Veterans are undoubtedly our nation’s heroes. They bring with them a set of skills honed through years of service, skills that, if clearly communicated, can achieve the same success in business that they achieved on missions. The key to transferring these skills to civilian roles is breaking down what was done in a military context into terms that show hiring managers how those capabilities can drive results for a company.

Yet too often, employers overlook or diminish this value. Without awareness, unconscious bias and outdated stereotypes can pigeonhole veterans into narrow roles. The reality is that the discipline, strategic execution, and situational awareness cultivated in service are exactly what organizations need to navigate the complexity of the marketplace and rally teams toward common goals. Employers who are intentional about being inclusive and who make the effort to understand these skills gain access to a high-performing, job ready talent pool.

Community-building within organizations amplifies that impact. Veterans’ networks, for example, offer mentorship and onboarding support from the start of the hiring process. Once hired, employee resource groups provide safe spaces that foster belonging, educate allies, and dismantle biases, ultimately creating an inclusive workplace culture. Even smaller companies can take meaningful steps by partnering with local veteran groups to source talent or provide job training.

In this episode of The New Mainstream podcast, Ari Friedman, Talent Development Manager, Global Early Careers at Microsoft, offers strategies for translating military skills into business impact and creating workplaces where veterans can thrive, benefiting both talent and employers alike.

Synthetic sample is changing how we think about data. Once static, data is now dynamic, opening up possibilities we’re only beginning to understand.

What is Synthetic Sample?

No, we’re not talking about bots or fabricated data. These are intelligent models generated from real data that allow us to simulate behaviors, attitudes, and responses of specific populations with a level of precision and control that traditional methods simply can’t deliver. It’s a way to fill the gaps where panels fall short, whether due to logistical limits, participation bias, or market fatigue.

Why Does It Matter Now?

It matters because the landscape has changed. It’s harder than ever to get people to participate in surveys, especially within diverse and underrepresented communities. There’s fatigue, there’s distrust, and there’s noise.

And while the industry continues chasing the “ideal respondent,” at ThinkNow, we’re building robust analytical models based on real data that allow us to generate insights with more agility, diversity, and depth.

The benefits of synthetic sample are clear:

• Speed: No need to wait days to collect responses, we model scenarios in real time.
• Smart Representativeness: We blend panel data, external sources, and demographic attributes to build models that reflect the complexity of the real world.
• Privacy & Ethics: By using anonymized data and advanced modeling techniques, we reduce exposure of sensitive information without compromising analytical value.
• Scenario Exploration: Want to know what happens if one variable is changed or how a group reacts to X or Y? With synthetic sample, you can explore possibilities without launching a new survey every time, saving time and costs.

It’s important to note that synthetic data is not a replacement for people. It’s an amplifier.

Synthetic doesn’t replace human voices, it only enhances them. It enables us to utilize our existing data in more strategic and responsible ways, such as helping to fill data gaps, anticipate trends, and design better questions.

And when we combine that with our real, culturally diverse communities – people who are genuinely motivated to share their opinions – the result is a robust, more agile, and far more representative insights ecosystem.

How we do it at ThinkNow:

Step 1: Integrate real data from our multicultural research.
Step 2: Apply AI and machine learning techniques to model specific audiences.
Step 3: Validate models through observable behavior and direct feedback.

We do all of this with a team that understands culture, context, and the responsibility of representing authentic voices within synthetic models.

The future isn’t just digital, it’s hybrid.

We’re moving past methods that only work “when everything goes right.” We’re investing in research that’s more resilient, more human, and yes, more intelligent. Because in the end, it’s not just about collecting responses. It’s about understanding people. With synthetic sample, we’re opening new ways to do exactly that.

Want to learn more about how ThinkNow is using synthetic sample to improve the accuracy and diversity of research? Reach out. We’re building the future of insights, and you can be part of it.

Are AI tools inclusive? 

We're halfway through 2025 and one thing is undeniable: AI is no longer on the horizon, it is in the room. For the market research industry, this has come faster than most expected. What felt like an existential threat just a year ago is now transforming how researchers approach everything from segmentation to recruitment to data analysis.

But as AI becomes embedded in our workflows, a critical question arises. Are the datasets powering these models truly inclusive? Do they reflect the diverse populations researchers aim to understand, or are they building the next generation of tools on top of the same old blind spots?

Why traditional datasets pose risks 

Market research has long struggled with inclusivity. Reaching Spanish-dominant Latinos, Gen Z respondents and even male participants has always been difficult. Despite decades of effort, many of these groups continue to be underrepresented in online panels and large-scale studies.

Now, imagine deploying AI on top of these incomplete datasets. Instead of closing representation gaps, AI trained on biased data risks amplifying them at scale. Biases that were once isolated can now be baked into algorithms and amplified across the entire research ecosystem, undermining the potential of AI to drive more inclusive insights. 

