Month: October 2021

The power to engage and inspire consumers involves innovative grit, and brands around the world aspire to rise above the rest by creating ads that consumers simply can’t bypass. Lofty aspirations aside, however, we know there will always be at least some resistance to advertising—no matter how inspiring it may be.

Advertising remains vital to the media industry, but the growing array of content options presents two primary challenges for advertisers: 1) Consumers don’t all experience the same content and 2) Ad-free experiences are available—for a price—and they appeal to many. 

While brands shouldn’t abandon their traditional advertising strategies, they certainly do need tailored initiatives to engage with their audiences—especially as the media landscape fragments across platforms and services. Importantly, there is an opportunity for strategies to focus on more than traditional advertising.

From an engagement perspective, branded content can be an effective alternative because it’s typically developed to resemble editorial content instead of traditional advertising. Given the heavier focus on storytelling and brand journalism in this type of content, Nielsen’s Branded Content Effectiveness studies have found that viewers of branded content are 62% more likely to react positively than those who watch 30-second TV ads. Additionally, 67% say they find branded content more entertaining, relevant and more likely to help them remember the brand.

Immersive gaming experiences are another growing opportunity for brands, including those that aren’t closely connected to video game culture. Mastercard, for example, is a brand that few would likely associate with esports, yet it has found notable upside in the space. In addition to reaching an audience that differs from its traditional clientele, Mastercard’s integration in Riot Games’ League of Legends Championship (LCS) series allows players to keep their card on file and use it for in-game e-commerce use.

Despite the growing range of newer marketing options, marketers surveyed for this year’s Nielsen Annual Marketing Report said they’re not interested in new ad formats like branded integrations and product placements. Only 19% said they consider these options very or extremely important, and 31% said they consider these formats very or extremely difficult to measure.

Measurement remains a hurdle for many advertisers, especially in non-traditional marketing efforts, such as product placements and brand integrations. These strategies  in TV programming and movies aren’t new, but assessing their impact has been a long-standing challenge. 

To help in this regard amid the rise of ad-free SVOD programming, Nielsen developed a metric that allows for SVOD brand integrations to be tracked in ways that put it on the same playing field as traditional advertising—using the traditional 30-second ad spot as a baseline.

To illustrate how brands and agencies can leverage this metric, Nielsen analyzed the viewership of the Netflix program Cobra Kai to assess the equivalized value of the branded integrations within the first four weeks the program was available to stream. Coors is the most prominent brand in the program, and the show’s lead character Johnny Lawrence drinks a lot of it. That favoritism pays off, as Coors exposures garnered almost 170 million equivalized and valued impressions among viewers 21 and older through the first four weeks the program was available on Netflix.

Branded integrations in SVOD content also provide marketers with incremental reach. Importantly, traditional television continues to reach a broad range of consumers, but a notable portion of streamers don’t watch any linear TV. For example, between Aug. 28, 2020, and Sept. 3, 2020, 10.4% of Cobra Kai viewers didn’t watch any linear TV. That means understanding channel preference and engagement has never been more important for brands looking to engage with media-savvy consumers—across SVOD platforms and all other channels.

For additional insights, download our recent Advertiser Playbook, which identifies five top advertiser challenges and highlights ways to navigate them.

As the end of 2021 comes into focus, the ripple effects of the pandemic aren’t the only disruptive factors for advertisers to contend with. Channel fragmentation, privacy, ad avoidance and social responsibility are additional considerations that affect everything from marketing strategy to channel choice to message tone.

The media landscape and shifting consumer preferences present an array of challenges for brands to navigate, but many pertain to a handful of universal hurdles that brands must navigate regardless of industry. Of these, advertisers are facing five key pain points:

• Ad avoidance
• The changing face of targeting
• Sharing brand ownership with consumers
• Growth and budgeting
• Measurement

To assess and overcome them, brands must have a holistic understanding of the media landscape and a comprehensive picture of consumer behavior. With that information as a foundation, brands can develop advertising strategies that bypass existing and future challenges to ensure efficient, effective and data-driven business growth.

There’s been a lot of energy and excitement in media circles of late about the future of measurement and the promise of big data. At Nielsen, we’ve long understood the value of big data, in fact just last month we announced additional details around how we are adding it to our national TV measurement service. 

We also know that no panel is perfect, as the past few months have demonstrated. 

But when our teams of data scientists hear some of the big, broad claims about big data coming to save the day and fix all the perceived challenges in the industry, it’s hard not to be skeptical.

