In a lot of ways, it’s similar: It involves panels, big data and technology to capture what people are doing online and who they are. As with TV, publishers use measurement to gauge the popularity of their content and value their ad inventory, and advertisers use it to verify that their campaigns are running and reaching their intended audience at the right frequency¹.

While the basic principles and ultimate objectives of TV and digital measurement are similar, the tools, processes and ecosystem involved are very different.

Let’s dive in to understand the nuances of how to measure digital audiences and campaigns.

What do we mean by ‘digital measurement’ anyway?

At the most basic level, digital measurement means monitoring a user’s exposure to ads and content delivered over the internet. When we talk about digital measurement in the media industry, we generally focus on two dominant digital experiences: walled gardens and the open web.²

The key difference between the two is that walled gardens restrict access to their first party data—you know, like a garden locked behind a wall—and the open web does not. Social media sites are an example of walled gardens, whereas sites and apps like Weather.com, Words With Friends and CNN are part of the open web.

This is an important distinction for measurement purposes: Technically, a walled garden should have a pretty clear idea of who is accessing content and seeing ads on its platform. But if other companies want to measure their ad or content consumption within these walled gardens, generally, they have to build custom integrations that are compliant with privacy regulations.

While websites on the open web can have robust and authenticated first party data, it’s not always a given. In those cases, general websites often rely on proxy IDs and other adtech solutions to identify, target and measure users.

Current industry challenges

On the open web, the ongoing deprecation of third-party cookies and device IDs is making it more difficult to identify users and is forcing stakeholders to rethink their measurement approach. Apple’s decision in 2021 to change default app tracking permissions (from opt-out to opt-in) wiped out three-fourths of IDFAs (Apple’s mobile ad IDs) from consideration. And Google is scheduled to phase out third-party cookies in the second half of 2024, the final blow to an ID system that held up for the most part, but was always an imperfect solution. Cookies aren’t people, after all.

For walled gardens, the practice of sharing granular subscriber data with outside parties is largely a thing of the past, even for anonymized measurement purposes. To comply with major data global privacy regulations, walled gardens are now sharing activity data with advertisers and measurement companies in aggregate form, if they’re sharing it at all.

Those are serious challenges for measurement that have forced the industry to look elsewhere for consumer identifiers, signals and attributes. And it all starts with an impression.

What’s a digital ‘impression’ exactly?

Before we get into the details of what a modern digital measurement process looks like, let’s spell out what an impression is.

Impressions measure the number of times an ad or piece of content was delivered to a digital device. While impressions give you the total volume of exposure to your ad or content, it does not measure how many people actually saw it. (That’s reach.) So, for example, if five people saw your LinkedIn ad twice, that means your campaign impressions would be 10. 

Current digital media viewability guidelines to qualify an impression stipulate that an ad must be at least 50% in focus on the user’s screen—not hidden behind another window, for example, or playing in the background—for at least 1 second for display ads and 2 consecutive seconds for video ads. Impression time and viewability thresholds now provide a robust foundation for advertisers and publishers to set the terms of their media transactions.

Now that we understand what digital activity we’re measuring, let’s get into how we measure it. 

5 key steps in the digital measurement process

At Nielsen, we look at digital measurement as a five-step process:

Moving toward cross-media measurement

The measurement industry is under heavy pressure to adapt to massive changes already underway in the digital ecosystem. Advertisers need a clear view of campaign performance across digital devices, confidence in the results, and reliable tools to optimize their campaigns in flight.

But there’s even more pressure to get digital and TV impressions on a level playing field. This is an ongoing effort—what constitutes an impression on linear TV and on digital platforms aren’t the same yet—but thanks to the development of a common ID system and launch of Nielsen ONE, we’re already helping marketers deduplicate reach and frequency across select digital and linear platforms in key markets around the world.

At Nielsen, we’ve also recently launched ‘Always On’ digital measurement with proactive partners like YouTube to emulate the way that linear measurement is done and help marketers turn on digital measurement capabilities on a continuous basis, rather than campaign-by-campaign.

