notable ways retailers can benefit from an increase in consumer spending for hedonic categories. We define managerial implications for this group of stakeholders into two broad categories:

1. Promotion and advertising, and
2. Corporate social responsibility and brand image building.

An increase in demand linked to air quality fluctuations presents an opportunity for retailers to develop tailored marketing strategies. Marketers can consider the following examples:

• As soon as the rise in air pollution is noted from the Air Quality Index (AQI) tracking, retailers can leverage displays or signage catering to hedonic consumption and comfort. In-store events, such as a hobby workshop or a wellness product demonstration, can be planned in advance and ready to deploy at the opportune time.

• Retailers can adjust store ambiance (e.g., music and in-store decorations) to serve current customer preferences more proactively.

• Retailers can prepare point-of-sale promotions during periods of high air pollution. These may include instant markdowns, special offers on mood-lifting items, or bundles that include hedonic items of increased demand.

• Retailers may also want to provide sales promotions to counteract an anticipated shrinkage in spending the day following higher air pollution (to correct for overspending) or from big spenders (who are less likely to spend after exposure to pollution).

Ideas for Chief Marketing Officers

Given the ambient nature of air quality, marketing strategies leveraging our results should be capable of quick and effective deployment over a short planning horizon. Chief marketing officers can consider implementing the following ideas:

• Employ digital marketing tactics such as online ads, social media, or customized content. These may include:
  • i) localized display or search ads for products offering enjoyment and comfort, such as gourmet snacks, entertainment gadgets, wellness products, or feel-good promotions on social media, and
  • ii) customized content, such as timely emails advertising leisure activities.

• Improve corporate social responsibility and brand image. For example, a company may want to launch a campaign that emphasizes the importance of self-care to address the effect of air pollution on individual well-being. They may partner with healthcare and wellness experts to generate content and resources that help consumers navigate stress and health concerns related to air quality. This campaign can tie into the idea that indulging in hedonic products responsibly is part of self-care during significant air quality drops.

• Develop a line of hedonic goods and services that are environmentally sustainable, including organic luxury comfort foods or ecofriendly leisure activities. This initiative aligns with the increased demand for such items during periods of high air pollution and reinforces the company’s commitment to sustainability.

Implications for Policymakers

This research is also valuable to policymakers for designing environmental and socioeconomic regulations.

• First, our main findings of increased spending due to deteriorating air quality raise public awareness about a major environmental crisis and its consequences for daily life, making the issue more relevant and urgent. Accordingly, policymaking institutions can develop campaigns that associate air quality with everyday consumer choices and illuminate how environmental health contributes to individual well-being and economic stability.

• Second, increased spending might lead to social costs for the general public, such as overconsumption of pleasure-seeking categories. Insights from this research should help consumers be cautious of their continual and habitual consumption of hedonic goods and services during periods of higher air pollution, while policymakers can promote healthier and more environmentally conscious alternatives.

• Third, our study has implications for household economics in that pollution-induced incidental spending, particularly overspending, may result in the accumulation of revolving debt.

• Finally, our study suggests an opportunity for industry collaboration involving retailers and manufacturers. Joint campaigns could support the development of sustainable practices, providing incentives for consumers to engage in more sustainable consumption (e.g., emphasizing the benefits of sustainable products) and ecofriendly practices (e.g., highlighting the benefits of eco-friendly transportation), hence promoting responsible consumerism.

Overall, we advocate for the execution of marketing strategies with a strong focus on sustainability, aiming to balance business profits with societal values in the face of escalating environmental challenges and practice more responsible marketing for a better world.

Source: Sanghwa Kim and Michael Trusov, “The Impact of Air Pollution on Consumer Spending,” Journal of Marketing.

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When customers choose BNPL installments at the checkout of a participating retailer, the bill is paid in full by the BNPL provider to the retailer. Customers pay the BNPL provider for the first installment at the time of purchase and repay the remaining interest-free installments over a short time period.

However, despite the growing popularity of BNPL installment payments, little is known about their impact on retail sales.