That’s because, for all it’s value and amazing potential, the big data sets that the industry currently has access to have very real limitations. 

A relevant recent example

After losing access to Nielsen’s Portable People Meters, Comscore reported that it will now be using data sets from Experian’s ConsumerView to help them identify individual viewers for measurement purposes. Their announcement was framed in the trade press as an advancement – after all, if big data is the future, any shift in that direction must be a good thing. 

Unfortunately for their customers, and for consumers, that’s not the case. 

There are a handful of third-party identity vendors out there who provide the ability to match data sets based on personally identifiable information and provide demographic characteristics, both directly collected and modeled. 

At Nielsen, we regularly check this data. We do it by directly measuring information from our robust panels to validate how accurate these data sets are in 1) correctly matching to a household and 2) accurately reporting demographics and characteristics. 

What we typically find should give advertisers pause. 

The majority of data sets out there today are built around billing information or online behavior collection, not demographic profiles. They don’t have the rich details about exactly who the people are on their lists—from age, to income, to race and ethnicity—the way you do with a robust panel. These data sets, because they’re created by machine-to-machine transfers, also increase the possibility of waste and fraud. 

Because of that, the level of certainty they can provide around who actually lives in a given household is limited. And they have no ability to say who within a given home is watching a given program at a specific time. 

Even when you triangulate that data with other sources, you’re almost guaranteed to have massive gaps and errors in your estimates. This may be acceptable if the use case is targeting, but this data on it’s own does not provide the accuracy, objectivity and transparency required to deliver measurement. 

Why it matters

So what does that practically mean? Well, it has a few implications. 

In the case of Comscore’s shift away from our Personal People Meters, which actually affix microphones to ~100,000 real life, verified people and track exactly what they’re watching, 

to a model that uses billing data to provide guesstimates of who within a dwelling might be watching a given program at a given time, the result will be a less accurate read on who is watching what. 

But the possibly bigger implication is that this shift is going to get the industry further away from capturing a true representation of the country. 

We know that many of these types of data sets do a better job of providing data around households when the people living there own their own home and have been there for a long time. And that stands to reason. The problem with that is that long-time homeowners tend to be more White, more affluent and significantly older than the nation as a whole. By design these data sets undercount Black and Brown people, lower income people and younger people, at a time when all of those segments are growing, not shrinking. 

The same is true of data sets built off of set top box data, which tends to overcount more affluent consumers who are willing to pay more for cable packages and thus disproportionately excludes lower income consumers who are important targets for many marketers. 

The media industry has, rightly, made accurately representing Black and Brown communities a central priority. At Nielsen our track record on this going back decades hasn’t been perfect, but today we have the most accurate and advanced view of the nation as it truly is. 

Big data-derived measurement tools that aren’t backed by a representative, validated and audited panel can’t make that claim. Nielsen panels can target many demographics within the census with 1% variability, but the big data-focused options out there aren’t even close to that. The industry needs to be open and honest with itself about the challenges that big data presents when it comes to representation.

A wider problem

To be clear, this is not just a Comscore issue. This is an issue with all the big data sets out there currently. 

In August of 2020 the ANA, in partnership with the MRC and Sequent Partners, used Nielsen data as a benchmark in a study designed to understand the degree to which the multicultural audiences were being accurately represented in media targeting. The study looked at an aggregated collection of high-quality marketing and media data and sought to understand how accurately it was targeting Black, Brown and Asian audiences. The findings were troubling, but not at all surprising to us. 

The study found that the big data sets the industry relies on weren’t up to the task of accurately targeting these critical communities. In part because the data sets weren’t designed to capture rich data about who these consumers truly are, the way robust panels are, there was rampant misrepresentation and underrepresentation in the data. 

Now contrast that with Nielsen’s robust panels, which provide a wealth of directly collected information from real-life people, representative of the entire U.S. population. Who lives in the home?  How old are they? What race and ethnicity do they identify as? Who is watching the television at a given point in time? Nielsen’s panel answers these questions. 

Again, panels on their own aren’t perfect, but there’s a reason other industries, namely pharmaceuticals, use approaches that are similar to panels in approving drugs. That’s because, when the stakes are high, there’s no substitute for real, verified people.  

We know that many industry players are excited about the promise of big data, we are too. But as an industry we need to be honest about what big data can and can’t solve for. And we too understand that the future of media measurement is an approach that combines the reach of big data with the verified personal data of robust panels.

This article originally appeared on Next TV.