AI’s pivot from threat to tool

When AI began gaining traction in the industry, initial skepticism emerged among some researchers, particularly regarding the use of synthetic data and AI-powered moderators. These tools seemed impersonal, disconnected from the human insights that drive understanding and trust among respondents.

Yet, over time, AI has proven itself capable of complementing, rather than replacing, researchers’ work. Instead of diluting what makes insights meaningful, AI can expand them by enabling researchers to finally address representation issues that more conventional methods have never been able to. This shift has prompted a more intentional approach to innovation. If synthetic data is going to shape the future of insights, it must be inclusive by design, representing the full diversity of the populations it aims to model.

How market research drives ethical AI

The market research industry is uniquely positioned to lead in this space. While many tech companies face lawsuits for training AI on copyrighted or illegally scraped data, researchers have operated under strict privacy laws like GDPR and CCPA for decades. Upholding consent, data stewardship and adherence to ethical standards has been the norm.

Our datasets are not only large, but they are also permission-based and carefully vetted. This makes them ideal for training AI models that need to mirror real-world diversity.

But it is not enough to have access to data. The same rigor applied when building representative samples must be applied to training AI models. This means proactively identifying gaps, asking who is missing from the data and taking measurable steps to responsibly include them.

Rethinking multicultural market segmentation

This brings us to the future of multicultural segmentation. Relying solely on broad demographic categories or historical internal datasets is no longer sufficient. Today’s consumers are multidimensional, and AI gives us the tools to see them more clearly. 

To generate synthetic data that accurately reflects multicultural audiences, it is essential to incorporate information from historically underrepresented communities. This requires collaboration between technologists and cultural experts, as well as a commitment to designing systems that accurately reflect the reality of diverse identities.

For researchers generating synthetic datasets, combining privacy-compliant methods with culturally rich data points, powered by AI, helps ensure that communities often left out of the conversation are fully represented moving forward. 

The road ahead

AI is not a passing trend. It is here to stay, and it is reshaping how we segment audiences, recruit respondents and activate insights. However, AI’s success depends on the quality and inclusiveness of the data behind it, and the researchers guiding its application.

For market research professionals, this is a challenge worth embracing. With deep expertise, ethical frameworks and a foundation in representative sampling, the industry is uniquely positioned to ensure that AI serves all communities, not just the most accessible ones.

The future of multicultural segmentation will belong to those who successfully integrate innovation and intention because the question is no longer whether to adopt AI, but how to use it in a way that advances representation. 

Those investing in synthetic data and inclusive segmentation strategies play a crucial role in achieving this, and those seeking better representation in data must continue to demand it.

This blog post was originally published on Quirk's Media.

Let’s face it! Traditional research panels aren’t cutting it anymore.

For years, market research has relied on large pools of pre-profiled individuals, often referred to as “panels,” to generate insights at scale. And while panels gave us reach and reliability, they also lulled the industry into a comfort zone, where respondents became data points, not people.

But the world has shifted. Audiences have evolved. Attention spans have shortened. Expectations have skyrocketed.

At ThinkNow, we believe it’s time to rethink how we engage respondents not as panelists, but as people.

The Problem with the “Professional Respondent”

You know the type, the person who’s in 15 panels, knows the right answers, and is simply rushing to the incentive. They’re the product of outdated engagement models where surveys are transactional, not relational.

This results in flat data, low authenticity, and insights that don’t reflect reality, especially when researching diverse, underrepresented communities where trust and context matter.

What Needs to Change?

The industry must move from mass reach to meaningful engagement. That means:

• Contextual Relevance: Surveys that reflect people’s lived experiences, languages, and cultural realities.
• Trust First: Especially with multicultural audiences, engagement starts with trust, not a survey link.
• Mobile-First, Human-Centric Design: It’s 2025 — stop designing surveys like it’s 2009. Respondents expect intuitive, mobile-first experiences.
• Rewarding Value, Not Just Time: Incentives should feel fair and respectful, not like a barter system for opinions.

Turning Panels into Communities

The online sample team at ThinkNow is building more than panels. We’re nurturing communities of people who want to be heard and willingly share their opinions, providing zero-party data brands can trust. Our approach combines cultural fluency, smart segmentation, and behavioural insights to go beyond checkbox answers.

We're also exploring new frontiers, including synthetic data modeling, AI-driven recontact strategies, and authentic content integration that makes surveys feel less like tests and more like conversations.

Because at the end of the day, insights don’t come from checkboxes. They come from connection.

The Way Forward

It’s time we ask ourselves: Are we collecting data, or are we listening? The future of market research lies in making every respondent feel like their voice matters, because it does. Let’s ditch the dusty “panelist” label and treat our respondents like what they truly are: individuals with stories, context, and value.

When we do that, the insights take care of themselves.

For many entrepreneurs, success isn’t just about top-line growth. It’s seizing opportunities to break barriers and shape their identities as cultural and economic drivers. That’s especially true within the Latino community, where small businesses continue to power economic growth in both the U.S. and Mexico. But thriving in today’s marketplace requires more than determination and grit. On a practical level, it takes access to digital tools.

