When we launched ThinkNow Audiences, our goal was simple: put multicultural data where media gets bought. We saw a gap between multicultural insights and how those insights were being activated in media buys, so we built a bridge.

Now, that bridge is getting wider, smarter, and faster.

ThinkNow Audiences 2.0 isn’t just a refresh. It’s a strategic evolution in multicultural research and programmatic media buying. We’ve doubled down on contextual relevance, expanded private marketplace (PMP) partnerships, and focused on what matters most to buyers – culturally relevant campaigns that drive top-line results.

From Demographics to Cultural Context

Traditional multicultural targeting has often been limited to high-level demographics, like age, ethnicity, and language. While still useful, those markers alone do not fully reflect how people engage with media or express their identities in 2025.

Today’s audiences are fluid. They move between languages, cultures, and platforms depending on their mood, the moment, and the medium. So, our audience strategy needed to evolve to capture the nuances of today’s consumers.

ThinkNow Audiences 2.0 introduces a new layer of cultural context built around behaviors, affinities, and signals that reflect this complexity, including:

• Spanglish fluency segments
• Cultural content affinity, such as regional music fans, Latin American sports loyalists, or bilingual comedy watchers
• Crossover consumers who blend multicultural identity with general market tastes in streaming, shopping, and social media

By mapping these signals, we’re creating segments that reach not only Latino, Black, and Asian consumers, but also those from other diverse backgrounds. They speak to who they are and what they care about in the moment they’re engaging.

Why Contextual Targeting Matters Now

The loss of cookies has made contextual data more valuable than ever. While much of the industry is still catching up, multicultural audiences have always been more effectively engaged through context, not just identity signals.

We’ve leaned into the shift to contextual by:

• Partnering with publishers that offer culturally-aligned content environments
• Layering survey-based insights into PMP strategies so inventory reflects not just who the user is, but how and where they consume content
• Building cultural contextual bundles around moments like Hispanic Heritage Month, Día de los Muertos, or Black Music Month

In short, we’re shifting from basic audience targeting to authentic audience connection.

PMP: The Quiet Power Play

A big part of our 2.0 rollout has been focused on private marketplace deals, where we’re seeing serious traction. The agencies and brands we work with are looking for:

• Efficiency with better performance per dollar spent
• Trust through inventory with verified cultural alignment
• Customization through the ability to match creative with context

PMPs allow us to deliver all three. They provide our partners with an easy entry point into multicultural activation, eliminating the need to overhaul their entire media strategy.

We’ve seen success working with Hispanic-focused agencies, Black-owned publishers, and general market programmatic buyers who want to reach growth audiences with more intention.

Built with Cultural Integrity

What makes ThinkNow Audiences different isn’t just the multicultural data. It’s how the data is created. Our segments are built on:

• Zero-party data from ThinkNow’s proprietary research panels, real people voluntarily sharing their perspectives
• Cultural nuance layered in by humans, not just algorithms that assign generic labels
• Validated behavioral signals that reflect lived experiences rather than broad modeled assumptions

ThinkNow Audiences is not repackaged, generic data with a multicultural label on it. It’s original and culturally grounded, the result of over a decade of working at the intersection of culture, data, and media.

Looking Ahead

As we move into 2026, we are committed to making it easier for brands to meet multicultural audiences where they are in ways that are important to them.

ThinkNow Audiences 2.0 is a step forward, but it’s also an invitation to the industry to make multicultural marketing, central, not secondary, to data strategy to drive relevance in marketing and media. The future of audience targeting is not just more diverse, it’s more human, and that’s what we’re building for.

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.

While popular demand-side platforms (DSPs) like Google DV360, Xandr, and The Trade Desk offer powerful tools for reaching vast target audiences programmatically, digital media buyers for Fortune 500 companies face a more profound challenge: effectively spending the massive budgets allocated to them, especially when it comes to reaching diverse audiences. 