There’s more work to be done for full cross-media measurement to become reality in our industry, but with the right priorities, tools and process in place, we’re closer than we’ve ever been.

Nielsen’s Need to Know reviews the fundamentals of audience measurement and demystifies the media industry’s hottest topics.

Sources

¹For an overview of TV measurement, read Need to Know: How Are TV Audiences Measured?
²Connected-TV platforms and retail media networks share many characteristics with both walled gardens and the open web. Stay tuned for a future Need to Know article on those fast-growing media channels.
³The Nielsen software development kit (SDK) is one of multiple framework SDKs that Nielsen provides to measure both static and video content across platforms.
⁴Nielsen’s Digital Ad Ratings estimate that 37% of digital ad spend is currently wasted on impressions that are off-target, out-of-view or SIVT.

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That complexity stems from the inherent nuances within the community—nuances that are critical considerations for any creator, distributor or brand thinking about engaging with Hispanic audiences. For those that invest in building trust with Hispanic audiences, the upside is significant.

“Building strong ties with Hispanic audiences goes beyond producing inclusive content and effective ads,” says Stacie de Armas, SVP of Diverse Insights and Intelligence at Nielsen. “Latinos value quality media and trustworthy content—the factors that lend authenticity and affirm credibility. Smart brands work within these ecosystems, boosting their standing and building loyalty among the community.”

According to our 2023 We Are All Human and Hispanic Sentiment Study, powered by Toluna, 84% of Latinos say they favor brands that play a positive role in their community, and 63% say they’re more likely to buy from brands that feature people like them in their advertising. 

To activate on these insights, brands and media companies can nurture relationships with the community by:

• Ensuring cultural relatability
• Advocating for authentic representation
• Maintaining consistent brand positioning
• Demonstrating responsibility
• Actively engaging with the community

Build trust through community

Representation, inclusion and cultural relevance are important well before consumers make purchase decisions. People are constantly exposed to brand messaging, and consumers recall brand messages even when they’re not considering a purchase. That’s why building strong brand sentiment, via authentically engaging with the community, is a critical step, regardless of where a person is within a purchase cycle. And when brands build positive sentiment with consumers, the consumers are more likely to become a customer when they ultimately seek to make a purchase.

Balancing language and relevance in media

Watching TV shows and consuming other forms of media hold different layers of significance for different audiences. For Hispanics, the focus isn’t solely on language proficiency or the language in which the content is delivered. Instead, it’s about striking a balance between language preference and the relevance of the content.

Our data highlights this complex relationship. Forty percent of Hispanics state that it’s important for shows to be in their preferred language, while an additional 32% find it somewhat important. Interestingly, this contrasts with 70% of non-Hispanic whites who find language an important factor in their media choices.

These numbers show that Hispanics are highly adaptable when it comes to language; they’re open to consuming content in Spanish or English, provided the content is culturally meaningful and resonant, demonstrating that shared experiences can be more pivotal than language itself. The finding for media and advertisers is clear: Focus not just on the language of delivery, but also on creating content that fits seamlessly into the cultural tapestry of Hispanics’ lives.

In the evolving media landscape, one truth stands out with absolute clarity: the burgeoning opportunity within the Hispanic market. The key to effectively engaging the Hispanic community depends on understanding the critical nuances within this rich tapestry of cultures. A potent mix of cultural relatability, authenticity and inclusion will be the touchstones of successful interactions. Trust building is not an abstract concept; it demands a deep understanding of the individuals that make up the community, and those who invest in understanding stand to benefit the most.

For additional insights, download our 2023 Hispanic Diverse Intelligences Series report. 

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What is big data?

In the linear media world, big data typically refers to two types of data streams produced by the very systems that deliver programming to end users: Return-path data (RPD) from cable or satellite set-top boxes (like Dish or DirecTV), and automatic content recognition (ACR) from internet-connected smart TV sets (like Samsung or Vizio).

