NPAW’s CMO Till Sudworth recently sat down with TEGNA’s CTO Kurt Rao at the NAB Show 2023 in Las Vegas to discuss how this NPAW customer uses video analytics in its day-to-day business to improve the end-user experience.
Kurt joined TEGNA five years ago and worked as a Chief Information and Technology Officer for some time, leading the transformation and growth of the media publishing organization into a global digital content platform company. Prior to Time Warner, he worked as Vice President of Technology for NBCU Television and was one of the founding members of Hulu, responsible for developing the ad tech stack. At the very beginning of his career, Kurt started at Viacom and was responsible for the development of the company’s technology portfolio.
You can watch the video of this interview here.
Before we jump into your current tasks and responsibilities at TEGNA, it would be great if you could give our audience a short overview of what TEGNA does
So, TEGNA is a local broadcaster. In the US, what a local broadcaster does is it has rights to broadcast television and sometimes radio across the country. We have 64 television stations in cities like Dallas, Denver, Seattle, Atlanta.
And, in those cities, we produce about on average 14 hours of content a day. It’s news, weather, sports, local sports, and we distribute it across a multitude of platforms. You know, over the air, we have an antenna, there is your traditional television on digital platforms, on cable satellite and then, as the world and the consumers move forward, increasingly on connected television.
So in all of these areas, we are producing and distributing content. That’s the core of our business. We also have an ad tech business called Premium where we monetize content, not only ours but other providers’ to get through the form of advertising primarily to match local advertisers with consumers.
What are the main challenges you are currently facing?
Yeah, so I think they fall into a few buckets. The first one is, you know, our core business today continues to be a linear challenge television. That’s where our largest audience is. So, in that space, it is all about how do you get more content, the right content in front of consumers, right?
Similarly, in the digital space, as we continue to ramp up digital, the question we work with and what we try to solve is who are the consumers in digital? What’s the kind of content that they look for?
Relative to a broadcaster like an NBC or a network like NBC, we serve very local communities. So, while there’s national news and global content and global news, we’re really focused on what really drives the communities that we serve. So, how do you make your content and your news really pertinent to those small communities?
The second set of challenges is, once you do all of this, what’s the best way to monetize it, right? So, we have a subscription model, we have an advertising model. There, you’re trying to connect your customers, which we call advertisers or subscribers, to our content. How do you match that?
And third one, the big challenge is: what is the future for us as consumer demand changes, as their habits change? How do we make sure we are relevant on a go-forward basis? And really, the way I think of this is, you know, today you have audiences you know, and audiences you don’t know. How do you connect them? How do you get deeper with the people you know today, and then how do you bring people in from the outside?
So, basically, you use analytics mainly to understand your end users better and to better know who they are and how you can monetize them.
Yeah, and I may say it slightly differently. Again, multiple pillars.
The first one is really to understand who your consumer is, right? What are they like? What’s their profile? What does their household look like? What are their interests?
The second is to really determine, why they consume content from us? Why do they come to us and how do you deepen that engagement? And then, the third part is, are there others in the community?
One of the advantages of being local is that you’re serving Dallas or Seattle or Atlanta, you know what that fixed population is. So, if you have a population that makes up to two million in Dallas, you know you could reach a certain percentage, and they, again, deepen that engagement. Then you ask the question: what do you need to do to get others? Why do they go to your competitors? What is it that drives them there? And what is the opportunity to bring them on to your platforms?
What is important to you when working with data in the tech environment? For instance, how important is it for you to have a single source for all the data points you collect?
Yeah, it is absolutely critical and it’s our future. If you go back 5, 10 years, you always had data. You just didn’t have the velocity of data that you have today. And so the challenge today is, you know, I call it, how do you sort of connect all these bread crumbs? So you’re collecting data from the exhaust of a DSB on the added pricing side, you’re collecting data when consumers come to your website or your CTV apps.