While diversity, equity, and inclusion seem to have fallen out of favor in some areas, DEI continues to thrive in others. Consumers are still very interested in engaging with brands that align with their values and show that support, or lack thereof, with their wallets. Future-focused brands see engaging with diverse audiences as a moral duty and sound business strategy for growth. However, achieving this in the digital realm can be difficult, particularly when traditional demographic targeting methods fall short. 

That's where an inclusive perspective on programmatic advertising becomes essential. It's not just about casting a wider net but leveraging insights into cultural nuances, behavioral patterns, and consumer preferences to reach diverse audiences with content they want to see. Doing so eliminates the need to create fictitious audiences or use identifiers subject to restrictions, which are common tactics on DSPs today. 

One key aspect to consider is the concept of zero-party data. Unlike third-party data, which can be unreliable and plagued with privacy concerns, consumers willingly provide zero-party data. It's the information they consciously share with brands because they see value in doing so. Since consumers are self-reporting across a range of classifications and categories, the insights can enrich programmatic strategies, improving campaign performance and ROI. 

Most DSPs, however, lack native capabilities to offer zero-party data to programmatic advertisers. By partnering with third-party providers specializing in zero-party data solutions, digital media buyers can segment their audience based not just on traditional demographics but on cultural affinities, language preferences, and even heritage. This unprecedented granularity unlocks a wealth of insights that enable media buyers to reach diverse audiences more effectively. 

Effective targeting is just one piece of the puzzle. Equally important is crafting messaging that resonates authentically with diverse audiences. This requires a deep understanding of cultural nuances and sensitivities and a commitment to representation and inclusivity in your creative approach. Achieving this demands C-level buy-in and a commitment to inclusion as a core pillar of the company's digital advertising strategy, positioning the brand to enhance its effectiveness in an increasingly multicultural marketplace. 

In closing, big-picture thinking, ingenuity, and an inclusive perspective on programmatic advertising are value-adds to digital media buyers responsible for managing ad budgets for some of the world’s largest brands. Central to this approach is embracing the potential of zero-party data and forging partnerships with innovative third-party providers. Doing so opens doors to new avenues for engaging diverse audiences in a genuine and impactful manner.  

This blog post was originally published on MediaPost.

Programmatic media buyers know that multicultural audiences are a rapidly growing and vital market segment. However, advertisers also know that targeting these audiences can be challenging, especially for those lacking cultural competence. Cultural competence is essential for programmatic media buyers aiming to reach multicultural audiences effectively while avoiding costly mistakes. 

What is Cultural Competence?

Cultural competence is the ability to understand, appreciate, and interact with people from cultural backgrounds, values, and beliefs different from one’s own. While necessary for companies and brands aspiring to reach and engage multicultural audiences meaningfully,  cultural competence is essential for programmatic media buyers who rely on data-driven strategies to target their ads.  

The absence of cultural competence in the multicultural data era can have negative consequences for marketers, so it’s important to remember the following: 

• Data can be biased. The data that programmatic media buyers use to target ads is often collected from various sources, including social media, search engines, and online surveys. However, this data can be biased, reflecting the biases of the people who collected it and the systems they used to collect and analyze it. For example, a social media dataset might be biased toward younger users, or a search engine dataset might be biased toward people interested in specific topics.  

Advertisers unaware of these biases could end up targeting ads to the wrong people or using offensive language in ads, risking the company’s brand reputation and alienating the target audience. 

• Different cultures have different values and beliefs. What's considered acceptable in one culture might be offensive in another. For example, direct eye contact is considered rude in some cultures, while others assume that those who avoid eye contact are rude. It is important to be aware of the cultural differences between the target audience and advertisers to avoid causing unintentional harm that jeopardizes brand health.
• Multicultural consumers are more likely to trust culturally competent brands. A study by ThinkNow found that 63% of multicultural consumers are more likely to trust brands that create ads that reflect their culture. When ads are culturally competent, they signal to the target audience that the advertiser understands them and respects their culture. This builds trust and loyalty, which can lead to more sales conversions over time. 