In a new Journal of Marketing study, we use transactional data from a major U.S. retailer and find that BNPL installment payments boost spending. By allowing customers to pay for purchases in smaller, interest-free installments, BNPL boosts both the number of purchases and the average amount spent.

We compare installment payments with upfront and delayed lump sum payments. We find that BNPL installment payments consistently boost spending across various products (e.g., party supplies, apparel, flights, mugs, coffee pods) and number of installments (e.g., three installments, four installments, six installments).

The Power of Perceived Financial Constraints

We uncover two main reasons why BNPL installment payments lead to more spending:

1. BNPL’s impact on spending stems from alleviating perceived financial constraints. In particular, BNPL installment payments increase spending among customers who previously relied more on credit cards and tended to buy smaller baskets of goods. Customers who pay in BNPL installments feel less financially constrained than those who pay an equivalent amount in a lump sum, both upfront and delayed. Customers may focus on the segregated installments (“four installments of $15”) and judge these as less costly than the aggregate term (“total cost of $60”). By alleviating perceived financial constraints, BNPL installment payments encourage customers to spend more.
   
   
2. Moreover, BNPL facilitates budget control. It is often easier to estimate budgets for shorter time frames (”next month”) than for longer time frames. Unlike traditional credit card payments (a single lump sum due at the end of the month), installment payments are segregated into shorter time frames (four weekly payments). By highlighting a shorter time frame, BNPL can give customers a sense of greater control over their budgets. By making payments appear less costly and facilitating budget control, we discover that BNPL installment payments feel less financially constraining. Consequently, this reduction in financial constraints translates into greater spending.

Previous studies have focused on framing prices in aggregate terms ($60/month) or segregated terms ($15/week) and demonstrated that segregating versus aggregating prices has consequential effects on perceptions and purchase intentions. Our work differs from these studies in the following ways.

• BNPL installments go beyond segregated price frames, requiring customers to make actual segregated payments across the specified time periods (”Pay $60 in four biweekly installments of $15”).
• Our research leverages transactional retailer data to study how segregating payments into BNPL installments impacts customers’ actual spending over time. This further enables us to answer managerially relevant questions about how shoppers will likely change their spending (i.e., depending on historical basket size and credit card use).
• Segregating payments makes customers feel more in control of their budgets, alleviating perceived financial constraints. By working through additional mechanisms, our effects not only apply to recurring consumption (e.g., car leases) but also generalize to purchases consumed on a one-off basis (e.g., a flight ticket)

Lessons for Chief Marketing Officers

Our research offers actionable insights for various stakeholders:

• Consumers can benefit by using BNPL installments as a tool for managing expenses by making them feel more in control of their budgets and less financially constrained.
• Retail managers should consider integrating BNPL options to boost sales. Retailers benefit because adoption of installment payments leads to more frequent purchases and larger basket amounts. The difference is significant, with an increase in purchase incidence of approximately 9% and a relative increase in purchase amounts of approximately 10%.
• Policymakers need to be aware of the significant impact BNPL has on consumer spending to ensure that regulations protect consumers while fostering financial flexibility.
• Societal stakeholders, including consumer advocates, should monitor BNPL’s growing influence to promote responsible spending practices.

Understanding the benefits and potential risks associated with BNPL is crucial as this payment method continues to reshape the retail landscape.

Source: Stijn Maesen and Dionysius Ang, “Buy Now Pay Later: Impact of Installment Payments on Customer Purchases,” Journal of Marketing.

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The Black Lives Matter movement and growing demands for corporate accountability have elevated minority ownership labels (e.g., “Black-owned”) as powerful tools for branding. These labels signal diversity and inclusion, but their impact goes far beyond surface-level representation. A new Journal of Marketing study finds that disclosing minority ownership can influence consumer behavior, particularly during product failures.

Our research team explores this phenomenon, which we call the “minority ownership awareness effect,” by analyzing 27,000 Google reviews of Black-owned businesses and conducting experiments with nearly 4,000 participants. We discover that when consumers are aware of minority ownership, they are more forgiving of product failures, especially from those who are motivated to avoid appearing prejudiced.