One of the biggest barriers for Latino entrepreneurs remains the digital gap. During the pandemic, many small business owners, particularly in underrepresented communities, found themselves forced to adapt overnight. They made a digital leap in three months, setting up e-commerce and learning video conferencing, that others took years to accomplish. Their determination highlights a crucial truth for marketers: to reach multicultural audiences, you must meet them where they are, not where you assume they should be.

Adaptation means more than bridging the digital divide, however. Global companies have traditionally viewed Mexico as just a source of inexpensive labor or materials. But today, it’s a hub for innovation, driving change not just in Mexico but worldwide. For brands, this means rethinking how they engage with the Mexican and broader Latin American markets, seeing them not just as suppliers but as partners and sources of influence.

In this new episode of The New Mainstream podcast, Israel Serna, entrepreneur and Partner Marketing Manager at Autodesk, shares how his work in digital education, entrepreneurship, and cross-border collaboration is reframing what it means to do business in a global, multicultural economy.

Meet Our Guest: Israel Serna 

Digital Marketing Strategist | Small Business Advocate | Bilingual Trainer & Speaker 

Israel Serna is a bilingual marketing strategist, brand consultant, and speaker with over 15 years of experience spanning tech, small business development, SaaS, and the design and interiors space. His expertise includes partner marketing, digital strategy, brand positioning, and content development—helping businesses and creators connect authentically with diverse audiences. 

Known for blending creative vision with data-driven insights, Israel approaches every project with cultural fluency, empathy, and a belief in purposeful growth. In addition to his marketing work, he curates antique collections and supports design-focused ventures bridging the past and present. 

In a digital environment where attention spans are measured in seconds, traditional metrics like clicks and views offer an incomplete picture. They tell us what users did but not what they saw, felt, or understood. Which parts of the creative actually registered with them? Did the ad spark interest, confusion, or indifference?

That’s where online neuroresearch comes in. By analyzing visual attention, emotional response, and cognitive load, marketers can move beyond surface-level performance to discover how audiences truly engage with content. The result is a sharper creative, stronger messaging, and a deeper understanding of what drives real impact.

Technology Reveals What Traditional Metrics Miss

With today's digital tools, it’s possible to conduct neuroscience-based research entirely online — no lab or specialized equipment required. Technologies like remote eye tracking, facial coding, and EEG sensors can now be deployed directly from a user’s computer or mobile device in a natural and familiar environment.

This shift enables marketers to evaluate a wide range of assets, from video ads and social media content to display banners, landing pages, and full user journeys. By going digital, researchers get instant insight into what captures attention, what emotions are triggered, and how cognitively taxing the experience is, all without leaving the screen.

Actionable Insights Before Launch

Unlike traditional metrics that show what happened, digital neuroresearch helps us understand why it happened. We can identify which visual elements attract attention, when users disconnect or feel confused, and which moments spark positive or negative emotional responses.

These insights empower teams to make data-driven adjustments to campaigns before they go live, such as reworking layouts, refining messaging, tweaking video pacing, or emphasizing emotionally resonant elements. It’s especially effective for early-stage concept testing, A/B comparisons, message validation, and UX optimization.

Seeing Beyond the Obvious

At ThinkNow, we integrate these tools into digital studies to capture real-time, real-human responses. That is, what users see, feel, and process as they interact with advertising campaigns. It’s a smarter way to move beyond vanity metrics like clicks and views, and uncover insights that drive ad effectiveness.

If you’re interested in applying this technology to your next study, reach out. We’d love to help you discover what your campaigns are truly communicating.

Contact: ventasfullservice@thinknow.com

Inclusive marketing isn't just about doing the right thing—it’s about doing what works. When companies fail to speak the cultural language of their audiences, they risk more than lost market share. Brands lose trust, relevance, and relationships. But when inclusion is rooted in strategy rather than performative gestures, it becomes a powerful business driver for long-term growth.

Even in industries not typically associated with emotional connection, like utilities or manufacturing, marketers can find more meaningful ways to engage. That starts with listening to real people, using data to understand their needs, and communicating in ways that reflect their everyday lives. The goal isn’t to craft the perfect message for everyone as much as it is to show each group that they matter.

The same applies inside the workplace. Inclusion has to go beyond written policies and procedures and glossy posters on the wall. It must be part of everyday actions being taken and decisions made, showing up in how people are treated, included, and supported. That means being mindful of the different life experiences employees bring, whether they have children or not, are married or single, or navigate life in a myriad of other ways, and ensuring every team member feels valued. When inclusion is lived, not just stated, it creates a culture where people feel safe to contribute, grow, and thrive.

In this episode of The New Mainstream Podcast, Crystal Marie McDaniels, Senior Manager of Product Marketing & Acquisition (B2B) at Duke Energy, shares how leading with inclusion in the marketplace and the workplace builds stronger brands and better teams.