Programmatic Media Tips 

Wondering how to employ cultural competence when using programmatic media to reach multicultural audiences? Here are a few valuable tips:

1. Be aware of your own cultural biases. We all have cultural biases, even if we're not always aware of them. So, the first step to becoming more culturally competent is awareness. To do this, consider taking a cultural bias assessment or talking with someone from a different cultural background. Then, embrace accountability.
2. Research the target audience. Once you have acknowledged your cultural biases, thoroughly research your target audience. Delve into their culture, understanding their values, customs and belief systems. This can be accomplished by immersing yourself in books and relevant articles, conversing with people from the target audience and participating in cultural events. 
3. Use zero-party data from a cultural research company. Zero-party data is voluntarily shared with companies and organizations by customers via surveys, online forms, applications, polls, etc. Cultural research companies can collect zero-party data from multicultural consumers that deliver insights about their culture. This data can inform programmatic media plans that result in culturally responsible advertising. 

By following these tips, advertisers can use programmatic media to reach and engage multicultural audiences respectfully and effectively.

This blog post was originally published on MediaPost.

Digital media buyers constantly seek ways to maximize return on investment (ROI) for their clients' digital advertising campaigns. But, achieving this goal is often easier said than done, as numerous factors can influence the results of a digital campaign.

Nevertheless, there is a powerful tool that can level the playing field – programmatic data. Below I explore best practices for using persona-based audience data to improve ROI and drive optimal digital campaign results.

Understanding Programmatic Data

Before we dive into best practices, let's take a moment to define programmatic data. Programmatic data is the foundation of programmatic advertising, which is the process of buying and selling advertising space in real time using automated systems. This data can include everything from basic demographics like age and gender to more complex data points like interests, behaviors and purchase intent.

Programmatic data enables advertisers to target their ads to specific audiences automatically so advertisers only spend money on what’s working instead of buying in bulk and having inventory left over. This precision ups the odds of reaching the right people on their preferred devices at the right times. But advertisers need access to high-quality, persona-based audience data to make the most of programmatic advertising.

What is Persona-Based Audience Data?

Persona-based audience data is a type of programmatic data that uses customer personas to help advertisers target their ads to specific audiences. A persona is a fictional representation of your ideal customer based on real data and insights. Persona-based audience data helps advertisers get beyond mere data points to how people actually live and be more intentional in their ad targeting. Doing so not only maximizes ad spend but also creates a better experience for the ad receipt because they aren’t served an irrelevant ad.

Programmatic Data Best Practices

Using persona-based audience data can help you create more relevant ads, improve targeting, and drive better campaign results. Here are some best practices for using persona-based audience data to maximize ROI:

Use Audience Segmentation to Improve Targeting

One of the key benefits of persona-based audience data is that it allows you to segment your audience into smaller, more specific groups. This can help you create more targeted ads tailored to each group's specific interests and behaviors.

For example, if you're advertising a new athletic apparel line, you might create different ads for people interested in running, yoga, or weightlifting. By targeting your ads to specific interest groups, you can create more relevant ads that are more likely to resonate with your audience.

Test and Refine Your Audience Segments

Once you've created your audience segments, it's important to test and refine them over time. This means tracking the performance of your ads for each segment and adjusting as needed.

For example, you might find that your ads perform better for certain age groups or that certain ethnic groups are more responsive to your ads. By tracking your performance data and adjusting your audience segments, you can continue improving your ads' targeting and effectiveness.

Use Lookalike Audiences to Expand Your Reach

In addition to targeting specific audience segments, you can use persona-based audience data to create lookalike audiences. Lookalike audiences are groups of people who share similar characteristics to your existing customers, allowing you to expand your reach to new, qualified audiences.

For example, if you have a group of customers interested in hiking, you might create a lookalike audience based on their interests and behaviors. By targeting this lookalike audience, you can expand your reach to new people likely to be interested in your product.