This effect stems from the narrative of the underdog. Consumers often perceive minority-owned businesses as facing unique challenges, which fosters empathy and leniency in the face of difficulties like delayed deliveries or product defects. However, we also find limits to this effect. Transparency about minority ownership helps mitigate product-related issues but does not extend to moral failings such as unethical behavior or discrimination.

The Power of Minority Ownership Labels

Our findings reveal how minority ownership labels create emotional connections with consumers:

• Fostering Empathy: Minority ownership labels highlight systemic challenges and social inequities faced by underrepresented groups. Consumers view these businesses as underdogs, which triggers emotional support and a willingness to overlook minor failings.
• Mitigating Product Failures: When customers encounter issues like poor quality or delivery delays, awareness of minority ownership softens their evaluations. For example, in reviews of Black-owned businesses, we found more forgiving language compared to reviews of non-minority-owned businesses with similar performance issues.
• Appealing to Consumer Values: Consumers motivated to avoid appearing prejudiced respond even more positively to minority ownership labels. These individuals may see supporting minority-owned businesses as a way to align with their values of fairness and equality.

Limits of the Effect

While minority ownership labels are effective in mitigating product failures, they have limitations. Transparency about ownership does not protect brands from ethical failures, such as cases involving workplace misconduct or discriminatory practices.

Consumers are unlikely to forgive these moral transgressions, regardless of the brand’s ownership status. This highlights the importance of maintaining consistent ethical practices alongside the use of minority ownership labels.

Practical Insights for Marketers

The study provides actionable insights for brands seeking to leverage minority ownership labels effectively:

• Use Labels Strategically: Labels like “Black-owned” or “Woman-owned” can differentiate a brand in competitive markets. These labels not only highlight diversity but also create stronger emotional connections with consumers.
• Build Resilience During Crises: Transparency about minority ownership can help brands navigate product-related challenges by fostering consumer empathy and trust. This approach is especially valuable during product failures, such as issues with quality or delivery.
• Focus on Authenticity: While labels can be powerful, they must be paired with genuine commitment to inclusion and ethical practices. Consumers will reject brands that use minority ownership labels as superficial marketing tactics without substantive action.
• Consider Consumer Values: Marketers should understand their target audience’s motivations. For consumers who prioritize social justice and fairness, minority ownership labels can serve as a strong signal of alignment with their values.

Implications for Policymakers and Industry Leaders

Beyond individual brands, the findings highlight the broader potential of minority ownership labels to drive societal change. By encouraging transparency about ownership, policymakers and industry leaders can foster more inclusive and equitable markets.

Lessons from the Underdog Narrative

The underdog narrative is central to the success of minority ownership labels. Consumers root for businesses they perceive as overcoming obstacles. By leveraging this narrative authentically, brands can build stronger emotional connections and foster long-term loyalty.

However, it is crucial for businesses to understand the limitations of this approach. While the underdog narrative can mitigate some challenges, it cannot shield brands from reputational damage caused by ethical missteps.

The “minority ownership awareness effect” reveals how transparency about ownership can transform consumer relationships. By highlighting diversity, fostering empathy, and aligning with consumer values, minority ownership labels offer a powerful tool for differentiation and resilience.

For marketers, the key is to use these labels strategically and authentically, ensuring they are backed by meaningful actions. For policymakers, the findings underscore the importance of promoting transparency and inclusivity in the marketplace.

This research offers a roadmap for businesses to navigate competitive markets, build consumer trust, and support a more inclusive economy.

Source: Esther Uduehi and Aaron Barnes, “The Minority Ownership Awareness Effect: When Promoting Minority Ownership Increases Brand Evaluations,” Journal of Marketing.

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Our research team uncovers how firms can strategically time their technology launches by aligning internal coordination with stakeholder readiness. Success comes when managers treat timing as a dynamic, strategic process that creates trust, clarity, and excitement among stakeholders.