In both cases, end users allow data collection on their devices. Cooperation is relatively high because data collection drives not just measurement but also much-desired features like user preferences and content recommendations. An RPD or ACR dataset might cover well over 30 million devices.

Why is big data a big deal?

There was a time when people had only a handful of channels to choose from. A household rating¹ over 60 (like the finale of M*A*S*H in 1983) or even 40 (like the Seinfeld finale in 1998) is unfathomable for a scripted show today. We live in a much more fragmented world, with a very long, long list of programming options.

That’s great for TV viewers, but it complicates things for panel-based research: In a nationwide panel with 101K people, a TV show with a 0.2 rating will be seen by 80 households, and perhaps only one in the Atlanta or Dallas metro area. With tens of millions of devices under measurement, big data makes it possible for research companies to report TV usage at a much more granular level, providing coverage for many more programs with small and often diverse audiences. But on its own, big data was never meant to be used for audience measurement.

Challenge #1: Big data isn’t representative

To transact with confidence, media buyers and sellers need a measurement solution that reflects the population in all its diversity: All age groups, races, ethnicities and many other key demographic and behavioral characteristics need to be present and proportional in the underlying data.

But size doesn’t guarantee representativeness. When analyzing installed counts in the Nielsen National TV panel, we’ve found that homes with RPD are disproportionately older and less racially diverse than the general population. Hispanic households, for instance, are underrepresented by about 30%, and heads of household under the age of 25 are almost entirely absent from RPD datasets. On the other hand, ACR datasets skew younger than the general population, and have more household members, too. Using statistical weighting in big data may hide the issue, but it can’t make up for the missing, unique viewing behaviors of underrepresented audiences.

To make matters worse, a measurement solution relying exclusively on RPD and ACR data would miss over-the-air² and streaming-only households, which are a growing piece of the pie.

Challenge #2: Big data may not capture all viewing behavior

Even if they included representative households, RPD and ACR datasets don’t capture viewing from every set-top- box set in the household or from other TV sets in the home that aren’t smart TVs. Those additional TV sets may play different programs to different family members (like cooking shows in the kitchen, or kids’ programs in the playroom), so not only are big data households not representative of the population, but the big data itself isn’t representative of all the viewing that may be happening in those homes.

A frustrating issue for research companies relying on RPD is that the set-top box often remains on when the attached TV set is turned off. That ‘phantom’ tuning can exaggerate actual viewing by 145% to 260%, depending on the provider. There are models that can be implemented to compensate for it, but without a point of reference—like a panel informed by real viewing—it can be difficult to develop the right heuristics.

ACR isn’t immune from data quality issues either. Some smart TV streaming applications block ACR from capturing the content on screen while the app is in use. It may look like the TV set is off when in fact the content has been blocked by an app. And most providers monitor only a small portion of all available programming. In a recent analysis, we found that ACR providers currently monitor just 31% of all available stations, and 23% of recorded minutes are still coming from stations that aren’t monitored. With no reference fingerprints to compare to, that viewing goes unreported.

Challenge #3: Big data is missing viewer demographics

RPD and ACR providers capture tuning data from millions of devices, but they don’t know who’s watching, which is what advertisers are ultimately asking for.

One way to make up for that shortcoming is to team up with third-party demographic suppliers. Those companies maintain a record of the demographic composition of every household in the country, and a research company might attempt to model who is watching what simply from the total sum of tuning data in a given household and that household’s demographic composition.

A kid’s program? That must be from a child in the house. A wrestling match? That must be from a male viewer. Without a real-life reference point to assist the machine learning algorithm, you can easily see where this type of modeling might break down. Unsurprisingly, it gets progressively less reliable with the size of the household, and that ends up hurting the accuracy of the data for larger families, like those with children, non-white and younger viewers. 

The persistent value of panel data 

For brands and media companies looking for a stable, reliable audience measurement solution, the challenges outlined above are nonstarters. Panel data is critical to overcome those limitations.