Use Zero-Party Data to Improve Personalization

Zero-party data is data that customers intentionally and proactively provide to a company, such as preferences, opinions, and purchase intentions. This permission-based data is highly valuable because it allows advertisers to create more personalized experiences for their customers.

Using persona-based audience data combined with zero-party data, advertisers can create personalized ads with a look and feel that resonate with consumers. For example, if a customer has indicated a preference for eco-friendly products, you might use that information to create ads featuring your company's sustainability initiatives.

Using zero-party data also allows you to build stronger relationships with your customers by showing that you care about their preferences and needs. By providing personalized experiences, you can increase customer loyalty and improve customer lifetime value.

Measure and Analyze Your Results

Finally, it's essential to measure and analyze the results of your campaigns to determine what's working and what's not, and programmatic puts all those metrics in one place for easy tracking. By tracking metrics like impressions, click-through rates and conversion rates, you can identify areas for improvement and make data-driven decisions about your future campaigns.

Persona-based audience data is a powerful tool for maximizing ROI with programmatic advertising. By using audience segmentation, lookalike audiences, dynamic creative optimization, and data analysis, advertisers can optimize their targeting and creative elements to create more personalized and effective ads that yield better results and achieve desired business outcomes.

This blog post was originally published on MediaPost.

Conducting market research in the Hispanic market can be challenging, especially for researchers unfamiliar with the community or living in another country. Here is a quick guide to building a representative sample and obtaining accurate results.

Define the study objectives: Before you begin, establish clear research objectives. Determine the information you need and the questions you want to answer. This will help you focus the study and determine the aspects of the Hispanic community you want to investigate.

Segment the Hispanic market: The Hispanic community is diverse with varying cultural, linguistic, and geographical characteristics. To better understand their needs and preferences, consider segmenting the Hispanic market into more specific groups based on factors like country of origin, generation, income level and geographic location. This segmentation will allow for a more comprehensive analysis of each segment.

Hispanics are geographically distributed throughout the country, with certain areas experiencing higher concentrations:

1. Southwest: California, Texas, Arizona, and New Mexico have significant Hispanic populations. In California, cities such as Los Angeles, San Diego, and San Francisco have substantial Hispanic communities. In Texas, San Antonio, Houston, and El Paso have sizable Hispanic populations.
2. Southeast: Florida is home to a large Hispanic population, particularly in the Miami and Hialeah areas. Additionally, cities like Orlando and Tampa also have significant Hispanic communities.
3. Northeast: In the northeastern United States, cities such as New York, Philadelphia, and Boston have considerable Hispanic populations. New York, in particular, boasts one of the country's largest and most diverse Hispanic populations.
4. Midwest: Although to a lesser extent than other regions, the Midwest also has noteworthy Hispanic communities. Chicago, Illinois, and Milwaukee, Wisconsin, for example, have considerable Hispanic populations

Design the questionnaire: Create a questionnaire that aligns with your research objectives and is tailored to the Hispanic audience. Use clear and understandable language, avoiding jargon or complex concepts. Translate the questionnaire into Spanish for those who prefer to respond in their native language.

Consider Hispanic culture: Culture plays a vital role in the Hispanic community's attitudes, behaviors, and preferences. When conducting your research, consider relevant cultural aspects like family, traditions, values, and festivities. Doing so will help you understand how these cultural nuances influence Hispanic consumer purchasing decisions and behavior. At ThinkNow, we have an acculturation algorithm that allows us to profile our panelists based on the number of years lived in the United States, language spoken at home, the language selected in media consumption, and self-identification giving us visibility into how these panelists see themselves, consume media and live their lives.

Use multiple data collection channels: To ensure a representative sample of the Hispanic community, it is important to analyze the ideal data collection channels. At ThinkNow , we primarily conduct online surveys when engaging our Hispanic panelists. We also conduct telephone interviews, focus groups, and in-person interviews to allow us to cater to diverse segments within the Hispanic community and individuals with different communications preferences.

