Influencer marketing has evolved into a powerful strategy for brands looking to engage diverse audiences. Influencers leverage their broad reach to drive awareness and inspire consumer buy-in, while creator marketing enables passionate content creators to engage and connect with niche communities. Brands are increasingly incorporating both approaches into their communication strategies, with social media being a key platform.
However, with both approaches, the goal goes beyond brand visibility. It’s about achieving third-party validation, where trusted voices, such as influencers or creatives, endorse a brand. While these endorsements may be paid, the willingness of these individuals to put their reputations on the line for a brand speaks volumes. This is essential for building consumer trust, as audiences connect more deeply with authentic experiences shared by relatable individuals than with traditional advertising.
A key aspect of this is ensuring that influencers and creators genuinely reflect the audiences brands aim to reach and ensure they are compensated fairly based on engagement and reach. By prioritizing this, brands can cultivate stronger, long-term relationships with influencers and creators. This approach benefits all parties—influencers and creators feel valued, and brands gain more authentic brand advocacy.
One of the biggest mistakes brands make with creator and influencer marketing is dictating content rather than trusting the influencer or creator to do what initially drew the brand to them. While key messaging is necessary, giving them the freedom to be creative ensures the content feels natural and authentic. When they seamlessly integrate brand messages into their content, it enhances both engagement and credibility.
In this episode of The New Mainstream Podcast, Gabe Mederos, Vice President of Creator Marketing with Edelman, discusses the importance of authenticity, diversity, and relationship-building in creator and influencer marketing.
Meet Gabe: Gabe is a creator marketing professional with extensive experience in influencer relations, strategy development, content strategy, analytics, and leadership. A University of Toronto graduate with over 19 years of PR and communications experience in corporate, not-for-profit and government, Gabe has completed his social media and digital marketing certification. Gabe has held senior digital roles at top Canadian brands such as Scotiabank, TELUS, and Nestlé Purina PetCare.
Gabe is currently a Vice President of Creator Marketing at Edelman, where he heads up the creator marketing function for an assortment of clients in Canada, including Samsung, Microsoft, PepsiCo, and eBay. Gabe is also an Instructor at Humber College, where he teaches social media and digital marketing.
I attended the Quirk's Los Angeles Market Research Event last week, and one thing became apparent: AI is coming for Market Research. I sat through presentations and sales pitches on AI Qual moderation, AI Co-Workers, AI Social Media Monitoring, AI-assisted Survey Creation, Data Analysis, and Report Writing. Towards the end of the conference, I wondered if next year we would all send our AI-enabled robot doppelgangers to listen to AI presenters discussing whether humans were still necessary in consumer research.
That’s not so say that I wasn’t impressed with some of the things AI is capable of doing. AI is revolutionizing market research by streamlining processes and providing faster, more efficient insights. Here are some of the major benefits:
Despite these advancements, AI has limitations that market researchers must acknowledge:
While AI promises many advantages, rapid adoption without careful oversight presents risks:
AI is undeniably transforming market research, but it should be viewed as a tool to enhance, rather than replace, human expertise. Running forward too quickly risks running into a dead-end. The best approach is a hybrid model, where AI handles time-consuming tasks while human researchers focus on interpretation, storytelling, and strategic decision-making.
As AI continues to evolve, the key to success will be striking the right balance—leveraging its strengths while mitigating its risks. Market researchers who adapt, upskill, and find ways to integrate AI effectively will be the ones leading the industry, not just observing its transformation. And hopefully, our AI doppelgangers will decide that humans are useful and nice to have around after all.
The transition from working in large companies to owning a startup is a journey of both challenge and opportunity. For many entrepreneurs, it's a chance to reconnect with their passions, streamline their offerings, and create deeper emotional connections with clients. However, all companies, regardless of size, must navigate the complexities of maintaining a strong brand identity and making decisions that align with their core values.
In today’s competitive marketplace, companies are not only navigating fluctuations in market demand but also facing intense scrutiny in the court of public opinion. Take Target, for example. Once celebrated for its commitment to diversity, equity, and inclusion and its thoughtful multicultural marketing campaigns, the retailer now faces boycotts from consumers and the loss of popular brands that once graced its shelves.
As many brands discovered in 2020, companies that stay true to their mission, vision, and values resonate more deeply with consumers. People invest in brands that align with their values, and when companies genuinely uphold their principles, their community will support them.
In this episode of The New Mainstream Podcast, Maribel Lara, Founder of Beget Love Consulting, shares insights on her journey into entrepreneurship and how authenticity can help brands thrive, even when faced with challenges.
Mental health awareness has seen significant shifts in recent years, but cross-cultural and regional differences still play a role in how individuals perceive and address their mental well-being. A recent ThinkNow study comparing mental health attitudes and behaviors in the U.S. and Mexico offers valuable insights into how people in both countries navigate their mental health journeys.
Download the report here.
ThinkNow surveyed 1,550 Americans and 560 Mexicans ages 18+ from late 2024 to early 2025. The survey was conducted online, using sample from ThinkNow’s DigayGane panel. Quotas were set to ensure balanced participation by age, gender, geographic region and socio-economic status in both countries. We broke out the results by Total Americans, Hispanics, Mexicans and generationally in both countries.
