The eventual death of the third-party cookie is shifting power toward the companies that own their data.
Media companies, especially, stand to benefit from the first-party data they’ve collected over the years, but it’s still not enough in this hyper-competitive, constantly shifting landscape.
The current patchwork solutions of first-party and third-party data leave a lot to be desired, but these companies are shifting toward audience intelligence solutions to fill those gaps.
You need to go beyond first-party viewing data to understand their full media diet. You need to go even further, to understand the hobbies and interests that occupy their time when they’re not watching. And you need to understand the motivations that predict what they’ll do next.
All of this is possible, now. Let’s explore how that progression has played out in practice.
The traditional linear television model was packed with middlemen. The limited audience data available to media companies necessitated a dependency on third-party audience measurement services, such as Nielsen ratings.
These measurement services drove the engine of TV ad sales for decades but were limited to viewership numbers and possibly some basic demographics.
Then came the digital age of content consumption where we saw content-producing companies distributing directly to consumers through their websites and apps. As a result, first-party data like account or profile information and viewing data were finally available for business decisions.
Media companies were able to understand where their subscribers were located (and by proxy, their household income) and explore their viewing habits, which correlated to their interests in the context of the catalog.
This model was a huge step forward in understanding the audiences, but had its own limitations. Companies knew everything that happened within their individual platforms, but little beyond that.
A few years ago, we witnessed a boom in the streaming market which massively shifted how we consume content. The streaming wars are at full throttle and the quickly expanding landscape is creating an unprecedented amount of choice — and competition.
To compete in this brave new world, you need solutions that can capture the nuance of any audience and provide a broader view of the industry and key competitors.
Tools like Helixa fill in the gaps by using machine learning to process vast amounts of online behavior data. The result is a better idea of what your audience is watching, across platforms, along with upgraded demographics and full psychographic profiles. You can use this additional insight to better understand your audience and align your strategy with the things they already care about.
To successfully take an industry-wide view, your tools need to account for the vast range of interests that any of those different audiences may engage with. This is much more difficult than analyzing and segmenting one specific audience.
According to Helixa’s lead machine learning engineer, Luc Mioulet, observed online behavior from Twitter’s API is the best source that checks all the boxes for this type of analysis: The dataset is publicly available, it fires off the right signals for our technology, and it’s massive enough to be both versatile and statistically significant.
“All of the things we engage with on Twitter, and the ways we engage, are a reflection of who we are and what makes us tick,” Mioulet said, “probably even more than self-reported survey data, which can be prone to response biases.”
On Twitter, you can like, reply to, and retweet posts, and tag and follow accounts. All of these actions demonstrate a different level of interest and engagement, and they are all registered in the API as distinct actions, including the frequencies. When analyzed holistically, these millions of actions can then be used to score our sample’s depth of engagement with specific accounts.
Here’s how our clients leverage Helixa to drive business results:
Your audience is cheating on you.
Even though streaming moved the industry from ratings to one-to-one viewing data, that first-party data is only one slice of your audience’s media diet.
A quick poll of our office determined most people had 3-5 services. If you’re lucky enough to be one of them, you’re still missing the majority of what they’re streaming.
Sure, third-party services like connected TVs can offer additional insight, but the average U.S. adult has 10 connected devices at home. There’s no way to know everything your audience is watching, and it becomes even more complicated when you consider what they’re listening to and reading.
Observed online behavior provides the closest thing we have to a holistic look inside your audience’s media diet.
As your audience engages online with the outlets, channels, and services that they care about, those signals are registered, along with their frequencies. Audience intelligence platforms like Helixa can turn these signals into scores that rate an audience’s engagement with each item.
There are some major benefits of looking beyond your own first-party data:
People have entire lives outside of the attention economy of modern media. To understand how to cater to your audience, you need to understand the interests, hobbies, and motivations that take up the rest of their time.
The content they consume isn’t always the best proxy for their interests. After all, we’ve all watched some questionable stuff, especially in the past year.
Luckily, psychographic profiles change the game, illuminating key interests down to the brands they frequent.
Adele Revella, of the Buyer Persona Institute, outlines five psychographic variables, all of which can be discovered in Helixa’s platform:
For example, if you’re a passionate home chef, you’re probably:
Together, these insights are far more valuable than knowing a viewer watched Chopped last Saturday at 2 a.m. (guilty). We can actually tell you that an audience has a lot of home cooks that try to get healthy food on the table for their kids, using top-quality ingredients.
As people, we are multi-dimensional and not easily classified. With the right audience intelligence tools, you can dig into the nuance and do more strategic work.
From April 2010 to Aug. 2010, Twitter’s homepage tagline was: “Discover what’s happening right now, anywhere in the world.” This is probably the tagline that most accurately describes the platform’s unique value proposition.
More than any other social media platform, Twitter is where online culture happens. Sometimes, trends and viral moments are born there. Other times, the platform just amplifies them. But, regardless, you would be hard-pressed to find a cultural moment in the past five years that didn’t cross Twitter’s radar.
These trending topics rise from obscurity at light speed. We update our platform at the pace culture demands and are continuously adding new items to our international catalog of 60,000+ items.
“Twitter is the ideal dataset for the kinds of analyses we run at Helixa,” Mioulet said. “When you look at these actions, it forms a graph that models the ways we are all connected on the platform.”
“That graph is always shifting,” he added, “and we’re able to capture those changes.”
The media industry can be unforgiving, and we have seen what happens to companies that refuse to adapt to the changing tides.
But to adapt in time, you need to see those tides changing in the first place. The patchwork solutions of first-party data and third-party solutions won’t get you there anymore.
If you are mostly limited to what happens in your own properties, you’re missing out on a treasure trove of information that can lead to new pathways for growth.
Audience intelligence solutions can analyze a vast number of different audiences, allowing for many different angles in an insights process not limited to your own properties.
If you’re ready to see our platform in action, just schedule 15 minutes with us. It’s that fast.