At Nielsen, when we analyze RPD or ACR data, we’re able to identify what homes and devices are part of our panels, and compare the tuning data in those homes to the viewing behavior captured by our meters. By using our panels as a source of truth in those homes, we can pinpoint where big data deviates from the truth and develop robust models to adjust for those anomalies.

For example, we developed a methodology to work out where a device is located inside a house and match its tuning data to specific viewers. Another model helps us determine whether a TV set is off while the set-top box is on. Yet another model can sort out device updates that register as extra tuning, as well as situations where a device returns more than one tuning event at the same time.

People, not devices

Ultimately, audience research is about people, not devices.

There’s no doubt that big data is a great addition to the media researcher’s arsenal. It opens the door to more granular reporting than was ever possible in the past. But it’s inherently faulty, biased and, most fundamentally, shortsighted: It captures tuning data, not viewing data.

To fulfill its potential, it needs to be cleaned up, filled in, calibrated and enriched with relevant demographics. That’s where panel data comes in. Machine learning works best with strong training and validation data, and there’s no better training data in the industry than the nationally representative panel data that sits at the heart of today’s media research business.

Note

 ¹ A household rating is the percentage of all households in the country tuned to a given program.
² Programming available via a “signal” from an antenna. Over the air (OTA) broadcasts were the first type of TV available.

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Follow along as we break down panel data: What it is, why it’s important and where it’s headed.

What’s a panel, exactly?

In media research, a panel is simply a group of households or individuals who have agreed to share personal details and take part in regular studies or ongoing measurement of their media usage for a set period of time. 

But not all panels are the same. There are two major types:

Probability panel data, combined with census data that speaks to the income, age and makeup of a household, gives you a statistically accurate look at who is consuming media.

Together, probability and opt-in panels can deliver direct media consumption insights, calibrate and remove biases from census-level data, and ensure the most accurate look at audience engagement across devices.

What are panelists signing up for?

Some panels require active rather than passive participation. Panelists may be asked to fill out regular surveys, press a button to verify that they’re watching TV, or wear a device to capture out-of-home activity like listening to the radio in their car or watching sports at a bar. Other panels don’t require any commitment besides authorizing the research company to install a piece of hardware or software (known as a “meter”) to record their media usage behind-the-scenes: what TV programs they’re watching, for instance, or what podcasts, websites, or apps they’re using. 

Active participation, versus automated measurement, is often necessary to capture the most precise person-level data and maximize its value. To keep cooperation high—which is critical to maintaining high data quality—serious research companies invest heavily in the panelist experience to eliminate friction every step of the way. 

At Nielsen, we have four different kinds of panels: 

• TV  — A probability panel that measures the who, what, how and where of TV and streaming audiences
• Audio — A probability panel that measures in-home and out-of-home audio consumption at the local and national level and consists of both metered and diary markets
• Digital  — Depending on the market, a metered probability and/or opt-in panel that measures ad and content exposure for computers, mobile and across platforms
• Participant — An opt-in panel of registered, non-metered panelists to enhance our measured panel assets with features like big data calibration and identity validation

How are media panels used?

While panel data may be used by research firms looking for consumer trends or government agencies looking to monitor population consumption habits, media panel data is most often used by media companies, brands and advertisers looking to understand content viewership and advertising campaign reach and frequency.

For networks, publishers and other media sellers, panel data helps them know their audience size, habits and trends, which is then used to inform programming, pricing and content distribution strategies. 

For brands, advertisers and other media buyers, panel data is used to understand who’s actually seeing their ads, which platforms their target audiences prefer, and predict how these behaviors may change over time.

Are panels obsolete in the age of big data?

You may be thinking: Do we even need panels now that we have big data from set-top boxes, smart TVs, streaming platforms, social media channels, retail media networks and everything in-between?

That’s a popular misconception.