One of the key findings of the report is that approximately three-quarters of adults in both the U.S. and Mexico rate their mental health as "excellent" or "good." However, age plays a crucial role in these self-assessments. Younger generations—Gen Z and Millennials—are more likely to report lower mental health ratings compared to older generations. This trend is consistent across both countries, suggesting that younger individuals may be facing unique stressors that impact their well-being.
Interestingly, U.S. Hispanics rate their mental health slightly higher (79% excellent/good) than the general U.S. population. Gender differences also emerge. In the U.S., men are more likely to rate their mental health as "excellent," whereas in Mexico, women are more likely to do so.
One of the most notable contrasts in this cross-cultural study is mental health diagnosis rates. Nearly 30% of U.S. respondents reported having been diagnosed with a mental health condition by a healthcare professional, compared to fewer than 20% of U.S. Hispanics and Mexican respondents. The lower diagnosis rate in Mexico may stem from limited access to mental health resources and stronger social stigma surrounding mental health discussions.
When it comes to discussing mental health with professionals, U.S. respondents—both in the general population and among Hispanics—have become more comfortable doing so compared to previous years. In contrast, Mexican adults report lower levels of comfort, potentially due to stigma and reduced accessibility to mental health services.
Mental health challenges can profoundly affect various aspects of life, particularly work and personal relationships. Around 30% of respondents in both countries report that their mental health has impacted their professional and personal lives to some degree. However, Gen Z workers in the U.S. are twice as likely as their Mexican counterparts to state that their mental health has significantly affected their work performance.
Amid growing mental health awareness, self-care practices have become a common coping strategy. About half of respondents in both countries report engaging in self-care activities, with exercise being the most popular choice. However, other practices such as meditation, journaling, and using mental health apps are notably more common in the U.S. than in Mexico. This cross-cultural difference may reflect variations in cultural approaches to mental well-being and the availability of digital mental health tools.
The search for mental health resources differs between the two countries. Surprisingly, Mexicans are more likely than Americans to seek out mental health information, with about half reporting that they have done so in the past 12 months. Social media is a particularly important source of mental health information for Mexicans, whereas Americans rely more on websites, personal doctors, and family and friends.
Access to mental health services remains a challenge in both the U.S. and Mexico, though the availability of resources varies. The most widely available resources in both countries include counseling centers or therapists, online information, and community support groups. However, crisis intervention services and hotlines are less common in Mexico, potentially limiting urgent support options for those in need. Mexicans are also half as likely to seek information from friends and family about mental health than Americans.
The ThinkNow report highlights critical cross-cultural and structural differences in mental health perceptions and accessibility between the U.S. and Mexico. While both countries recognize the importance of mental well-being, younger generations, in particular, are struggling with their mental health. Of particular interest is the difference in how mental health is experienced by generation and gender in the two countries. Why are American women less likely to say their mental health is good compared to American men or women in Mexico? Regardless, the key challenge moving forward is increasing accessibility to mental health resources, reducing stigma, and encouraging open conversations—especially in regions where discussing mental health remains taboo.
By understanding these cross-cultural differences, policymakers, mental health professionals, and community leaders can work toward creating more inclusive and effective mental health support systems. Whether through expanding digital resources, increasing the affordability of services, or promoting workplace mental health initiatives, there is much each country can learn from the other to ensure that mental health care is accessible to everyone.
Download the report here.
The United States is experiencing a significant demographic shift, with multicultural communities driving the nation's growth. This highlights the importance of data accurately representing this multicultural reality.
In artificial intelligence and machine learning, the quality and representativeness of data are paramount. Synthetic data – artificially generated information that maintains the statistical properties of real-world data – has emerged as a powerful tool for training AI models. However, the effectiveness of these models hinges on the diversity embedded within the synthetic data.
Without adequate representation of various cultural and ethnic groups, AI systems risk perpetuating existing biases which can lead to skewed outcomes and can reinforce systemic inequalities.
Companies investing in synthetic data are particularly interested in capturing the nuances of diverse consumer behaviors. As multicultural communities drive population growth and influence market trends, understanding their unique preferences and needs becomes essential for businesses aiming to remain competitive. Synthetic data that accurately represents these groups offers a cost-effective way to gain insights compared to traditional data collection methods.
Representation is a significant issue facing AI today. But, by starting with the hardest-to-reach groups, such as multicultural communities, synthetic data creators can address the most complex challenges first. Addressing these challenges results in a more inclusive dataset and leads to higher-quality AI systems overall. Models that can effectively handle the nuances of diverse populations tend to perform better across all demographics, creating more robust and versatile solutions.
Multicultural communities not only represent the fastest-growing demographic groups in the U.S., but they are also leading drivers of economic expansion. For instance, in 2023, the employment rate among Black and Hispanic Americans aged 25-54 reached a record high. These groups also experienced faster wage growth, contributing to higher income levels. Black women are the fastest-growing group of entrepreneurs, while Hispanics represent one of the fastest-growing populations in the U.S.