Consider linguistic diversity: English and Spanish proficiency among Hispanics varies. If relevant to your study, offer bilingual response options or allow participants to respond in their preferred language. Through our ThinkNow panel, we can profile respondents based on acculturation level: High, Medium, and Low. High acculturation levels indicate predominantly English-speaking individuals and medium levels denote balanced bilingualism where individuals speak Spanish and English equally. Low levels of acculturation represent non-acculturated individuals who do not speak or adopt the English language.

Analyze the results: Once data is collected, analyze it appropriately. Conduct comparative analyses among different segments of the Hispanic community, and compare them with other relevant demographic groups. Look for patterns, trends, and significant differences to obtain valuable insights.

Remember that each market research study is unique and may require specific approaches. Adapting your research methods and questions to the Hispanic community will help you obtain more relevant and valuable data, enabling informed decision-making in your marketing strategy.

As digital marketing continues to evolve, creating personalized marketing experiences for consumers has become critical to successful marketing strategy. In the past, marketers relied on tools like third-party cookies to personalize the customer journey. But with cookies going away in 2024, it’s more important than ever to collect zero-party data to create those personalized marketing experiences while respecting consumer privacy.

Equally as important, however, is the use of multicultural data. The U.S. is becoming increasingly diverse, with much of that growth driven by young consumers. Using multicultural insights helps to personalize their experiences, thus creating stronger bonds that ultimately improve business outcomes.

Diversity is driving personalized marketing.

According to the U.S. Census Bureau, multicultural consumers currently represent approximately 40% of the U.S. population and are projected to account for 55% of population growth over the next five years. Therefore, brands looking to succeed in the U.S. market must understand the needs and preferences of these consumers. It’s important to remember that people change, societies evolve, and cultures shift. Brands that stay attuned to national population trends and behavioral pivots and make efforts to understand the cultural drivers influencing them are in the best position to engage this consumer market successfully.

Zero-Party Data is permission-based.

Personalized marketing experiences are no longer a ‘nice to have’ but a necessity. Consumers today expect to receive messages relevant to their interests and needs, and marketers who fail to deliver such experiences will be left behind. One of the keys to creating personalized marketing experiences is the use of zero-party data. Zero-party data is data that consumers intentionally and proactively share with companies. This type of data is valuable because it provides insights into what consumers want. As third-party tracking tools retire, zero-party data is becoming one of the most sought-after permission-based tools for engaging consumers more effectively.

Multicultural data aids cultural competence.

Zero-party data, however, is just one piece of the puzzle. Another key component of personalized marketing is the use of multicultural data. ThinkNow research shows that multicultural consumers have unique needs and preferences, and understanding these nuances is crucial for creating effective marketing campaigns. For example, diverse cultures may have different values, beliefs, and traditions that can influence their purchasing decisions. By understanding these differences, marketers can tailor their messaging to resonate more strongly with multicultural audiences.

Multicultural data can also help brands avoid cultural missteps that could damage their reputation. ThinkNow research has shown that multicultural consumers are more likely to engage with brands that prioritize diversity and inclusion in their marketing efforts and are willing to stop frequenting a store that does not. From campaign strategy to execution, multicultural data can help brands build a deeper connection with multicultural consumers by helping them market in-culture, avoiding common mistakes that could prove very costly.

To effectively use multicultural data, it's important to ensure that it is collected and analyzed ethically and responsibly. Brands must take care to avoid stereotypes and assumptions when analyzing multicultural data and should work to understand the nuances and complexities of diverse cultures. Additionally, brands should be transparent about their data collection practices and ensure that consumers know how their data is being used.

In Summary

Using zero-party and multicultural data to personalize marketing experiences has become a business imperative. Multicultural consumers are a diverse and rapidly growing segment of the population, and brands that don't consider their needs and preferences risk alienating a significant portion of their potential customer base. Cookies are on their way out, so the demand for zero-party data will only increase.

By using these types of data in an ethical and responsible manner, brands can create more authentic and meaningful connections with their audiences and drive business success.