First off, big data (like automatic content recognition {ACR} data from smart TVs) can tell us what’s playing on screen, but not who is watching, or how many friends and family might be sitting on the couch and watching too. In fact, it’s impossible to tell from big data alone whether a show or a movie is playing to an empty room. Nobody wants to pay for media without an audience.

What’s more, big data isn’t representative of the full media audience. The only way it could be is if everyone used the same technology and had access to the same content available to them. A cable company might have tens of millions of subscribers, but those viewers don’t all pay for the same channels or watch the same programs.

Without the ability to identify real audiences and then pinpoint and represent the demographic profile of viewers, it’s impossible for research companies that rely exclusively on big data to deduplicate audiences across platforms, devices and services—and put the whole story together.

How do you get the best of both worlds?

To be clear, biases that come from sampling or nonresponse issues can cripple a probability panel just as much as a big dataset. But with the right size, the right attention to details and a keen understanding of statistics, a well-run panel is still the best way to represent the general population and provide reliable estimates of audience composition across today’s incredibly diverse media ecosystem.

So, is big data entirely useless? Of course not! Its scale makes it possible to analyze media usage with much granularity, and with the right calibration and people-based modeling in place, big datasets can offer invaluable insights for long-tail programming and hard-to-reach audiences.

A number of organizations, including the World Federation of Advertisers, now believe that the combination of panels and big data is the true future of audience measurement, and many research companies are hard at work developing these capabilities.

Note

^1. Two notable early examples were the National Consumer Panel, launched by Samuel Barton in 1942 under Roosevelt’s Office of Price Administration initiative to measure household consumption of rationed goods during WWII; and the panel behind the Nielsen Radio Index, launched that same year by Arthur C. Nielsen to capture radio on/off and channel tuning activity using an ingenious mechanical device first developed at MIT: the Audimeter.

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The push for change:

Examining LGBTQ+ representation in media and advertising

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The trend toward increasing LGBTQ+ representation in media reflects forward progress for the community, but the road ahead is far from smooth. As recent cancellations and shortened series disproportionately affect queer representation on screen, finding LGBTQ+ inclusive content to help carry inclusive brand messaging may prove even more challenging.

The future of marketing is personal, and audience data is critical in an era where people are looking for content—and brands—they can connect with. In this report, Nielsen examines how gender nonconforming audiences  are more comfortable with brands targeting them based on their sexual orientation and/or gender identity than cisgender audiences. 

When it comes to media content, streaming is leading the way. While LGBTQ+ related video content is limited, streaming platforms account for 87% of what’s available. LGBTQ+ audiences view movies and programs on traditional TV as notably more non-inclusive than movies and programs on streaming services—and so do heterosexual audiences.

Other key highlights include:

• More than 25% of global audiences believe that celebrating inclusivity and sharing positive stories would improve LGBTQ+ inclusivity in ads and content.
• When audiences did receive targeted advertising based on sexual orientation and/or gender identity, 64% say the products and messaging were relevant. 
• Streaming platforms account for 87% of what’s available for representative content, with Black LGBTQ+ content leading representation for the community.

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Headlines aside, people, including the LGBTQ+ community, are increasingly looking for content—and brands—they can connect with. That’s where having a precise understanding of anyone a brand may want to engage with can make all the difference.

In general, our most recent international global LGBTQ+ inclusive media perceptions study found that all audiences are receptive to brand targeting based on sexual orientation and/or gender identity. Bisexuals are the most receptive, as 19.7% say they’re very comfortable with this practice, closely followed by heterosexuals at 19.4%. People who identify as gay are less receptive, as only 13.9% report being very comfortable with this type of brand targeting.

The findings from our study also highlight that non-cisgender identifying¹ audiences are more comfortable with brand targeting than cisgender² audiences. Receptiveness among this audience is highest in Spain, and lowest in the U.K.

To the credit of brands, almost 64% of non-cisgender identifying audiences say that both the products and messages within the targeted ads they’ve received are relevant to them. On the other hand, however, only 26.4% of non-cisgender identifying audiences say they’ve received targeted ads. Among the broader LGBTQ+ community, the percentage drops to just 19%.