Key Findings 

The Four Timing Scenarios

We identify four timing scenarios that shape the outcomes of tech launches: 

1. Antagonistic Timing: Low firm coordination and low stakeholder readiness create a “delegitimate” launch moment. For example, Google Glass failed in 2013 because of privacy concerns and cultural resistance. 

2. Synergistic Timing: High firm coordination and high stakeholder readiness lead to a successful launch. Ray-Ban Meta Smart Glasses exemplify this, entering a market now open to augmented reality eyewear. 

3. Flexible Timing: High stakeholder readiness but low firm coordination. Stakeholders drive the market, requiring firms to act swiftly to meet demand. 

4. Inflexible Timing: High firm coordination but low stakeholder readiness. Firms must work to build trust and align expectations to overcome skepticism. 

Timing as a Strategic Process

Timing is a social game that requires tact, patience, and foresight. Launching too early risks overwhelming stakeholders, while launching too late can result in missed opportunities. Success lies in calibrating firm actions to meet stakeholder readiness. 

Firms must build market readiness by addressing four key factors: utility, legislative standards, shared values, and interpersonal trust. These efforts ensure stakeholders view the launch as credible, relevant, and aligned with their needs. 

Lessons from Technology Markets

The journey from antagonistic to synergistic timing often involves reintroducing products that failed previously. For instance, the augmented reality market took a decade to mature after Google Glass, paving the way for current successes. Flexible and inflexible timing scenarios are transitional stages. Managers navigating these moments must focus on bridging gaps between stakeholder expectations and firm actions. For example, firms facing inflexible timing need to create boundaries and trust to make disruptive technologies more accessible. 

Practical Recommendations for Managers 

Understand the Timing Scenarios: Managers must assess whether their launch moment aligns with stakeholder readiness and internal coordination. Identifying the current scenario—antagonistic, synergistic, flexible, or inflexible—provides a roadmap for action.

Managers should be aware that individuals’ timing norms may differ by technology type, as evidenced by Google’s various product launches occurring in different market timing situations: Google Glass was launched in antagonistic timing, Google Gemini and its extension Google Lumiere are facing flexible timing, and Google Fitbit 6 was launched in an inflexible timing situation

Build Stakeholder Readiness: Invest in education, marketing, and regulatory alignment to create a foundation of trust and familiarity. These steps help stakeholders understand the product’s value and reduce resistance. 

Treat Timing as a Continuous Process: Rather than viewing timing as a single decision, managers should approach it as a series of adjustments. This dynamic approach ensures launches remain aligned with evolving market conditions.

Decision Tree

So how can managers make the right decision? We provide a decision tree with suggestions for marketing research:

Before launching a product, managers must ensure alignment between their firm’s and stakeholders’ timing norms (e.g., consumers, influencers, regulators). This involves market research through surveys or interviews to identify optimal timing (see potential questionnaire below). If timing norms align, the market is ready and a launch date can be set immediately. Misalignment requires further analysis of stakeholders’ willingness to adapt, using specific questions to gauge flexibility.

If stakeholders are willing to adapt, managers should use strategies like preannouncements, demos, and soft releases to cocreate an ideal launch moment. Publicizing minor imperfections can help build readiness, especially in market-driving situations. For stakeholders unwilling to adapt, managers should focus on building trust by controlling the product’s scope and allowing gradual changes to prepare the market.

If these approaches fail, managers should consider waiting for the market to mature naturally before revisiting the decision-making process. However, if the market remains resistant, any launch risks failure, necessitating a revision of the product.

Sample Questionnaire

Questions to gauge if a firm’s employee and stakeholder timing norms are aligned:

1. Do you watch out for new technology releases?
   a. Probe: If so, for which product categories?
   b. Probe: If so, how do you hear about new tech product releases?
   
