NPAW’s Bruno Giner Talks Insights-Driven Streaming at Streaming Media 2025
Bruno Giner, VP Sales, Global, at Nice People At Work (NPAW), discusses the importance of insights in streaming optimization and how NPAW works with its collaborators and partners to cultivate a data-driven and data-sharing culture across the streaming industry in this interview with Streaming Media contributing editor Timothy Fore-Siglin from Streaming Media 2025.
What NPAW Does
Giner explains that he’s responsible for NPAW’s digital experience intelligence vertical, which aims to unify “the whole digital experience of the end users to support business decisions and automation and customer experience orchestration, using unification of these data points that we know about how users are behaving in any video platform.” NPAW offers end-to-end data intelligence, including monitoring infrastructure, doing content delivery optimization, and tracking quality of experience.
Fore-Siglin notes, “The company has been around for quite some time and obviously has made an impact in the industry. Enough so that you were on a panel this morning around thought leadership in the industry.” He asks Giner to share his thought leadership standpoint.
NPAW started as a data provider and has a history of quality-of-experience solutions, Giner says. It evolved into insight, i.e., looking into how something happens and then why it happens based on the data-driven culture of the industry. Giner says the company now asks, “How can we optimize using the data to optimize directly the end-user experience?” AI supports this goal, which he calls “very exciting to witness.”
Fore-Siglin adds that NPAW started out using real user monitoring (RUM), which “was great because it gave us a lot of information, but it’s also really hard to aggregate that into actionable items. Does the machine learning part/AI help with taking that data and turning it into action?”
“Absolutely,” Giner says. The capacity for data processing has changed a lot, and NPAW is focused on “tracking how many events are happening, how many actions” and on asking, “How’s the evolution of my x KPI?” Giner explains, “And that can be the engagement level of my users combining 10 different metrics on number of sessions per day, per month, whatever; a number of titles watched; level of engagement with different genres; all of that. It’s very, very democratized and evolved at this point. So we can process a lot of metrics in real time.”
He continues, “Using AI or machine learning to process the insights, it’s the only way to get to real outcome. I mean, we cannot depend on human beings [to be] looking at dashboards and trying to draw decisions. So for us right now, it’s one very, very important step to try to invest on building agents that can … give [information] to the humans” for processing; humans can make “decisions that really are dependent on strategy, on creativity, and so on that only humans can make.”
Standardization and Algorithms
Fore-Siglin addresses the importance of data standardization, noting that he’s heard that AI can be used agentically to build dashboards that showcase data in a standard form, “which ideally we’d like to see the industry do as a whole.” He notes that agentic AI can “essentially build a dashboard that’s customized just to what that customer is trying to figure out in their KPI” and wonders what Giner thinks.
Giner says it’s natural to have as many dashboards as possible because analytics is an end goal for data intelligence. “I mean, it doesn’t help anyone,” he concedes.
Fore-Siglin reiterates, “It looks cool but it doesn’t help.”
“It looks cool, [it] gives you visibility on what’s happening, but what matters is what you do with that data. And at some point it’s not really needed,” Giner adds. “You need to have the KPIs, but we have examples that are very established, like personalization [and] personalized recommendations. Nobody’s thinking like, ‘Okay, who’s this user? What should I offer to him?’”
He continues, “The algorithm does it for you. And we are working right now for instance, in customer experience orchestration, where the algorithm is thinking, ‘On which experience should I enroll to this new user that I have?’” He throws out other examples, including: a user watched these three titles, so which experience should I offer? “Those decisions doesn’t need to be reflected on a dashboard, and you don’t need a person to think about it.”
“Fair enough,” Fore-Siglin replies. “I go on Facebook and Insta so infrequently, like twice a year, that there is no algorithm for me. So what I get a chance to see is the trend of what that agent is thinking should be offered to me. And it’s, sometimes it’s disconcerting, because it has nothing to do with me, but on other times it’s like …”
“‘How did you know I thinking about it?’” Giner laughs.
Fore-Siglin laughs too. “Right, exactly.”
The Start of CDNs
Fore-Siglin reminisces about the early days of the content delivery network (CDN) concept. “But then there was the question of what is the actionable item for the CDN based on RUM versus what was the actionable item for the content owner? Where do we stand in that?”
Giner notes that with a CDN, processes can be managed on the back end by a machine. “So we can get the perceived quality of the end user. Is it really impacting their experience? [That’s] the first thing. And then, if it is, we can work on ways to improve it or put in delivery.” The second thing is financials. “‘How can I save money and optimize my content delivery?’ So we get, for instance, the capability to track the perceived quality, and chunk by chunk in the video, select the best CDN possible to deliver the next chunk, ... preload the next chunk, and so on. All of that is running in the back end. So by an algorithm that is managing that for you, you don’t really know which CDN is being used. Of course, you define the logic and then what you see is that the end user’s experience just improved because you are acting before issues are happening,” Giner explains.
The Right Quality at the Right Price
Fore-Siglin carries the financials piece forward to tie it to experience quality: “In the telecom world, we had third-party billing. When you transferred across long-distance providers, it was … cost routing, is what we called it back then. If you have these multiple CDNs involved, how do you build the level of trust to them that we really are making a decision based on the quality of experience for the end user versus I want to use more of this CDN versus this CDN because of the cost models and stuff like that?”
Giner says that’s what NPAW controls, the perceived quality and the contextualized experience. “It’s what you were saying about social media for instance, and the algorithms—you don’t need to use it,” he asserts. “So we know that user’s similar to you, so they’re … liking this kind of experience. It’s the same for the algorithm for the CDN selection for instance. We know that people in your area using our ISP, using our device, and so on, they’re having this kind of experience and we can predict where the issues will be and select the best option either for the best quality, or well, getting the best needed quality with the best price possible.”
He restates it another way: “So we don’t need to have overkill in quality, we need to reach the level of quality that you want to deliver for the best price as possible.”
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