While the noise surrounding some recent brand initiatives has grown loud in recent months, the data from our study highlights that brands have more of an engagement opportunity than they’re acting on. That’s where a critical understanding of consumers—customers and prospects—comes into play, combined with the knowledge that the borderless media landscape makes it impossible to limit who does and who doesn’t see something.

Data and technology can help marketers identify audiences and engage with them, but brands can’t control how people share their messages. Said differently, ad delivery is much different from ad exposure. Brand integrity is critical on this front. Compared with the brands that have faced consumer backlash this year, a number of other well-known brands have been praised for upholding their positions on transgender inclusivity, including Victoria’s Secret this past March. And what’s more, a December 2022 GLAAD-Edelman report found that Americans are two times more likely to use a brand that demonstrates a commitment to expanding and protecting LGBTQ rights.

Best intentions aside—and as recent history demonstrates—not everyone is receptive to inclusivity. Brand purpose will always need steadfast support for long-term gains, particularly when there is pushback, as opposition is a real consideration for brands today. Globally, only 25.6% of cisgender people say they’d like programming and advertising to do more to celebrate inclusivity and positive stories about LGBTQ+ individuals. Receptiveness is highest in Brazil (33.6%) and lowest in France (13.8%).

On the subject of LGBTQ+ inclusion, Sarah Kate Ellis, president of GLAAD, says that brands know that it’s good for business. Within the context of recent news, she was quoted in a TIME article, saying that “Companies will not end the standard business practice of including diverse people in ads and marketing because a small number of loud, fringe of anti-LGBTQ activists make noise on social media.”

Despite any short-term effects associated with divided audiences, experts agree that the vast majority of boycotts fail in the long term. Maurice Schweitzer, a professor at University of Pennsylvania’s Wharton School of Business, tells ABC News that boycotts need to be sustained and coordinated—which is rare. Nike stock, for example, is up 48.8% from when the brand faced backlash for partnering with Colin Kaepernick back in 2018.

For additional information, download our latest LGBTQ+ report.

Sources

 ¹Non-cisgender identifying refers to people who do not follow other people’s ideas about how they should look or act based on the female or male sex they were assigned at birth.

 ²Cisgender refers to people whose gender identity corresponds with the sex they were assigned at birth.

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The AANHPI audience has made it clear – through their voices and dollar spend – that they desire for their stories to be seen and heard. In the 2022 Social Tracking of Asian Americans in the U.S. (STAATUS) study — an assessment of attitudes and stereotypes toward Asian Americans — 88% of Asian Americans say they want to see more Asian American characters on TV and in movies, compared with 77% of the total population. Brands and media need to do more to engage the Asian population, and content with Asian representation is winning: Squid Game topped the streaming chart in 2021, Everything Everywhere All At Once dominated the Oscars this year, and in advertising, P&G’s campaign “The Name” and Honda’s “Through the Window” campaign for its CR-V focuses on the Asian American consumer and their unique experiences. Yet, the question lingers: Will the media and marketing industry embrace more AANHPI representation?  

With anti-Asian hate crimes on the rise in the U.S.,¹ advertisers and media companies have a unique opportunity to change hearts and minds. Representation is not only the right thing to do; it makes tremendous business sense.

Connecting with America’s fastest-growing population and their buying power

Among racial and ethnic groups in the U.S., Asian Americans are the fastest growing, according to the U.S. Census Bureau.

As the AANHPI population grows, so does its buying power — as well as the demand for representation in both content and advertising. When a company’s ads are seen in Asian-inclusive programming, it illustrates that the brand sees the Asian consumer, and that it values them. Nielsen’s Attitudes Toward Representation research found that Asians are the most likely identity group to say that they are more likely to buy from brands that advertise in content that represents them. 