   
2. How do prospective technology innovation releases make you feel? (e.g., excited, horrified,
   worried, hopeful)
   a. Probe: What kinds of technologies are you most excited about?
   b. Probe: What kinds of technologies are you most scared of?
   • i. Probe: What changes would have to happen to switch your fear to enthusiasm
     for the new technology?
     
     
3. Do you feel equipped to incorporate prospective technology innovations at your workplace?
   a. Probe: How do you feel equipped or not?
   
   
4. Do you feel equipped to incorporate prospective technology innovations in your home?
   a. Probe: How do you feel equipped or not?
   
   
5. Do you feel equipped to incorporate prospective technology innovations in your hobbies and
   leisure activities?
   a. Probe: How do you feel equipped or not?
   
   
6. Is [the specific function] of [firm’s new technology] useful to you? (Question relates to
   pragmatic legitimacy pillar)
   a. Probe: If no, can you describe a future situation where [specific function] of this
   technology would become useful you?
   
   
7. Does [specific function] of [firm’s new technology] make you feel anxious? annoyed? angry?
   displeased?
   a. Probe: If yes, can you describe a future situation where [specific function] of [firm’s
   new technology] would not make you feel positive emotions?
   
   
8. In your opinion, are there current laws and official regulations in place to regulate [specific
   function] of [firm’s new technology]? (Question relates to regulative legitimacy pillar)
   a. Probe: If yes, please describe the current laws and regulations that you think apply.
   b. Probe: If not, what laws and regulations should be put in place in the future to regulate
   [specific function] of this technology?
   
   
9. Do you think the world would be a better place overall with [firm’s new technology]?
   (Question relates to normative legitimacy pillar)
   a. Probe: Please describe your answer.
   
10. Do you think [specific function] of [firm’s new technology] can improve your standing
    among your peers at work? Among your family and friends? (Question relates to relational
    legitimacy pillar)
    a. Probe: If no, can you describe a future situation where [specific function] would not
    compromise you with your peers at work? At home and in your social circles?
    
    
11. Can you currently make sense of [specific function] of [firm’s new technology]? (Question
    relates to regulative cultural-cognitive legitimacy pillar)
    a. Probe: If no, can you describe a future situation where [specific function] of this
    technology would make sense to you?
    
    
12. When do you think [firm’s new technology] should be launched?
    a. Probe: Please justify your answer.

Questions to gauge if stakeholders are willing to change their timing norms:

1. Are you willing to change your practices and habits now if a new technology was created that
   significantly improved society?
   a. Probe: If no, can you imagine a future where you would change your practices and
   habits for this prospective technology? What would this future look like?
   
   
2. Are you willing to change your practices and habits now if a new technology was created that
   made your work routines easier and/or more efficient?
   a. Probe: If no, can you imagine a future where you would change your practices and
   habits at work for this prospective technology? What would this future look like?
   
   
3. Are you willing to change your practices and habits now if a new technology was created that
   made your home life and routines easier and/or more efficient?
   a. Probe: If no, can you imagine a future where you would change your practices and
   habits at home for this prospective technology? What would this future look like?
   
   
4. Are you willing to change your practices and habits now if a new technology was created that
   made your hobbies and leisure time more entertaining?
   a. Probe: If no, can you imagine a future where you would change your practices and
   habits during your leisure time for this prospective technology? What would this future
   look like?
   
   
5. Are there certain industries where you are comfortable with a company releasing an unfinished
   technological innovation for consumers to try and test?
   a. Probe: Which industries?
   
   
6. Are there specific industries where you think companies should never release a technological
   innovation before it is fully finished and thoroughly tested?
   a. Probe: Which industries?

Timing is not just about “when” but about “how.” Firms that treat timing as a strategic tool can transform innovation into market success. Whether rescuing a failed product or launching a groundbreaking new technology, aligning firm actions with stakeholder readiness is key to achieving synergistic timing. 

Source: Thomas Robinson and Ela Veresiu, “Timing Legitimacy: Identifying the Optimal Moment to Launch Technology in the Market,” Journal of Marketing.