But it’s been next to impossible to put all of these together and then really be able to make intelligent decisions about it. So, a lot of people have focused on taking that data and using it for things like personalization. But there is a lot more we could do if you have all of this data in one place and can make rational decisions all the way up on what content should be produced.
So it’s really about knowing the customer from A to Z.
That’s right. It’s a journey, it’s a customer journey.
Would you say there is one single metric that is the most important to you?
I don’t think there’s one single metric, You look at it from different perspectives. In our world, we’ve got at least three big constituents, maybe more. The first one are the folks that are actually producing the content. And they need a set of metrics on how engaged are the consumers. Why are they interacting with our content? What do we need to do to bring them on?
Then you have what I call customers, which are your advertisers. And they’re looking at it very differently. So, we’re looking at what are the interests that they have? What are their affinities? As an example, do they belong to a household with children? Because the advertising message to them is going to be very different to someone that does not have children, single parents, or no kids in the household. And so you have a lot of segments that you try to address and reach on that on the backs of the same content,
The third, is the marketing angle, which is how do you market to those folks? How do you let them know that in the next 24 hours we got a special coming up. And those, you know, what we call is on property, right? So if you’re traditional, you already know they’re coming to you. But then you have this opportunity of people that you do not. So the metric for them is going to be very different in terms of how do I go acquire new consumers and bring them onto our platforms?
In these silos, eventually, you may be right in that you have to get to is there one metric? And so sometimes people look at lifetime value or churn. Those are all things we look at. But I think very specifically, they are applicable in those three areas for us in a slightly different way.
How important is it for you that all departments at TEGNA speak the same language when it comes to data? How do you ensure that the data is understandable to every department and that they have access to the same data?
Some of that I think comes organizationally. What we have done, as an example just from the technology team, we have lots of different groups that serve these customers. So internally, as an example, I have a team of folks that work with the content teams on what’s the workflow solutions, how they produce content. Similarly, I have a team that’s supporting the sales and the advertising process, and then a team on the marketing side.
If you think of those as kind of sort of vertical areas, we also then have to look horizontally across, and so the data piece is a unified team that goes across all of those. So in many ways, that team I think, and you know, when you look at engineers and data scientists, those are the folks that are able to look at the data being captured in those three areas and say, all right, how do I help the right set of people make decisions, or, when they ask questions, how does the data help them make the right set of decisions?
So you got to bring these three things together. Sometimes, not everyone is going to be able to speak that language because they’re all skilled differently. But you have to have people who can connect the dots and make those things happen.
You mentioned how widely spread across the country TEGNA is. How do you manage that?
I think one of the challenges for lots of large organizations is some of them grow organically, some of them grow organically, some of them grow inorganically, and we’re no exception. I’ve talked about how we have 64 stations, but in the last three years, we acquired 15 stations.
And so when you acquire groups of stations like that, it takes time to kind of sort of normalize the tech stack. They come with their own infrastructure, they come with their own processes. So over time, we start to standardize things but it doesn’t happen on day 1.
The second part I’d say is, you know, when we do put in infrastructure, you know, like what we’re doing with NPAW, it’s a one step, right? We start off fresh and it goes in and then, to the extent we acquire new products or new stations or new properties, we say this is the fabric we’re going to standardize on. So it becomes a prioritization exercise, but we strive to get to a one size fits all.
So, you know, one of the things that, even at TEGNA, is not possible all the time, but we use the expression “we got way too many snowflakes”. How do you bring things together, and then, what makes the most sense? One of the expressions we use internally is, you know, is the juice worth the squeeze? It’s a very US term for, but is it worth putting the investment in and is there an ROI for it?
You mentioned acquisitions as well. How do you ensure that all TV stations learn from the challenges and key learnings of others?