The advertising dollars from brands help fund the content that gets created. Prioritizing spend in Asian-inclusive content is an opportunity to influence the media and marketing industry; it can also affect how audiences see themselves portrayed.

Our study found that a quarter of brands are investing just 6% or less in the programs with Asian share of screen at or above the representation of Asians in the U.S. population. Brands with the most Asian-inclusive ad spend invest almost four times as much. 

Affinity within AANHPI community

As AANHPI audiences are drawn to content that represents their community in appropriate, accurate and respectful ways, brands that increase their advertising investment in such content stand a better chance of increasing their awareness within the community. Increased investment in advertising is driving affinity for those categories in the AANHPI community. 

For example, Asian Americans are spending more than the general population in fashion, electronics and travel—three of the top categories where brands are investing above-average ad dollars in Asian-inclusive content. Brands in those categories can differentiate themselves through advertising, reaching consumers who are already spending more, but may not already have an affinity for a particular brand.

AANHPI representation drives audience engagement

Winning eyeballs is still a key metric when media publishers are deciding what content to greenlight. When it comes to attracting the Asian American audience, viewers are looking to TV to be entertained and informed just as much as they’re tuning in to feel seen, connected and inspired. About 30% of AANHPI audiences felt more engaged when a show features a cast member who looks like them, Nielsen’s Attitudes Toward Representation 2022 study found. Evaluating Asian representation overall in the top 1,000 TV programs in 2022, we see that streaming video on demand (SVOD) is leading the way, with more than three times the representation of Asians compared with broadcast and cable. No wonder that in January 2023, Asians in the U.S. streamed more content than any other group – 43% compared with 32.8% for the total U.S. population. With people in the U.S. watching more than 19 million years’ worth of streaming video content in 2022 alone, this also opens new opportunities for all audiences to engage with TV programs that include Asians.

In addition, streaming shows with AANHPI representation are engaging all audiences. In 2022, the top streaming programs with high bingeability score that the total U.S. audiences can’t stop watching, also have high Asian share of screen.

Spotlight

With the ongoing racial reckoning in the U.S., where and how brands show up in content matters even more to communities that have historically been left out of American media. Asian audiences who are still reeling from the effects of anti-Asian hate are continuing to search for content that connects with their experience, showing “people like me” — and are more likely to buy from brands they encounter once they find it. Industry investment in inclusive content opens the doors to a more engaged audience ready to watch content and to buy products and services.

For additional insights, download our 2023 Asian American Engagement Report

Note

¹ In March 2023, the FBI reported that anti-Asian hate crimes in the U.S. were up dramatically from the year earlier (746 incidents in 2021 – the most recent data available – compared with 249 in 2020.

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Seen, heard, valued

Engaging Asian Americans through media

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After the triumph of Everything Everywhere All At Once at the Oscars this year, many people from the Asian American Native Hawaiian and Pacific Islander (AANHPI) community were left feeling incredibly proud of that historic night. For one night, the community saw a moment of triumph, for a story and characters that reflected so much of their real-life experiences.

The AANHPI audience has made it clear – through their voices and dollar spend – that they desire for their stories to be seen and heard. Studios and advertisers can tap into the growing value of authentic stories and inclusive representation to engage an audience that is eager to see itself represented on screen. 

In this report, Nielsen explores the media platforms and content that’s drawing Asian Americans. For marketers, content creators and media publishers, we hope you’ll see there is value – and audiences – to be gained when you embrace our community.

Highlights from the report include:

• AANHPI audiences watch about 27% more streaming content – the platform with the highest AANHPI representation at more than 10% share of screen. 

• Despite a slight dip in representation from 2021 to 2022, streaming programs are still significantly more inclusive of AANHPI people than other platforms. Streaming had more than twice the representation on broadcast and three times the representation on cable. In addition, Asian-inclusive content is highly bingeable and attracts all audiences beyond AANHPI viewers.