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In a new Journal of Marketing study, we find that LLMs offer significant efficiency and effectiveness gains in the marketing research process for both qualitative and quantitative research. We show that LLMs serve as excellent assistants for insights managers through different stages of the research process: study design, sample selection, data collection, and data analysis.  

The AI-Human Hybrid Approach  

Consider a business context in which a brand manager collaborates with a consumer insights manager to formulate the problem the research is trying to address and come up with a set of research questions. The two may collaboratively agree on a research design that, for example, begins with exploratory research (e.g., in-depth interviews) followed by descriptive research (e.g., a survey). These first two steps of the research process are largely led by humans. Although the brand and insight managers could consult an LLM to gather secondary research on the topic and explore use cases that could help inform the research questions or research design, they would still largely rely on their knowledge of the business context to formulate the research problem, questions, and design.  

Our central premise is that a human–LLM hybrid approach can lead to efficiency and effectiveness gains in the marketing research process. For this study, we partnered with a Fortune 500 food company and replicated two studies the company had conducted using an LLM. The first study was qualitative and centered around business questions for the Friendsgiving celebration. The second study focused on testing a new refrigerated dog food. For each study, we treated the original (human) studies as the “ground truth” and benchmarked the LLM generated studies against them. This approach allowed us to objectively evaluate the quality of synthetic data and investigate the role LLMs could play in knowledge generation.

For qualitative research, we find that LLMs are excellent assistants for data generation and analysis.  

• On the data generation front, LLMs effectively create desirable sample characteristics, generate synthetic respondents that match those characteristics, and conduct and moderate in-depth interviews. Our results show that LLM-generated responses are superior in terms of depth and insightfulness.  

• On the analysis front, LLMs perform well, matching human experts in identifying key ideas, grouping them into themes, and summarizing information. Although LLMs missed some themes that humans detected, they generated some that humans did not. Expert judges find that human–LLM hybrids outperformed their human-only or LLM-only counterparts. The upshot here is that LLMs and humans bring unique, complementary insights that managers should leverage. 

A Handy Research Assistant 

An LLM can be an excellent starting point for creating the first draft of a survey and can generate survey introductions, screener questions, and demographic questions with relative ease. The LLM can focus on the laborious, repetitive, and uninteresting tasks while the human expert can use this time savings to think more creatively about answers to the business questions and the quality of the insights. 

A significant advantage of LLMs as an assistant is their low cost. We believe that this single factor will contribute toward rapid adoption of LLMs for insight generation. The gains here are likely to be higher for hard-to-reach respondents (e.g., doctors, senior managers) because synthetic respondents do not get tired and can provide lengthy answers to many questions. In the B2B arena where the end users and buyers are not easy to reach, LLMs could be quite helpful in supplementing the information gathered from human respondents. As an intelligent engine, an LLM could be a revolutionary generator of prior information for a wide variety of business questions at a low cost. 

It is important to note that LLMs can be wrong, biased, or hallucinate when not trained on the relevant data. Therefore, a human supervisor is a necessary part of the marketing research knowledge production process. For example, the human can make decisions about when not to ask an LLM for help. This could occur when the information sought is new not only to the company but also to the world. Other examples include marketing research in cultural contexts to understand local customs and traditions, topics with ethical considerations such as targeting vulnerable populations, and obtaining insights from data containing personal information, where LLMs may lack the necessary safeguards for data security and privacy.  

Source: Neeraj Arora, Ishita Chakraborty, and Yohei Nishimura, “AI-Human Hybrids for Marketing Research: Leveraging LLMs as Collaborators,” Journal of Marketing.

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In a new Journal of Marketing study, we find that online A-B testing in digital advertising may not be delivering the reliable insights marketers expect. Our research uncovers significant limitations in the experimentation tools provided by online advertising platforms, potentially creating misleading conclusions about ad performance.