I think that it’s not a technical problem, it’s a people and cultural problem. I’m very fortunate. I have the support of our leadership team. And the mission of this company being to serve our local communities. You know, it starts there, right? So everyone’s kind of aligned on how do you do that? And then, you peel the onion back a little bit and say, to do that, you need a certain set of capabilities, whether it’s around process, or whether it’s around tech. And we, I think have been very fortunate in our structure that we do have a hybrid model where some things are standardized and centralized and other things are regionalized, and then other things are localized.
But I think a strong leadership and management team brings all of this together. And so we do have a lot of people at the corporate level and in the field that are able to be influencers on whatever we need to do. As you know, if you’re trying to roll out a new piece of technology, the tech piece is usually easy, it’s getting the people to adopt it. And so you need the folks on both sides to be advocates of what you’re trying to do.
How do you work with external providers and share with them NPAW data?
Again, we’re somewhat early in this journey. Data is becoming a new currency, right? So, in our business, especially in media, we have data, our customers have data. You know, when I think of political elections, advertising is huge for us. They come with their voter registration data. So eventually you’re trying to map these.
So, when I talk about trying to reach the right set of consumers: if I have an auto dealership that has a customer base, they come to us and say, these are our customers, we want to send a message to them. And then they’ll come to us and say, here are people that have come to our dealership but never really transacted. Can we send a different message to them? In that case, we’re sharing our data or their data and ours, we’re combining it together to create that unification. I think there’s going to be more opportunities for that kind of stuff going forward, but we’re still very early in that space.
How do you implement and filter data so that it becomes actionable insights for teams at TEGNA?
Yeah, again, I will be very transparent. I think this is the holy grail that we’re all going after. There’s a tremendous amount of data out there. Platforms like NPAW really help us digest that data. Taking that data and creating a story is a whole different issue. And a lot of times you have to know what questions to ask. So when I think of, to give an example, if it’s an advertiser like an automobile, a car dealership, we could produce a lot of data for them on who saw their ad, when they saw that ad, what program they saw it in. To take that and then to say, of all the people that saw that ad, here’s how many actually walked into your dealership, here’s how many of them actually converted. That’s the art of telling the story.
So what we’re trying to do is take all the kinds of data that we get, put it into a platform like NPAW’s, and then figure out how we assess that to make that journey and make it easier for our sales people to share that story with their customers. Similarly, and something for which we’re very hopeful on the NPAW side, is on the consumer side, taking that data, understanding what’s the lifetime value of that consumer, what is the churn? And then how do you use that data to tell our content people: here’s what the consumer is asking for, how do we deepen that engagement? They want more of this kind of information, less of this kind of information. And then you start to move it up the chain, which is, here are the topics that are really resonating with people, we need to produce more of this content. And then you start to think about, well, if they like this kind of content, what else would they like? So look-alike analysis.
Those kinds of things, again, all come out of data. But someone’s got to be able to take that data and create that story for someone to action on.
What did you do before you had the NPAW Suite?
Some of that I think is very driven by the gut. People in this business know their consumers, know their audiences. So a lot of this, I think, has been really kind of leaning in based on the gut. When you didn’t have this level of granular data, that was the best you could do.
Today, you have a lot more data. And I think the first step, when you have this kind of data, is it reinforces what people have in their gut. The next part of the evolution is then to be able to go to those folks realizing the data is telling them a different story than what they thought was in their gut. And that’s an evolution process. It’s just like any new technology. As people adopt it, they start to realize they can do different things with the tech and the data that they have access to.
How important is it that your analytics tools are customizable and adapt to your needs?
All of us need platforms that are very flexible. If you talk to five different broadcasters, we all probably have a very similar mission. But how we get at it is going to be very different, how your internal processes work is going to be very, very different. So, any platform has to be able to kind of be molded into the way you operate.
It’s my personal belief that it’s much harder for organizations to change based on how a product or a system operates. It’s much easier if the system can be molded into the way you operate. And look, there’s a happy medium there, because you don’t want to over customize things because it becomes a nightmare to manage. But at the same time, if it’s a one size fits all, adoption becomes very, very hard.
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