• Good content appeals to all audiences
  • 91% of AANHPI audiences and 87% of general audiences are open to content featuring people outside of their identity group. 
  • In addition, the report shows high bingeability scores of Asian-led content across top streaming platforms and opportunities for advertisers to better engage AANHPI audiences. 

• Advertising in Asian-led content delivers value
  • AANHPI audiences are 46% more likely than the total population to buy from brands that advertise in inclusive content.
  • In 2022 brands in the fashion, pet care, electronics and travel categories allocated a significant portion of their advertising budget toward content that features and appeals to the AANHPI community. These are also the categories where Asian Americans are spending more than the general population. 

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With this report, we seek to provide a deeper understanding of how to be more inclusive in TV programming and connect with the valuable audiences who want to watch meaningful content. 

Download the report

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And while some media outlets can fail to resonate with Black audiences, audio—especially radio and podcasts—stand out as efficient and effective channels to engage the Black community and even influence purchase decisions.

Radio, the original ad-supported medium, reaches 92% of Black consumers monthly, and the addition of unduplicated audiences from ad-supported and ad-free streaming music services, podcasts and satellite radio, brings total reach to an incredible 99%. And when you combine reach with exposure time—Black consumers spend over 20 billion minutes with radio in a given week—it’s easy to see the opportunity audio provides for advertisers keen to connect with Black audiences.

A daily companion for millions, radio can be a particularly effective medium for advertisers because it reaches consumers during peak action hours while they are out of home commuting, working—and shopping. And with time in vehicles on the rise after several years of pandemic disruption, radio continues to be the primary audio source for Black consumers in the car.

Of note is the exceptional draw of Black-owned radio stations and their ability to attract and engage Black audiences. Among all audiences, Black-owned radio stations reach 11 million listeners weekly with Black consumers making up 6.2 million, or 56%, of the total audience. In fact, nearly a quarter (21%) of the total Black population is reached by Black-owned radio stations, representing a huge opportunity for brands and advertisers to meet Black consumers where they are—in the car and tuned in to the radio.

Advertisers are beginning to take note of the power of Black-owned stations and are investing accordingly—2022 saw an 80% increase in ad spend with Black-owned radio stations compared to the same period last year.

But even with such incredible scale, Black-owned outlets have not always been a part of the media plans designed to reach Black consumers. Brands and advertisers can change these disparities by proactively seeking out partnerships with Black-owned stations, and investing in content that matters to the Black community.

“Authentic messages, delivered by the voices who are part of the Black community themselves, is an unbeatable combination,” said Deon Levingston, Regional Vice-President Radio One. “Listeners trust Black-owned media outlets, and they reach audiences where it matters, locally and nationally, always providing a microphone to amplify the voice of Black America.”

Partnering with Black-owned stations doesn’t just increase reach, it can also help advertisers keep their brand top-of-mind with consumers when it comes time to make a purchase. Home and personal care brands, for example, can work with Black-owned radio stations to build their brand awareness among Black consumers who are more likely to switch to a new brand based on reputation, according to Nielsen Scarborough. In the year ahead, investing with Black-owned stations presents opportunities for brands to build trust, credibility and their customer base.

Radio isn’t the only audio channel making an impact with Black listeners. Podcasts are also becoming increasingly popular with Black audiences, with 35% of Black daily consumers  just starting listening to podcasts within the past two years. And Black podcast audiences are listening more often and to more titles than they did two years ago, with 44% saying they listen more often, and 35% saying they listen to more titles⁴.

With trillions in buying power at stake, advertisers can’t afford to miss with Black consumers. And while new media like streaming and social media are taking over ad budgets, brands and advertisers looking to maximize reach and impact with Black audiences should embrace audio as an integral part of multichannel campaigns.

Notes:

1.  2020 U.S. Census
2.  Selig Center for Economic Growth, Terry College of Business, The University of Georgia, June 2021
3.  Nielsen Ad Intel, Black-owned radio stations, PPM markets, 1H 2021 vs. 1H 2022
4.  Nielsen Custom Consumer Sentiment Study, March 2022

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