The Issue with Divergent Delivery

We highlight a phenomenon called “divergent delivery,” in which the targeting algorithms used by online advertising platforms like Meta and Google target different types of users with different ad content. The problem arises when the algorithm sends different ads to distinct mixes of users using A-B testing: an experiment designed to compare the effectiveness of the two ads. The “winning” ad may have performed better simply because the algorithm showed it to users who were more prone to respond to the ad than the users who saw the other ad. The same ad could appear to perform better or worse depending on the mix of users who see it rather than on the creative content of the ad itself.

For an advertiser, especially with a large audience to choose from and a limited budget, targeting provides plenty of value. So large companies like Google and Meta use algorithms that allocate ads to specific users. On these platforms, advertisers bid for the right to show ads to users in an audience. However, the winner of an auction for the right to place an ad on a particular user’s screen is not based on monetary value of the bids alone but also the ad content and user–ad relevance. The precise inputs and methods that determine the relevance of ads to users, how relevance influences auction results, and, thus, which users are targeted with each ad, are proprietary to particular platforms and are not observable to advertisers. It is not precisely known how the algorithms determine relevance for types of users and it may not even be able to be enumerated or reproduced by the platforms themselves.

Our findings have profound implications for marketers who rely on A-B testing of their online ads to inform their marketing strategies. Because of low cost and seemingly scientific appeal, marketers use these online ad tests to develop strategies even beyond just deciding what ad to include in the next campaign. So, when platforms do not explicitly state that these experiments are not truly randomized, it gives marketers a false sense of security about their data-driven decisions.

A Fundamental Problem with Online Advertising

We argue that this issue is not just a technical flaw in this tool but a fundamental characteristic of how the online advertising business operates. The platform’s primary goal is to maximize ad performance, not to provide experimental results for marketers. Therefore, these platforms have little incentive to let advertisers untangle the effect of ad content from the effect of their proprietary targeting algorithms. Marketers are left in a difficult position in that they must either accept the confounded results from these tests or invest in more complex and costly methods to truly understand the impact of creative elements in their ads.

Our study makes its case using simulation, statistical analysis, and a demonstration of divergent delivery from an actual A-B test run in the field. We challenge the common belief that results from A-B tests that compare multiple ads provide the same ability to draw causal conclusions as do randomized experiments. Marketers should be aware that the differences in effects of ads A and B that are reported by these platforms may not fully capture the true impact of their ads. By recognizing these limitations, marketers can make more informed decisions and avoid the pitfalls of misinterpreting data from these tests.

Advice for Advertisers

We offer the following recommendations for those using A-B testing tools:

• If your goal is to predict which ad creatives will perform best in a targeted environment—under the same conditions on the same ad platform with the same campaign setting— our advice is to carry on using the available A-B testing tools. Experimenters with this goal may not mind—and even may prefer—that their A-B tests lack balance across ad creative treatments and lack representativeness of the subjects.
• If the goal is to learn how different ad creatives generate different responses more generally, the report of the test should include the disclaimer that the A-B comparisons were made on a subset of the audience, across different mixes of users optimized for each ad separately, where subjects were selected by the proprietary algorithm.
• If the marketing objective is to extrapolate comparisons between ad content for use outside of the current platform (e.g., marketing strategy development, or offline advertising where randomized experimentation and user tracking is more challenging), our advice is to not rely on these A-B tests for causal evidence about the effects of creative content across ads. The analytics team, for instance, should warn that results are confounded by how the algorithm determined which ad treatments were most relevant to different experimental subjects. These disclosures should also be made by academic researchers who use A-B test results for scientific inference.

To summarize, an A-B test may appear to be an easy way to run field experiments to learn about the effects of ads, imagery, and messaging. But experimenters who run A-B tests in targeted online advertising environments should know what they are really getting. Our concern is not the mere usage of certain types of A-B tests. Rather, it is the presentation of results as if they came from balanced experiments and subsequent conclusions and managerial decisions based on those results.

Source: Michael Braun and Eric M. Schwartz, “Where A-B Testing Goes Wrong: How Divergent Delivery Affects What Online Experiments Cannot (and Can) Tell You About How Customers Respond to Advertising,” Journal of Marketing.

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