Businesses that fail to recognize these shifts risk missing out on opportunities to engage with a significant portion of the market. However, these communities are not monoliths. Due to the complexity of these thriving markets, tapping into them from a research perspective, can be daunting.
Generating synthetic data allows market researchers, marketers and strategists to address this growth opportunity in a scalable way. Instead of being hampered by incomplete or biased real-world datasets, they can rely on synthetic data that mirrors the full spectrum of human diversity.
By understanding the value of underrepresented groups, companies can create more relevant marketing strategies that deliver greater value to their audiences.
The future of synthetic data is inherently multicultural. As the U.S. becomes more diverse, it is important to create AI and data solutions that reflect this reality. Training AI with multicultural insights helps create reliable synthetic data, leading to more inclusive applications and ultimately, better outcomes for businesses, consumers and society.
This blog post was originally published on Quirk's Media.
Imagine market research as navigating a vast ocean. For years, we've used simple maps – surveys and panels – to guide us. But the ocean is changing, new currents are emerging, and those old maps just aren't enough anymore. That's where the new online sampling comes in – it's like having a smart compass that shows you exactly where to go and enabling researchers to collect data from diverse, geographically dispersed audiences quickly and efficiently. Removing barriers like travel constraints and logistical delays offers a more accessible and cost-effective way to reach the right respondents. Think of it as a “smart compass” getting you precisely where you want to go.
Think of it this way:
This new approach to online sampling can help businesses:
The future of online sampling is all about being smarter, faster, and more personal. It's about having a smart compass that helps businesses navigate the ever-changing market and reach their destination successfully. It's not just about collecting data; it's about using that data to make better decisions and build a stronger business.
U.S. consumer demographics are shifting, with multicultural consumers projected to become the majority by 2050. These audiences drive population growth, influence cultural trends, and wield significant buying power. For programmatic media buyers, it’s clear that effectively engaging multicultural consumers isn’t just an ethical choice—it’s a strategic business imperative.
Yet, despite their importance, the tools we use to connect with these audiences often fall short. While the conversation around diverse media has gained traction, it’s time we give equal weight to an often-overlooked counterpart—diverse data.
From Hispanic-focused streaming services to Black-owned publications, diverse media platforms have emerged as powerful channels to engage multicultural audiences. The industry’s push to invest in diverse media is paying off, with more brands dedicating budgets to platforms that authentically reflect the communities they aim to reach. However, while media outlets are the vehicles, the data fueling these campaigns often lacks the nuance necessary to drive authentic connections.
Let’s address the elephant in the room: Not all data is created equal. Many programmatic campaigns rely on datasets that fail to capture the complexities of multicultural consumers. Generic datasets often rely on outdated assumptions, grouping diverse communities into monolithic categories. For example, “Hispanic consumers” might be treated as a single entity, ignoring the rich diversity of language preferences, generational differences, and cultural nuances within this group.
This lack of specificity leads to missed opportunities. Imagine a campaign targeting bilingual Millennials who seamlessly navigate between English and Spanish. Without granular data that identifies this segment, a brand risks delivering ads that feel irrelevant or, worse, alienating. These blind spots hinder campaign performance and the broader mission of building trust with multicultural audiences.
So, how do we address these blind spots? The answer lies in diverse data, specifically privacy-compliant data rooted in authenticity. Zero-party data—information willingly shared by consumers through surveys, quizzes, or direct interactions—is a game changer. Unlike inferred or third-party data, zero-party data offers insights directly from the source.
For programmatic buyers, this means the ability to create audience segments that go beyond basic demographics, such as identifying African American homeowners interested in sustainability or LGBTQ+ families seeking inclusive financial services. Programmatic campaigns can achieve greater precision and resonance by starting with strong seed data, ensuring that every impression counts.
One of the greatest challenges in programmatic media buying has been bridging the gap between planning and activation. Survey data has traditionally been used for planning purposes, such as shaping strategy and identifying key segments. However, this data often gets lost in translation when it comes time to activate campaigns.
Diverse data addresses this concern by enabling seamless integration with demand-side platforms (DSPs). For instance, a campaign targeting first-time Latino homebuyers can move from a strategic idea to an activated campaign with minimal friction. This end-to-end connection ensures that the data guiding your strategy is the same data driving your execution.
As Connected TV (CTV) expands, so does the need for diverse data. CTV offers unparalleled opportunities to reach audiences in a highly engaging format, but its effectiveness hinges on accurate targeting. By leveraging diverse data, ads are more likely to resonate with multicultural viewers because they align with their values and identities, driving deeper engagement and maximizing ROI.
The same principle applies across all digital channels, from display to social. Programmatic media buyers have the tools to layer diverse data onto existing programmatic pipes, enabling campaigns that are not only scalable but also deeply resonant.
As programmatic media buyers, we have an opportunity—and a responsibility—to push the industry forward. Investing in diverse data is not just a tactical decision, it’s a strategic one. We must ensure that the stories we tell through media reflect the realities of the audiences we serve. By aligning our media strategies with the growing demand for authenticity in advertising, we can drive growth that benefits both brands and consumers.
This blog post was originally published on MediaPost.